Humans of Martech

What's up everyone, today we have the pleasure of sitting down with Joshua Kanter, Co-Founder & Chief Data & Analytics Officer at ConvertML. Summary: Joshua spent the earliest parts of his career buried in SQL, only to watch companies hand out dashboards and call it strategy. Teams skim charts to confirm hunches while ignoring what the data actually says. He believes access means nothing without translation. You need people who can turn vague business prompts into clear, interpretable answers. He built ConvertML to guide those decisions. GenAI only raises the stakes. Without structure and fluency, it becomes easier to sound confident and still be completely wrong. That risk scales fast.About JoshuaJoshua started in data analytics at First Manhattan Consulting, then co-founded two ventures; Mindswift, focused on marketing experimentation, and Novantas, a consulting firm for financial services. From there, he rose to Associate Principal at McKinsey, where he helped companies make real decisions with messy data and imperfect information. Then he crossed into operating roles, leading marketing at Caesars Entertainment as SVP of Marketing, where budgets were wild.After Caesars, he became a 3-time CMO (basically 4-time); at PetSmart, International Cruise & Excursions, and Encora. Each time walking into a different industry with new problems. He now co-leads ConvertML, where he's focused on making machine learning and measurement actually usable for the people in the trenches.Data Democratization Is Breaking More Than It's FixingData democratization has become one of those phrases people repeat without thinking. It shows up in mission statements and vendor decks, pitched like some moral imperative. Give everyone access to data, the story goes, and decision-making will become magically enlightened. But Joshua has seen what actually happens when this ideal collides with reality: chaos, confusion, and a lot of people confidently misreading the same spreadsheet in five different ways.Joshua isn't your typical out of the weeds CMO, he's lived in the guts of enterprise data for 25 years. His first job out of college was grinding SQL for 16 hours a day. He's been inside consulting rooms, behind marketing dashboards, and at the head of data science teams. Over and over, he's seen the same pattern: leaders throwing raw dashboards at people who have no training in how to interpret them, then wondering why decisions keep going sideways.There are several unspoken assumptions built into the data democratization pitch. People assume the data is clean. That it's structured in a meaningful way. That it answers the right questions. Most importantly, they assume people can actually read it. Not just glance at a chart and nod along, but dig into the nuance, understand the context, question what's missing, and resist the temptation to cherry-pick for whatever narrative they already had in mind.“People bring their own hypotheses and they're just looking for the data to confirm what they already believe.”Joshua has watched this play out inside Fortune 500 boardrooms and small startup teams alike. People interpret the same report with totally different takeaways. Sometimes they miss what's obvious. Other times they read too far into something that doesn't mean anything. They rarely stop to ask what data is not present or whether it even makes sense to draw a conclusion at all.Giving everyone access to data is great and all… but only works when people have the skills to use it responsibly. That means more than teaching Excel shortcut keys. It requires real investment in data literacy, mentorship from technical leads, and repeated, structured practice. Otherwise, what you end up with is a very expensive system that quietly fuels bias and bad decisions and just work for the sake of work.Key takeaway: Widespread access to dashboards does not make your company data-informed. People need to know how to interpret what they see, challenge their assumptions, and recognize when data is incomplete or misleading. Before scaling access, invest in skills. Make data literacy a requirement. That way you can prevent costly misreads and costly data-driven decision-making.How Confirmation Bias Corrupts Marketing Decisions at ScaleExecutives love to say they are “data-driven.” What they usually mean is “data-selective.” Joshua has seen the same story on repeat. Someone asks for a report. They already have an answer in mind. They skim the results, cherry-pick what supports their view, and ignore everything else. It is not just sloppy thinking. It's organizational malpractice that scales fast when left unchecked.To prevent that, someone needs to sit between business questions and raw data. Joshua calls for trained data translators; people who know how to turn vague executive prompts into structured queries. These translators understand the data architecture, the metrics that matter, and the business logic beneath the request. They return with a real answer, not just a number in bold font, but a sentence that says: “Here's what we found. Here's what the data does not cover. Here's the confidence range. Here's the nuance.”“You want someone who can say, ‘The data supports this conclusion, but only under these conditions.' That's what makes the difference.”Joshua has dealt with both extremes. There are instinct-heavy leaders who just want validation. There are also data purists who cannot move until the spreadsheet glows with statistical significance. At a $7 billion retailer, he once saw a merchandising exec demand 9,000 survey responses; just so he could slice and dice every subgroup imaginable later. That was not rigor. It was decision paralysis wearing a lab coat.The answer is to build maturity around data use. That means investing in operators who can navigate ambiguity, reason through incomplete information, and explain caveats clearly. Data has power, but only when paired with skill. You need fluency, not dashboards. You need interpretation and above all, you need to train teams to ask better questions before they start fishing for answers.Key takeaway: Every marketing org needs a data translation layer; real humans who understand the business problem, the structure of the data, and how to bridge the two with integrity. That way you can protect against confirmation bias, bring discipline to decision-making, and stop wasting time on reports that just echo someone's hunch. Build that capability into your operations. It is the only way to scale sound judgment.You're Thinking About Statistical Significance Completely WrongToo many marketers treat statistical significance like a ritual. Hit the 95 percent confidence threshold and it's seen as divine truth. Miss it, and the whole test gets tossed in the trash. Joshua has zero patience for that kind of checkbox math. It turns experimentation into a binary trap, where nuance gets crushed under false certainty and anything under 0.05 is labeled a failure. That mindset is lazy, expensive, and wildly limiting.95% statistical significance does not mean your result matters. It just means your result is probably not random, assuming your test is designed well and your assumptions hold up. Even then, you can be wrong 1 out of every 20 times, which no one seems to talk about in those Monday growth meetings. Joshua's real concern is how this thinking cuts off all the good stuff that lives in the grey zone; tests that come in at 90 percent confidence, show a consistent directional lift, and still get ignored because someone only trusts green checkmarks.“People believe that if it doesn't hit statistical significance, the result isn't meaningful. That's false. And danger...

What's up everyone, today we have the pleasure of sitting down with Samia Syed, Director of Growth Marketing at Dropbox. Summary: Samia Syed treats martech like hiring. If it costs more than a headcount, it needs to prove it belongs. She scopes the problem first, tests tools on real data, and talks to people who've lived with them not just vendor reps. Then she tracks usage and outcomes from day one. If adoption stalls or no one owns it, the tool dies. She once watched a high-performing platform get orphaned after a reorg. Great tech doesn't matter if no one's accountable for making it work.Don't Buy the Tool Until You've Scoped the JobMartech buying still feels like the Wild West. Companies drop hundreds of thousands of dollars on tools after a single vendor call, while the same teams will debate for weeks over whether to hire a junior coordinator. Samia calls this out plainly. If a piece of software costs more than a person, why wouldn't it go through the same process as a headcount request?She maps it directly: recruiting rigor should apply to your tech stack. That means running a structured scoping process before you ever look at vendors. In her world, no one gets to pitch software until three things are clear:What operational problem exists right nowWhat opportunities are lost by not fixing itWhat the strategic unlock looks like if you doMost teams skip that. They hear about a product, read a teardown on LinkedIn, and spin up a trial to “explore options.” Then the feature list becomes the job description, and suddenly there's a contract in legal. At no point did anyone ask whether the team actually needed this, what it was costing them not to have it, or what they were betting on if it worked.Samia doesn't just talk theory. She has seen this pattern lead to ballooning tech stacks and stale tools that nobody uses six months after procurement. A shiny new platform feels like progress, but if no one scoped the actual need, you're not moving forward. You're burying yourself in debt, disguised as innovation.“Every new tool should be treated like a strategic hire. If you wouldn't greenlight headcount without a business case, don't greenlight tech without one either.”And it goes deeper. You can't just build a feature list and call that a justification. Samia breaks it into a tiered case: quantify what you lose without the tool, and quantify what you gain with it. How much time saved? How much revenue unlocked? What functions does it enable that your current stack can't touch? Get those answers first. That way you can decide like a team investing in long-term outcomes, not like a shopper chasing the next product demo.Key takeaway: Treat every Martech investment like a senior hire. Before you evaluate vendors, run a scoping process that defines the current gap, quantifies what it costs you to leave it open, and identifies what your team can achieve once it's solved. Build a business case with numbers, not just feature wishlists. If you start by solving real problems, you'll stop paying for shelfware.Your Martech Stack Is a Mess Because Mops Wasn't in the Room EarlyMost marketing teams get budget the same way they get unexpected leftovers at a potluck. Something shows up, no one knows where it came from, and now it's your job to make it work. You get a number handed down from finance. Then you try to retroactively justify it with people, tools, and quarterly goals like you're reverse-engineering a jigsaw puzzle from the inside out.Samia sees this happen constantly. Teams make decisions reactively because their budget arrived before their strategy. A renewal deadline pops up, someone hears about a new tool at a conference, and suddenly marketing is onboarding something no one asked for. That's how you end up with shelfware, disconnected workflows, and tech debt dressed up as innovation.This is why she pushes for a different sequence. Start with what you want to achieve. Define the real gaps that exist in your ability to get there. Then use that to build a case for people and platforms. It sounds obvious, but it rarely happens that way. In most orgs, Marketing Ops is left out of the early conversations entirely. They get handed a brief after the budget is locked. Their job becomes execution, not strategy.“If MOPS is treated like a support team, they can't help you plan. They can only help you scramble.”Samia has seen two patterns when MOPS lacks influence. Sometimes the head of MOPS is technically in the room but lacks the confidence, credibility, or political leverage to speak up. Other times, the org's workflows never gave them a shot to begin with. Everything is set up as a handoff. Business leaders define targets, finance approves the budget, then someone remembers to loop in the people who actually have to make it all run. That structure guarantees misalignment. If you want a smarter stack, you have to fix how decisions get made.Key takeaway: Build your Martech plan around strategic goals, not leftover budget. Start with what needs to be accomplished, define the capability gaps that block it, and involve MOPS from the beginning to shape how tools and workflows can solve those problems. If Marketing Ops is looped in only after the fact, you're not planning. You're cleaning up.Build Your Martech Stack Like You're Hiring a TeamMost teams buy software like they're following a recipe they've never tasted. Someone says “we need a CDP,” and suddenly everyone's firing off RFPs, demoing the usual suspects, and comparing price tiers on platforms they barely understand. Samia draws a clean line between hiring and buying here. In both cases, the smartest teams treat the process as exploration, not confirmation.Hiring isn't static. You open a rec, start meeting candidates, and quickly realize the original job description is outdated by the third interview. A standout candidate shows up, and suddenly the scope expands. You rewrite the role to fit the opportunity, not the other way around. Samia thinks buying Martech should work the same way. Instead of assuming a fixed category solves the problem, you should:Map your actual use caseTalk to vendors and real usersCompare radically different paths, not just direct competitors“You almost need to challenge yourself to zoom out and ask if this tool fits where your company is actually headed.”Samia's lived the pain of teams chasing big-budget platforms with promises of deep functionality, only to realize no one has the bandwidth to implement them properly. The tool ends up shelved or duct-taped into place while marketing burns cycles trying to retrofit workflows around something they were never ready for. That kind of misalignment doesn't show up in vendor decks or curated testimonials. You only catch it by doing your own research and talking to people who don't have a sales quota.Buying tech is easy. Building capability is hard. Samia looks for tools that match the company's maturity and provide room to grow. Not everything needs to be composable, modular, and future-proofed into infinity. Sometimes the right move is choosing what works today, then layering in complexity as your team levels up. Martech isn't one-size-fits-all, and most vendor conversations are just shiny detours away from that uncomfortable truth.Key takeaway: Treat your Martech search like a hiring process in motion. Start with a goal, not a category. Stay open to evolving the solution as new context surfaces. Talk to actual users who've implemented the tool under real constraints. Ask what broke, what surprised them, and what they'd do differently. Choose the tech that fits your team's real capabili...

What's up everyone, today we have the pleasure of sitting down with Ankur Kothari, Adtech and Martech Consultant who's worked with big tech names and finance/consulting firms like Salesforce, JPMorgan and McKinsey.The views and opinions expressed by Ankur in this episode are his own and do not necessarily reflect the official position of his employer.Summary: Ankur explains how most AI personalization flops cause teams ignore the basics. He helped a brand recover millions just by making the customer journey actually make sense, not by faking it with names in emails. It's all about fixing broken flows first, using real behavior, and keeping things human even when it's automated. Ankur is super sharp, he shares a practical maturity framework for AI personalization so you can assess where you currently fit and how you get to the next stage. AI Personalization That Actually Increases Retention - Practical ExampleMost AI personalization in marketing is either smoke, mirrors, or spam. People plug in a tool, slap a customer's first name on a subject line, then act surprised when the retention numbers keep tanking. The tech isn't broken. The execution is lazy. That's the part people don't want to admit.Ankur worked with a mid-sized e-commerce brand in the home goods space that was bleeding revenue; $2.3 million a year lost to customers who made one purchase and never returned. Their churn rate sat at 68 percent. Think about that. For every 10 new customers, almost 7 never came back. And they weren't leaving because the product was bad or overpriced. They were leaving because the whole experience felt like a one-size-fits-all broadcast. No signal, no care, no relevance.So he rewired their personalization from the ground up. No gimmicks. No guesswork. Just structured, behavior-based segmentation using first-party data. They looked at:Website interactionsPurchase historyEmail engagementCustomer service logsThen they fed that data into machine learning models to predict what each customer might actually want to do next. From there, they built 27 personalized customer journeys. Not slides in a strategy deck. Actual, functioning sequences that shaped content delivery across the website, emails, and mobile app.> “Effective AI personalization is only partly about the tech but more about creating genuinely helpful customer experiences that deliver value rather than just pushing products.”The results were wild. Customer retention rose 42 percent. Lifetime value jumped from $127 to $203. Repeat purchase rate grew by 38 percent. Revenue climbed by $3.7 million. ROI hit 7 to 1. One customer who previously spent $45 on a single sustainable item went on to spend more than $600 in the following year after getting dropped into a relevant, well-timed, and non-annoying flow.None of this happened because someone clicked "optimize" in a tool. It happened because someone actually gave a damn about what the customer experience felt like on the other side of the screen. The lesson isn't that AI personalization works. The lesson is that it only works if you use it to solve real customer problems.Key takeaway: AI personalization moves the needle when you stop using it as a buzzword and start using it to deliver context-aware, behavior-driven customer experiences. Focus on first-party data that shows how customers interact. Then build distinct journeys that respond to actual behavior, not imagined personas. That way you can increase retention, grow customer lifetime value, and stop lighting your acquisition budget on fire.Why AI Personalization Fails Without Fixing Basic Automation FirstSigning up for YouTube ads should have been a clean experience. A quick onboarding, maybe a personalized email congratulating you for launching your first campaign, a relevant tip about optimizing CPV. Instead, the email that landed was generic and mismatched—“Here's how to get started”—despite the fact the account had already launched its first ad. This kind of sloppiness doesn't just kill momentum. It exposes a bigger problem: teams chasing personalization before fixing basic logic.Ankur saw this exact issue on a much more expensive stage. A retail bank had sunk $2.3 million into an AI-driven loan recommendation engine. Sophisticated architecture, tons of fanfare. Meanwhile, their onboarding emails were showing up late and recommending products users already had. That oversight translated to $3.7 million in missed annual cross-sell revenue. Not because the AI was bad, but because the foundational workflows were broken.The failure came from three predictable sources:Teams operated in silos. Innovation was off in its own corner, disconnected from marketing ops and customer experience.The tech stack was split in two. Legacy systems handled core functions, but were too brittle to change. AI was layered on top, using modern platforms that didn't integrate cleanly.Leaders focused on innovation metrics, while no one owned the state of basic automation or email logic.To fix it, Ankur froze the AI rollout for 120 days and focused on repair work. The team rebuilt the essential customer journeys, cleaned up logic gaps, and restructured automation to actually respond to user behavior. This work lifted product adoption by 28 percent and generated an additional $4.2 million in revenue. Once the base was strong, they reintroduced the AI engine. Its impact increased by 41 percent, not because the algorithm improved, but because the environment finally supported it.> “The institutions that win with AI are the ones that execute flawlessly across all technology levels, from simple automation to cutting-edge applications.”That lesson applies everywhere, including in companies far smaller than Google or JPMorgan. When you skip foundational work, every AI project becomes a band-aid over a broken funnel. It might look exciting, but it can't hold.Key takeaway: Stop using AI to compensate for broken customer journeys. Fix your onboarding logic, clean up your automation triggers, and connect your systems across teams. Once the fundamentals are working, you can layer AI on top of a system that supports it. That way you can generate measurable returns, instead of just spinning up another dashboard that looks good in a QBR.Step by Step Approach to AI Personalization With a Maturity Framework - The First Steps You Can Take on The Path To AI PersonalizationMost AI personalization projects start with a 50-slide vision deck, three vendors, and zero working use cases. Then teams wonder why things stall. What actually works is starting small and surgical. One product. One journey. Clear data. Clear upside.Ankur advised a regional bank that had plenty of customer data but zero AI in play. No need for new tooling or a six-month roadmap. They focused on one friction-heavy opportunity with direct payoff: mortgage pre-approvals. Forget trying to personalize every touchpoint. They picked the one that mattered and did it well.They built a clustering algorithm using transaction patterns, savings trends, and credit utilization to detect home-buying intent. From there, they pushed pre-approvals with tailored rates and terms. The bank already had the raw data in its core systems. No scraping, no extra collection, no “data enrichment” vendor needed.That decision paid off fast:The data already existed, so implementation moved quicklyThe scope was limited to a single high-stakes journeyThe impact landed hard: mortgage application rates jumped 31 percent and approval-to-close conversions climbed 24 percent within 60 days> “Start with a high-value product journey where pers...

What's up everyone, today we have the pleasure of sitting down with Kim Hacker, Head of Business Ops at Arrows. Summary: Tool audits miss the mess. If you're trying to consolidate without talking to your team, you're probably breaking workflows that were barely holding together. The best ops folks already know this: they're in the room early, protecting momentum, not patching broken rollouts. Real adoption spreads through peer trust, not playbooks. And the people thriving right now are the generalists automating small tasks, spotting hidden friction, and connecting dots across sales, CX, and product. If that's you (or you want it to be) keep reading or hit play.About KimKim started her career in various roles like Design intern and Exhibit designer/consultantShe later became an Account exec at a Marketing AgencyShe then moved over to Sawyer in a Partnerships role and later Customer OnboardingToday Kim is Head of Business Operations at Arrows Most AI Note Takers Just Parrot Back JunkKim didn't set out to torch 19 AI vendors. She just wanted clarity.Her team at Arrows was shipping new AI features for their digital sales room, which plugs into HubSpot. Before she went all in on messaging, she decided to sanity check the market. What were other sales teams in the HubSpot ecosystem actually *doing* with AI? Over a dozen calls later, the pattern was obvious: everyone was relying on AI note takers to summarize sales calls and push those summaries into the CRM.But no one was talking about the quality. Kim realized if every downstream sales insight starts with the meeting notes, then those notes better be reliable. So she ran her own side-by-side teardown of 22 AI note takers. No configuration. No prompt tuning. Just raw, out-of-the-box usage to simulate what real teams would experience.> “If the notes are garbage, everything you build on top of them is garbage too.”She was looking for three things: accuracy, actionability, and structure. The kind of summaries that help reps do follow-ups, populate deal intelligence, or even just remember the damn call. Out of 22 tools, only *three* passed that bar. The rest ranged from shallow summaries to complete misinterpretations. Some even skipped entire sections of conversations or hallucinated action items that never came up.It's easy to assume an AI-generated summary is “good enough,” especially if it sounds coherent. But sounding clean is not the same as being useful. Most note takers aren't designed for actual sales workflows. They're just scraping audio for keywords and spitting out templated blurbs. That's fine for keeping up appearances, but not for decision-making or pipeline accuracy.Key takeaway: Before layering AI on top of your sales stack, audit your core meeting notes. Run a side-by-side test on your current tool, and look for three things: accurate recall, structured formatting, and clear next steps. If your AI notes aren't helping reps follow up faster or making your CRM smarter, they're just noise in a different font.Why Most Teams Will Miss the AI Agent Wave EntirelyThe vision is seductive. Sales reps won't write emails. Marketers won't build workflows. Customer success won't chase follow-ups. Everyone will just supervise agents that do the work for them. That future sounds polished, automated, and eerily quiet. But most teams are nowhere close. They're stuck in duplicate records, tool bloat, and a queue of Jira tickets no one's touching. AI agents might be on the roadmap, but the actual work is still being done by humans fighting chaos with spreadsheets.Kim sees the disconnect every day. AI fatigue isn't coming from overuse. It's coming from bad framing. “A lot of people talking about AI are just showing the most complex or viral workflows,” she explains. “That stuff makes regular folks feel behind.” People see demos built for likes, not for legacy systems, and it creates a false sense that they're supposed to be automating their entire job by next quarter.> “You can't rely on your ops team to AI-ify the company on their own. Everyone needs a baseline.”Most reps haven't written a good prompt, let alone tried chaining tools together. You can't go from zero to agent management without a middle step. That middle step is building a culture of experimentation. Start with small, daily use cases. Help people understand how to prompt, what clean AI output looks like, and how to tell when the tool is lying. Get the entire org to that baseline, then layer on tools like Zapier Agents or Relay App to handle the next tier of automation.Skipping the basics guarantees failure later. Flashy agents look great in demos, but they don't compensate for unclear processes or teams that don't trust automation. If the goal is to future-proof your workflows, the work starts with people, not tools.Key takeaway: If your team isn't fluent in basic AI usage, agent-powered workflows are a pipe dream. Build a shared baseline across departments by teaching prompt writing, validating outputs, and experimenting with small use cases. That way you can unlock meaningful automation later instead of chasing trends that no one has the capacity to implement.When AI Systems Meet The Chaos Of Actual Workplace ProcessesAI vendors keep shipping tools like everyone has an intern, a technical co-pilot, and five extra hours a week to configure dream workflows. The real buyers? They're just trying to fix broken Salesforce fields, write one less follow-up email, or get through the day without copy-pasting notes into Notion. Somewhere between those extremes, the user gets lost in translation.Kim has felt that gap from both sides. She was hesitant to even start with ChatGPT. “I almost gave up on it,” she said. “I felt late and overwhelmed, and I just figured maybe I wasn't going to be an AI person.” Fast forward to today, and it's one of her most-used tools. She didn't get there by wiring up agents. She started small. Simple things. Drafting ideas, summarizing content, clarifying messy thoughts. That built trust. Then momentum.“There's a lot that has to happen before your calendar is filled with calls and nothing else. AI can help, but you have to let it earn its spot.”If you're trying to build that muscle, forget the multi-tool agent orchestration for a second. Focus on everyday wins like:Turning a messy Slack thread into a clean summaryWriting a follow-up email in your toneRewriting a calendar event title so it makes sense to your future selfCleaning up action items from a sales call without hallucinationsDrafting internal documentation from bullet pointsThe pace is accelerating. People feel it. You don't need to watch keynote demos to know that change is coming fast. It's easy to feel like you're already behind. Kim doesn't disagree. She just thinks most teams are solving the wrong problem. Vendors are focused on the sprint. Most people haven't even laced up. “Everyone wants the big leap,” she said. “But most wins come from small, boring tools that actually do what they say they'll do.”That's the root issue. A lot of AI features today are solving theoretical problems. They assume workflows are tidy, perfectly tagged, and documented in Notion. Real work is messier. It happens in Slack threads, half-filled records, and follow-ups that never got logged. If your tool can't handle that, then it doesn't matter how shiny your roadmap is.Key takeaway: Stop evaluating AI features based on potential. Evaluate them based on current chaos. Ask whether the tool handles your worst-case scenario, not your ideal one. Prioritize small, boring use cases that save time immediately. That way yo...

What's up everyone, today we have the pleasure of sitting down with Keith Jones, Head of GTM Systems at OpenAI. Also just a quick disclaimer that Keith is joining the podcast as Keith the technologist and human, not the employee at OpenAI. The views and opinions he expresses in this episode are his own and do not represent OpenAI.Summary: The best martech buying process isn't a spreadsheet. It's a cognitive extraction exercise.Keith Jones asks stakeholders to write what they want, say it out loud, and then feeds both into GPT to surface what actually matters. That discipline applies to agents too. Most teams chase orchestration before they have stable logic, clean data, or working workflows. Keith's bet? The future of SaaS is fewer tools, built in-house, coordinated by agents not a graveyard of dashboards pretending to be automation.Why Sales Ops People Who've Actually Sold Have the Sharpest KnivesKeith Jones did not set out to work in sales operations earlier in his career. He landed in it sideways, like a lot of the best people in ops do. He was hired with the catch-all title of “Business Operations Associate,” which could mean anything or nothing, depending on the day. His job, in practice, involved forecasting bookings and revenue in Excel based on shipping data. No one told him he was in sales ops. No one even used that phrase. If someone had asked him whether he wanted a career in sales operations, he wouldn't have known what they meant.The company later shifted him into a field sales role. They were trying to grow the team internally, so they dropped him into the southeast region and told him to start talking to CIOs and chief nursing officers. He moved to Atlanta and started selling. That job was hard in a way that most people who build systems for sales teams never understand. The structure was just enough to keep things moving, but not enough to support real learning. He had a quota, a few tools, and a manager who held weekly one-on-ones. There was no real training. No consistent coaching. No safety net. If he wanted to make it work, he had to figure it out himself.That experience never left him. Now that Keith leads systems for go-to-market teams, he still thinks about what it felt like to sit in a seller's chair. Every tool that didn't work, every field in Salesforce that meant nothing, every process that made his job harder stuck with him. He builds differently because of that.> “You're given a quota, a few tools, some vague expectations, and then shoved into the wild.”The biggest disconnect he sees in GTM systems comes from people who have never sold anything. Many of the systems designed to help sales teams are built by career admins or operations specialists who've never had to ask for a purchase order or explain why a deal fell through. These people often optimize for what the business wants, not for what the seller needs to survive the quarter. Keith doesn't speak about this in abstract terms. He lived through it.After his healthcare role, he joined a startup in Atlanta as employee number eight. He came in as an account executive, but quickly became the go-to person for explaining the product. He wasn't the most technical person, but he could speak the language. That mattered. As the company grew and new reps joined, Keith found himself teaching them how to explain the product to customers. He was still selling, but he was also building shared knowledge. That part felt natural.Then his CEO pulled him into a room and told him something blunt. “You're really bad at cold calling. You don't even do it.” Keith agreed. He hated that part of the job. As an introvert, it never felt right. But the CEO followed up with something more important. “You know the product better than anyone else on the floor. I think you should be our first sales engineer.” Keith said yes immediately.There was one more thing. The Salesforce admin had just quit, and the CEO asked if he wanted to learn Salesforce too. Keith said yes to that as well. That moment when he stepped into a role that combined technical depth with operational design set the course for everything that came next.Today, he leads systems at a scale that touches thousands of sellers. He remembers what it felt like to sell without support, and he refuses to push that experience onto others. He builds tools that actually work because he knows what failure feels like.Key takeaway: Sales ops works best when it is built by people who have actually sold. If you want to build tools that sellers will use, you need someone who has lived with the friction of broken ones. Sellers do not care about elegant reporting architecture if the CRM slows them down. They care about speed, clarity, and context. Hiring operators who have carried a quota gives you an unfair advantage. They remember how it felt to lose time chasing bad leads or cleaning up messy data. That memory turns into better workflows. You can teach someone how to configure Salesforce. You cannot teach someone how it feels to miss your number because your systems were designed by someone who never had one.The Difference Between GTM Ops and GTM SystemsWhen people talk about GTM operations, most of them blend it with GTM systems like it's all one job. It's not. They share a Slack channel, maybe a budget, and definitely a few dashboards, but the actual work is completely different. Keith has lived on both sides of that line. At OpenAI and before that at Mural, he ran GTM systems. Back at Gartner, he saw how every company defines these roles differently, sometimes with intention, sometimes out of inertia. But when he breaks it down, the split is actually pretty clear.GTM ops exists to support the field directly. That means helping sellers, marketers, and customer success teams get their work done. Think enablement, process design, live troubleshooting, deal support, and training that doesn't feel like a waste of time. These teams sit next to the people they're helping and shape operations based on actual conversations and feedback.GTM systems is a whole different rhythm. These are the people writing the workflows, building automations, owning the CRM, and threading together tools that are supposed to work seamlessly but rarely do. They are not front-facing. They are deep in the guts of your tech stack. They touch code, configuration, architecture, and logic trees that determine whether your rep gets the right lead or a ghost contact from 2017.> “We rely heavily on our ops colleagues to feed us guidance from the field so we can build the right solutions. That's the balance that works.”Keith's favorite model is one where GTM ops and GTM systems are separate but inseparable. Not one inside the other. Not one reporting into the other. Two teams, side by side, solving for different parts of the same outcome. Ops listens and adapts. Systems builds and scales. When that rhythm is right, sellers feel supported without even knowing why. When it breaks, people stop trusting the process and start hacking together their own.He makes an important distinction when talking about marketing ops. Unlike sales ops, which skews toward operational execution, or systems, which skews technical, marketing ops often lands in the uncomfortable middle. It needs to speak both languages. You might be setting up nurture logic in Marketo one hour and then coaching a team through campaign QA the next. Keith sees it as a dual-mode function, one that requires:Operational discipline to support marketers with templates, briefs, budgets, and targeting logicTechnical fluency to build and maintain systems that track performance across platformsThe tension between systems and ops is real. I's not a fight. It's a rhythm. And when ...

Summary: Elena has done what most startup marketers only guess at; made it through multiple acquisitions and now leads global integrated marketing at Visa. In this episode, she breaks down what actually changes when you go from scrappy lead gen to enterprise brand building, why most martech tools don't survive security reviews, and how leadership without authority is the skill that really matters. We get into messy tech migrations, broken attribution dreams, and why picking up the phone still beats Slack. If you've ever wondered why your startup playbook stops working at scale, this conversation spells it out.What Startup Marketers Learn the Hard Way When They Land at a Big CorporationElena does not call herself an “acquisition master,” even though her resume might suggest otherwise. Three startups she worked at were acquired, Sivan by Refinitiv, WorkMarket by ADP, and Currencycloud by Visa, where she works today. Some might spin that track record as a strategic playbook for career navigation. Elena sees it differently. She credits great teams and good companies, not some personal Midas touch.The truth is, you cannot force an acquisition. What you can do is get really good at reading the room. Elena's career started deep in the weeds of lead generation and demand marketing, chasing performance metrics and measuring everything that moved. Early on, she dipped into other areas, event planning, employee engagement, but demand gen was where she built muscle. That was her lane at WorkMarket, where the first big learning curve hit.It turns out the skills that build the lead gen engine are not the same ones you need when a company shifts from hypergrowth to prepping for acquisition. Elena experienced firsthand the moment when leadership stops asking about lead volume and starts asking about brand perception. Suddenly the focus pivots from how many MQLs you can squeeze out of a campaign to how the company is positioned in the market, what the media is saying, and whether the brand looks credible at scale. She admitted she did not fully appreciate that switch at first.> "I came there with a mindset of if I can't track it, I'm not gonna do it," Elena said. "Every performance marketer would probably relate."That perspective doesn't fly for long in environments where brand and reputation start to outweigh click-through rates. Elena's time at Visa has only reinforced that lesson. Today, much of her work revolves around brand building and awareness, the same areas she once side-eyed for being soft and unmeasurable. It is one thing to believe in brand. It is another thing entirely to understand how hard it is to build one well.The scale jump from startup life to a company with over 30,000 employees does not just change the headcount. It rewires the entire pace and process of how work gets done. Elena described the gut-check moment that made it clear she was not at a scrappy startup anymore. It was not a high-level strategy meeting or a sweeping corporate memo. It was the moment she tried to get a simple social graphic approved.In a startup, that kind of thing takes a few minutes on Canva and the green light from whoever's closest to the Slack channel. At Visa, especially as a regulated financial institution, it involves legal reviews, vendor contracts, approval workflows, and enough compliance checks to make your head spin. Campaigns that once rolled out in days now take months. Not because anyone is slow, but because the stakes are high and the rules are different.That culture shock is where many startup marketers either adapt or tap out. What Elena figured out is that the skills that work at one stage of company life are not the ones that get you through the next. If you want to survive the jump from lean team to enterprise machine, you have to stop resenting the process and start respecting what it protects.Key takeaway: If you're coming from startup life, expect a painful adjustment when you move into a large, regulated company. The speed, autonomy, and scrappiness you are used to will collide hard with approval chains and compliance processes. The faster you stop fighting it and start learning why those systems exist, the faster you'll find your footing. Metrics-driven marketing only gets you so far. To thrive at scale, you need to understand the power and patience required to build brand trust.What Nobody Tells You About Merging Tech Stacks After an AcquisitionThe fantasy version of an acquisition is clean and celebratory. Two companies come together, the deal closes, the press release goes out, and life moves on. The reality, especially for marketing teams, is a long, often frustrating grind of systems audits, security reviews, and endless conversations about whether your beloved tools will survive the merger.Elena has lived through that grind more than once. When Visa acquired Currencycloud, she was not navigating that shift alone. Many of her teammates made the journey with her, which helped. But solidarity does not make the process move faster. It just means you have people to vent to while you wait for approvals.One of the first and hardest parts of that transition was not a debate between marketers. It was the clash between marketing teams and security teams. Every single piece of tech Currencycloud used, whether it was their website hosting, HubSpot marketing automation, or even individual add-ons, had to go under the microscope. Security teams needed to assess, vet, and approve each tool, often asking questions that made sense from a cybersecurity perspective but sounded completely out of touch to anyone in marketing.The back-and-forth was not casual. It escalated all the way up to the chief technology officer and the cybersecurity team at HubSpot sitting down with Elena's group to explain, in detail, what the platform could and could not do. None of this was about malice or incompetence. It was about two fundamentally different mindsets trying to find common ground.> "These are security people. They're not marketers. They don't always know why we need a particular tool or what it does," Elena explained.That learning curve is brutal if you're not prepared for it. The deeper into operations you sit, the more of these conversations you end up having. Elena found herself in rooms with people from multiple marketing ops teams across Visa, comparing tech stacks, workflows, and priorities. There was no easy answer to which system would win out. Sometimes the decision was clear. Other times it came down to questions like, is it really worth fighting for this tool, or is now the time to adapt to what already exists?She describes it as less like transferring from one job to another and more like moving from a Montessori school to a traditional classroom. Both systems can deliver a good education. They just teach in wildly different ways. One thrives on flexibility and autonomy. The other runs on structure and process. Neither is wrong. They are simply different environments, and surviving the switch requires a willingness to adjust.The biggest mistake marketers make in these situations is believing the process is about what *they* want. Elena was quick to point out that the companies she has worked for, especially Visa, keep customer experience at the center of these decisions. It is not about which tool is most familiar to the internal team. It is about which systems create the least friction for the end user. That mindset helps keep the process grounded, even when the day-to-day feels like a slow march through bureaucracy.Patience is not optional in these transitions. You will hit walls. You will repeat yourself. You will explain the same use case to five different people across three different teams. And eventually, you will e...

What's up folks, today we're diving into the AI talent crunch and exploring which marketing roles have the strongest staying power and which are most likely to be replaced by AI.Summary: Shit is changing fast. Don't wait for someone to guide you. Navigate this transition by focusing on judgment tasks while letting AI handle predictions. At risk are campaign operators, generic content creators, and report-pulling analysts. Set to thrive are resident AI implementation experts who select worthy tools, data orchestrators connecting proprietary data to AI, product/customer marketers with genuine empathy, ethics guardians preventing bias issues, and localization specialists understanding cultural nuances.Marketing Jobs AI Will Kill (And What Skills Actually Matter Now)AI tools have cut strange new patterns into the marketing job market. Pay attention and you'll spot which roles face extinction risk, which command premium salaries, and which hang precariously in the balance. We've watched marketing teams across dozens of companies scramble to realign their talent strategies around this new reality. Some roles vanish while entirely new job titles materialize almost weekly.One of the good things is that AI impacts marketing jobs based on task predictability and context, not seniority or experience. A CMO who mostly approves creative and manages schedules faces more displacement risk than a junior analyst who excels at extracting bizarre but valuable insights from data chaos. You probably feel this tension already. Half your marketing tasks could disappear next quarter, but the other half suddenly requires superpowers you're frantically trying to develop before your next performance review.This episode is meant to give you something to think about in terms of your particular role in marketing. We'll explore roles we think are at risk of vanishing and roles that are well positioned to become even more valuable. Shit is changing fast, no one is going to take your hand through this transition. You need to own it and take action.Marketing Roles Most at Risk to be Replaced by AIAI's Coming for Your Campaign Ops Job (Unless You Evolve Now)Phil and Darrell explored which campaign operations roles will vanish first and which might actually strengthen in the algorithmic storm ahead. Darrell struck first with brutal honesty about traditional campaign operations: "The role of configuring marketing automation tools to spec will be definitely at risk." He's talking about those roles where marketers simply implement predefined elements - predetermined images, pre-written text, established CTAs, and mapped-out lead routing. AI already handles this configuration work. Darrell has witnessed actual demos from startups building tools where marketers type requirements and - poof - the system builds it automatically. What seemed like science fiction months ago now exists in alpha versions across the industry.Phil slightly pushed back by referencing one of Darrell's recent posts, fracturing campaign ops into distinct categories rather than treating it as one vulnerable block. "Campaign ops encompasses way more than pressing buttons in Marketo," he insisted. He sorted these functions into two buckets:* **Highly vulnerable to AI replacement**:   * Reporting execution  * Campaign analysis and performance tracking  * Paid media bid adjustments  * Email automation and nurture flows  * Landing page and form creation* **Likely to survive the AI wave**:  * Setting strategic objectives and KPIs  * Creative decision-making requiring business understanding  * Budget planning involving cross-functional negotiation  * QA processes demanding human judgment  * Development of truly innovative best practices> "I had it in the unclear bucket because there's a box of some things under there that I feel like are still pretty likely to survive," Phil explained. "Coming up with campaign goals requires so much business understanding, strategic alignment, and political navigation."The conversation crystallized around evolution rather than extinction. Darrell sees campaign ops professionals transforming from button-pushers to strategic partners: "What it's going to evolve into is actually looking at objectives and KPIs, changing requirements, and modifying briefs." He advocated for campaign ops to shift toward continuous "always-on programs" requiring constant optimization rather than churning out repetitive one-off campaigns - a far more AI-resistant position.Key takeaway: To keep your campaign operations job when AI comes knocking, immediately shift your focus from tactical execution to strategic functions. Master business alignment skills, develop creative decision-making capabilities, and build continuous optimization programs. The marketers who survive will be those who stop configuring systems to spec and start reshaping campaign requirements based on deep business understanding and cross-functional collaboration.AI Will Eat Generic Content Creation (But Experts Will Thrive)Phil explored a pretty obvious category of marketing roles: "I think a lot of folks are really excited about Generative AI and using it to create basic posts and pages without editing any of the text." The bloodbath has already begun. Copywriters and content marketers producing unremarkable work find themselves outpaced by algorithms that can churn out mediocre content at scale, for pennies. The particularly exposed are those creating "routine content without a distinctive voice or cultural nuance," especially when working across global markets where nuance matters deeply.Darrell pulled no punches on what's coming: "Bad content is going to become obsolete." AI tools supercharge this dynamic, flooding channels with generated material that looks competent but lacks soul. The truly valuable is content that actually connects with people. Content that makes them feel something. Content that solves real problems in ways that show genuine understanding.What struck me as particularly insightful was Darrell's observation about subject matter experts potentially winning big in this new reality. These experts:* Often possess deep knowledge but lack time or writing skills* Can now leverage AI to amplify their expertise with minimal effort* Only need to provide "the spark of an idea and a few bullet points" * Create output that vastly outperforms generic content from disconnected marketers> "All it takes is like the spark of an idea and a few bullet points. And you have a full post and it's gonna be way better than someone, like a marketer for example, that doesn't really care about the product or about the industry and is writing like crappy content."This represents a fundamental power shift in content creation. The value no longer sits with those who can string sentences together but with those who bring authentic expertise, perspective, and lived experience. AI struggles with these human elements, the exact qualities that make readers stop scrolling and actually pay attention.Key takeaway: Your content survival strategy requires becoming either irreplaceably human or strategically AI-augmented. Build genuine subject matter expertise, develop a distinctive voice that reflects your unique perspective, and learn to use AI as an amplifier rather than a replacement for any kind of original thought. The future belongs to the specialized expert who can provide the strategic direction that AI can't generate on its own.Which Data Analyst Jobs Will Survive the AI Revolution?Marketing data analysts who build dashboards for a li...

What's up everyone, today we have the pleasure of sitting down with Moni Oloyede, Founder at MO Martech. Summary: Your buyers can't remember why they bought from you, our brains physically can't store that information correctly. But we've built elaborate attribution systems pretending otherwise. Moni helps us understand why we need to stop crediting random touchpoints and start measuring how effectively each content piece performs its specific job in moving people through your funnel. We also cover why not all marketing activities need to drive revenue, why you shouldn't ditch ideas just because you can't track them and why GTM engineering is just job title inflation. About MoniMoni started her career at Sourcefire, a cybersecurity company where she dabbled in everything from Eloqua, Salesforce and AdwordsShe shifted to the agency world and joined a revenue marketing agency and later a growth consultancyShe went back in house in cybersecurity where she would spend the better part of 5 years becoming a Director of Marketing InfrastructureToday Moni (moo-nee) is the founder of MO Martech where she teaches and runs workshops to help business that struggle with marketingMost Tech Stacks Are Stitched With Duct TapeBorn in the prehistoric age of marketing automation, Moni witnessed marketing technology evolve from early concept to tablestakes. Her first employer, a cybersecurity company, maintained such intimate ties with Eloqua that they earned a literal place in the vendor's office. "I cut my teeth in the early days of lead scoring and nurturing, like all those concepts were new," she recalls. While most marketers today inherit established systems, Moni helped build the prototype.Those early days bristled with raw technological potential. Her CMO burst back from a conference, wide-eyed about "this new thing called the Cloud." Marketing teams fumbled through uncharted territory, concocting solutions with no rulebook. Moni found herself repeatedly cast as the test subject for nascent concepts:* Early lead scoring algorithms that barely understood buyer intent* Rudimentary nurture campaigns that seem prehistoric by today's standards* Primitive ABM approaches before the category even existed* First-generation dynamic content that barely qualified as "dynamic"Her technical immersion might have continued indefinitely, but a pattern emerged across agencies and client engagements. The technology consistently underdelivered on its promise. "We seem to get to a point and then we can't ever get to the promise," she explains. The gap between vendor slideware and actual results remained stubbornly unbridgeable regardless of budget size, team composition, or technical architecture.This revelation propelled Moni toward the marketing roots beneath the technology. She uncovered the industry's dirty little secret: nobody has their marketing technology working smoothly. Not even close.> "Everybody always thinks that other people's tech stacks are perfect. You attend webinars and listen to podcasts and think, 'oh my gosh, that brand has it all figured out. Why don't I have it figured out?'"Pull back the curtain on these supposedly perfect marketing technology implementations and you'll discover chaos. That Fortune 500 company presenting their "integrated customer journey orchestration"? They can't even track basic lead conversion properly. That unicorn startup showcasing their "AI-powered personalization engine"? Most of their segments contain default content. The larger the company, the more chaotic the implementation. "The bigger the company, the more mess it is," Moni confirms. "It's more duct tape and glue and just hobbled together things."Marketing technology works as an amplifier, not a miracle cure. "Technology is not automagical," Moni states bluntly. "It can only do so much, and if the marketing's bad, the technology is not going to fix that." Her journey from tech specialist to marketing strategist stems directly from this understanding: fix the foundation first.Key takeaway: Stop comparing your messy marketing stack to the sanitized versions presented at conferences. Even the most sophisticated enterprises run on cobbled-together systems and manual workarounds. Focus first on creating marketing that resonates with real humans, then apply technology selectively to amplify what already works. You'll save yourself the frustration of trying to automate broken processes while building something sustainable that actually delivers results.The Marketing Ops Identity ParadoxMarketing operations professionals inhabit a peculiar career limbo. You build the systems that power modern marketing, yet find yourself trapped by your own expertise. Moni, a 16-year marketing veteran, captures this frustration perfectly: "For at least 10 years I've been doing my damnedest to try to run away from marketing ops, and it won't let me go."> "No matter what I do, I can't get away from it even though I've tried forever."This career quicksand pulls you back each time you attempt to climb out. Your specialized knowledge becomes both your superpower and your career ceiling. While executives strategize future campaigns in boardrooms, you transform their whiteboard sketches into measurable reality. The truth? Marketing strategy without operational execution amounts to wishful thinking on a slide deck.The operational brain works differently. You see systems where others see individual campaigns. You spot integration failures where others blame the platform. Your value comes from this unique perspective—connecting dots across the marketing ecosystem that others don't even know exist. Moni describes this experience viscerally: "There's so much nuance into making it work that they don't get or understand unless you're in it or have that historical knowledge."Marketing ops professionals often bear the weight of accountability without corresponding authority. When campaigns fail, executives look to you for answers. As Moni explains, "Since you're responsible for the results and the analytics, you feel like it's on you. When it doesn't happen, they come to you." This creates immense pressure: "You feel that pressure and it's like, 'but you gave me a crappy campaign that doesn't have good messaging and doesn't make sense to anybody. I'm not a magician.'"Rather than fighting this identity, Moni transformed it into something bigger. She embraced her role as a "marketing educator" focused on teaching fundamentals to a generation that reduces marketing to:* Getting attention* Creating content * Generating leads"That's the result," she argues. "That's not what marketing is." This educational perspective allows her to leverage her operational expertise while addressing systemic issues in marketing practice.Key takeaway: Your marketing operations expertise gives you unique system-level insights nobody else possesses. Stop trying to escape this identity. Instead, use your operational knowledge to command respect by translating technical realities into business language executives understand. Create clear boundaries around what technology can and cannot solve. When handed unrealistic expectations, respond with specific prerequisites for success. Your value comes from connecting strategy with execution; making you the bridge that transforms marketing from theory into measurable results.Stop Crediting Random Marketing Assets For ConversionsThat gnawing feeling you get when reviewing complex attribution reports should be trusted.. Your instincts know something your dashboards don't. Moni cuts through years of marketing dogma with a refreshingly brutal assessment: "I thi...

What's up everyone, today we have the pleasure of sitting down with Constantine Yurevich, CEO and Co-Founder at SegmentStream. Summary: Multi-touch attribution is a beautifully crafted illusion we all pretend to believe in while knowing deep down it's flawed. The work is mysterious, but is it important? The big ad platforms sell us sophisticated solutions they don't even trust for their own internal decisions. Is it time we accept marketing causation is a thing we can't measure? Visitor behavior scoring is a really interesting alternative or extra ingredient to consider. Often thought of as a tool for lead management to help prioritize your SDR's time, the team at SegmentStream started using the same scoring methodology, but with an attribution application. Enter synthetic conversions. Instead of just tracking conversions, track meaningful visits like  time spent, pages explored, comparisons made. This allows you to connect upper-funnel campaigns to real behavior patterns rather than just looking at who converted in a single session. About Constantine/SegmentStreamSegmentStream was founded in 2018 in LondonFeb 2022 raised a first funding round of 2.7MSegmentStream is now trusted by more than 100 leading customers across the globe including L'Oreal, KitchenAid, Synthesia, Carshop, InstaHeadShots, and many othersThe Messy Truth About B2B vs B2C Attribution ModelsPrice tags and decision timeframes obliterate the B2B/B2C attribution divide faster than most marketers realize. Constantine shatters conventional wisdom by showing how his team leverages their own attribution tools to measure website engagement because enterprise software purchases rarely follow predictable patterns. "Trusting last click is impossible," he explains, "because it takes too much time before conversion happens."You've likely noticed this pattern in your own marketing stack. A $2,000 direct-to-consumer exercise bike creates the same multi-touch, 60-day consideration journey as many supposedly "straightforward" B2B software purchases. Meanwhile, those $30/month SaaS tools targeting small businesses convert with the immediacy of consumer products. Constantine points out how this pricing reality creates measurement challenges that transcend business categories:High-ticket B2C products demand extended 30-60 day consideration windows SMB-focused B2B subscriptions ($20-30/month) behave like impulse purchasesEnterprise B2B sales cycles stretch beyond a year with critical offline componentsThe offline measurement void plagues marketers everywhere. Constantine admits many of his most valuable marketing activities resist quantification. "I write a lot of LinkedIn posts, newsletters, we do podcasts. Some of these activities are very hard to measure unless you explicitly ask someone, 'How did you hear about us?'" Your gut tightens reading this because you've felt this same tension between attribution models and marketing reality.Scale transforms your attribution approach more dramatically than business classification ever could. Small operations handling 100 monthly leads can simply ask each prospect about their discovery journey. Large enterprises processing thousands of conversions require sophisticated multi-touch models regardless of whether they sell to businesses or consumers. Constantine explains this convergence clearly: "When we talk about larger B2B businesses with thousands of leads and purchases, it becomes more similar to B2C with a long sales cycle plus an offline component."The unmeasurable brand-building activities require a leap of faith that makes data-driven marketers squirm. Constantine embraces this uncertainty with refreshing honesty: "When you post on LinkedIn, build your personal brand, share content—that's really hard to measure and I don't even want to go there." His team focuses on delivering value through content, trusting that results will materialize. "You just share your content and eventually you see how it plays off." This pragmatic acceptance of attribution limitations feels like cool water in the desert of measurement obsession.Key takeaway: Match your attribution model to purchase complexity rather than business category. Implement multi-touch attribution with lead scoring for high-consideration purchases across both B2B and B2C, while accepting that valuable brand-building work often exists beyond the reach of your measurement tools.Why Marketing Attribution Still Matters Despite Its FlawsAttribution chaos continues to haunt marketers drowning in competing methodologies and high-priced solutions. Constantine blasts through the measurement fog with brutal practicality when tackling the Multi-Touch Attribution (MTA) debate. While many have written MTA's obituary due to its diminishing visibility into customer journeys, his take might surprise you.The attribution landscape brims with alternatives that look impressive in PowerPoint presentations but crumble under real business conditions:Geo holdout testing sounds brilliant: Turn off ads in half your markets, keep them running in others, measure the difference. Simple! Except it'll cost you millions in lost revenue during testing. Constantine points out the brutal math: "For some businesses, this is like losing 1 million, $2 million during the test. Would you be willing to run a test that's gonna cost you $1 million?" These tests require a minimum 5% revenue contribution from the channel to even register effects, making them impractical for anything but your biggest channels.MMM promises statistical rigor: But demands absurd amounts of data covering everything from your competitors' moves to presidential elections and global conflicts. Good luck collecting that comprehensive dataset spanning 2-3 years, then validating whether the TV attribution your fancy model spits out actually reflects reality.> "Mathematically, everything works fine, but when you apply it in reality, there is no way to test it. You just see some numbers and there is no way to test it."For scrappy D2C brands, SaaS startups, and lead gen businesses, Constantine argues MTA still delivers more practical value than its supposedly superior alternatives. You won't achieve perfect attribution, but you can compare campaigns at the same funnel stage against each other. Your lower-funnel campaigns can be measured against other lower-funnel efforts. Mid-funnel initiatives can compete with similar tactics.Constantine drops a bombshell observation that should make you question the industry's MMM evangelism: "If Google and Facebook so willingly open-source different MMM technologies and they really believe in this technology, why wouldn't they implement it into their own product?" These data behemoths with unparalleled user visibility still rely on variations of touch-based attribution internally. Something doesn't add up.Key takeaway: Stop chasing perfect attribution unicorns. MTA delivers practical campaign comparisons within funnel stages despite its flaws. For most businesses, sophisticated alternatives cost more than they're worth in lost revenue during testing or impossible data requirements. Compare apples to apples (lower-funnel to lower-funnel campaigns) with MTA, test different creatives, and focus on relative performance improvement. The big platforms themselves don't fully trust their publicly promoted alternatives - why should you bet your marketing budget on them?Simplified MMM is a Measurement Fantasy You're Being SoldMarketing Mix Modeling has roared back into fashion as third-party cookies crumble and marketers scramble for measurement alternatives. Constantine cuts through the hype with brutal clarity. Traditional MMM demands...

What's up everyone, today we have the pleasure of sitting down with Ashley Faus, Head of Lifecycle Marketing at Atlassian. Summary: Marketing frameworks often fail because they ignore how humans actually behave. People don't follow neat, linear paths; they explore, double back, and leap ahead based on genuine interests. Drawing from her diverse experience across corporate communications and lifecycle leadership, Ashley exposes how artificial walls between marketing functions create dysfunction while offering a solution: an integrated ecosystem where audience insights, compelling content, and strategic distribution flow continuously between teams. Her approach identifies truly predictive behaviors and measures success through bold experiments rather than smaller tweaks. By respecting how people naturally learn and make decisions, Ashley's content structure creates pathways that connect conceptual, strategic, and tactical pieces, making your content genuinely valuable to visitors and dramatically more effective at converting those ready to purchase.About AshleyAshely started her career with generalist marketing roles at a bunch of different small companies before settling into a role in the commercial aviation industryShe took on a generalist Marketing role at a training firm where she got a taste of marketing operations including a Marketo integration and lots of email campaignsShe later had 2 content strategy and product marketing roles at network security companiesToday Ashley is Head of Lifecycle Marketing, Portfolio at Atlassian where she's been for over 7 yearsShe's been interviewed on more than 50 podcasts, her writing has been published on TIME, Forbes, MarketingProfs, she's a well traveled speaker and she has an upcoming book coming out in May called ‘Human-Centered Marketing: How to Connect with Audiences in the Age of AI'Why You Should Look for a New Job Every 18 MonthsAshley has spent over seven years at Atlassian, navigating through four distinct roles while the company itself transformed dramatically around her. This longevity stands out in an industry where most professionals change employers every 2-3 years. Through corporate communications, integrated media, product marketing, and now lifecycle marketing, she's crafted multiple careers without changing her email address.> "I look for a new job every 18 months, so that I am prepared to make a move and solve for any gaps at that roughly two to two and a half year mark.""I look for a new job every 18 months," Ashley explains, "so that I am prepared to make a move and solve for any gaps at that roughly two to two and a half year mark." This calculated strategy creates perpetual career momentum. You begin exploring opportunities six months before the typical stagnation point, positioning yourself to evolve professionally right when most people start feeling restless. The genius lies in the timing: plan your next move while you still love your current role, not after burnout or boredom sets in.The company Ashley joined barely resembles today's Atlassian. "We actually have grown like five or six times, both from an employee standpoint and from a revenue standpoint as well," she notes. This parallel evolution of both person and organization created a unique synergy, allowing her to ride waves of company growth while pursuing her own skill development.Her initial role came with an unexpected twist. Despite being hired for corporate communications, PR represented one of her weaker skill areas. During interviews, the hiring manager focused more on her versatility across content strategy, email marketing, and social media. Genuine curiosity opened doors that formal applications never could. "Because I was nosy and stuck my nose in other people's business," she admits candidly, "they were like, 'should you come sit with us?'" These informal interactions led to her integrated media role, which connected previously siloed functions:Press relationsOwned channels like email and socialThought leadership contentBrand marketing campaignsAshley applies this proactive mindset when managing her team. She challenges them with pointed questions about their future: "Who do you want to be when you grow up? Are you growing up in the next year? In the next five years?" This framing transforms vague aspirations into concrete timelines. "That breakdown of how to get to where you want to be in 10 years, 15 years, 20 years starts with the next 12 months or 24 months," she explains.The social media team placement at Atlassian illustrates how organizations evolve their understanding of marketing channels. "At the time, our social media person sat on the email team because the mindset was that this is a broadcast channel," Ashley recalls. Both she and her interviewer recognized the flawed logic in treating social platforms as one-way communication tools, creating immediate rapport around a shared marketing philosophy.Key takeaway: Schedule dedicated job hunting time every 18 months, even when fully satisfied with your current position. This practice maintains your market value, expands your professional network, and positions you to make strategic moves at the two-year mark when growth typically plateaus. The next perfect role might exist within your current company if you actively seek it out.The Overlap Between Lifecycle, Content and Product MarketingMarketing departments love creating artificial walls between functions. Product marketing owns messaging. Content creates assets. Lifecycle handles channels. We've all seen the org charts with their neat little boxes. Ashley brings refreshing clarity to this organizational fallacy, particularly for companies using product-led growth strategies where traditional marketing borders simply cannot hold.The organizational divide shifts dramatically depending on your go-to-market motion. "In larger companies using product-led growth versus a sales-led motion, there's a lot more blurring of the lines," Ashley explains. SEO strategy, trial signups, and in-product upgrade experiences often migrate to product marketing in PLG companies, even at enterprise scale. This reveals a fascinating truth many marketers miss: your core GTM motion fundamentally reshapes role boundaries more than company size does.> “I don't understand how you're gonna write content with no insights from the market, the competition, and the audience. I don't understand how you're gonna distribute content with no understanding of the channel mix and the quirks of the different channel."Ashley's decade of experience across multiple marketing functions gives her rare perspective on their interdependence. Ten years ago, she led marketing strategy at Duarte when marketing automation platforms were just becoming table stakes. "I actually had to do the RFP, choose between Marketo, Pardot, or Silverpop," she recalls. This hands-on experience taught her how lifecycle marketing (channels, nurture campaigns, cross-sell strategies) and content marketing (creating assets for those channels) form an inseparable partnership:Content marketing typically focuses on creating assetsLifecycle marketing typically focuses on channel strategyBoth become meaningless without the other's expertiseAt large companies like Atlassian, specialization creates absurd scenarios where a single email might involve five different people: one writing copy, another creating visuals, someone handling lead scoring, another doing audience segmentation, and finally someone building and testing the actual email. While this level of specialization brings depth, it risks bre...

What's up everyone, today we have the pleasure of sitting down with Ruari Baker, Co-Founder and CEO of Allegrow. Summary: Your fancy AI personalization messaging strategy doesn't mean anything if you don't also have a strategy for email deliverability. Ruari busts long-standing myths about HTML vs plain text, why open rates died with Apple's 2021 privacy changes, and why the spam complaints visible in your marketing platform represent a fraction of reality. You'll walk away with 3 deliverability tactics that will help you reach the inbox and stay there: implement multi-subdomains to isolate high-risk traffic, adopt contact risk scoring that transcends basic validation and start using Google Postmaster to see your actual reputation metrics. Escape the promo tab without sacrificing design, resurrect damaged domains, and find out why traditional seed testing is worthless. If you depend on email, this might be the best 40 minutes you'll spend this month. About RuariRuari started entrepreneurship early (at 18 years old) and joined a startup accelerator where he received mentorship from top tech founders in the UK as well as his first investmentHe co-founded Direct Software, a GDPR-first marketing automation solution where he gained a deep understanding of email deliverabilityToday, Ruari is Co-Founder and CEO of Allegrow, an email deliverability platform to help emails reach the primary inbox, not the spam folderPlain Text Emails Will Always Outperform HTML Emails When it Comes to Inbox PlacementThe HTML vs text email question hangs over every marketer's campaign planning session like a dark cloud. Ruari slices through this persistent debate with razor-sharp clarity. Context dictates winners here, not blanket rules. For outbound sales, plain text creates an authenticity that HTML instantly kills. Think about it—you craft personal emails without fancy formatting. The second your recipient spots that polished design, their brain categorizes your message as "marketing material," and your personalization efforts crumble.> “You can't just simply say 'always plain text, that's better.' The reality is there are still good business reasons for using Rich HTML, and that's why it is such a popular way to send emails from a marketing perspective.”Email providers have learned to associate complex formatting with promotional content that users often ignore. Your deliverability suffers accordingly. Yet HTML emails persist for good reason:Large subscriber lists benefit from HTML's clickthrough tracking capabilitiesE-commerce companies generate higher engagement when customers see products directlyVisual brands communicate their identity more effectively through designed templatesData-heavy messages become more scannable with proper formatting and hierarchyThe winning strategy lives somewhere in the messy middle. "If you're using HTML for legitimate marketing emails to an opted-in list, implement these practices to maintain deliverability," Ruari advises. Clean your entire list monthly—remove invalid contacts, keep bounce rates low, and eliminate potential spam trap subscriptions. This simple 30-day hygiene ritual dramatically improves your sender reputation with both ESPs and inbox systems.HTML devotees should strategically incorporate plain text messages at key points in the subscriber journey. These unadorned communications slip past promotion folder algorithms, landing you in the primary inbox. This placement success creates a virtuous cycle, improving future message placement—even for your HTML campaigns. You must also implement a sunset policy for engagement maintenance. When subscribers show zero activity over your predetermined period, place them into a final-attempt workflow. No response? Remove them proactively. This keeps your engagement metrics healthy, the exact data points email providers scrutinize when judging your sending quality."I once worked with an e-commerce client who switched half their abandoned cart emails to plain text," Ruari shares. "Their revenue per email jumped 22% because more messages reached the primary inbox." The results speak volumes about matching format to objective rather than defaulting to what looks prettiest in your marketing dashboard.Key takeaway: Match email format to specific objectives. Use plain text for sales outreach and relationship-building. Deploy HTML strategically for e-commerce and visual campaigns. Maintain ruthless list hygiene by removing invalid contacts monthly, sending occasional plain text messages regardless of your primary format, and cutting unengaged subscribers after final reactivation attempts. Your deliverability—and ultimately your results—depend on this discipline.Create a Sunset Policy Based on Your Specific Industry Engagement PatternsYour email list contains a ticking time bomb of disengaged contacts that silently damage your sender reputation with every campaign. When asked about the right timeframe for removing inactive subscribers, Ruari offers a refreshingly nuanced take that shatters the "six-month rule" most marketers blindly follow. The optimal sunset policy timing depends entirely on your industry and baseline engagement metrics. Smart marketers look to identify and remove the bottom quartile or decile of subscribers based on engagement patterns specific to their audience.High-engagement industries demand different standards than low-engagement sectors. Imagine running email marketing for a compliance software company—a field few people find "sexy." Your engagement metrics naturally run lower than consumer brands, but those rare engagement spikes matter tremendously. When someone suddenly engages with your SOC 2 audit content after months of silence, that signals a critical buying window. Cutting them off after six months of inactivity would sacrifice valuable revenue opportunities unique to your industry cycle.You must establish internal benchmarks that reflect your specific business reality. Study your engagement patterns over 12-18 months. Look for natural dropoff points. Analyze which inactive subscribers eventually reactivate and what triggers that behavior. Create segments based on these findings, then craft sunset workflows that reflect the actual customer journey in your space. For some businesses, 90 days makes sense. For others, 12 months barely captures their sales cycle.> “At least having some sunset policy in place would already put you leaps and bounds ahead of the majority of your peers.”The mere existence of a sunset policy puts you "leaps and bounds ahead of the majority of your peers," Ruari points out. Most marketers obsessively protect their list size, treating subscriber counts as a vanity metric rather than focusing on engagement quality. They hoard inactive emails like digital dragons, destroying deliverability in the process. Your sunset policy doesn't need to be perfect—it simply needs to exist and run consistently. Start by removing obvious dead weight: bounced addresses, spam complaints, and truly inactive accounts. Then refine your approach as you gather more data about your specific audience patterns.Key takeaway: Create a sunset policy based on your specific industry engagement patterns rather than arbitrary timeframes. Identify your bottom-performing subscriber segment (by quartile or decile) and implement an automated workflow to either re-engage or remove them. Even an imperfect sunset policy executed consistently will dramatically improve your deliverability metrics and campaign effectiveness compared to never removing inactive subscribers.How to Escape Google Promotions Tab Prison Without Sacrificing DesignYou send a gorgeous HTML email campai...

What's up everyone, today we have the pleasure of sitting down with Danielle Balestra, Director of Marketing Technology and Operations at Goodwin. Summary: Marketing operations power organizational change through deep system understanding. Danielle reveals how strategic operators transform corporate landscapes by mapping intricate human networks, turning complex bureaucracies into adaptive innovation platforms. Her approach reconstructs marketing from a tactical function into a critical strategic driver, where understanding organizational dynamics becomes the primary method of creating meaningful business transformation.About DanielleDanielle started her career at a big ad agency in NYC before trying marketing at all sorts of different places like b2b media, financial education and brand reputation intelligenceShe spent time as a Senior consultant at a boutique agency and also freelanced as a Marketo specialistShe became Director of Marketing Ops at one of the top cancer hospitals in the US and later VP of Marketing Ops at CIT Bank where she led a big MAP transformationToday Danielle is Director of Martech and Operations at Goodwin (a global law firm), where she manages of team of 16 that includes web, CRM, Ops, Email and Solution ArchitectHow to Defeat Enterprise Inertia with Tactical Marketing Ops StrategiesMarketing ops in enterprise moves like molasses compared to SaaS startups—and Danielle has the battle scars to prove it. After years in consulting, she deliberately jumped into the enterprise arena, not despite its notorious sluggishness but because of the massive internal transformation potential. "The reason I pivoted into large enterprise was because it's an opportunity to sell innovation internally, but also get paid," she explains with refreshing candor.You face a completely different animal when implementing martech in a 4,000+ employee organization. Your job morphs into part-marketer, part-internal lobbyist:Finding the hungry change-makers scattered across departmentsBuilding coalitions with colleagues who crave efficiency Selling the vision repeatedly to overcome institutional inertiaImplementing solutions that feel revolutionary in environments resistant to changeThe satisfaction comes from moving mountains that seemed immovable. Tech startups already expect and fund scaling technologies—the path glows with green lights. Enterprise paths bristle with red tape and "we've always done it this way" roadblocks.Danielle's enterprise journey reads like a marketing ops fairytale gone rogue. "My three enterprises was like Goldilocks," she laughs. Memorial Sloan Kettering, despite its prestigious reputation, crawled at a pace that drove her to distraction. "It took us six months to put a preference center up. This is way too slow." The bed was too soft. CIT offered more speed but lacked investment for sustained growth. The bed was too hard.Then came Goodwin, where the legal industry's appetite for evolution aligned with her expertise. Fresh leadership—a new COO and chairman committed to "running business with data and intelligence"—created fertile ground for her marketing ops vision. This bed was just right. The transformation feels electric precisely because legal firms typically move at glacial speeds.You'll recognize the right enterprise fit when leadership actively hungers for data-driven decisions rather than merely talking about them. Words matter less than resource allocation and willingness to disrupt comfortable patterns.Key takeaway: Map internal influence networks, document wins with leadership-valued metrics, and secure early budget control. Build a six-month roadmap of small victories that advance your larger vision without triggering organizational resistance. Treat internal stakeholders as customers by selling efficiency improvements as competitive advantages.Why Enterprise Martech Can Be as Fun as Tech StartupsEnterprise martech gets a bad rap for being outdated and slow. "Legacy enterprise tools-ish," as the skeptics call platforms like Microsoft Dynamics and Marketo. But this surface-level dismissal misses what actually happens inside regulated industries. Danielle dismantles this misconception with the calm precision of someone who's lived both worlds. "Being in a healthcare organization, being at a bank, do you really want to put your data out there for anyone to grab?" It's a practical question that trendy martech vendors conveniently sidestep.> "The banks and even some financial institution clients have had data lakes and orchestration systems in place for over two decades. This is old hat for them and just new for the tech world."Regulated industries pioneered data intelligence while today's "innovative" startups were still in diapers. "The banks and even some financial institution clients have had data lakes and orchestration systems in place for over two decades," Danielle points out with a hint of amusement. "This is old hat for them and just new for the tech world." The irony stings: what passes for cutting-edge today has been standard operating procedure in banking since before most SaaS companies existed. These industries understood customer behavior, engagement patterns, and product usage long before "customer journey orchestration" became a conference buzzword.The real enterprise challenge isn't technological capability—it's processing time. When vendor onboarding takes nine months and you need a solution in six, you return to established platforms with comprehensive portfolios. Danielle's experience with an event scanner technology purchase illustrates this perfectly: "We started the process in 2019 and ended it in mid-2020. It took us almost a year to process that." During that implementation period, the vendor was acquired by another company! You face two options:Wait patiently through lengthy security reviews for innovative toolsExpand usage of already-approved enterprise platformsAccept that this gatekeeping prevents wasteful impulse purchasesAcknowledge that crucial tools still eventually make it throughMicrosoft Dynamics gets unfairly maligned in this "latest and greatest" obsession. Danielle's first experience with the platform revealed unexpected advantages: "Working with an organization that still programs and builds from their own code is pretty awesome." With native integrations, consistent data across systems, and direct connections to BI reporting through Fabric, Dynamics eliminates the integration headaches that consume marketing operations teams. No more asking, "Why is this in Salesforce but not in Marketo?" The data lives in one cohesive environment.Key takeaway: Master enterprise martech by: (1) Ruthlessly audit system integration points, recognizing each connection as a data vulnerability and maintenance challenge. (2) Distinguish between product limitations and implementation failures by testing workflows across deployments. (3) Create a security-first evaluation matrix scoring tools on compliance, data isolation, and authentication before considering features. Transform security constraints into competitive advantages that protect data and career.Building Martech Stacks That Solve Actual Business ProblemsEnterprise martech builds differently—forget your perfect-world stack exercises. While workshop participants happily connect hypothetical Salesforce instances to Outreach in frictionless diagrams, real enterprise teams face vendor mandates and security roadblocks that crush agility. "You can't really just connect to this," as the stark reality goes. Danielle brings refreshing clarity to this enterprise constraint, flipping perceived limitations into p...

What's up everyone, today we have the pleasure of sitting down with Rich Waldron, Co-founder and CEO at Tray.ai. Summary: Marketing ops folks stand at a crossroads where iPaaS platforms and AI agents are colliding in crazy ways. Rich pulls back the curtain on what happens when workflows become agent "skills": Imagine your carefully built automations transformed into autonomous assistants that diagnose tech issues, provision applications, and manage complex Salesforce campaigns without manual intervention. Your marketing stack could suddenly act like a "junior admin" on demand, while you focus on strategy. The explosion of AI features has turned martech leaders into "AI referees" juggling competing vendor tools, yet those who master both fundamentals and experimental curiosity become "10X automation heroes" - the first teammates that are called when problems need solving. As Rich explains, career security comes from momentum, not stability.About RichAfter University, Rich spent several years building different projects in the UK which included a web agency, a media company and a mobile app for social gatheringsTray was officially founded in 2013, bootstrapped by selling Wellington boots on eBay – the early product idea was email automation but pivoted to enabling less technical people to utilize APIs to integrate their tech stackAlongside his 2 co-founders, they spent the better part of 4 years building the product and raising a seed round in 2015. Between 2018 and 2020, Tray grew from $500k to $20M ARRToday, Tray processes Billions of transactions across the platform every month and they've gone all in on the composable AI integration and automation movementThe Rise iPaaS and AI OrchestrationiPaaS exploded because enterprise suites were too slow to open up their integration capabilities. CDPs made similar mistakes with rigid architectures, birthing today's composable alternatives. Every software system eventually faces the same primal challenge: intercommunication. Rich recounts how this pattern also repeats throughout computing history with startling consistency. Monolithic ERPs dominated early landscapes, where engineers cobbled together custom connections between internal components. These hand-built bridges crumbled easily, leaving teams scrambling for standardized frameworks that could withstand daily operational stress.As specialized software proliferated around these central systems, integration pressure mounted. "We're still not that far through on adopting the cloud," Rich points out, puncturing the tech bubble many of us live in. While cloud technologies feel omnipresent to industry veterans, countless organizations remain firmly planted on physical servers. This reality created distinct evolutionary phases for iPaaS:On-premise to on-premise connections (the original integration challenge)On-premise to cloud bridges (MuleSoft's territory)  Cloud-to-cloud orchestration (where Tray focused)Each phase demanded fundamentally different architecture. Cloud applications introduced unique payload structures, execution patterns, and API designs that rendered previous integration approaches obsolete. "Every application now has an API," Rich explains, describing how this technical shift triggered organizational transformation. Marketing departments grew increasingly technical, with marketing ops professionals discovering they could craft custom experiences by tapping into these newly accessible APIs.> "iPaaS has to evolve because if your iPaaS was built purely for an era when AI wasn't a consideration and your customers are now suddenly saying, 'We're looking at how we infuse AI in these processes,' the requirements have changed again."You've likely witnessed this evolution in your own organization. Remember when connecting two systems required an IT ticket and weeks of waiting? Now your marketing team builds automations while the sales team creates their own customer journey orchestrations. Technical power diffused across departments, democratizing integration capabilities previously locked behind developer expertise.Today's iPaaS platforms face their greatest evolutionary pressure yet: AI integration. Rich describes how existing processes built on traditional platforms now crumble under AI's weight. Semantic analysis, novel reasoning models, and entirely new integration approaches have rewritten the rules. iPaaS vendors who built for the pre-AI era now race to adapt as customers demand intelligent workflows. The platforms that flourish will embrace AI as a core architectural principle rather than a bolted-on feature.Key takeaway: Evaluate your integration platform based on whether it was (re)designed for today's AI-centric landscape or simply patched to accommodate it. The most effective iPaaS solutions evolve alongside major architectural shifts rather than struggling to catch up after they've occurred.What Makes an Agent Truly "Agentic" Beyond the Marketing HypeThe AI agent landscape is blurring with contradictions and wild claims and it's only going to get crazier. While vendors plaster "agent" labels on everything with an algorithm, Rich isn't worried about definition. The terminology matters far less than what these systems actually do. > "The AI isn't just reasoning over a set of data, but it's actually going and taking action on a user's behalf... I've done the response for you and I've handled the follow up and I've gone and filed this over here, and it's actually carrying out a series of actions based on the reasoning that occurred in the first place."AI agents take autonomous action. They handle support tickets end-to-end. They file documents. They complete multi-step processes without human intervention. They execute rather than suggest.Tray's team experienced genuine goosebump moments when they combined their connector infrastructure with LLM reasoning. You could almost hear the click as puzzle pieces fell into place. Their ten-year vision suddenly materialized before their eyes:Semi-technical staff performing complex cross-organizational tasksTeams breaking free from application limitationsWorkers escaping data accessibility problemsAI executing the best next steps, not just recommending themThis capability triggered an immediate "holy shit" reaction during internal testing. Everything changed in that moment. The strategic implications struck like lightning: adapt or die. Many category leaders fail exactly here, at this precipice of change, clinging to outdated paradigms while disruptive innovation rewrites the rules.The adoption curve is also likely to be shockingly steep. Century-old enterprises with conservative DNA are already running AI workloads in production using Tray. Some skipped entire technological generations, leapfrogging directly into AI implementation. They've dumped their data into databases, layered AI analysis on top, and built reactive systems around the outputs. The comfort level with these technologies has accelerated across industries at a pace that defies conventional adoption timelines.When Tray rebranded from tray.io to tray.ai, they acknowledged that connection alone provides insufficient value in this new world. The platforms that enable autonomous action through AI will dominate the future landscape. The rest will fade into technological obscurity, remembered only as stepping stones.Key takeaway: The future competitive advantage in your martech stack is going to come from AI that acts on your behalf, not just analyzes and recommends. When you implement systems where AI executes complex workflows based on reasoning, you empower your teams to achieve broader impact with fewer technic...

What's up everyone, today we have the pleasure of sitting down with Angela Rueda, Director of Business Martech at Meta. Summary: Angela walked into Meta's engineering-first culture, discovering a sprawling mess of DIY custom martech solutions, and leading the organization through a fundamental mindset shift about build vs. buy decisions. She brings us through the technical and emotional journey of aligning more than 150 stakeholders ultimately forcing them to embrace a hybrid build-and-buy approach during a pivotal merger. Angela shares an honest look at what it means to lead big changes at a company like Meta, showing what really works when you're trying to transform how marketing and technology work together.About AngelaAngela started her career in the agency world before moving over to the financial services sector at Capital Group She took a break from the corporate world and co-founded a lifestyle product company for moms and babiesShe later returned to finance and joined Citibank where she would spend the next 8 years growing into a Director of Marketing Capabilities roleToday Angela is Head of Business Martech at Meta where she's building a new team of data and performance marketersBuild vs Buy: Meta's Transformation to a Hybrid Martech StackBuilding custom marketing technology sounds like a tech leader's dream: unlimited resources, world-class engineers, and total control over the final product. Angela walked into Meta with stars in her eyes, ready to architect a marketing infrastructure that would reach 200 million global businesses. The mandate sparkled with possibility - create something truly custom, uniquely Meta, uniquely powerful.Then reality hit. Meta's growth had spawned a sprawling organism of marketing tools, each piece stitched onto the next as urgent needs arose. What looked like a blank canvas from the outside turned out to be a complex tapestry of tactical solutions, each thread woven tight to solve an immediate problem. The engineering team kept adding features:Custom targeting modules for specific campaignsProgram-specific deployment toolsSiloed analytics systemsFragmented automation workflowsFor that first year, Angela doubled down on the in-house vision. Meta's engineering DNA made external tools feel almost taboo. The team kept building, feature by feature, convinced they could craft the perfect solution. You might recognize this mindset - when you're surrounded by brilliant engineers, buying off-the-shelf software feels like admitting defeat.A major organizational shift cracked the foundation of this thinking. Business marketing teams merged, exposing a stark reality: half the company used internal tools while the other half relied on third-party platforms. Maintaining multiple stacks drained resources and created confusion. The breaking point arrived organically - continue forcing an internal-only approach, or step back and reimagine the entire stack?This constraint sparked the creative breakthrough Angela had dreamed of, just not in the way she expected. The pressure to consolidate forced hard questions about build versus buy decisions. The team had to examine their assumptions about custom development and weigh them against business needs. That original blank canvas materialized after all, painted with the colors of experience rather than theory.What makes Meta's story feel universal is that enterprise teams everywhere build tech kingdoms in isolation, they're all racing toward their own goals with blinders firmly in place. Marketing squads assembling custom tools and processes at breakneck speed, treating enterprise-wide alignment as a distant luxury and a future-team problem. Then all of a sudden, organizational shifts take place. Restructures, mergers, leadership overhauls… they generate enough force to crack these silos open. When the dust settles and processes collide, teams finally see the cost of their fragmented systems.Key takeaway: Build a hybrid Martech approach: identify core functions that need customization, integrate best-in-class tools for standard operations, and focus engineering resources on unique competitive advantages. Track implementation time and team satisfaction to measure impact.Why Meta Ultimately Ditched Their DIY Martech StackMeta's engineering culture practically demanded they build everything in-house. You could feel it in every meeting: the subtle eye rolls when someone mentioned third-party tools, the reflexive reach for custom solutions, the collective pride in crafting bespoke technology. Their homegrown marketing stack embodied this philosophy, sprouting feature after feature until it required a small army of PhDs just to create basic audience segments.Angela walked into this technical labyrinth with a mandate to reach 200 million global businesses. The existing tools scattered across Meta's landscape told a story of rapid growth and tactical thinking:Data lived in isolated kingdoms, making it impossible to identify true marketable audiencesCampaign targeting required advanced degrees and dedicated data science teamsChannel activation cobbled together "omnichannel" experiences through manual patchesSales and marketing data existed in parallel universes, never quite connectingThen came the organizational earthquake: a massive merger that exposed half the company running on internal tools while the other half relied on external platforms. The duplicate systems drained resources faster than a leaky pipeline. This crisis created a rare moment of organizational clarity, pushing Angela's team to step back and question their build-everything DNA.The evaluation process sparked intense emotions. Engineers who poured years into custom solutions defended their work with spreadsheets and scoring frameworks that mysteriously always ended in perfect ties. You could see the internal struggle written across faces in every meeting: let go of years of custom development or double down on the DIY approach? The breakthrough came through radical simplicity. Meta chose to build where they held unique advantages (their data foundation) and buy proven solutions for standard capabilities. This hybrid model gave both the engineering perfectionists and practical business stakeholders something to embrace.Key takeaway: Start with ruthless problem definition before touching tools. Map your unique challenges, build organizational alignment around those problems, then evaluate build versus buy decisions through that lens. Your best solution might combine internal strengths with external innovation, creating a practical path forward that serves both technical excellence and business reality.Build vs Buy Was Really Privacy Control vs Speed to MarketEngineering pride runs deep at Meta. Their developers wield a particular swagger, architecting some of the world's most sophisticated social platforms. So when Angela's team questioned whether to keep building marketing tools in-house, the debates turned fierce. The war room crackled with strong opinions about resource allocation, privacy constraints, and the true cost of maintaining bespoke systems.The arguments for building centered around three thorny challenges:Privacy requirements demanded granular control over data handlingData transfer costs between systems could balloon into millionsComplex account mapping for B2B marketing defied off-the-shelf solutionsYet the buy advocates painted a compelling picture: Meta's elite engineers could focus on revenue-generating products instead of reinventing marketing wheels. Angela watched the back-and-forth intensify as both camps dug in their heels. One side...

What's up everyone, today we have the pleasure of sitting down with Mac Reddin, Founder and CEO of Commsor. Summary: Mac treks through the Jurassic wilderness of modern sales, where outbound campaigns cannibalize themselves while AI-powered sequences are degrading response quality by the day. Real marketing power flows through human networks, forward-thinking companies are transforming their SDR teams into relationship architects who measure success through network depth and authentic engagement. Be the team that does better. Your competitive edge lives in human connections that no algorithm can replicate, requiring a complete rethinking of how we incentivize and measure revenue team success.About MacMac is a career-long entrepreneur, his first business was a gaming network built on top of Minecraft which peaked at 150k users per dayHe went on to create various bootstrapped businesses over the course of 5 yearsHe created a substack newsletter for the community space which eventually evolved into an actual community of over 10k people One day he took part in a no-code hackathon and the idea of Commsor was born, initially a community reporting and metrics platformToday Commsor is a 40-person company focused on curated introductions and building the go-to-network movementThe Origin of the Dinosaur Brand Came From a TypoA misspelled tweet transformed Commsor's brand identity forever. Someone wrote "Commsaur" instead of "Commsor" on Twitter, sparking an organic evolution that proves how authentic brand moments outperform manufactured marketing strategies.The story unfolds with raw honesty from Mac: "It became an inside joke, then our internal branding, and eventually our entire visual identity." No marketing committees. No focus groups. No desperate attempts to retrofit meaning into the accident. The team simply recognized the genuine enthusiasm building around their accidental dinosaur mascot and rolled with it.Consider these organic moments that cemented the dinosaur's place in Commsor's DNA:* A casual Slack screenshot sparked employee excitement* Internal conversations naturally incorporated dinosaur references* Team members added dinosaur emojis to their social profiles* Customers started associating the brand with its prehistoric mascotThe business impact materialized in unexpected ways. One prospect lost Commsor's name but remembered the dinosaur. They scoured LinkedIn for employees with dinosaur emojis in their profiles, found the company again, and booked a demo. This kind of brand recall demonstrates how authentic visual elements create deeper connections than carefully crafted corporate identities.Mac's experience teaches a powerful lesson about modern branding: manufactured meaning falls flat. When the team needed a new logo, they faced zero resistance to the dinosaur concept because it already represented their culture. You can't engineer this kind of organic brand evolution in a marketing workshop or through trend analysis.Key takeaway: Authentic brand moments emerge from genuine team interactions and customer connections. A typo-inspired dinosaur logo drives more business value than countless hours of strategic brand planning because it represents something real: a company culture that embraces creativity, humor, and happy accidents.Why Your Mass Outbound Strategy Cannibalizes ItselfMass outbound marketing operates like a ravenous snake devouring its own tail. Every blast campaign you send erodes response rates across the entire ecosystem, forcing you to send even more emails to hit your targets. Mac draws on the ancient Ouroboros symbol to illustrate this self-destructive pattern playing out in marketing departments worldwide.You feel the tension daily: outbound outreach serves essential business functions. Your team needs to:* Connect with potential podcast guests* Build strategic partnerships* Source vendor relationships* Develop sales opportunities* Nurture industry relationshipsYet the industrialization of this process through purchased contact lists and templated messages has created a toxic environment. Response rates plummet while marketing teams double down on volume, hoping quantity will save them. The math gets uglier each quarter: 10,000 emails become 20,000, then 50,000, as engagement metrics spiral downward. Your carefully crafted messages drown in an ocean of automated noise.Mac points to the last two years as a breaking point. Marketing teams hurtle toward catastrophe like Thelma and Louise, eyes locked on the dashboard metrics instead of the cliff ahead. The cognitive dissonance feels suffocating - everyone privately acknowledges the broken system while publicly defending increasingly desperate tactics. AI tools threaten to accelerate this race to the bottom by making it even easier to flood inboxes with personalized-but-soulless outreach.Your outbound strategy needs a reset focused on human connection. Replace mass automation with careful curation. Send fewer messages with deeper personalization. Study your target accounts' actual needs before reaching out. The marketers who thrive will build systems around quality interactions, not maximum velocity. This shift feels counterintuitive when every internal metric pushes for more volume, but the alternative leads off a cliff.Key takeaway: Break the cycle of mass outbound marketing by prioritizing quality over quantity. Build genuine connections through carefully researched, personalized outreach that demonstrates real value to your recipients. The future belongs to marketers who choose meaningful engagement over maximum velocity.The Brutal Math Behind Why Your Sales Outreach Dies UnreadB2B buyers now receive 500% more cold outreach than three years ago. The math becomes brutal: every sales message you craft competes with hundreds of others in an attention economy that's hitting its breaking point. Your thoughtfully personalized email drowns in the same inbox flood as automated spam blasts and LinkedIn form messages.Think of outbound sales channels like a public park destroyed by overuse. Each individual visitor might leave only a small trace, but multiply that impact by thousands. That's what's happening to email, phone, and social outreach. Even when you craft the perfect message, your prospects have already built defensive walls:* Automated email filters that quarantine anything resembling sales language* Phone settings that send unknown numbers straight to voicemail* Browser extensions that block LinkedIn connection requests* Calendar apps that require "approved sender" statusA recent conversation with a frustrated sales leader crystallized this reality. He argued that CEOs who ignore cold outreach risk missing game-changing opportunities. But flip that logic: as a CEO of a small company, Mac sees hundreds of pitches monthly. Each one demands attention, evaluation, and response time. For leaders at larger organizations, that number multiplies exponentially. The brutal reality is that most prospects physically lack the hours needed to evaluate your message, no matter how brilliant.The psychology of modern buyers reflects this overwhelm. When you receive 50+ sales messages daily, pattern recognition kicks in. Your brain builds shortcuts, filing anything that looks like outbound into the "deal with later" folder (which really means never). Sales teams chase prospects through an ever-shrinking window of attention, while buyers fortify their defenses against the growing assault on their time.Key takeaway: The outbound sales crisis stems from pure mathematics: too many messages chase too...

What's up everyone, today we have the pleasure of sitting down with Ana Mourão, CRM, Customer Data and CDP Advisor.About AnaAna started her career in the financial services sector before moving to field marketing and ecomm partnershipsShe then spent 5 years as a Marketing leader at 3MShe created the Experimental Marketer framework to help marketers take ownership of martech Today Ana is CRM, Customer Data and CDP Advisor working with Fortune 500 customers advising on data architecture, digital engagement and customer journeysMartech Leaders Must Become Systems ArchitectsIn theory, we all understand that martech has the potential to shape customer experiences, transform internal processes, and drive business growth. But mastering individual tools offers limited value. Ana's experimental marketer framework proposes an interesting ideat: martech professionals must evolve into systems architects who orchestrate intricate technological ecosystems while maintaining laser focus on business outcomes.The framework, born from Ana's battlefield experience, advocates for marketers to embrace technology as a force multiplier. You already understand how martech drives conversions and engagement. Now imagine wielding that same power to revolutionize marketing operations, break down departmental barriers, and create seamless workflows that amplify team performance. This systems-level thinking separates strategic leaders from tactical operators.Marketing technologists possess unique insights into customer engagement processes, campaign execution, and performance optimization. The framework pushes you to leverage this knowledge beyond traditional boundaries. Step into cross-functional conversations with authority. Guide IT and operations teams toward solutions that serve marketing's mission while improving organizational efficiency. Your perspective proves invaluable in bridging the gap between technical capabilities and business objectives.Consider the ripple effects of your technology decisions. Each tool implementation, integration choice, and process automation creates waves that impact multiple teams and workflows. By viewing martech as an interconnected system rather than isolated solutions, you'll spot optimization opportunities invisible to those stuck in departmental silos. This elevated perspective transforms you from a tool specialist into a strategic architect of marketing operations.Some practical applications Ana recommends:Map your martech ecosystem to identify connection points and dependenciesDocument cross-functional workflows to pinpoint friction and improvement opportunities Facilitate regular discussions between marketing, IT, and ops teamsEvaluate new tools based on their system-wide impact, not just feature listsBuild processes that scale across teams and technologiesKey takeaway: The future demands marketing technologists who think in systems, not silos. Build your strategic value by understanding how technologies interconnect, impact multiple stakeholders, and drive both customer engagement and operational excellence. Your ability to architect comprehensive solutions while maintaining big-picture perspective will determine your success in this increasingly complex landscape.Lessons from Stanley Black & Decker's Data TemplateMarketing technology demands ruthless precision in system design. When tools operate in isolation, data fragments and teams falter. Ana examines how Stanley Black & Decker, the world's largest industrial tool company, architected a unified martech ecosystem that transformed scattered tools into an integrated engine of market intelligence.Strategic Foundation & Business ContextMost B2B companies operate with dangerous blind spots between their distribution channels and end users. Ana shares how Stanley Black & Decker dismantled these barriers by architecting an integrated martech system across emerging markets. Their goal transcended basic data collection; they sought to reshape product development and go-to-market strategies through direct end-user intelligence.The system's strategic architecture spanned Latin America, Asia, Middle East, and Africa, deliberately excluding mature markets to focus on high-growth regions. This geographic scope demanded sophisticated balance between centralized control and local market agility. Rather than imposing rigid global templates, the architecture provided regional teams with dynamic frameworks for market-specific adaptation while maintaining brand integrity.Local empowerment emerged through granular control mechanisms. Teams gained the ability to modify email templates, adjust campaign elements, and launch market-specific promotions without technical dependencies. This operational autonomy accelerated time-to-market while reducing vendor reliance. A promotion in the Philippines could launch within hours instead of weeks, using pre-approved templates that maintained brand standards while accommodating local market conditions.The Tech Stack Evolution and Adding a CDPMarketing automation tools give your stack lightning-fast reflexes. They'll send emails, trigger workflows, and chase leads across channels with robotic precision. But Ana's work with Stanley Black & Decker exposed an uncomfortable truth: pure automation creates mindless action without strategic intelligence. You need a brain, not just a nervous system.The team's marketing automation platform fired off messages like clockwork. Yet it remained blind to the deeper patterns hiding in plain sight. User behaviors painted intricate stories: Anna gravitating toward e-commerce content while ignoring product launches, segments showing distinct engagement rhythms across markets. These crucial signals vanished into the void between automation triggers.The Customer Data Platform (CDP) entered as the cognitive center, not another mechanical add-on. This neural hub absorbed data streams from every market, brand, and channel. It learned to recognize behavior patterns, predict engagement paths, and surface hidden user affinities. The stack evolved from a collection of reflexes into an intelligent system capable of adapting to market-specific needs while maintaining coherent user understanding.Data Governance Through a Data TemplateData governance rarely sparks joy. Yet Ana's work at Stanley Black & Decker proved that operational elegance hides in unexpected places. A data template, speaking the CDP's native language, transformed scattered global operations into a synchronized intelligence network without strangling regional teams in process.The system worked through elegant behavioral design, not brute-force mandates. Forms matching the template's structure flowed seamlessly into unified customer profiles within 36 hours. Non-compliant data languished in digital limbo, requiring manual resurrection through tedious cross-departmental coordination. This natural selection pressure rapidly evolved team behavior from template resistance to passionate advocacy.Market dynamics morphed at quantum speed. Regional teams caught form errors before deployment. Landing pages multiplied perfectly across continents. Data streamed automatically into unified profiles while teams slept. New requirements integrated organically without breaking existing flows. Most critically, cross-market performance comparison transformed from weeks of reconciliation hell into instant insight generation.The template's adaptive properties challenged conventional governance wisdom. It maintained rigid standards while enabling local flexibility....

What's up everyone, today we have the pleasure of sitting down with Jeffrey Lee, Lifecycle Marketing Technical Lead at Calm. About JeffJeff started his career as an IT specialist at IBM He then joined Merchant Circle as a FE Web dev and eventually ended up managing a team of web developers He later joined Flipboard – a popular social magazine app – where he spent 5 years embedded into email development and marketing operations. He built and grew their email capability to sending over 400M emails per monthToday Jeff is Lifecycle Marketing Tech Lead at Calm where he architected their adoption of push notifications as a messaging channel; they now send over 300M push notifications and 2B emails per yearBuilding Engineering-Marketing Partnerships With a Technical and Emotional BlueprintProduct collaboration is the cornerstone of impactful marketing initiatives, yet many organizations struggle with this crucial partnership. Jeff's unconventional journey from engineering to marketing reveals a powerful framework for building authentic cross-team relationships that deliver both immediate results and long-term value.The Technical FoundationMost marketing teams fall into the trap of overwhelming engineering with urgent requests, only to face a wall of indifference. Jeff's engineering background helped him recognize that technical credibility forms the bedrock of successful collaboration. Rather than making desperate pleas for resources, he leveraged his technical expertise to create working prototypes that demonstrated clear business impact.His subscription management project exemplifies this approach. By bootstrapping a solution achieving 90% accuracy in promotional targeting, he transformed abstract marketing concepts into concrete engineering challenges. The remaining optimization represented pure customer experience enhancement and operational efficiency – metrics that resonated deeply with the engineering mindset.Building Emotional CapitalThe impact extends beyond technical competency into the realm of emotional intelligence and operational empathy. Engineers particularly value colleagues who demonstrate respect for their workflows and time constraints. Jeff's approach of presenting production-ready queries and implementation frameworks eliminated the typical friction of translating marketing requirements into technical specifications.This combination of technical fluency and operational understanding creates a powerful multiplier effect. When marketing teams blend technical capability with genuine empathy for engineering processes, they evolve from being perceived as an external burden to becoming a valued strategic partner. Each successful collaboration reinforces credibility and builds momentum for future innovations.Creating Sustainable PartnershipsThe formula for lasting engineering-marketing collaboration emerges from this dual focus on technical excellence and emotional intelligence:1. Start with working prototypes that prove business value before requesting engineering resources2. Present technically sound solutions in engineering-ready formats that respect existing workflows3. Build credibility through consistent delivery of measurable impact4. Demonstrate genuine understanding and respect for engineering priorities5. Leverage initial wins to create natural advocacy for future marketing technology initiativesThe result is a partnership model that transcends traditional departmental divisions, creating sustainable value for both teams. By approaching collaboration through both technical and emotional lenses, marketing teams can transform skepticism into enthusiasm for projects that deliver meaningful impact across the organization.This framework provides a blueprint for marketing teams looking to build authentic engineering partnerships that drive innovation and results. The key lies in demonstrating both technical competence and operational empathy – proving value through tangible outcomes while building emotional capital through genuine understanding and respect for engineering workflows.Key takeaway: Win engineering trust by showing, not telling. Build working prototypes that demonstrate clear value, then present solutions in engineers' technical language while respecting their workflows. This combination of proven results and operational empathy transforms marketing from a burden into a valued partner, creating momentum for future collaboration.Why it Took 3 Years to Convince the Product Team at Calm to Implement Push NotificationsWhether it's product, martech or channels, sometimes decisions masquerade as data-driven choices but are actually running on raw emotion and bias. At Calm, adding push notifications sparked a three-year battle that exposed how deeply personal experiences shape enterprise product strategy. Through their struggle to balance user psychology with organizational resistance, we uncover essential principles for building sustainable engagement in mobile products.The Psychology Behind Product ResistanceProduct teams operate on gut reactions and personal biases more often than anyone wants to admit. At Calm, Jeff discovered this reality when a straightforward push notification feature turned into a three-year battle, exposing how deeply personal experiences shape product decisions at the highest levels.The resistance stemmed from visceral reactions to notification overload. Product leaders, scarred by their own encounters with aggressive casino apps and notification spam, projected these experiences onto Calm's notification strategy. Their instinct to protect the product from becoming "one of those apps" created a powerful organizational inertia, even in the face of compelling engagement data.The turning point arrived through an unexpected avenue: leadership turnover. A new Chief Product Officer, armed with positive experiences from previous roles, transformed the three-year roadmap struggle into a six-week sprint. This shift illuminates the stark reality of enterprise decision-making; technical complexity often plays second fiddle to personal conviction and past experiences.Jeff's evolution from email skeptic to engagement advocate mirrors this journey. His own transformation from viewing email as "the scammiest thing" to recognizing its profound impact on user engagement adds a layer of irony to his push notification crusade. Small-scale pilots proved ineffective at winning support because they failed to demonstrate the compound effects that emerge over time. Like SEO, the true power of these engagement channels only becomes apparent through sustained, systematic implementation.Industry-Standard Functionalities is More Important Than Competitive DynamicsCompetitive pressure normally drives product decisions, except when you're number one in the market. Jeff experienced this paradox at Calm, where their market leadership position actually worked against the adoption of push notifications. The common rationale? "We're number one. We don't need to do what others are doing to catch up."This mentality exposes a fascinating blind spot in product strategy. While lagging competitors enthusiastically embrace proven engagement channels, market leaders sometimes cocoon themselves in a false sense of security. Their position at the top becomes a psychological barrier to adopting industry-standard features, creating vulnerability to more nimble competitors.The definitive proof of push notifications' value emerged through an accidental experiment. When discussing hypothetical scenarios about turning off push n...

What's up everyone, today we have the pleasure of sitting down with Sandy Mangat, Head of Marketing at Pocus. Summary: AI and outbound prospecting has flooded our inboxes with poorly personalized, irrelevant, and frankly lame template attempts at human connection. But some teams are seeing the light… the purple light. Sandy takes us inside the dimly lit fortune telling parlor of Pocus where we gaze into the swirling galaxies of the crystal ball of modern sales. We travel through visions of product-led sales, network referrals, signal correlation and AI agents all swirling together to fill pipelines. About SandySandy is based in beautiful Vancouver BC, she got her start at GE Digital in Product MarketingShe later moved on to ThoughtWire, a tech company specializing in smart buildingShe then joined Charli AI, a multidimensional AI company specializing in the finance sectorToday Sandy is Head of Marketing at Pocus, an AI-native prospecting platform trusted by high growth companies like Asana, Monday, Canva, and MiroOutbound Needs a Cold Hard ResetThe blunt reality about outbound sales is that automation obsession and meeting quotas have created a wasteland of deleted emails and blocked LinkedIn profiles. Sales teams continue spraying prospects with templated messages, while response rates plummet to new lows. Yet leadership keeps pushing for higher volumes, creating a self-destructive cycle that poisons potential customer relationships before they begin.This mess stems from sales organizations fundamentally misunderstanding what drives genuine business relationships. Sales leaders chase efficiency through automation, treating prospects like data points rather than future partners. The result? Inboxes overflow with desperate attempts at "personalization" that read like they were written by a caffeinated robot trying to sound human. Meanwhile, genuinely interested prospects have built fortress-like defenses against the daily barrage of cookie-cutter outreach.Consider how actual business relationships form: through authentic interactions, shared understanding, and carefully built trust. Successful outbound motions mirror this natural process, whether through thoughtful event networking, well-researched phone conversations, or precisely targeted digital outreach. Even companies swimming in inbound leads eventually require strategic outbound capabilities, especially when expanding into new markets or launching products that demand fresh customer conversations.The path forward demands embracing what experienced sales professionals already know: shortcuts and automation cannot replace genuine human connection. Sales organizations must rebuild their outbound approach from the ground up, focusing on quality interactions over vanity metrics. This means investing serious time in prospect research, crafting genuinely personalized messages, and showing patience as relationships develop organically.Key takeaway: Sales teams have to abandon the lame industrial approach to outbound prospecting and return to building relationships and human-centered selling. Ditch your batch and blast automation addiction, focus on qual over quant, and giving sales professionals the time and tools to build authentic relationships rather than chasing arbitrary activity and volume metrics.Building Sales Teams for Product Led Growth CompaniesProduct-led growth companies harbor a poorly kept secret: they all run sales teams. The idealistic vision of products that "sell themselves" crashes into market realities faster than venture capitalists can say "negative churn." Companies like Miro, Asana, and Canva discovered that relying solely on product-driven acquisition limits their growth potential, especially when expanding into new markets or use cases.The evolution of PLG sales teams reflects a sophisticated marriage between product usage data and human-driven outreach. These teams capitalize on product signals that indicate expansion potential, creating what Sandy calls "warm outbound" opportunities. When users demonstrate specific engagement patterns or hit usage thresholds, sales professionals step in to guide them toward broader adoption or premium offerings. This approach transforms traditional cold outreach into data-informed conversations with already-engaged users.Yet even these PLG darlings recognize the strategic value of traditional outbound sales. They approach their go-to-market strategy like a diversified investment portfolio, using cold outreach to hedge against the limitations of product-led acquisition. This hybrid model proves particularly valuable when testing new markets, launching products, or exploring different use cases. The rapid feedback loop from direct sales conversations provides invaluable insights that pure product analytics might miss.The WordPress.com experience illustrates this evolution perfectly. Despite massive organic traffic and brand recognition, they eventually built a sales team to capture enterprise opportunities and service-based revenue. This mirrors the broader industry pattern where even the most product-centric companies discover that sustainable growth requires a balanced approach combining automated product experiences with strategic human intervention.Key takeaway: Successful PLG companies build sales teams that leverage both product usage signals and traditional outbound tactics. Rather than choosing between product-led or sales-led growth, organizations should create a balanced strategy that uses product data to inform outreach while maintaining direct sales capabilities for market expansion and enterprise opportunities.How Product Led Sales Teams Time Their Customer OutreachThese days every SaaS company wants the magic of product-led growth: minimal sales headcount, viral expansion, and revenue that scales without an army of account executives. Yet behind the glossy investor decks and growth charts lurks an uncomfortable reality about human intervention in the sales process. Even the most automated, product-led companies scramble to hire sales teams the moment enterprise deals enter the picture.The data tells a ruthlessly practical story: throwing sales resources at every free trial wastes everyone's time while ignoring high-value accounts costs serious money. Smart companies obsess over usage patterns, tracking signals that indicate when a prospect needs human guidance versus automated nurturing. They build sophisticated scoring models to spot accounts teetering between self-service success and quiet abandonment, timing their outreach to tip the scales toward expansion.Sandy points out how divergent growth patterns demand radically different playbooks. Some products drive natural expansion through viral team adoption but struggle with initial activation. Others convert early users easily yet hit a wall when trying to expand across departments. These distinct patterns create clear intervention points where human touch generates outsized returns, whether that means helping a complex enterprise implementation succeed or guiding teams toward advanced features that unlock real value.The reality of product-led sales revolves around mapping your market's actual behavior, not following someone else's playbook. Enterprise deals often demand early sales involvement due to security requirements and complex buying processes. Other segments thrive on automated expansion until they hit specific technical or organizational barriers. Companies who understand these patterns build flexible systems that deploy sales resources at precise moments of maximum leverage rather than burning cycles on low-value outreach.Key takeaway: Map your actual user b...

What's up everyone, today we have the pleasure of sitting down with Chris Golec, Founder & CEO at Channel99. Summary: The Godfather of ABM takes us through his humble beginnings in Detroit's industrial trenches to category creation and entrepreneurial expeditions. His journey spans building magnetic company cultures, cracking the code on remote work, sharing candid hiring wisdom, and transforming marketing failures into fuel for growth. Now building Channel99, he's rewriting attribution with a touch of AI engineering, predicting marketing ROI, using a white box approach. About ChrisChris started his career in the manufacturing world, working at DuPont and then GE where he moved from Engineering, Sales and Marketing rolesThe first startup he co-founded was a supply chain enterprise software where he also had the role of VP of Marketing, He grew the company to 75 people and raised $10M in VC. After only 6 years he sold to i2 Technologies for $380M A few years after his exit, Chris started his next company, Demandbase, the well known ABM platform. Along a 13 year journey as CEO he would create and lead the category of ABM software, hiring more than 1,000 people and crossing the elusive 200M in revenueToday Chris is on his 3rd company, Channel99, an AI powered attribution platform for B2B marketersFrom Industrial Paint Lines to Silicon ValleyChemical engineering graduates in Detroit followed a well-worn path: automotive paint lines, waste treatment facilities, and methodical career progression through established industry giants. The conventional trajectory promised stability but offered minimal room for pioneering new ground. This reality sparked Chris's pivotal decision to pursue innovation beyond Motor City's industrial confines.DuPont's Delaware operations presented an intriguing opportunity to spearhead European manufacturing technology adoption in the US market. The role demanded technical expertise while cultivating strategic thinking, setting the stage for an unorthodox career evolution. Engineering polymer sales, though seemingly mundane, opened doors to Boston's dynamic business landscape, where GE recognized potential in this chemical engineer turned sales strategist.The 1990s tech boom transformed the West Coast into a crucible of innovation. As GE's industry marketing lead for high-tech materials, Chris orchestrated global deals with Apple and HP, bridging the gap between traditional manufacturing and Silicon Valley's emerging titans. The experience revealed a stark reality: technical expertise alone created opportunities, but market understanding determined success. In 1995, this insight drove Chris and fellow GE engineers to launch Supply Base, despite their complete unfamiliarity with software development.Supply Base embodied Silicon Valley's audacious spirit. A team of engineers, armed with industrial experience but zero software knowledge, secured funding through sheer determination. The venture grew into a profitable enterprise, culminating in an exit that coincided precisely with the market peak on March 13, 2000. Yet amid this success, frustration brewed. B2B marketing remained technologically underserved, a gap that became increasingly apparent as Supply Base scaled. This observation planted seeds for future innovations in marketing technology, proving that sometimes the most valuable insights emerge from professional pain points.Key takeaway: Career evolution thrives on identifying market gaps and embracing unconventional paths. Chris's journey demonstrates how technical expertise combined with market understanding creates opportunities for innovation, especially when traditional industry boundaries blur in the face of technological advancement.Why Top Talent Gravitates to Companies with Purpose-Led CultureCreating genuine company culture runs deeper than the usual corporate playbook suggests. Demandbase's remarkable journey illuminates how sustained, intentional investment in organizational DNA attracts and retains exceptional talent. Chris discovered through years of leadership that authenticity, transparency, and meaningful impact serve as the bedrock of thriving workplace environments, transcending typical office perks or superficial initiatives.Demandbase's cultural investment materialized into tangible recognition, propelling them to the tenth spot among 500,000 companies on Glassdoor by 2016. The achievement reflected genuine employee satisfaction measured through independent surveys rather than manufactured accolades. This momentum persisted as the company consistently earned "Best Places to Work" distinctions throughout the Bay Area, validating their approach to fostering genuine workplace connections.The company's distinctive approach integrated philanthropy seamlessly into their organizational fabric. A partnership with Stop Hunger Now transformed from an office-wide meal-packaging initiative into a stadium-scale operation at their annual customer conference. This resonated profoundly with their marketing-focused clientele, spawning similar programs across multiple organizations. Additional initiatives supporting women's education and the Challenge Athlete Foundation enabled employees to contribute meaningfully beyond their B2B software focus, creating ripple effects throughout the industry.Cultural development demands attention from inception, though its manifestation evolves with company growth. While Series A funding often marks the formal introduction of HR functions and recruitment strategies, companies under 20 employees thrive when leadership directly shapes and nurtures cultural foundations. The rise of remote work introduces new challenges, requiring deliberate effort to maintain community through strategic in-person gatherings and shared experiences that transcend virtual boundaries.Key takeaway: Purpose-driven culture requires deliberate cultivation from day one. Organizations that prioritize authentic connections, maintain radical transparency, and create opportunities for meaningful impact naturally attract and retain exceptional talent. This foundation enables sustainable growth while fostering genuine employee satisfaction and engagement.Why Remote Work Fails Junior Employees (And Soars for Veterans)Remote work demands a brutally honest examination beyond the standard flexibility narrative. The stark reality reveals a complex equation where career stage, personality type, and organizational DNA collide to determine distributed success. During a pre-pandemic executive assessment at Demandbase, the remote work preference split tracked perfectly along introvert-extrovert lines, foreshadowing the fundamental role of personality in distributed work effectiveness.Career stage emerges as the make-or-break factor in remote work dynamics. Fresh graduates and early-career professionals require an apprenticeship period that Zoom simply cannot replicate. The professional polish developed through observing seasoned colleagues handle meetings, presentations, and workplace politics creates an invisible foundation for later career success. Close CRM's remote-first model crystallizes this reality; they exclusively hire veteran professionals with 10+ years of experience, acknowledging that virtual environments demand battle-tested practitioners who learned their craft in the trenches of traditional offices.The SDR experience at Demandbase's New York office illustrates this principle in vivid detail. Post-pandemic, a group of SDRs met face-to-face for the first time, creating an impromptu laboratory for examining remote work's limitations. Physical proximity unlocked a treasure trove of professional development opportuniti...

What's up everyone, today we have the pleasure of sitting down with Meg Gowell, Director of Growth Marketing at Typeform. Summary: Marketing leadership in 2025 is a wild time. After years of learning martech and technical concepts to become a full stack marketer, you finally land that dream director gig... only to watch your hard-earned tech skills collect dust while you drown in meetings. Megan helps us see the way forward. She takes us on a ride that covers marketing measurement, experimentation and building brand momentum, all while having tons of fun. We get into how data warehouses are not so quietly changing the martech universe while most teams are still stuffing everything they can in their CRM. Welcome to the wild world of modern marketing leadership – where you somehow need to be both a tech wizard and a strategy genius just to keep up. And we're here to guide ya. About MegMeg started her career in wedding planning while she was in college, she also started a luxury branding business for high-end weddingsShe then worked at a marketing agency for 4 years where she focused on social media, paid media and budget managementShe switched over to a boutique agency where she got a breath of experience across all facets of marketing including web design, conversion rate optimization, project management and also got to lead a team of marketersShe then moved over to a real estate startup – which was one of her former clients – as VP of Marketing and automation where she helped grow the company from $9MM to $22MM in less than a yearShe then moved over to B2B SaaS at Appcues as Director of Growth marketing where she led funnel optimization, experimentation strategy and execution, event sponsorships, biz dev and moreToday Meg is Director of Growth Marketing at Typeform where she oversees paid, web/site, lifecycle, partner marketing and campaigns How Full Stack Marketers Drive Marketing ExcellenceFull stack marketing capabilities command premium compensation in today's market, mirroring the pattern seen with full stack engineers who rank among the highest-paid technical professionals. The comparison raises interesting questions about the relationship between full stack and T-shaped marketing skill sets, particularly regarding depth versus breadth of expertise.The distinction between full stack and T-shaped marketers centers on the distribution of knowledge and capabilities across different marketing disciplines. While T-shaped marketers typically possess deep expertise in one area complemented by broader surface-level knowledge, full stack marketers maintain substantial working knowledge across multiple marketing domains. This broader distribution of skills enables them to engage meaningfully with specialists and make informed decisions across the marketing spectrum.A critical advantage of the full stack marketing approach lies in its impact on team building and hiring decisions. When marketing leaders possess comprehensive knowledge across various disciplines, they can better evaluate potential hires and identify genuine experts in specialized roles. This knowledge framework helps prevent the common pitfall of making poor hiring decisions due to limited understanding of specific marketing functions or technologies.The full stack marketer's broad knowledge base serves as a foundation for effective collaboration and decision-making. Rather than requiring mastery in every area, the key is maintaining sufficient expertise to ask incisive questions, recognize genuine talent, and understand the interconnections between different marketing functions. This comprehensive perspective enables better strategic planning and more efficient resource allocation.Key takeaway: Full stack marketers need sufficient knowledge across marketing disciplines to recognize expertise, make informed hiring decisions, and drive strategic initiatives. Success in this role doesn't require mastery of every area but rather the ability to understand key concepts, ask relevant questions, and identify genuine expertise when building and managing teams.Balancing Technical Proficiency and Leadership in Marketing TeamsRemember getting that dream marketing leadership role? Corner office, eager team, the works. But then reality hits - you're spending more time in strategy meetings than actually doing the hands-on work you love.It's a weird spot to be in. The higher you climb, the further you get from the technical skills that got you there. Take Megan's story - she was crushing it at AppCues, deep in the technical weeds while leading cross-functional teams. Now at Typeform, she's managing 10 people and her calendar is packed with meetings while her technical skills collect dust.Here's the thing - you can't fake technical knowledge. Real understanding comes from getting your hands dirty - tweaking platforms, figuring out complex filters, and really getting how things work under the hood. The best marketing leaders are like chefs who still know their way around the kitchen, not just writing menus. Your team can smell it a mile away if you've lost touch with the technical side. The real magic happens when you can switch between big-picture thinking and nuts-and-bolts knowledge. It's like being bilingual in both strategy and technical speak.Some leaders live in the strategy clouds, others get lost in the details. The sweet spot? Knowing when to zoom in and when to step back. When you ask about campaign metrics or question technical decisions, your team knows if you're genuinely curious or just micromanaging. Feedback is a delicate art, you have to ask yourself if your input makes something better versus just different. Sometimes we suggest changes based on personal preference rather than what actually works. The key is knowing when to speak up and when to let your team run with it.Takeaways: Your technical skills got you the leadership role. Now they need to evolve, not evaporate. The future belongs to marketing leaders who keep one foot in the code and one in the boardroom – masters of both the how and the why.Trusting Your Gut vs Measuring All Of The ThingsThe marketing metrics obsession has gone too far. While CFOs salivate over spreadsheets demanding ROI calculations for every LinkedIn post and email blast, they're missing a crucial reality check: humans are gloriously unpredictable creatures who refuse to follow our carefully crafted attribution models. The digital advertising revolution sold us a compelling fantasy of perfect measurement, but reality stubbornly refuses to play along. After the "growth at all costs" party ended with a nasty hangover, companies sobered up and started demanding receipts for every marketing dollar spent. Logical? Sure. Realistic? Not even close. This myopic fixation on measurable channels creates a dangerous illusion of control. Paid search might give you beautiful conversion tracking, but try building a billion-dollar brand on Google Ads alone. Spoiler alert: it won't work. Real growth demands embracing the uncomfortable truth that some of your most powerful marketing moves will resist neat ROI calculations.Modern marketing success requires omnipresence, not just optimization. Your target audience bounces between platforms like a caffeinated pinball, interacting with your brand across countless touchpoints. Social media, influencer collaborations, and content marketing often defy precise attribution, yet they create the vital ambient awareness that drives long-term growth. The magic happens in the messy middle, where multiple channels work together in ways that no attribution model can fully capture.Getting leadership buy-in for this reality requi...

What's up everyone, today we have the pleasure of sitting down with the lads from We're not marketers. Summary: When did everyone on LinkedIn suddenly become a GTM expert? The misfits from ‘We're Not Marketers' dive into this chaos, explaining why Go-to-Market strategy has become the most misused term in marketing. They share product marketing stories about rigid product launches, cross-functional chaos, and small test groups. They open up about their love and admiration for marketing operations folks, similar cross functional translators between tech and marketing and how martech can support message testing. We explore the debate of who should have final word on messaging, PMMs or the channel SMEs. Join us for the laughs, stick around for the love between PMMs and martech. About the 3 MisfitsAll 3 of these gentlemen work for themselves as fractional PMMsGab Bujold (Bu-jo) is based in Quebec city, Canada. He's a messaging expert and also a marketing advisor for early-stage startups, he's a former product marketer and 4-time solo marketer at various different brands and sports an incredible mustacheAlso joining us today is Zach Roberts is based in California, he worked in B2B SaaS sales for half a decade before pivoting to product marketing with a focus on enablement, he's worked at big names like Dropbox, LinkedIn and Google. He's a 2x recognized Product Marketing Influencer by PMALast but certainly not least, we're also joined by Eric Holland who's based in Pennsylvania, he's a product-led content pro also runs a retail apparel startup and is a recovering in-house product marketer. He's the mastermind behind the creative AI skullies artwork of their podcastWhy Go to Market Strategy Has Become a BuzzwordThe concept of go-to-market (GTM) strategy has entered peak buzzword territory in recent years. What was once a product marketing-specific term focused on launching new products or features has been hijacked by nearly every department under the sun. These days, everyone from sales and marketing ops to customer success is suddenly a "GTM expert" on LinkedIn. The term has become so diluted that it's starting to lose its meaning entirely.The transformation of GTM into a catch-all phrase stems largely from corporate politics and self-preservation. Teams across organizations are scrambling to attach themselves to GTM initiatives, fearing that being left out might signal their irrelevance. As Zach points out, there's an underlying anxiety that not being involved in GTM somehow makes a team dispensable, leading to a kind of organizational FOMO that has stretched the term beyond recognition.The reality is that successful GTM execution has always required coordinated effort across multiple teams. Product marketing traditionally orchestrates these initiatives, but they can't execute alone. It takes sales for implementation, product teams for development, and marketing for awareness. The problem isn't collaboration; it's the current trend of every team claiming to be the primary GTM driver, creating confusion about who actually owns the strategy.Eric makes a crucial distinction between "going to market" and "go-to-market strategy" that cuts through some of the noise. While the strategy might come from product marketing or revenue leadership, the execution involves multiple teams working together. The challenge is maintaining clear ownership of the strategy while preventing it from becoming another meaningless corporate buzzword that everyone claims expertise in.Key takeaway: Organizations need to stop the free-for-all claiming of GTM expertise and return to clearly defined roles within the GTM process. Success depends on having centralized strategic ownership while enabling individual teams to excel in their specific GTM responsibilities, not turning every department into self-proclaimed GTM experts.Who is Responsible for Operationalizing GTMPicture a chill Broadway production: everyone from lighting to sound plays a crucial role, but someone needs to direct the show. Product Marketing's role in GTM execution presents a fascinating operational challenge. While multiple teams claim ownership over GTM initiatives, the real question isn't about territorial control but about orchestrating complex product launches effectively.The operational reality of GTM involves intricate coordination across specialized teams. Marketing and sales ops teams manage the technical infrastructure, configuring everything from CRM workflows to marketing automation. Lifecycle marketing teams often gatekeep new feature and product notification announcements and balance that with existing messages. Product marketing develops the strategy and messaging, while sales teams handle direct customer engagement. Each group brings essential expertise to the table, making territorial claims over "GTM Ops" not just unnecessary but counterproductive.Gab's makes a really good point that Product Marketing Managers excel at running small-scale experiments, gathering feedback, and iteratively refining go-to-market approaches. This methodology allows teams to validate strategies before full-scale deployment, reducing risk and improving outcomes. It's not about owning GTM ops; it's about facilitating successful product launches through methodical testing and collaboration.You should view GTM operations as a collaborative framework rather than a power structure. PMMs serve as strategic conductors, coordinating efforts across teams while respecting each group's expertise. When campaigns underperform, the root cause typically traces back to poor coordination or unclear direction, not technical execution. Success requires letting each team excel in their domain while maintaining a unified strategic vision.Key takeaway: Focus on establishing clear operational frameworks where Product Marketing Managers guide strategy and testing, while specialized ops teams manage technical implementation. Success comes from collaboration and respect for expertise, not from claiming ownership over the entire GTM process.Prioritizing Product Marketing Requests vs Martech RoadmapsThere's often a natural tension between PMMs who think every feature deserves a big email to everyone in the database and the martech or marketing ops team who has an existing roadmap and existing comms in place. New GTM initiatives don't get to market on certain channels without the SME team converting words into code and automation. This creates a complex decision making process that often requires somewhat lame but important evaluation of business impact and strategic alignment.Strategic prioritization requires product marketers to approach each situation with an analytical mindset focused on identifying the most pressing business needs. As Eric explains, the process resembles assessing multiple issues requiring attention but having limited resources to address them all simultaneously. The key becomes determining which initiative will deliver the most significant impact toward established organizational goals and objectives.The reality of product marketing involves making difficult trade-offs between seemingly equally important initiatives. While new product launches naturally generate excitement and momentum, they must be weighed against the potential impact of operational improvements that are already on the martech roadmap like enhanced product analytics or refined lead scoring mechanisms. These behind the scenes projects often create foundational improvements that enable better execution of future go to market activities.At the end of the day, most product launches have flexible timing - what's critical is identifying the few relea...

What's up everyone, today we have the pleasure of sitting down with Sundar Swaminathan, author of the experiMENTAL newsletter and part time Marketing and Data science advisor?Summary: After leading Uber's Marketing Data Science teams, Sundar shares insights that work for both tech giants and startups. Beyond uncovering that Meta ads generated zero incremental value (saving $30 million annually), they mastered measuring brand impact through geo testing and predicting LTV through first-week behaviors. Small companies can adapt these methods through strategic A/B testing and simplified attribution models, even with limited sample sizes. Building data science teams that embrace business impact over technical complexity, and maintaining curiosity, like when direct driver engagement revealed that recommending Saturday afternoon starts over Friday peak hours improved retention. About SundarSundar started his career as a software developer at Bloomberg before managing $19 Trillion at the US Treasury as a Debt ManagerHe pivoted to growth marketing and data science consulting where he worked with DirectTV and an ed-tech AI startupHe then made the mega move to Uber where he spent 5 years building Brand, Performance, and Lifecycle Marketing Data Science teamsHe moved over to a travel tech startup and helped them go from $0 to $100K MRRToday, Sundar is a marketing and data science advisor, he helps B2C founders and marketers He's also working on an upcoming podcast and has a newsletter where he shares frameworks, how-to guides to help B2C marketersMarketing Incrementality Testing Reveals Meta Ads Ineffective at UberPerformance marketing often reveals surprising truths about channel effectiveness, as demonstrated by a fascinating case study from Uber's marketing operations. When confronted with unstable customer acquisition costs (CAC) that fluctuated 10-20% week over week despite consistent ad spend on Meta platforms, Uber's performance marketing team, led by Sundar, decided to investigate the underlying causes.The investigation began when the team noticed significant volatility in signup rates despite maintaining steady advertising investments. This inconsistency prompted a deeper analysis of Meta's effectiveness as a primary performance marketing channel. The timing of this analysis was particularly relevant, as Uber had already achieved substantial market penetration eight years after its launch, especially in major urban markets where awareness wasn't the primary barrier to adoption.Through rigorous data analysis, the team implemented a three-month incrementality test to measure Meta's true impact on user acquisition. The test utilized a classic A/B testing methodology, comparing a control group receiving no paid ads against a treatment group exposed to Meta advertising. The results were striking: Meta advertising showed virtually no incremental value in driving new user acquisition, a finding that was validated by Meta's own data science team.The outcome of this experiment led to a significant strategic shift, resulting in annual savings of approximately $30 million in the U.S. market alone. While this figure might seem modest for a company of Uber's scale, its implications were far-reaching when considered across global markets. The success of this experiment also highlighted the importance of data-driven decision-making and the willingness to challenge assumptions about established marketing channels.Key takeaway: Established marketing channels should never be exempt from rigorous effectiveness testing. Regular incrementality testing can reveal unexpected insights about channel performance and lead to substantial cost savings. Marketing teams should prioritize data-driven decision-making over assumptions about channel effectiveness, even for seemingly essential platforms.How to Run Marketing Experiments With Limited DataMost companies don't have the volume of signups or users that an Uber does. Marketing experiments require a mindset shift when working with small data samples. While A/B testing remains the gold standard for measuring marketing effectiveness, Sunday thinks that companies with limited data can still validate their marketing efforts through strategic pre-post testing approaches.Pre-post testing, when properly implemented, serves as a valuable tool for measuring marketing impact. The key lies in isolation: controlling variables and measuring the impact of a single change. For instance, a marketplace company successfully conducted a pre-post test on branded search keywords in France by isolating specific terms in a defined region. This focused approach provided reliable insights despite not having the massive data volumes typically associated with incrementality testing.That being said, Sundar adds that early-stage companies should prioritize high-impact experiments capable of delivering substantial results vs testing tiny changes that will barely have detectable effects. With small sample sizes, tests should target minimum detectable effects (MDE) of 30-40%. These larger effect sizes become measurable even with limited data, making them ideal for fundamental changes such as exploring new ideal customer profiles (ICPs) or revamping core value propositions, rather than pursuing minor optimizations.An example that Sundar recalls while working at a travel tech startup demonstrated the value of running A/B tests even with limited data. Despite having only 100-200 weekly signups, they detected a 40% conversion drop after modifying their onboarding flow. While the test might have been considered "poorly powered" by strict statistical standards, it successfully prevented a significant negative impact on the business. This illustrates how even small-scale testing can provide crucial insights; it's better to have 60% confidence in a positive change than to miss a catastrophic drop with 95% confidence.The confidence level in marketing experiments operates on a spectrum, with A/B tests providing the highest confidence and pre-post tests offering valuable but less definitive insights. Success depends on maintaining experimental discipline, carefully controlling variables, and understanding the tradeoffs between confidence levels and the humbling reality of practical constraints. Marketing teams must balance their confidence requirements against their risk tolerance when designing and interpreting tests.Key takeaway: Companies with limited data should focus on measuring high-impact marketing changes through carefully controlled pre-post tests. Success comes from isolating variables, targeting substantial effect sizes, and maintaining experimental discipline. This approach enables meaningful measurement while acknowledging the practical constraints of smaller data sets.The Difference Between AB Testing and Incrementality TestingMarketing experimentation terminology often creates unnecessary complexity in what should be straightforward concepts. The fundamental structure of both A/B testing and incrementality testing follows the same principle: comparing outcomes between groups that receive different treatments.Statistical analysis remains consistent across both testing approaches. Whether using Bayesian or frequentist methods, the underlying comparison examines differences between groups, regardless of what those groups receive. The statistical calculations remain indifferent to whether one group receives no treatment (as in incrementality tests) or a variation of the treatment (as in traditional A/B tests).Incrementality testing extends beyond simple presence versus absence comparisons. For example, marketers can test spending increm...

What's up everyone, today we have the pleasure of sitting down with Sarah Krasnik Bedell, Director, Growth Marketing at Prefect. Summary: What happens when a data engineer with an obsession for truth-testing crashes into marketing's sacred cows? Sarah's journey from code to campaigns unfolds like a detective story, where she picks apart marketing myths and rebuilds them with an engineer's precision. Her fresh take transforms marketing tools from black boxes into purposeful instruments, while her approach to AI echoes "Limitless" - it's not about letting machines take the wheel, but supercharging human creativity. Whether you're wrestling with developer outreach or trying to get sales and marketing teams to actually talk to each other, Sarah's technical-meets-tactical perspective offers a compelling roadmap for modern marketing that actually works.About SarahSarah studied math and cognitive science before completing a masters in data scienceShe started her career at Amsted working on data aggregation and machine learning models and eventually moved to a customer-centric role where she helped engineer data architecture for supply chain optimizationsShe had short stints in financial forecasting and company-wide data architectureShe then joined Perpay as a data engineer focused on product analytics as well as reverse-ETL for their marketing team. She was eventually promoted to Lead data eng, managing the full team of data engineers She's an Analytics and GTM Advisor for devtoolsToday she's Director of Growth Marketing at Prefect, a workflow orchestration tool for data and ML engineersUnconventional Paths From Data Engineering to Marketing LeadershipThe traditional career trajectory rarely follows a straight line, particularly in Sarah's fascinating pivot from data engineering to marketing. While leading the data engineering team at Perpay, she found herself knee-deep in an Iterable implementation project that would unknowingly alter her professional DNA. This wasn't just another technical integration; it was a complex orchestration of customer data streams, product catalogs, and audience segmentation capabilities that secretly doubled as an apprenticeship in modern marketing mechanics.Marketing technology projects have a peculiar way of revealing their true nature over time. What begins as lines of code and data pipelines often transforms into something far more intriguing: a window into the soul of marketing operations. Sarah discovered that while her peers remained captivated by the elegance of their code, she found herself increasingly magnetized by the downstream impact of these technical solutions. This subtle shift in perspective proved transformative, compelling her to venture beyond the comfortable confines of engineering meetings and into the dynamic world of marketing strategy sessions.The pandemic's isolation birthed unexpected opportunities, as Sarah's technical writing began attracting attention in the data community. What started as casual documentation of her engineering adventures morphed into paid writing engagements, creating a surprising bridge between technical expertise and marketing communications. This organic evolution suggested something more profound lurking beneath the surface, a hidden pathway connecting the precision of data engineering with the artistry of marketing strategy.The final pieces of her transition fell into place through a combination of hands-on consulting work, mentorship from industry veterans, and immersion in marketing literature. Her participation in the Reforge community added structured learning to her toolkit, while her unique perspective as a former technical buyer provided invaluable insights into marketing dynamics. This multifaceted approach to learning, mixing practical experience with theoretical knowledge, transformed what might have seemed like an improbable leap into a natural progression.Key takeaway: Career transitions in technology rarely require formal education; they thrive on practical experience and curiosity. The most valuable skills often develop through side projects, technical writing, and a willingness to understand the business impact of your work. For those considering a similar path, start by documenting your technical experiences, engaging with cross-functional teams, and focusing on how your current role impacts business outcomes rather than just technical implementations.First Principles Marketing Against Best PracticesMarketing orthodoxy often goes unchallenged, with practitioners blindly following conventional wisdom without questioning its validity. Sarah brings a refreshing perspective to this dilemma, approaching marketing strategies with an engineer's skepticism and a commitment to first principles thinking. This natural inclination to question established norms stems from her background in data engineering, where decisions require rigorous validation rather than mere acceptance of industry standards.The notion that Tuesday morning at 8 AM represents the optimal time for email sends exemplifies the kind of unexamined marketing wisdom that pervades the industry. Rather than accepting such practices at face value, Sarah advocates for a two-pronged approach: first envisioning the ideal outcome, then assessing what's practically achievable within existing constraints. This methodology creates space for innovation while maintaining pragmatic boundaries, allowing marketers to challenge assumptions without losing sight of business objectives.The parallel between architectural decisions in software engineering and strategic choices in marketing reveals an interesting pattern. Just as engineers must carefully consider system architecture before writing code, marketers benefit from establishing solid strategic foundations before diving into tactical execution. This shift in focus from immediate implementation to thoughtful strategy design represents a more sophisticated approach to marketing operations, one that prioritizes intentional decision-making over reflexive adoption of industry practices.In the context of accelerating AI adoption, this first-principles approach becomes even more crucial. Rather than immediately jumping to content creation or campaign execution, successful marketing strategies begin with fundamental questions about audience selection, engagement methods, and value proposition. This methodical approach ensures that technological tools serve strategic objectives rather than dictating them, maintaining human judgment at the core of marketing decisions.Key takeaway: Transform your marketing approach by questioning established practices and applying first-principles thinking. Start by clearly defining your ideal outcome, then work backward to create practical strategies that challenge conventional wisdom. This method often reveals more effective approaches than blindly following industry "best practices." When evaluating any marketing tactic, ask yourself: "What problem are we really trying to solve, and is this truly the most effective solution?"Systems Thinking Applications For Marketing AnalyticsSystems thinking represents the essential bridge between marketing and data engineering, offering a framework for understanding how data flows through modern marketing operations. The ability to visualize and architect data pathways across platforms separates proficient marketing technologists from those merely executing tactical campaigns. This foundational skill proves invaluable when orchestrating the complex dance of customer data across marketing systems.Consider the journey of a single lead signal as it traverses through various marketing platforms. The ...

What's up everyone, welcome to our first episode of 2025 – today we have the pleasure of sitting down with Austin Hay, Co-Founder and Co-CEO at Clarify and Martech Teacher at Reforge. Summary: Something extraordinary is brewing in the world of martech. In the near future, Austin thinks AI agents will turn into an omniscient digital butler, anticipating your needs with uncanny precision while vanishing into the background of your workday. But the real revolution unfolds in the seemingly mundane machinery of marketing operations, where innovative companies are transforming their spaghetti mess of data pipes and platforms into something approaching digital poetry. The fundamental building blocks of our systems aren't disappearing, they're gaining superpowers. Hear it from one of our industry's most thoughtful builders. About AustinAustin started his career at Accenture but he left the Fortune 500 world to join a startup called Branch where he became the 4th employeeAustin then created his own boutique mobile growth engineering consultancy. He grew the practice to 1.5M with big names like Walmart, Jet, Airbnb, Foursquare and more.His consulting practice was aqui-hired by mParticle – a leading CDP solution where he would eventually become VP of Growth He later joined Runway as VP of Business OperationsHe also started building The Marketing Technology Academy – an online learning center for martech which he would eventually sell to Reforge and become the Instructor for the new Martech courseHe was also Head of Martech at Ramp, a fintech startupLast year, Austin strapped on his jetpack and became a product founder at Clarify conquering SF and Hubspot and building the first flexible, intelligent CRM that people actually enjoy using. AI Agents and the Hidden Promise of Ambient ComputingLet's face it, manually feeding context to AI feels a bit like teaching a fish to ride a bicycle. Current AI systems, brilliant as they may be at crunching numbers and crafting responses, still stumble around our digital workspaces like a tourist without a map. Sure, they can write a decent blog post or solve complex equations, but they're essentially working with one hand tied behind their virtual back.Now, imagine your AI assistant as more of a digital detective, quietly observing and understanding everything happening on your screen. No more copying and pasting chunks of text or explaining what's in your Notion workspace for the hundredth time. Picture having a conversation with your computer while it maintains an almost supernatural awareness of your digital environment, from those buried Slack threads to that spreadsheet you've been avoiding. Recent demonstrations, like Kieran Flanagan's adventure with Gemini's screen reader, hint at this future, even if current versions move with all the grace of a sleepy sloth.The real magic kicks in when we start thinking about operating system-level integration. Platform-specific AI agents are like horses wearing blinders; they can only see what's directly in front of them. But desktop applications from companies like GPT and Anthropic are pushing toward something far more interesting: AI that can understand your entire digital world, not just a tiny slice of it. It's the difference between having a personal assistant who can only help you in the kitchen versus one who can manage your entire house.Here's where things get particularly juicy: this isn't some far-off sci-fi fantasy. We're looking at a five-year horizon where the clunky, permission-asking AI of today evolves into something far more sophisticated. The transformation won't happen overnight (sorry, instant gratification seekers), but when it does, we're talking about a 10x boost in productivity that makes current productivity hacks look like using a butter knife to cut down a forest.Key takeaway: While today's AI assistants feel like overeager interns requiring constant supervision, the next five years will usher in truly ambient AI that seamlessly integrates with our operating systems. The future isn't about teaching AI to understand us; it's about AI that already knows what we need, when we need it, across our entire digital landscape.The Limitations of AI Agent MarketplacesThe AI marketplace concept raises important questions about automation's role in our daily work. While downloading specialized AI agents for every task might sound appealing, reality suggests a different path forward. Current marketplace models mirror the Chrome extension ecosystem, where tools often remain peripheral rather than becoming essential to core workflows.Austin frames the central debate in venture capital circles clearly: will we depend on AI agents that require explicit commands, or will we embrace ambient intelligence that works proactively in the background? Looking at the CRM space, Austin points out a crucial consideration that many futurists overlook. You can't simply discard two decades of sales methodology and expect professionals to embrace a completely alien interface. Instead, sellers need familiar elements: contacts, companies, opportunities, and tasks, all presented in recognizable formats that align with established workflows.The intersection of traditional software and AI becomes particularly interesting when Austin discusses CDP platforms. Users expect certain fundamentals, like accessing persona views and tracking customer behavior. The innovation opportunity lies not in replacing these elements but in enhancing them through intelligent automation. Austin suggests that the key difference emerges in how these agents operate: will users actively assign tasks, or will agents run continuously in the background, performing expected functions without explicit direction?While some platforms champion what Austin calls the "jack of all trades" approach with Notion-style customizable workflows, he makes a compelling case for specialized, industry-specific solutions. This focused approach, where AI agents operate autonomously within well-defined parameters, might prove more valuable than a marketplace full of generic tools. Austin emphasizes that the more specialized you are in understanding user needs, the more effective your agentic experience can be, particularly when it runs seamlessly in the background without requiring constant configuration.The reality likely lies somewhere in between these two extremes. Certain straightforward tasks, like data enrichment for new records or basic categorization, seem well-suited for autonomous AI agents. However, more complex decisions involving customer lifecycle management, timing of promotional offers, or predictive modeling for next-best-action recommendations require deeper integration with historical data and sophisticated propensity models. The key to success may not be choosing between marketplace agents or integrated solutions, but rather understanding which approach best suits specific use cases and organizational needs.Key takeaway: Success in AI automation won't come from marketplace-driven point solutions but through deeply integrated, industry-specific AI that enhances existing workflows while maintaining familiar interfaces. Austin's insights suggest focusing on building AI that complements rather than replaces established business processes, creating tools that feel natural rather than revolutionary.The Core Primitives of Martech and the Path to Self-Designing APIsEver tried explaining Bitcoin to your grandparents? That's roughly how it feels watching companies try to skip straight to AI automation without understanding their data foundations. Austin breaks down the concept of primitives in martech, those fun...

What's up everyone, today is our last episode of the year and if you paid attention to the intro, I'm excited to officially welcome Darrell Alfonso as the newest co-host of the podcast!Summary: The Humans of Martech enters an exciting new chapter with Darrell Alfonso joining as co-host, bringing fresh energy and insights to the show. As a long-time listener and new dad, Darrell offers relatable stories of juggling work, family, and community while sharing bold predictions like the shift to warehouse-native architectures in martech, which promise to streamline data operations for enterprises. With AI poised to handle executional tasks, Darrell emphasizes the evolving role of marketers as strategic thinkers guiding AI with emotional intelligence and ethical oversight. As the podcast heads into 2025, it remains committed to delivering actionable insights, thought-provoking predictions, and a fresh perspective for the martech community.Welcoming a New Co-Host and Celebrating Baby MilestonesDarrell's journey to becoming a co-host on the podcast came full circle, blending mentorship, passion, and personal milestones. He shared how one of his mentees suggested the idea, sparking an opportunity he immediately embraced. As an early listener of the show, Darrell highlighted his admiration for its unfiltered and geeky deep dives, calling it his favorite podcast—a sentiment that fueled his excitement for the road ahead.On a personal note, Darrell and his wife recently welcomed their baby boy, just eight weeks ago. Parenthood, he admitted, has been a whirlwind of sleepless nights and steep learning curves. As ambitious and organized as he and his wife are, they've quickly discovered that babies don't operate on predictable timelines. Moments of progress—like better sleep—often take a step back as developmental leaps shake up routines. While the lack of rest is taxing, Darrell's outlook reflects a blend of exhaustion and gratitude.Balancing professional life with a newborn is no small feat. Darrell recounted a whirlwind day of delivering a keynote, driving home, and immediately diving into baby duties. He joked about the unpredictability of these moments while acknowledging the personal growth they inspire. Virtual support groups like Maven have also helped him navigate the early stages of parenthood, offering both guidance and camaraderie with other new parents.For all the challenges that come with parenthood, I always like to emphasize gratitude. Reflecting on the struggles my family faced in our journey to parenthood (and how many other couples have it much harder), we need to emphasize the importance of cherishing even the tough parts. The joy and fulfillment of finally welcoming our child outweigh the sleepless nights and ever-changing routines. Key takeaway: Parenthood is a mix of exhaustion, growth, and gratitude. Embracing the ups and downs, leaning on community support, and focusing on the meaningful moments can help navigate this transformative stage of life.Marketing Tools Without DatabasesOkay… enough baby talk haha. Darrell predicts that in 5 years, most marketing tools will no longer rely on databases. At first glance, this concept might seem shocking—after all, marketing automation platforms, CRMs, and CDPs are fundamentally built on relational databases. But Darrell suggests this assumption is rooted in tradition, not necessity, and outlines a shift toward a warehouse-native or zero-copy data architecture that could redefine how tools operate.To illustrate this point, he draws a simple analogy. Consider apps like Yelp or Google Places. When you share a restaurant with a friend, the app doesn't create a duplicate of your contacts database; it accesses the data on-demand. Contrast this with the typical marketing stack, where almost every tool replicates contact data, creating endless updates, sync errors, and manual fixes. Darrell estimates that more than 80% of a team's data work revolves around ensuring consistency across these copied datasets—a cumbersome and inefficient process.The inefficiency extends beyond wasted effort. Darrell shares examples of bi-directional sync loops that occur when two systems endlessly update each other, introducing a frustrating complexity to even the simplest workflows. These scenarios highlight how deeply ingrained data copying is within current systems and how much time is spent combating its limitations.Shifting to a zero-copy model, Darrell argues, could eliminate these inefficiencies. A warehouse-native approach would enable tools to work directly from a centralized data warehouse, bypassing the need for constant synchronization. This not only streamlines operations but also reduces the risk of errors. It's a radical departure from the status quo but one he believes is inevitable as teams demand greater agility and accuracy in their tools.Key takeaway: The future of marketing tools lies in a warehouse-native approach, eliminating the inefficiencies of duplicated data. By moving beyond traditional databases, teams can reduce errors, streamline processes, and focus their energy on strategic initiatives rather than endless data synchronization.Preparing for a Warehouse Native FutureI think the shift toward a warehouse-native approach for marketing tools feels inevitable, but its timeline remains uncertain. While this approach won't entirely replace APIs, it will change how tools interact. Instead of passing data back and forth through integrations, tools will increasingly work directly from a centralized data warehouse, eliminating inefficiencies tied to duplication and synchronization.This prediction, often misunderstood as futuristic, is already shaping current tools. Vendors like MessageGears and Castle.io are leading the charge, offering solutions that bypass traditional database structures and avoid charging based on record counts. Despite their innovations, the challenge lies in industry adoption. Many teams are accustomed to older models, making this transition as much about change management as it is about technology.A critical insight from my past research and conversations with experts on the podcast highlights the importance of internal readiness. Tools can only perform as well as the data they rely on. High-quality, structured data is the foundation for warehouse-native success. Teams must focus on improving internal processes now, rather than waiting for the perfect tool to arrive. This means investing in data hygiene, organization, and strategy to prepare for the opportunities that a warehouse-native architecture will bring.However, the path forward isn't without challenges. Many companies are still immature in their data strategies, making widespread adoption a longer process than anticipated. Whether this shift takes five years or more, the direction is clear: vendors and teams must align their operations with the possibilities of a warehouse-first world.Key takeaway: Warehouse-native tools represent a significant step forward in reducing inefficiencies and modernizing operations. Teams can prepare for this shift by prioritizing high-quality, well-structured data. The strength of these tools lies in how they interact with clean, organized data, making internal readiness the best first step for embracing this future.Understanding When Warehouse Native Tools MatterDarrell explains that the value of warehouse-native tools becomes clear especially when dealing with large volumes of data. For small and mid-sized companies, the classic setup—a CRM, marketing automation platform, and a few connected tools—works perfectly fine. He notes that for organizations with 500 employees or fewer, traditional data architectures remain suff...

What's up everyone, today we have the pleasure of sitting down with Kacie Jenkins, SVP Marketing at Sendoso. Summary: Marketing isn't about cramming creativity into a spreadsheet, and Kacie's journey proves it. She took on last-touch attribution, broke free from narrow metrics, and built a system that told the whole story, one where sales and marketing actually worked together. It wasn't flashy; it was months of unsexy foundational work that led to record-breaking results. Kacie's advice is to stop obsessing over proving your worth with perfect data. Focus on collaboration, long-term strategies, and building something so good it proves itself.About KacieKacie started her career as a recording artist for 6 years where she recorded and released 2 top 30's singles on country radioShe transitioned to FANDOM as Marketing Manager where she helped build and scale entertainment and gaming communitiesShe then shifted to consumer tech and worked at Roku where she helped take their streaming stick to marketShe later joined Fastly when they were still a tiny startup and was eventually promoted to VP of Marketing while helping them scale to $200M in ARR and a massive IPOShe moved on to a few other VP of marketing stints at Ace Hotel and then SourcegraphToday Kacie is Senior Vice President of Marketing at Sendoso, the top gifting and direct mail platform for revenue teamsWhy Marketing Needs to Break Free from Last Touch AttributionKacie has strong opinions about last touch attribution and its role in marketing, calling it both misguided and overused. She recounts a memorable example where a company's finance team mandated that every marketing touchpoint be unique, forbidding multiple efforts for a single account. The result was a fragmented strategy, with marketing forced to isolate efforts rather than integrate them—a scenario she describes as fundamentally broken. This, she says, reflects a wider misunderstanding of marketing's role in driving success.In her experience, marketing is often held to an unrealistic standard that no other department faces. “No one questions whether a sales team should exist,” Kacie points out, yet marketers are repeatedly asked to prove their value in isolation. This obsession with single-point attribution—whether first or last touch—reduces complex buyer journeys to simplistic, unrealistic models. She likens it to sports, where success is measured by the contributions of the entire team, not just the final goal or play. In marketing, the same principle applies: campaigns succeed when brand, product, sales, and customer experience work cohesively.Kacie highlights how marketers often agree to flawed measurement practices under intense job pressure. Many leaders, she notes, demand immediate, trackable results and dismiss longer-term investments like brand building. When these short-sighted strategies fail, the blame lands on the marketing team, perpetuating a destructive cycle. This became especially apparent during the pandemic, when companies slashed budgets for brand and integrated marketing, only to see their performance suffer months later.At its core, the problem stems from a demand to quantify marketing in ways that are convenient rather than meaningful. Kacie insists that attribution models like last touch can provide insights but have been misused to force marketing into a demand capture role that undervalues its broader impact. Effective marketing, she argues, cannot succeed in a vacuum—it depends on the health and alignment of the entire organization.Key takeaway: Attribution models like last touch offer insights but become problematic when used in isolation. Marketing thrives on collaboration across teams, long-term investments, and integrated strategies. Simplistic measurement frameworks undermine this by reducing success to isolated metrics, which fail to capture the bigger picture. Focus on fostering collaboration and investing in holistic strategies rather than chasing immediate, trackable wins.What's the Best Way to Prove What Drives Revenue in Marketing?Kacie's candid take on the challenges of attribution didn't stop there. She explains that board members and leadership often seek simple answers, asking, “What drove the most revenue?” This, she notes, is rarely a question with a singular answer, and it certainly doesn't lie solely in the last touchpoint.Her approach combines every available data point, UTMs, self-reported attribution, and multi-touch models, to create a comprehensive picture. This isn't about assigning credit to one channel or tactic but understanding the collective influence of all touchpoints. For instance, at Sendoso, Kacie leveraged this holistic perspective to reinvigorate outbound sales. By investing in trust-building, strong branding, and thoughtful partnerships, the team shifted outbound calls from cold to warm, creating an environment where sales and marketing aligned seamlessly. The results were tangible, but proving causality required a deeper story, not just a simple report.She recalls challenging her finance team's reliance on last-touch data. When presenting a report that suggested “more direct traffic” as the solution, she asked bluntly, “What does that even mean?” This moment underscored how reductive metrics fail to capture the true impact of marketing efforts. By shifting the focus to sales-qualified opportunities and long-term patterns, she built trust with stakeholders and steered conversations toward what truly drives growth.Kacie emphasizes that this broader view isn't fast or easy, and it requires fighting against short-term thinking. Marketers must advocate for strategies that don't immediately show up in last-touch reports but are essential for sustainable growth. She also draws from B2C insights, where buying decisions often happen long before measurable touchpoints, reminding us that customers' journeys rarely follow a predictable path.Key takeaway: Attribution isn't about isolating success to one channel or tactic. By combining multiple data sources and focusing on long-term causality, marketers can tell a more accurate story. This approach builds trust with leadership, aligns teams, and justifies investments that might not show immediate ROI but are crucial for sustainable success.How to Convince Leadership to Rethink MeasurementKacie explains that driving change in marketing attribution and measurement requires aligning cross-functional teams and proving value over time. When she joined Sendoso, the disconnect between sales and marketing created distrust, and outdated metrics like MQLs dominated conversations. To address this, she set clear expectations with leadership: changes would be foundational, require significant investment, and take time to show results. This up-front agreement ensured her efforts had initial backing, though challenges arose as the process unfolded.A crucial part of the transformation was bridging the gap between marketing and finance. Kacie worked with a finance partner who embraced curiosity, seeking to understand marketing's perspective by educating himself through webinars and discussions. This mutual respect and collaboration were essential for aligning goals and building trust. She demonstrated that her approach wasn't about gaming numbers or securing credit but about laying a foundation for sustainable growth.Despite initial alignment, skepticism crept in as foundational work—cleaning up Salesforce fields, rethinking sales stages, and redefining metrics—took longer to yield visible results. Kacie emphasizes the importance of perseverance during this phase. Companies often lack the patience for foundational changes, cutting le...

What's up everyone, today we have the pleasure of sitting down with Stephen Stouffer, Director of Automation Solutions at Tray.ai and the first ever returning guest. We had Stephen on earlier in the year in episode 112 where we unpacked the practical wonders of combining AI tools with iPaaS solutions. Summary: AI can transform your marketing without overwhelming you. Start with one use case. Watch the results, and go from there. You don't need to master data science to add AI value, but you need to be willing to experiment, keep what works, and let the tech do the heavy lifting. Customer Journey Mapping EssentialsCustomer journey mapping, as Stephen puts it, is best approached as a clear, structured framework. For marketers, this often starts by examining the visitor's first few seconds on a website. Stephen's “three, five, seven rule” is a useful guide: three seconds to capture attention, five to build engagement, and seven to prompt action. Reviewing homepage or landing page performance through this lens keeps the focus on essentials. Are calls-to-action (CTAs) clear and accessible? Does the page guide users toward the intended outcome effectively?Stephen further notes the importance of every element “above the fold.” Content here needs to be concise, visually appealing, and should naturally lead users to the next step. A well-placed CTA, such as a prominent button, encourages forward motion, while a hidden or confusing one can derail the journey. Each interaction should be straightforward and intuitive.Beyond landing pages, Stephen highlights the journey before a visitor even arrives. Campaign managers, for instance, should ensure that ad copy and visuals align with the landing page, creating a smooth transition from ad to action. Consistency here reduces friction and keeps the experience cohesive.For advanced mapping, Stephen recommends storyboarding different customer personas and their digital pathways. By tuning each stage to fit these profiles, marketers can craft a journey that feels relevant and trustworthy, engaging each segment from the very first interaction.Key takeaway: Use the "three, five, seven rule" to evaluate each customer touchpoint on your homepage or landing pages. This approach helps ensure your content captures attention, fosters engagement, and prompts action—all within a few seconds.AI's Role in Automating Personalized EmailsStephen recently demonstrated how AI automates personalized emails with just a first name, last name, and email. AI uses data from sources like LinkedIn, company details, and job history to craft messages that feel genuinely tailored to each recipient, far beyond typical generic responses.This level of automation doesn't just boost engagement; it saves significant time. Instead of setting up complex variable fields or spending 15-20 minutes per email on manual research, AI handles it all in seconds. Stephen notes that marketing teams can skip intricate field configurations, while sales teams gain back valuable time to focus on high-impact tasks.AI also serves as a replacement for traditional enrichment tools, pulling in dynamic contact details without third-party data providers. For sales, it means delivering relevant, personalized content effortlessly. AI does the heavy lifting, creating an email that feels custom-built for the recipient—no manual assembly required.Key takeaway: AI enables efficient, data-rich personalization for customer outreach, saving marketing and sales teams time and resources while boosting the quality of each touchpoint.Automating Personalized Outreach with AI AgentsAI agents are redefining how teams approach personalized outreach, offering new ways to automate highly customized interactions. Stephen explains how Tray.ai leverages a powerful combination of APIs—OpenAI, Google, LinkedIn, and more—to build out complex automation processes directly within its platform. Each AI agent is designed to use the best tool for the task at hand. Given the right context and instructions, these agents can gather relevant data from press releases, Crunchbase, LinkedIn profiles, blog posts, and other sources to craft an email that feels genuinely tailored.Imagine a marketing email generated entirely by an AI agent. With the recipient's email, role, and other contextual clues, the AI might produce a message like, “Hey, congratulations on your recent speaking slot at AntiCon in London. Hope you had a safe journey back!” This level of personalization would usually require about 15 minutes of research by a BDR or ISR. Now, it can be fully automated, freeing up sales and marketing teams to focus on strategy and high-priority tasks rather than time-consuming data gathering and crafting.Stephen points out that the true power of AI agents comes from implementing them in real, tangible ways. For instance, rather than abstract promises of efficiency, Tray.ai demonstrates AI's impact with practical use cases like this automated email personalization, which resonates more directly with the people using it. By creating a functional demo that allows teams to see this technology in action, Tray.ai bridges the gap between AI's potential and its practical application.For anyone curious to test it out, Stephen offers a live demo of the personalized email automation. This hands-on approach helps users understand the realistic possibilities AI agents bring to customer engagement and outreach, transforming the process from concept to actionable, impactful workflows.Key takeaway: AI agents streamline personalized outreach, combining data sources and automation tools to generate highly customized emails without manual research. By automating these tasks, teams can focus on high-impact activities while still delivering meaningful, individualized interactions.Challenges in Implementing AI-Driven Customer Journey MappingImplementing AI-driven customer journey mapping and personalization comes with its share of challenges. Stephen highlights three primary obstacles teams face: complexity, connectivity and compliance.The technology's complexity. Even technical professionals sometimes struggle to understand the nuts and bolts of AI integrations, making it difficult for organizations to determine how to effectively deploy these tools. The ambiguity around building and customizing AI solutions internally often becomes a barrier to adoption.The challenge of data connectivity. For AI agents to deliver relevant outputs, they need access to comprehensive data across systems. Whether it's a CRM, sales records, or product usage data, these inputs provide the context for AI to make useful recommendations. While crafting a prompt might sound straightforward, gathering and linking all the necessary data to inform that prompt is anything but simple. Stephen explains that AI can only be as effective as the information it's fed, making seamless data integration a top priority for effective personalization.Perhaps most daunting, the challenge is compliance. When feeding sensitive data into large language models, teams must navigate a maze of security requirements like SOC 2, HIPAA, and GDPR compliance. Many organizations hesitate to dive into AI because of the fear of regulatory risks. Legal teams often step in, concerned abo...

What's up everyone, today we have the pleasure of sitting down with Nataly Kelly, CMO at Zappi. Summary: Global expansion is a wild process that connects brands to the unique vibe of each market, it's not just creating a website or translating content. Every market brings its own needs, from how audiences navigate sites to what resonates visually and emotionally. Moving into international territories means showing up prepared, with a localization strategy that's flexible and has a ton of local insight. Marketing Ops and RevOps both play a key role in localization as a strategic partner, organizing data and decision-making to fuel growth across departments. About NatalyNataly started her career as an interpreter at AT&T and later co-founded a research and consulting company which was acqui-hired by her biggest customer where she would serve as Director of Product DevelopmentShe later held Chief Research Officer and VP of Market Development titles at a market research firm and a translation and localization companyNataly then made the mega move to HubSpot as VP of Marketing where she would spend nearly 8 years – involved in all aspects of full-funnel marketing globally, including International Ops and LocalizationShe then moved to Rebrandly as Chief Growth Officer leading sales, marketing and product Nataly's also an author, she's published 3 books and 1 coming out next year, she has a Newsletter called ‘Making Global Work'Today, Nataly's moved into her 4th SaaS marketing leadership role as CMO at Zappi–the leading consumer insights platform Why LinkedIn Works for Building a NewsletterNataly decided on LinkedIn for her newsletter with one primary goal: reaching more people, fast. In marketing, there's always talk of “owning your audience,” but for Nataly, the built-in reach LinkedIn offers outweighed the usual risks. Sure, LinkedIn could shift its algorithm or start favoring video, but Nataly isn't fazed. She believes adaptability is more valuable than control. “If LinkedIn ever moves entirely to video, I might reconsider,” she says. “But for now, it's a writer's platform, and I'm a writer.”What really sold her, though, is LinkedIn's “triple play” effect. Each time she publishes a newsletter, her audience doesn't just see it once—they get three reminders. The content appears in their feed, triggers a platform notification, and even lands in their email inbox. This multi-touchpoint delivery isn't just convenient; it significantly boosts her visibility. In a crowded digital space, those three nudges are powerful. And the best part? It doesn't take any extra work on her end. For Nataly, this setup is gold: “If I can reach my audience in three different ways without doing three times the work, I'm in.”On top of that, LinkedIn's algorithm has started indexing her posts for keywords, so they pop up in search results long after she hits “publish.” Nataly likes this longevity. She's seen her posts gather momentum over time, which reassures her that LinkedIn isn't likely to abandon text-based content anytime soon. This layered exposure works in her favor, especially since she's already built a solid following on LinkedIn. Her audience is naturally expanding, without any additional ad spend or email list management.This approach ties back to a guiding principle Nataly picked up at HubSpot: follow the growth. When a channel shows traction, commit fully and ride the momentum. LinkedIn's growth trajectory fits perfectly with her goals, allowing her to spend her time effectively—engaging with followers, creating relevant content, and letting the platform do the heavy lifting. “I see LinkedIn growing, and I'm here for the ride,” she says.While email newsletters and other platforms might come into play in the future, right now, LinkedIn is her sweet spot. It's a low-maintenance option that lets her connect with her community directly, on the platform where she's already active. She's writing for the sake of sharing knowledge, and LinkedIn offers a direct, hassle-free way to reach a broad audience without splitting her focus across multiple channels.Key takeaway: For marketers aiming to maximize reach, LinkedIn's multi-touchpoint setup and organic audience growth make it an ideal platform. When traction is the goal, LinkedIn's notification, email, and feed distribution offer valuable, low-effort exposure—perfect for those who want to focus on content, not channel management.Understanding the Nuances of Going GlobalNataly makes a clear distinction between "going global" and "going local," a distinction that goes beyond simply putting content online for everyone to see. Launching a website, or even setting up a LinkedIn profile, can technically connect a person to a global audience. But creating an intentional, local connection demands a specific approach, one that carefully considers language, cultural context, and user experience. For Nataly, globalization isn't just about reaching people across borders—it's about meeting those audiences where they are, with language and content that resonate.Her insights stem from years of experience, including her work at HubSpot, where she developed a practical framework to explain these concepts to teams across the company. She found that simplifying these ideas into one-word definitions helped cut through the confusion. For example, “internationalization” is about adapting the technical side, like making code accessible to different languages and regions. This step ensures the foundational structure can support localized content, but it's just the beginning.Translation, Nataly explains, isn't about directly swapping words. True translation involves adapting the message itself. For one audience, a particular phrase might evoke excitement; for another, it might fall flat or even offend. Nataly emphasizes that effective translation reaches beyond literal words to convey a message that feels native to each audience, maintaining intent, tone, and cultural relevance.Localization goes further, adapting the entire user experience for specific markets. It's not just about making text comprehensible but ensuring every interaction—from navigation to design—feels intuitive for users in diverse regions. For instance, a website optimized for American users may assume all visitors speak English, but this model doesn't apply universally. In countries like Canada, India, or across the EU, multi-language realities complicate navigation. This level of adaptation requires deep cultural and technical knowledge to avoid common pitfalls and create a seamless experience.Globalization, however, is the ultimate adaptation, demanding a complete rethinking of the framework itself. Nataly notes that one of the biggest challenges is getting teams to shift from a single-market mindset to a truly global perspective. A platform initially designed for one language or culture may struggle when stretched to fit a multilingual or multicultural user base. Globalization requires a build-it-right-from-the-start approach, anticipating diverse user needs and ensuring the platform can expand without limitations.Key takeaway: Successful globalization is about more than just reaching an international audience; it requires intentionally adapting every layer—from code to experience—to create content that resonates locally while remaining accessible globally.Strategic Timing for Going GlobalWhen HubSpot considered expanding internationally, it wasn't about leaping into new markets; it was about waiting until the timing and resources aligned. Nataly recalls that CEO Brian Halligan was deliberate, even drafting a Harvard Business Review piece outlining Hu...

What's up everyone, today we have the pleasure of sitting down with Jim Williams, CMO at Uptempo. Summary: Forget version control spreadsheets and stale budgets, Jim's take on marketing planning is about putting purpose behind every dollar. Instead of throwing darts at a board, focus on creating a blueprint that connects goals to actual business impact. For him, goals shouldn't be handed down from the top like a royal decree but hammered out together with practitioners so they're ambitious… but you know, grounded in reality. Marketing Ops pros are the unsung heroes, bringing sanity to the madness with data and KPIs that keep every piece aligned. Plus, AI's set to take over the boring bits—updating data, tracking budgets, making sure no dollar gets lost—leaving marketers free to do what they do best: make real magic happen.About JimJim started his career in PR and Product Marketing before spending 7 years at Eloqua as Sr Dir of Product Marketing and helping the company rise from 15M ARR to 92M and IPO. He later moved on to Influitive – the popular advocate marketing platform – as VP of Marketing where he helped grow the company from pre revenue to 12M in ARRHe then moved over to the DNS world as Snr VP of Marketing at BlueCat where he led all facets of marketingHe then became CMO at BrandMaker which has since rebranded to Uptempo, the leading enterprise marketing operations software that helps marketers plan better, spend smarter and execute with confidence.What Is a Marketing PlanJim dispels the idea that marketing planning should be like “throwing darts at a dartboard.” A marketing plan isn't a guessing game; it's a strategic framework for how teams tackle the future. One of the most common mistakes Jim sees? Dusting off last year's plan and rebranding it for the new year. This tactic, he argues, is the quickest way to stay stuck. In a world that demands fresh thinking, relying on past strategies doesn't cut it.The old-school concept of a “pivot” has taken on a new life in marketing. It's no longer about just one big strategy shift but about building in constant adaptability. Jim suggests that, unlike traditional yearly plans, today's marketing requires continuous recalibration. The best teams aren't just agile once—they're agile all the time. That flexibility to assess, pivot, and refine isn't a luxury; it's the core of modern marketing planning.Another common pitfall Jim highlights is the habit of dividing up the budget before solidifying a game plan. For too many teams, budget allocation is seen as the end goal rather than just a piece of the puzzle. Getting the numbers in place is just step one, not the entire strategy. A plan isn't simply a breakdown of costs; it's the strategic “why” and “how” behind each dollar spent. Without defining the intended outcomes, budgets lose meaning.Jim makes an essential distinction: budgets support the mission, but plans set the course. The budget tells you what's possible financially, but the plan clarifies what needs to be achieved. This separation between resources and goals keeps marketing teams focused, providing a framework to measure success rather than just track expenses. With a clear strategy in place, budgets go from static numbers to dynamic assets driving real outcomes.Key takeaway: A budget is just a set of numbers; a marketing plan is the vision behind those numbers. By keeping intent at the forefront, teams can transform budget allocations into impactful actions, staying adaptable and ready for whatever's next.Building a Marketing Plan That Aligns Top-Down and Bottom-Up GoalsJim dives into the complexities of planning in a large organization, pointing out that it's not a matter of simply setting goals at an offsite retreat. At the enterprise level, planning is a detailed, phased, six to nine-month process. Yet, he notes that surprisingly few accessible resources break down this method. For many marketers, planning seems shrouded in mystery—a skill they're expected to learn on the job, often after they've already taken on leadership responsibilities.Jim explains that marketing planning often starts with annual, top-down forecasts. This approach provides broad company objectives, which interlock with a bottoms-up plan in later stages. Rather than seeing top-down and bottom-up planning as opposing methods, Jim views them as stages in a coordinated approach. At Optempo, they've formalized this method in a seven-step “blueprint for marketing planning” to guide teams through each phase. This blueprint begins with setting overarching company objectives—determining whether the focus is on market expansion, product launches, margin improvements, or even mergers and acquisitions. Until these objectives are set, marketing teams can't start defining specific growth tactics.Once top-level objectives are clear, Jim explains that the marketing team distills them into a focused “plan on a page,” a roadmap outlining how marketing will support each objective. This document serves as a communication tool, clarifying what marketing intends to achieve and aligning these goals with company-wide expectations. According to Jim, defining these specific objectives—whether they involve selling to new buyers, entering fresh markets, or optimizing existing processes—is foundational for cohesive planning.Jim also breaks down the budget allocation process, which directly follows the plan on a page. This is where marketing teams work with finance to divide funds, categorizing costs into programmatic and non-programmatic expenses, as well as campaign-based and non-campaign-based spending. By grouping expenses into clear, high-level “buckets,” Jim explains, teams ensure their budgets align with strategic priorities and company-wide financial targets.Key takeaway: A successful marketing plan balances top-down objectives with bottom-up execution. Begin with high-level company goals, then translate them into actionable steps and align budget allocations accordingly. This approach ensures that both strategy and resources are directed toward achieving meaningful impact.Why Marketing Goals Need to Be a Two-Way ConversationJim counters the misconception that company goals are simply handed down from a closed-door board meeting, with marketers then left scrambling to hit those targets. He clarifies that in most forward-thinking companies, the setting of financial objectives isn't a secretive, top-down affair. Instead, it's a dialogue involving senior leadership across all departments—including marketing. When the ownership of a business, be it public shareholders or private investors, establishes financial ambitions, these aren't randomly assigned numbers; they're set with input from an executive team that includes the CMO or head of marketing.Jim explains that technology companies, for example, often focus on maximizing valuation. The board or ownership group typically benchmarks these goals using standards like the “Rule of 40”—a common framework in SaaS that blends growth rate and profitability. But these objectives are usually part of a larger, multi-year vision, not just a single-year target. Once these broad metrics are set, the board works backward to define the current year's objectives. From there, it's up to the executive team, including marketing leadership, to devise the most effective strategies to meet these targets.Jim emphasizes that marketing isn't just a passive recipient of goals. Marketing leadership works closely with other executives to determine how marketing can help hit specific benchmarks. It's at this stage that the conversation turns practical. For instance, if a company needs a particular level of market penetr...

What's up everyone, today we have the pleasure of sitting down with Barbara Galiza, Growth and Marketing Analytics Consultant.Summary: Attribution is a bit like navigating Amsterdam's canals: mesmerizing but full of hidden turns that don't always make sense. You don't need to chart every twist—just focus on finding the direction that moves you forward. Instead of obsessing over every click, use attribution like a compass, not a GPS. Multi-touch attribution (MTA) gives you some of the story, but often misses those quiet yet powerful nudges that drive real decisions. Layering in rule-based or incrementality testing can fill the gaps, giving a clearer picture of what's driving your wins. For startups, it's even simpler: stick to what's working and forget complex attribution—qualitative feedback is often the best guide in the early days. Data doesn't need to be perfect, just practical, and sometimes trusting that a strategy is working is enough to keep pushing it.About BarbaraBarbara was an early employee at Her (YC), the biggest platform for LGBTQ women where she would eventually become Head of GrowthShe was also Head of Growth at different startups like Pariti and HomerunShe worked at an agency where she led data and analytics for Microsoft EMEABarbara then went out on her own as a GTM and Analytics consultant for various companies like Gitpod, WeTransfer, Sidekick and dbt LabsShe has a newsletter on marketing data: 021 newsletter.She produces content for data brands (dbt, Mixpanel, Amplitude) like case studies and webinarsBuilding Data Literacy Through SQLData literacy is essential for modern marketers, but it doesn't have to be intimidating. Barbara's advice is simple: learn SQL. While marketers today are surrounded by user-friendly tools and drag-and-drop interfaces, those who want to truly grasp their data should get comfortable with SQL. It's not about becoming a data engineer but about understanding how the numbers you rely on every day are built. SQL helps you see how data connects, how it's organized, and how you can group it to make sense of what's happening in your campaigns.What's great is that you don't need to dive into formal classes or certifications. Start where you are. Most companies are sitting on a goldmine of structured marketing data, whether it's Google Analytics data in BigQuery or Amplitude events stored in a data warehouse. The next time you're building a report, try using SQL for a small part of the process. It's a skill that compounds over time. Once you get familiar with the basics, you'll start to see data in a different way, and you'll be able to spot insights faster.Barbara also points out a crucial, often overlooked skill: understanding why your tools give credit to certain campaigns. Why does one Facebook ad outperform others in your reports? Why does Google Analytics attribute more conversions to certain sources? Getting to the bottom of these questions puts you in a much stronger position as a marketer. If you can explain how attribution models work and why certain data points appear, you're already ahead of most.At the end of the day, it's about making smarter decisions. Barbara believes that marketers who can confidently say, “I know why these numbers look the way they do,” are in the top 10% of data-driven marketers. It's not just about collecting data; it's about making sense of it and using it to steer your strategies.Key takeaway: Learning SQL gives marketers the power to truly understand their data. Starting small, even with basic queries, can unlock a deeper understanding of how marketing data is structured and why campaigns perform the way they do. The key is to build practical skills that help you make more informed decisions.Rethinking Attribution and Understanding Its Role in MeasurementBarbara brings clarity to two commonly conflated concepts: attribution and measurement. While many marketers default to thinking of attribution as purely click-based or multi-touch attribution (MTA), Barbara challenges this view. She argues that attribution goes beyond just tracking clicks and touches throughout a customer's journey. It's about understanding the overall impact of marketing efforts—whether through incrementality tests, media mix modeling (MMM), or holdout groups. Attribution is meant to explain how marketing drives results, but it's not the only tool for assessing campaign success.MTA, particularly click-based models, excels at measuring bottom-funnel actions like search marketing, where high-intent users click on an ad and then convert. This method works well for campaigns that rely on clicks to move the needle. However, Barbara notes that it has its limitations, especially when it comes to non-click-based channels like video or display. MTA often over-credits search campaigns because that's where the conversion is tracked, but it misses the broader influence of awareness-building efforts. In essence, MTA can tell you what happened after the click, but not what inspired it in the first place—be it a podcast mention or an engaging piece of content seen days before.On a broader level, Barbara explains that attribution is not the same as measurement. Attribution focuses specifically on tying marketing efforts to business results, such as leads or revenue. Measurement, on the other hand, casts a wider net. It includes performance across various metrics, not just conversions. For instance, measuring how well different messaging resonates with audiences is crucial, but it doesn't always directly lead to immediate sales. Measurement can inform future strategies by offering insights into engagement, customer preferences, and channel effectiveness.As Barbara sees it, attribution is a subset of measurement. It's a tool for understanding what drives business outcomes, but it shouldn't be the only tool marketers rely on. For example, MTA has its place but should be used alongside other models like MMM to paint a fuller picture. Measurement, meanwhile, helps marketers assess the effectiveness of everything from messaging to customer touchpoints, beyond just the end goal of conversion.Key takeaway: Attribution is one piece of the measurement puzzle, focusing on business outcomes, while measurement encompasses a broader range of insights. Marketers should use a mix of attribution models to understand their campaigns and apply measurement tools to gain a holistic view of performance.Limitations of Multi-Touch Attribution in Credit DistributionMulti-touch attribution (MTA) is often seen as a way to distribute credit across different customer touchpoints, but Barbara questions its effectiveness in this role. She argues that MTA is inherently limited because it only attributes credit to interactions that involve a click. This creates a skewed view of the customer journey, where only click-driven strategies—like search ads—are recognized, leaving other key touchpoints, like connected TV (CTV) or social media, out of the equation. The result is a narrow perspective that doesn't capture the full influence of various channels.Barbara points out that for marketers to make better decisions, MTA needs more than just click data. One alternative she suggests is pairing MTA with rule-based attribution models, where data from "How did you hear about us?" surveys are integrated into the analysis. This way, marketers can capture insights from channels that don't typically generate clicks but still play a crucial role in driving awareness or consideration. By adding this type of first-party data, businesses get a broader understanding of what's really influencing their customers.Some data agencies are also experimenting with es...

What's up everyone, today we have the pleasure of sitting down with Steven Aldrich, Co-CEO and Co-Founder at Ragnarok NYC. Summary: Like the aftermath of Ragnarök according to Norse mythology, the martech world is emerging stronger, more focused, and ripe with potential. Rather than being overwhelmed by the chaos, marketers should use this time to rethink how to evaluate technology choices through the lens of business value. Prioritize platforms that drive real-world impact and avoid getting lured by features that blaze brightly for a moment, only to be swallowed by the tide of irrelevance.About StevenSteven's first job out of business school was a customs broker in Colombia, before his Visa ran out and he was forced to return to the US He started his marketing career as a Marketing and Comms Associate at a market research firm where he discovered the wonders of HTML, email development and Adobe dreamweaverWhile continuing his full time in-house career working in email and CRM roles for different industries, Steven and his co-founder Spencer launched Ragnarok, first as a side hustle where they spent their evenings moonlighting as marketing technology consultantsIn 2017, both co-founders decided to take the leap and go all in on their agencyToday Ragnarok is a 50+ person full service martech agency that's helped well known brands like zapier, dropbox, asana, adobe and many more!The Evolution of Martech and the Impact of ConsolidationWhen asked about the future of martech, Steven immediately highlighted the ongoing consolidation in the industry. He pointed to acquisitions like Twilio snapping up Segment and Salesforce expanding its Customer Data Platform (CDP) offerings as clear signals. According to Steven, these moves indicate that we're in the midst of a reshuffling phase—one that will shape how martech platforms are built and used over the next decade.However, it's not just about merging and acquisitions. Steven sees the next wave of growth stemming from generative AI. This technology, while still in its infancy for many organizations, will soon be as fundamental as marketing automation tools were a decade ago. Platforms are experimenting with Gen AI features like automated content creation, but they're still scratching the surface. “Right now, a marketer isn't likely to sit down and have their AI tool write an entire creative brief,” Steven noted. “But once the tech reaches a level where it's drafting briefs and campaign strategies, it'll fundamentally change what marketers do day-to-day.”He also predicts that the next few years will separate the genuine innovators from the rest. Startups focusing on AI-powered automation and advanced integrations will emerge as key players. Those that fail to embrace this trend will struggle to maintain relevance. Steven pointed to companies like Castle.io as an example—a newer entrant that has managed to make a name for itself by rethinking traditional automation and going all-in on a warehouse-first approach.Looking ahead, Steven envisions a future where marketers become more like strategic curators rather than operators. Instead of creating every campaign element manually, marketers will outline goals and high-level structures, and let the tools figure out the rest. “Think of a platform where you set your conversion goals, outline your audience, and the tool builds the journey for you,” he explained. Some companies are testing these capabilities internally, but we're still far from a world where it's the norm. To reach that stage, platforms need to overcome significant technical challenges and gain marketer trust.Ultimately, Steven believes that by the ten-year mark, the martech industry will look entirely different. The focus will shift away from basic integrations and automation to more complex AI-driven orchestration. Platforms will evolve into decision-making engines, allowing marketers to focus on strategy, creativity, and innovation, leaving the grunt work to the machines.Key takeaway: The martech industry is undergoing a consolidation phase as it readies itself for the next wave of innovation: generative AI. Startups that embrace AI-driven automation will emerge stronger, while legacy platforms must integrate these new capabilities or risk becoming obsolete. In the next decade, marketers will transition from hands-on campaign execution to strategic oversight, as tools handle more of the complex work autonomously.Blending Automation with Human Spark for Smarter Martech StrategiesWhen it comes to AI and automation in martech, there's a spectrum of opinions. On one end, some marketers insist that only a human can truly understand and engage their audience. On the other end, there's a growing camp eager to hand over the repetitive tasks to machines and focus on strategy. Steven pointed out that the real value lies in finding a balance between the two extremes, especially for industries with strict compliance requirements like FinTech and health tech.Steven used abandoned cart programs as a foundational example of automation's role in marketing. Not long ago, these campaigns were inconsistent and cumbersome. Companies like Klaviyo and Shopify stepped in, making abandoned cart emails table stakes for eCommerce. Now, if you abandon your cart, you can almost predict when you'll receive that follow-up email offering a discount or reminder. “It's just expected,” Steven explained. He believes this kind of automated functionality has become the baseline for what customers and marketers alike view as the norm.But not every industry can afford to automate at that level. With sectors like finance or healthcare, there's a need for humans to review and validate messages for compliance. “A legal person is at the end of every review,” Steven said. “It's frustrating and time-consuming, but the cost of sending the wrong message at the wrong time is just too high.” He sees these industries gradually adopting AI where they can—incremental optimization, message testing—but keeping a human in the loop for quality assurance.The evolution of martech, in Steven's view, will be about advancing beyond these early stages. He predicts that the future will bring a seamless integration where humans set high-level goals, and AI takes care of execution. The role of the marketer shifts from managing individual campaigns to curating experiences and setting strategic parameters. Some platforms are already testing these capabilities, but they're far from ready for mainstream adoption. “Imagine a future where marketers simply set their audience, goals, and content, and the tool builds the entire journey for them,” Steven envisioned. This approach would redefine what it means to be a marketing operator, giving professionals more time to think strategically rather than tactically.Ultimately, Steven sees the evolution of martech as an interplay between speed and quality. Some companies will succeed by automating faster, launching multiple initiatives, and iterating based on outcomes. Others will opt for a more deliberate approach, spending more time crafting the perfect message. “There isn't one clear winner,” Steven concluded. “It's about choosing the right tool for the job and understanding what's at stake when the human element is minimized.”Key takeaway: Martech's future lies in balancing automation with human oversight. While some industries can embrace full-scale automation, others need humans in the loop to maintain compliance and quality. Marketers must choose tools that fit their strategic goals—whether that's rapid iteration or precision crafting.The Value of Data Science in Martech OptimizationWhen asked about the role of data science in marketing operations, Steven was quick to point out the di...

What's up everyone, today we have the pleasure of sitting down with Danny Lambert, Director of Marketing Operations at dbt Labs. Summary: Marketers often feel like they're battling a dragon when it comes to integrating data. We're overwhelmed by technical jargon, stuck with outdated methods, and facing roadblocks from data teams. Danny walks us through his journey of cautiously entering the data world and the role dbt can play for marketing teams. By learning just enough SQL, knowing what tools you need to get started with and leaning on dbt's tools, you can start small and gradually build a warehouse-first martech stack. The reward is more control over your data, flexibility to deploy personalized campaigns independently, and a competitive edge that no pre-packaged solution can match.About DanielDanny started his career at an event solutions company where he wore several different marketing hats including getting his first taste of marketing automation  He then worked in marketing ops at IZEA, at marketplace that connects brands with influencers before having a short stint at McGaw.io one of the leading martech and analytics agenciesHe then moved over to healtech at CareCloud where he led Demandgen and ABMHe then transitioned to Rev.com the popular transcription company where he started in marketing ops, then demand gen before being promoted to Director of Integrated MarketingAnd today Dan is Director of Marketing Operations at dbt Labs, the creators of the most popular software for data transformation used by data engineers at more than 20k companiesNavigating the Disconnect Between Marketers and Data TeamsMany marketers struggle to engage with data teams because they feel worlds apart. Danny points out that it's a lot like the early days of marketing's relationship with product teams. Before product-led growth (PLG) became a buzzword, marketers and product teams operated in separate silos. It took a concerted effort to break that wall, and the same shift is needed with data. Marketers often find the mechanics of data engineering and warehousing intimidating, and for good reason—they weren't trained for it. But it doesn't have to be that way.Danny recounts his time at CareCloud, where he was exposed to the concept of a data warehouse. The idea was gaining traction, and he attended a Snowflake event to grasp the essentials. After an hour of slides and schemas, he walked out just as confused as when he walked in. The issue wasn't the information; it was the delivery. Marketers need to see things in action. Theoretical talks don't cut it—practical, straightforward tutorials that walk you through the steps are what marketers crave. Installing tools like dbt and seeing data move can make it all click. It's the difference between hearing about a new tool and actually feeling it work in your hands.There's also a major gap in educational resources that cater to marketers. As Danny highlights, marketing professionals who want to embrace data often get lost in the flood of courses and jargon-heavy materials. It's a jungle out there—marketers want concise, actionable guidance, not a deep dive into tech theory. Without the right content, many opt to stay in their lane, using tools and methods they already know. It feels safer, especially when they're under pressure to perform quickly.Danny points out that this pressure to ramp up fast can discourage experimentation with a warehouse-first approach. New roles often come with tight timelines, and there's a tendency to lean on old habits. Shifting to something like data warehousing means slowing down, learning the ropes, and building enough belief in the new approach to back it up internally. But if you've spent years doing things differently, it's hard to develop the conviction needed to push for change. Confidence comes from exposure and understanding, but without that, the warehouse-first idea feels too foreign to champion.Key takeaway: Marketers often shy away from data teams because they lack practical, accessible education and feel pressured to stick with familiar methods. Building confidence through hands-on learning and real-world examples is crucial for integrating data and marketing in a meaningful way.Overcoming Barriers to Data Literacy in MarketingMany marketers hesitate to engage deeply with data, often because they don't see it as central to their roles. Danny explains that for most, data feels like a secondary tool—something meant to assist rather than dominate their day-to-day work. The challenge is that the pathway to becoming data-savvy isn't straightforward. Even among those who've made the leap, each person's journey looks different. Some take online courses, like those on Codecademy, learning SQL from scratch. Others find mentors who guide them through the maze of data management, or they happen to work in environments where they can lean on a data specialist nearby. But there's no universal roadmap, which makes the process feel daunting.Danny believes that the lack of a clear, predictable path to mastering data is one of the biggest hurdles marketers face. With so many options available—some technical, others more hands-on—marketers often struggle to identify which approach will actually get them the skills they need. For those with limited time, this uncertainty can be a dealbreaker. Without knowing if the investment will pay off, it's easier to focus on other areas of marketing that feel more familiar and essential. Danny points out that while resources like Udemy are improving the situation, marketers still need a straightforward, reliable way to become proficient in data.Another critical factor is the perceived opportunity cost. Marketers are often juggling multiple responsibilities, from staying up-to-date with industry trends to managing campaigns. For many, the idea of dedicating time to learning data—an area they may feel they have minimal expertise in—feels like too large a barrier. Why spend time learning about data warehousing when there are immediate, pressing marketing concepts to master? This fear of committing time and energy to an unfamiliar, complex area keeps many from taking the first step.Danny emphasizes that while the accessibility of learning tools is improving, there's still a significant gap. Even for those who want to upskill, the fear of the unknown and the lack of a guided pathway can make it feel like an insurmountable challenge. Until marketers can see a clear, accessible way to develop these skills, many will remain hesitant to dive into data, choosing to stick to familiar ground instead.Key takeaway: Marketers often shy away from learning data skills due to a lack of accessible, consistent learning paths and the fear of time investment without guaranteed outcomes. Creating structured, easy-to-follow resources is crucial to making data literacy a viable option for busy professionals.Unlocking the Full Potential of Data with dbtDanny describes the transformation dbt brings to the data landscape, making it accessible not just to engineers but also to marketing ops and other non-engineering teams. In the past, accessing and manipulating data was a highly specialized skill, often requiring a marketer to rely heavily on a single engineer. As Danny puts it, you needed to build a relationship with this “one person in a closet somewhere” to get any insight or change implemented. This old approach made data access exclusive, slow, and frustrating for teams trying to move fast.With dbt, Danny explains, the dynamics shift dramatically. It creates different roles and permission levels for everyone interacting with data, enabling a self-service model for marketers and operat...

What's up everyone, today we have the pleasure of sitting down with Lourenço Mello, Product Marketing Lead at Snowflake. Summary: Lourenço drops us straight into the gravity well of martech, where Snowflake's latest report pulls in the tools that really matter, letting the fluff float away. It's all about data gravity, bringing the applications to the data instead of wasting energy shuttling data around. This shift is redefining what's possible, streamlining operations, and giving marketers a new superpower to harness the forces of AI and analytics. With composability blurring boundaries and AI breaking down silos, the takeaway is crystal clear: master data quality and you'll have the gravitational pull to outpace the competition.About LourençoLourenço started his career at an enterprise telecom company based in Portugal where he dabbled in competitive analysis, pricing and biz devHe later completed his MBA at UCLA and then spent 5 years at Microsoft as a Senior PMM focused on Azure and their data businessToday, Lourenço is Product Marketing Lead for the Solutions team at SnowflakeUnderstanding the Marketing Data Stack Report MethodologyLourenço's perspective on Snowflake's Marketing Data Stack Report centers around a fundamental commitment to objective analysis. Rather than focusing on internal partnerships or pushing favored solutions, Snowflake's report leverages comprehensive telemetry data to identify which tools are truly gaining traction among its 8,000+ customers. This approach enables them to deliver a more impartial view of the martech landscape.The methodology starts by categorizing the landscape according to current trends and customer adoption. Snowflake first identifies the relevant categories that its customers are using for marketing use cases, based on a snapshot of the industry. Lourenço emphasized that the analysis isn't limited to tools with direct business relationships or joint ventures but looks holistically at the adoption metrics across the board. This objectivity sets the report apart, as it can spotlight tools that Snowflake hasn't actively partnered with—yet are clearly valuable to their customers.Two primary metrics guide the analysis: breadth of adoption and depth of adoption. Breadth measures how many customers are using a particular tool or solution, offering an initial view of popularity. However, without understanding how deeply those tools are being utilized, breadth alone can be misleading. Lourenço highlighted that a platform may have thousands of users but very minimal actual engagement. Thus, the second metric—depth of adoption—assesses how sophisticated the usage is within each customer's implementation, revealing the true stickiness and impact of the tool.By indexing both breadth and depth of adoption, Snowflake is able to create a ranked list of tools and platforms within each category. This process ensures that the final report is rooted in genuine customer behavior and preference, rather than internal biases. As Lourenço puts it, “the cool thing about this and really what's been so fun to be a part of is really the objectivity of the analysis.” The report not only highlights tools that are already well-integrated but also uncovers opportunities to build relationships with platforms that customers have independently gravitated towards.This level of transparency ultimately fosters stronger collaboration between Snowflake and its partners. By showing where their customers are seeing success, the report opens the door for potential go-to-market initiatives that were previously unexplored. In a martech landscape often clouded by promotional bias, this approach offers a rare glimpse into which technologies are truly making a difference.Key takeaway: The core strength of Snowflake's Marketing Data Stack Report lies in its objectivity. By focusing on customer adoption metrics and removing subjective biases, the report provides a clearer view of the tools that are genuinely resonating with the market. This methodology enables Snowflake to support its customers with data-driven insights, and it paves the way for more meaningful partnerships with emerging leaders in the field.Key Shifts Defining Martech and AdTech TodayWhen asked about the notable shifts between 2023 and 2024, Lourenço from Snowflake made it clear—what were once considered trends are now fundamental changes that have reshaped marketing. Last year's report pointed to themes like the convergence of AdTech and martech, data privacy, generative AI, and the pursuit of a single source of truth. This year, these aren't just trends—they're seismic shifts that have permanently altered how the industry operates.Instead of being temporary developments, Lourenço emphasized that these themes are “not going away,” likening them to the foundation of the industry itself. The report identifies three key forces driving transformation: data privacy, data gravity, and generative AI. These forces influence everything from how companies measure performance to how they monetize and manage first-party data. One of the more interesting dynamics highlighted this year is the emergence of commerce media, where industries traditionally characterized by thin margins—like retail and travel—are leveraging their vast pools of first-party data to unlock new revenue streams and drive higher profitability.Data gravity, in particular, is a crucial concept. It describes how data is increasingly becoming the central point for both martech and AdTech activities. As Lourenço points out, brands are now using the same data source for real-time bidding on the AdTech side and for personalized experiences on the martech side. This convergence is made possible by advancements in data infrastructure, such as Snowflake's native app framework. By allowing applications to run where the data resides, brands eliminate the need to move data back and forth, reducing latency and improving privacy. An example Lourenço shared involved identity resolution, where an eight-day process to reconcile identity data is now achievable in mere hours, sometimes even minutes, thanks to this infrastructure shift.Another powerful change mentioned was how companies are transforming their roles—from being purely ad buyers to becoming ad sellers. This shift, Lourenço explains, is a direct consequence of organizations capitalizing on the value of their first-party data, looking to move up the value chain by creating new revenue channels through data monetization. Meanwhile, customers are increasingly interested in Marketing Mix Modeling (MMM) and other approaches to understand and optimize their media investment in light of these shifts.The takeaway is clear: these are not passing trends but fundamental changes in how the industry functions. Snowflake's position at the intersection of martech and AdTech provides a unique vantage point to observe these developments, and Lourenço's insights offer a glimpse into the future of data-driven marketing.Key takeaway: The convergence of data privacy, data gravity, and generative AI are not just fleeting trends—they're transformative forces that are redefining the marketing landscape. Brands that align their strategy with these shifts can unlock new revenue streams, capitalize on efficiency gains, and strengthen data security, ensuring they stay ahead of the curve.The Concept of Data Gravity in Modern Data ArchitectureWhen Lourenço introduced the idea of data gravity, it wasn't just about centralizing data; it was about rethinking how applications interact with it. The term itself evokes a sense of drawing everything—data, applications, and processes—toward a unified center. But in a broader sense, Lourenço emphasized that it'...

What's up everyone, today we have the pleasure of sitting down with Rutger Katz, GTM Operations Consultant. Summary: Rutger helps us cut through the fluff of Lean methodology in marketing and how to spot when process gets in the way of efficiency. His advice is to cut out the waste—whether in your process, your tech stack, or how you measure success. Focus on what drives conversions, keep your systems lean, and use simple structures to maintain speed without sacrificing alignment. We also tackle tech debt and how a top-layer AI interface could simplify the case for a composable martech stack.About RutgerRutger started his career in Neuroscience as a virtual reality developer at two different public research universities to study bodily illusions in VRAs the VR industry was quite immature at the time he pivoted to martech consulting, where he would spend 12 years working with different technology consulting firms getting a breadth of experience across marketing operations, martech, customer data and go-to-market across a variety of clients including Unilever where he focused on social analyticsAnd last year Rutger decided to go out on his own as a GTM Operations Consultant and recently launched NEON Triforce, a boutique consultancy focused on optimizing GTM for B2B scale-upsHe also recently joined The Martech Weekly as Content Lead for EU & UK organizing their first event in London.Lean Marketing in PracticeLean marketing is all about eliminating waste and doubling down on what truly matters. Rutger emphasizes that no matter the size of the company, from a startup to an enterprise, inefficiencies always creep in. These processes—whether learned from someone else or ingrained as “the way things are done”—often aren't optimal. Lean seeks to strip down these ingrained habits, perfecting the path to deliver value to customers.Rutger highlights that lean marketing goes beyond just being "efficient." It is about understanding how every action connects back to the entire organization. The real challenge is aligning marketing efforts with revenue-driving KPIs, rather than fixating on vanity metrics like page views or social media follows. For Rutger, Lean is about cutting through those superficial measures to ensure that marketing impacts the business holistically.What makes lean particularly valuable is that it doesn't stop at marketing. Rutger explains that Lean should apply to your entire go-to-market strategy. This means assessing not just how marketing operates but how it interlocks with sales, customer success, and even product development. It's about delivering maximum value to the customer while ensuring that the organization operates as efficiently as possible in providing that value.Lean marketing is not a standalone function—it's a way to optimize the whole organization. When done right, it leads to higher customer satisfaction, longer-term retention, and ultimately, a more streamlined business. For Rutger, this is where the real impact of Lean lies—not just in marketing efficiencies but in enhancing the customer experience across every touchpoint.Key takeaway: Lean marketing is about focusing on what truly drives value. It's not just about marketing—it's about creating efficiency across your entire go-to-market approach, from sales to customer success, all while tying back to key business metrics.Solving Inefficiencies in Sales and Marketing AlignmentWhen asked about real-world applications of lean methodologies, Rutger didn't hesitate to dig into a common yet overlooked issue: the disconnect between sales and marketing. In his experience, CMOs often claim that everything is running smoothly. But when the conversation shifts towards collaboration with sales, the cracks begin to show. One CMO even mentioned that their sales team requested fewer leads, as they were overwhelmed by the volume. Others spoke of back-and-forth frustrations trying to sync efforts between both departments.For Rutger, the root of inefficiency often comes at the handoff between marketing and sales. He explained that marketing teams frequently misinterpret sales-qualified leads (SQLs), sending what they define as SQLs but which sales deems unqualified. This misalignment creates friction, wasting time and resources on both sides. To fix this, Rutger advocates stepping back from just marketing processes and focusing on sales first. Understanding sales capacity and needs becomes essential to deliver the right leads at the right time.A critical step in this process is optimizing for sales' actual conversion capacity. Rutger highlights that if sales needs to convert 100 leads per month, with a 5% conversion rate, marketing needs to deliver 20 times that amount—2,000 SQLs. He stressed the importance of timely response, pointing out that conversion rates jump by 40% when sales follows up with a lead within 10 minutes. Aligning on this kind of data helps both teams work more effectively toward shared goals.Rutger also urged teams to reevaluate the quality and cost-effectiveness of their campaigns. While campaigns may generate leads, some are far too costly or inefficient, with payback times stretching out to three or four years. Google paid accounts, for example, are notoriously expensive, yet still widely used, particularly in larger organizations. For Rutger, focusing on the most effective campaigns, while pruning inefficient ones, is key to driving sustainable growth.Key takeaway: Marketing and sales alignment is critical for driving efficiency. Understanding sales capacity, optimizing lead delivery, and focusing on high-converting campaigns can reduce friction, improve collaboration, and significantly increase conversion rates.Tackling Tech Debt and Building a Lean Martech StackWhen asked about navigating the complexities of consolidating a tech stack, Rutger didn't mince words: aligning stakeholders across IT, marketing, and sales is often more political than it is technical. Large enterprises, in particular, face daunting hurdles when trying to scale back on overlapping tools. Rutger noted that the desire to build a “Frankenstack”—a collection of fragmented technologies—comes from every department wanting its own ideal solution. As a result, the journey to a leaner tech stack can seem like a never-ending project.Rutger's approach starts with identifying the biggest redundancies. While some overlap is by design, like when one product offers a superior feature, the challenge is to minimize overlap where it's unnecessary. In some cases, up to 60% of a company's tools perform redundant functions. His advice: focus first on those areas where feature overlap is significant, perhaps 90% or more, and tackle these redundancies gradually. Start small, prioritize high-cost inefficiencies, and avoid a complete tech overhaul in one go.Another common issue Rutger raised is "shadow IT"—the tools that departments purchase without full organizational knowledge or alignment. Marketing might opt for a quick-fix solution, or sales might buy something that works for them but doesn't integrate with other systems. These rogue tools further complicate efforts to streamline technology, making the case for better communication across departments.One of Rutger's key strategies is calculating the cost of maintaining outdated systems against the cost of migration. In legacy-heavy sectors like insurance and banking, this is critical. His pragmatic approach weighs the resources, time, and potential revenue impact of migrations. With the rise of AI, Rutger suggests that migration tools could become faster and cheaper, potentially offsetting the costs of restructuring a tech stack. His advice? Keep your options open and l...

What's up everyone, today we have the pleasure of sitting down with Jared DeLuca, Director of Operations at Appcues.Summary: Jared takes us inside the mad but amazing world of martech at Appcues – the top product adoption SaaS on the planet. We cover his transition from demand gen to ops, how he's integrated demo bookings within the product using RevenueHero, the difference between ops and revops. We also cover a ton of ground on AI topics for marketers like machine learning lifecycle management, how to QA AI-driven messages and how to leverage AI to uncover incremental lifts in your campaigns. About JaredJared started his career with a few internships in PR before joining a Market Research firmThat firm was later acquired by a UK based marketing data and analytics company where he worked his way up to Marketing ManagerHe then had a brief detour from SaaS at Keurig Dr Pepper in IoT Marketing Automation and Connected Panel Ops Finally Jared landed at Appcues, first in Demand Gen then Senior Martech and Ops Manager Today Jared is Director of Operations at AppcuesMoving from Demand Gen to Front-End DevelopmentJared's shift from demand generation to front-end development was a mix of opportunity and curiosity. When his team's operations lead left, he stepped in naturally. As the demand gen guy who relied heavily on those systems, Jared was the most logical choice. It wasn't a calculated career move—it was about filling a gap. That's how things go in startups, where you often find yourself doing a bit of everything.His transition into front-end development had a different spark. Budgets were tight, and they didn't have the luxury of hiring contractors. With years of HTML and CSS experience under his belt from working on emails and landing pages, Jared figured he could handle some of the coding work. AppCue supported the idea, allowing him to stretch into JavaScript. For small teams, having someone in-house with a broad skill set is invaluable, and Jared was more than willing to step up.What made this shift special was Jared's personal interest in coding. He enjoyed it. Coding wasn't just a job; it was something fun to experiment with. One evening, while watching TV, he built a lead-gen magnet prototype in just an hour. It was born from a simple idea pitched by the content team, but Jared's ability to quickly turn that into a working model showed the kind of spontaneous creativity that startups thrive on. The prototype may soon go live on their website.Jared's experience highlights the unpredictable nature of roles in smaller companies. You often find yourself taking on responsibilities you never planned for, and those unexpected opportunities can lead to new skills and career growth. For him, it wasn't about following a clear path—it was about being adaptable and ready to learn.Key takeaway: In a startup, being adaptable and willing to learn new skills can lead to unexpected career opportunities. It's less about having a perfect plan and more about being open to filling gaps when they appear.How AI Tools Are Shaping HTML and CSS LearningWhen asked if tools like ChatGPT make learning HTML and CSS easier today, Jared didn't hesitate to agree. He pointed out how much simpler it is for anyone looking to pick up coding now compared to when he started. Back then, you had to figure things out manually, while now, AI tools can assist with the heavy lifting. However, there's a caveat—knowing what to ask for is still crucial.Jared challenged the idea that AI is replacing developers. Instead, he emphasized that understanding the underlying structure of HTML and CSS is still key. Tools like ChatGPT can help speed up the process, but without knowledge of where to apply that code, the benefits are limited. AI can't tell you how to structure a website; it can only help fill in the blanks once you know what you need.He highlighted that while AI can handle repetitive keystrokes, the real value comes when you already know what you're aiming for. It's not about AI replacing junior developers—it's about leveraging these tools to work more efficiently. If someone understands the basics of coding and web structure, AI can cut down the time it takes to implement those tasks significantly.For Jared, the most significant takeaway is how much time he saves. What used to take him hours can now be done in minutes with AI. The difference is in the efficiency, not the replacement of skill. If you know what you're doing, ChatGPT and similar tools become an incredible resource for improving speed and output, but they don't replace the need for foundational knowledge.Key takeaway: AI tools can dramatically speed up coding tasks, but the real advantage comes when you already understand the basics of HTML and CSS. It's not about replacing developers, but about working smarter with the right knowledge and tools.Why Developers Avoid Marketing in Software StartupsWhen asked why developers often seem disinterested in marketing, Jared's perspective was insightful. In his experience, particularly in software startups, it's not that developers are “allergic” to marketing; they simply don't think about it. Their focus is on building and coding—creating the product itself. Marketing, and the role it plays in attracting users, often doesn't even cross their mind.Jared pointed out that many developers operate with a clear mindset: give them the requirements, and they'll build exactly what you need. They're more concerned with functionality than how the product will reach customers. This differs from product teams, who tend to think more about market fit and bridging the gap between building something and getting it to the user.However, Jared has worked with engineers who do think more broadly. In some cases, especially in smaller teams, developers will ask key questions about the user experience and how people will engage with the product. But this tends to fade as companies scale. Jared mentioned his time at Keurig, where engineers were more specialized—focused on delivering exactly what was requested, with little thought to the next steps.In Jared's view, it's less about a lack of interest in marketing and more about developers not having the bandwidth or inclination to focus beyond the task at hand. Their job is to build, and for many, thinking about the next phase—how the product reaches customers—isn't a priority.Key takeaway: Developers in startups aren't necessarily disinterested in marketing; they're simply focused on building. For those seeking to bridge the gap between engineering and marketing, fostering collaboration and highlighting the user journey can encourage developers to think beyond their immediate tasks.How Responsive Support Transforms Marketing OpsJared emphasized how crucial responsive support is in marketing ops. When discussing his shift to Revenue Hero, he highlighted the frustration many teams face when relying on traditional support teams. He described how long it can take to get a response—sometimes 24 to 48 hours—and how those responses are often unhelpful, requiring even more back-and-forth communication.What made Revenue Hero stand out to Jared was its approach to customer support. The team integrated seamlessly into his company's Slack workspace, offering real-time access to their expertise. This level of support was a game changer. For Jared, it wasn't just about the product performing well (which it did), but about the reassurance of knowing that if something went wrong, help was just a Slack message away.One example Jared shared was when a demo request system broke—a critical part of ...

What's up everyone, today I have the pleasure of sitting down with Ron Jacobson, Co-founder and CEO of RockerboxSummary: Multi-touch attribution doesn't tell you what really caused a conversion or revenue, it's a credit distribution system. It's still a useful guidepost in understanding where your efforts are making an impact. Incrementality testing, on the other hand, digs deeper—helping you pinpoint what's really driving results by answering, "What would've happened without this campaign?" But to get there, it's not about finding the perfect model, it's about asking the right questions. Don't get stuck in the basics like Google Analytics. True measurement demands first-party data and statistical modeling, especially as third-party cookies fade. For startups, the goal is momentum—nail one channel before diving into complex measurement. Build success first, then refine with tools like MTA or MMM to truly understand what drives growth.About RonRon started his career as a software engineer before transitioning to product management at AppNexus where he ran the platform analytics team and later the real time platform product teamHe then took the entrepreneurial plunge Co-founding Rockerbox, first as a programmatic advertising platform then a multi touch attribution platform And today they've added a suite of marketing measurement tools that also leverage marketing mix modeling. Rethinking the Role of Multi-Touch AttributionMulti-touch attribution (MTA) often sparks debate around its effectiveness in driving marketing decisions. While many recognize it as a flawed tool, few fully grasp the extent to which it misses a crucial element: causality. When asked whether MTA should be seen as a credit distribution mechanism rather than a way to measure causality, Ron agrees wholeheartedly, explaining that this is exactly how his team has framed the discussion for years.Ron emphasizes that MTA's purpose isn't to assign cause-and-effect between marketing touchpoints and revenue generation. Instead, it's a retrospective tool designed to distribute credit across various touchpoints in a customer's journey. He argues that marketing teams need to shift their focus from chasing causality to understanding how customers interact with marketing efforts. This approach helps marketers assess what channels or strategies might be working, even if the exact causal impact remains elusive.A specific example Ron highlights is when clients test new channels like OTT, CTV, or linear TV. Frequently, these clients aren't sure if the new channel is even making an impact. The issue, he notes, isn't necessarily that the marketing is ineffective—it's that the data simply doesn't reflect customer engagement due to gaps in tools like Google Analytics. While causality is still out of reach, MTA can at least show that the new channel is on the customer's path to purchase, providing some reassurance that the efforts are not entirely in vain.Ron points out that this shift in perspective helps marketing teams function more effectively. Rather than getting bogged down by the impossibility of determining exact causality, teams can use MTA to answer more immediate, practical questions: What are the touchpoints that seem to drive the most engagement? Where should we focus next? It's not about perfectly predicting outcomes, but about gathering insights that improve day-to-day operations.Key takeaway: MTA isn't designed to establish causality, but rather to help distribute credit among touchpoints. When marketers focus on how customers engage with their efforts rather than trying to measure cause-and-effect, MTA becomes a valuable tool in refining strategy.Understanding the Value of Path to ConversionWhen diving into the value of the path to conversion, we often struggle with the fact that it doesn't fully address causality. Just because a customer clicks on a Google link and converts doesn't necessarily mean that click caused the purchase. It's possible the customer had already been influenced by a social ad or an email from days prior. Understanding the motivations behind these actions remains elusive.Ron's take on this is refreshingly straightforward. He suggests ignoring the model entirely when pitching multi-touch attribution (MTA). Instead, focus on the question: What can you learn from understanding the customer's path to conversion? By treating MTA as an alternative lens to last-click or first-touch attribution, Ron emphasizes that it provides more context but doesn't necessarily give a definitive answer to causality. He argues that last-touch attribution, for example, isn't the best method for understanding the full customer journey.The real value of analyzing the path to conversion, according to Ron, comes from the variety of questions you can answer. Questions like time to conversion, comparing paths for new versus retained customers, or how adding a new channel influences customer behavior. Retention, in particular, has gained importance as rising interest rates push companies to focus on profitability, and understanding how existing customers engage without paid media is crucial.Ron points out that the path to conversion isn't just a credit distribution mechanism but a core dataset that allows marketers to do their jobs more effectively. By looking beyond conversions alone and examining full paths, even those that don't lead to a sale, marketers can better assess conversion rates and session data. Still, he concedes that none of this answers the critical question of whether marketing spend was truly incremental or whether a customer would have converted without it.Key takeaway: While path to conversion analysis doesn't solve for causality, it opens the door to deeper insights. Marketers can use it to answer key questions about customer behavior, retention, and channel effectiveness, but should remain aware of its limitations in proving incremental impact.Defining Incrementality in MarketingWhen we discuss incrementality, the core question is simple: Would the business results still have happened without marketing? It's a shift in mindset from how we traditionally report on marketing outcomes. Instead of simply attributing revenue to specific touchpoints, incrementality forces us to ask whether that revenue would exist at all if we hadn't spent that marketing dollar.Ron emphasizes the importance of having a baseline when assessing incrementality. Without this, everything looks like it's driven by marketing, which isn't always true. For him, the key is understanding the marginal return on that last dollar spent. In other words, is each dollar spent still driving profitable results? This approach helps marketers gauge if they're spending wisely and achieving their business goals.The real challenge comes in determining the best methodologies to uncover incrementality. Ron explains that while modeling tools like multi-touch attribution (MTA) aren't designed to measure incrementality, they provide valuable insights when combined with testing methodologies. He highlights that running a holdout test, for example, can reveal incremental results, and applying that test's findings to MTA reporting allows marketers to optimize daily decisions while still understanding broader trends.Ultimately, Ron advises marketers to focus less on the methodologies themselves and more on the questions they need answers to. Whether you're trying to allocate next quarter's budget or determine the effectiveness of a new creative, the right approach depends on what you're trying to uncover. By starting with the right questions, marketers can select the best tools or methods to answer them, rather than getting caught up in finding a one-size-fits-all solution.Key takeaway: In...

What's up everyone, today we have the pleasure of sitting down with Erin Foxworthy, Industry Lead, Advertisers & Agencies at Snowflake. Summary: In this episode, Erin takes us on a ride through the merging worlds of martech, adtech, AI, and privacy, giving a bold glimpse into what's next for customer data. We cover how you can use 1st party data for seed predictions, why it's time you move on from APIs and adopt data sharing and what the unified data layer means for marketers. Oh and Erin gives us her take on the uncertainty of Google's cookie deprecation rollback.About ErinErin is former Category Development Lead at Microsoft Advertising collaborating with product, marketing and sales teamsShe later became Executive VP of Partnerships and Innovation at Horizon Media – the popular NYC-based ad agency –  focused on first-to-market creative and data opportunities for her clientsShe's also a well traveled speaker and was awarded the Technology Leader at Cynopsis Top Women in Media in 2020Today Erin serves as the Industry Principal for media, entertainment and advertising at Snowflake, focusing on advertisers and agencies The duality of creativity and measurement in advertisingIn the early days of advertising, media was often an afterthought. Erin recalls how the majority of a CMO's focus was on perfecting commercial spots, direct mail, or magazine ads, with meticulous attention to detail. The creative side was the talk of the industry, leaving media playing a supporting role. However, as digital platforms emerged and ad units fragmented, the dynamic shifted. Creative and media teams, which were once tightly knit, began to drift apart, especially as agencies expanded to handle the complexity of new media channels.Erin notes that media became so specialized across different digital platforms that it gradually separated from the creative process. In her own career, which began at a full-service agency, she experienced this firsthand. Early on, she worked side by side with creative directors and copywriters, but as agencies scaled and media buying spread across hundreds of channels, those joint discussions became fewer. The focus shifted to simply managing the volume, leaving less time for deeper creative collaboration.What's promising, though, is the potential for artificial intelligence (AI) to bridge that gap again. Erin suggests that advancements in AI are already pushing the industry toward more integrated workflows. Platforms are increasingly using AI-driven algorithms to optimize ad performance—automating decisions and delivering results in a more turnkey fashion. This, she believes, will allow media teams to shift some of their focus back toward creative strategy.In her view, AI could also democratize creativity, empowering marketers who may not traditionally be involved in creative production to step into that space. With AI handling the data-driven optimization, there's an opportunity for marketers and agencies to bring creative and media closer together once again, regaining the collaboration that once defined the advertising world.Key takeaway: AI advancements are reshaping the relationship between creative and media in advertising, offering a chance to reconnect these disciplines. This evolution could allow marketers to step into creative roles while freeing up time to focus on what works, both organically and through paid channels.The future of automation in creative marketingWe often wonder how far we can trust machines to handle core marketing tasks, especially in areas like email where AI-driven recommendations are common but often met with skepticism. When asked about automation in creative marketing, Erin shared a candid perspective on where the industry stands.Erin points out that automation's impact is already visible in marketing operations, particularly in tasks like resizing creative and ad serving. These areas are primed for disruption, and automation is becoming essential in managing the growing complexity of campaign delivery. However, when it comes to more creative and brand-focused ad units, she remains unconvinced that AI is ready to replace the human touch anytime soon.For Erin, the heart of the issue lies in the nuances of brand messaging. Creative ad units are designed to build emotional connections with consumers, and this often requires a level of empathy and intuition that AI can't replicate—at least not yet. While AI can handle logistics and optimization in areas like programmatic advertising, the human element remains critical for conveying the personality and tone of a brand.She sees AI's role expanding in marketing operations, but for now, brand messaging is where human creativity holds its ground. As AI continues to evolve, marketers will need to find the right balance, leveraging automation for efficiency while maintaining the human insight necessary to craft compelling, emotionally resonant ads.Key takeaway: Automation will continue to disrupt marketing operations, particularly in optimizing workflows and ad delivery. However, for creative brand messaging, human creativity remains irreplaceable. Marketers should embrace AI for its efficiency while ensuring it complements, rather than replaces, the human touch in their messaging strategy.Understanding the convergence of Martech and AdTechWhen asked about the distinction between Martech and AdTech, Erin provides an insightful perspective. Traditionally, people often simplify the divide: Martech is for marketers and AdTech is for advertisers. However, she views this as an oversimplification that doesn't capture the true nature of the industry's evolution. Both are ultimately driven by technology—platforms created by companies that serve both marketers and advertisers as users. The complexity lies not in who controls the platform, but in finding the right technology to meet the needs of a specific enterprise.Erin emphasizes that this convergence is especially noticeable as personalization becomes central to marketing and advertising strategies. Where Martech was once seen as powering owned channels like email and SMS, and AdTech controlled paid channels like social ads and programmatic buys, today, the line between the two is blurring. Personalization is no longer limited to owned channels; it's becoming essential in paid media, social platforms, and even connected TV (CTV) campaigns. This level of integration hinges on having the right data infrastructure, enabling one-to-one conversations across all customer touchpoints.What makes this especially challenging is the industry's historical lack of unified strategy across these channels. Erin notes that traditionally, marketers have operated in silos—sending emails, running social ads, and buying media independently. Now, with the growing expectation for a seamless, personalized experience, businesses must integrate these efforts to understand how various touchpoints—whether through an SMS campaign, social ad, or CTV buy—are interacting to shape the customer journey.At its core, this shift is about harnessing data across all platforms and using it to create personalized, consistent messaging. For Erin, the convergence of Martech and AdTech means unifying applications on a scalable platform that can support this kind of holistic approach. This trend is exciting and challenging, pushing companies to rethink the ways they manage customer data and interactions.Key takeaway: The traditional divide between Martech and AdTech is becoming outdated. As personalization continues to drive both marketing and advertising, the real challenge lies in unifying customer interactions across all channels on a scalable platform. Businesses must move beyond simple categorizations and focus on ...

What's up everyone, today we have the pleasure of sitting down with Liam Moroney, Co-Founder of Storybook Marketing. Summary: Liam handed us warm tea and one of his hand-knitted beanies as we explored how marketing goes beyond just hitting pipeline numbers. It's about building trust, shaping perceptions, and ensuring your brand is top-of-mind when it matters. Balancing short-term wins with long-term brand-building is crucial, yet often misunderstood. Clear communication and a broader approach to measuring impact are key. For startups, focusing on trust and credibility lays the foundation for success. Marketing's true power lies in creating a lasting impact that drives real decisions.About LiamLiam started his career in various industries wearing several different marketing hatsEventually he landed at NewsCred, a content marketing agency for enterprise teams where he started leading Demand Gen before shifting to client side and advising clients on attribution and ROIHe then had Revenue Marketing leadership stints at various startups across different industries like personalization, travel, mobile and identity verificationHe then started his entrepreneurial journey by founding a consulting firm for growth-stage B2B companiesLiam is also a contributing writer at Martech.org and recently started his own podcast called The B2B BrandToday Liam is the co-founder of Storybook Marketing, a full-service demand gen agency for B2B SaaS specializing in paid media programsMarketing's Role Beyond the PipelineMarketing, historically viewed as the "arts and crafts department," has evolved significantly. Yet, according to Liam, there's a lingering misperception, particularly in B2B, that needs addressing. When asked about his concerns with marketing being reduced to a mere pipeline number, Liam didn't shy away from dissecting the issue. It's not about rejecting accountability—marketing should indeed own a number. The real problem lies in how we've overcorrected, narrowing the focus to such an extent that it undermines the broader role marketing plays.Liam points out that this shift in perception—driven by the need to demonstrate that marketing is a data-driven, outcome-producing function—has caused demand generation to become nearly synonymous with marketing. This reductionist view oversimplifies marketing's contribution. When marketing is pigeonholed into a single metric, such as its share of the overall pipeline, it suggests that marketing is just another channel, responsible only for a fraction of the sales process. This perspective shortchanges the true purpose of marketing.Liam believes that marketing's ultimate goal is to make the sales process smoother and more efficient. When more people know about a product, believe in its value, and have confidence in its efficacy, selling becomes easier. Marketing should be responsible for influencing the entire pipeline, not just a portion of it. The role of marketing is to make deals faster, bigger, and more frequent. By restricting marketing's scope to its contribution to the pipeline, we inadvertently diminish its impact.In B2C, marketing drives consumers directly to purchase. In B2B, it drives prospects into the sales process, partnering with salespeople to guide the purchase decision. While the dynamics differ, the overarching responsibility remains the same: marketing should facilitate the entire journey, not just the initial steps.Key takeaway: Marketing should not be reduced to a pipeline number. Its true value lies in its ability to influence and enhance the entire sales process, driving not just awareness but also belief, confidence, and ultimately, conversion.Balancing Short and Long-Term Marketing GoalsWhen asked about the perception that marketing hides behind long-term goals to avoid accountability, Liam was quick to dispel this myth. He argues that marketing isn't unique in balancing both short and long-term objectives—many functions, like data science and financial advising, operate with a future-oriented perspective. Yet, marketing often faces undue scrutiny because it's expected to produce immediate, tangible results each quarter.Liam acknowledges that some of this mistrust is self-inflicted. Marketing has, at times, oversold its capabilities and doubled down on being seen solely as a pipeline-generating function. This narrow focus has contributed to the misconception that marketing's only job is to deliver immediate results. However, Liam emphasizes that marketing's true role is both long-term and short-term. The primary objective is to generate future customers by building awareness, while also activating efforts that yield results today.In B2B and B2C alike, successful marketing requires a dual approach. Brand awareness campaigns, for example, are designed to create a long-term impact by making more people aware of a product. Simultaneously, demand generation activities work to convert that awareness into action. The two functions are interdependent—effective demand gen relies on strong brand awareness, and vice versa.Liam draws an interesting parallel with B2C marketing, where the distinction between long and short-term strategies is often clearer. Brand campaigns might run over months or years to build awareness, while in-store promotions are designed to trigger immediate purchases. The same principles apply in B2B marketing, where demand gen efforts must be supported by a solid foundation of brand awareness. Without this balance, even the best demand gen strategies will falter.Key takeaway: Marketing must balance long-term brand building with short-term activation efforts. Success comes from integrating these approaches, ensuring that immediate demand generation is supported by strong brand awareness.Educating Leadership on the Value of Brand MarketingWhen marketers find themselves trapped by the constant demand for immediate pipeline results, it can be challenging to advocate for the long-term value of brand building. Liam addresses this issue head-on, acknowledging that while it's easy to champion long-term thinking on platforms like LinkedIn, the reality for in-house marketers is different. Every marketer has targets to meet, and failure to hit those can lead to quick dismissal. However, Liam emphasizes that this doesn't mean abandoning the long-term strategy—rather, it's about balancing both while educating leadership on what brand marketing truly entails.Liam points out that part of the problem lies in a lack of education—both for marketers and the C-suite. Marketers need to articulate better what brand marketing is and how it contributes to the overall business objectives. However, the burden of education doesn't end there. Liam advises against the common notion of only working for CEOs who "get" marketing, as those opportunities are rare. Instead, much of the work involves reeducating leaders on the role and impact of marketing.The key, according to Liam, is alignment with the sales team. If sales perceive that marketing isn't contributing to their efforts, it can create friction that quickly undermines marketing's initiatives. By engaging in conversations with sales, marketers can uncover the real challenges that hinder sales efforts. For instance, if sales teams find themselves consistently listed last in RFPs, it might indicate a brand awareness issue. Or, if there's a widespread misconception about pricing, that points to a perception problem that marketing can address.By identifying these pain points and framing them as marketing challenges, marketers can gain the trust of their sales counterparts. This trust can, in turn, lead to greater permission to allocate resources toward long-term brand-building efforts. It's not an overnight process, but Liam stresses that when done correctly,...

What's up everyone, today we have the pleasure of sitting down with Benoit Leggieri, Head of Growth at Livestorm. Summary: Benoit offers a behind-the-scenes look at how Livestorm's martech stack drives growth and personalization. At its heart is Customer.io, seamlessly integrated with tools like Amplitude, Segment, and Mutiny, creating a powerful system that delivers tailored experiences while scaling effortlessly. By leveraging data-driven workflows to address user needs with precision and automating processes like product certification, Livestorm not only boosts conversions but also deepens customer relationships. Their strategic use of gated content for complex demos further enhances engagement, showcasing a martech strategy that's as effective as it is thoughtful.About BenoitBenoit started his career at a B2B comms agency before joining HUB Institute, Paris' top think tank as a Growth marketerHe later joined an event software startup as a product marketing managerHe was also a part time trainer at a digital marketing school in ParisIn 2020 he joined Livestorm – the top video engagement software – as a growth manager to work CRO and after only a year he was promoted to Growth Lead and later Head of Growth where he leads a team of 3 growth managersLivestorm's Martech Stack Built for Personalization and RetentionLivestorm's martech stack is a powerhouse, meticulously crafted to enhance every stage of the customer journey. They use Customer.io, Hubspot, SEMRush, and Clay and Benoit unpacks a few other elements. The stack also features Amplitude, the go-to tool for analyzing website conversion rates. Amplitude also helps identify exactly where the user experience can improve, turning insights into action.Mutiny takes center stage for personalization. By tailoring website content to specific industries and personas, it ensures that each visitor feels like the site was made just for them. Whether it's through social proofs or custom messaging, this tool helps Livestorm engage B2B clients on a deeper level, making every interaction count.Segment serves as the backbone of data management. It captures user data and seamlessly distributes it across various platforms, from email marketing to in-app messaging. This orchestration guarantees that every touchpoint with the customer is personalized and relevant, driving better engagement and retention.Benoit also gives a nod to Refiner, a key player in capturing user feedback. Whether it's through NPS surveys or specific feedback on new features, Refiner ensures Livestorm stays in tune with its users. Integrated with Segment, it not only gathers data but triggers timely follow-ups, helping to refine the product based on real user input.Key takeaway: A well-integrated martech stack is essential for delivering personalized experiences and driving user retention. Tools like Amplitude, Mutiny, Customerio.io and Segment work together to create a seamless journey, while Refiner ensures user feedback directly informs product improvements.The Orchestrator and the Center of Your Martech StackBenoit doesn't hesitate when asked about the centerpiece of Livestorm's martech stack. For him, the core has always been their marketing automation tool, Customer.io. This tool has been instrumental since Livestorm's early days, especially when they were a small, self-serve business. Benoit attributes much of their growth to the strategic use of Customer.io, which not only automated specific messaging but also provided critical insights into the buyer's journey. The integration with Segment further amplified its impact, allowing Livestorm to capture and utilize data points effectively, which in turn, scaled conversions and expanded their customer base.As Livestorm grew, so did the complexity of their martech stack. Benoit mentions that as the company evolved, the data warehouse and Customer Data Platform (CDP) began playing a more significant role. Yet, despite this evolution, he remains adamant that the true orchestrator of their stack continues to be Customer.io. Its role in managing and optimizing the buyer journey is so ingrained in their operations that it remains central, even as new tools and processes are introduced.This perspective reflects a broader trend where companies initially rely heavily on marketing automation tools as their primary orchestrator. But as they scale and gather more data, the role of CDPs and data warehouses becomes increasingly important. However, for Livestorm, the foundational importance of a tool like Customer.io cannot be overstated, especially given its ability to adapt and integrate as the company's needs grew more complex.The evolution of Livestorm's stack from a single orchestrator to a more complex, data-driven system underscores the importance of flexibility and scalability in martech tools. While the CDP and data warehouse have become critical, the consistent thread has been Customer.io's capacity to grow with them, demonstrating that even as the tech stack evolves, the initial building blocks remain crucial.Key takeaway: The backbone of a successful martech stack often starts with a solid marketing automation tool. As a company scales, additional tools like CDPs and data warehouses become vital, but the original orchestrator, like Customer.io in Livestorm's case, continues to play a crucial role in managing and optimizing the customer journey.Why Customer.io Stands Out for LivestormWhen asked about what makes Customer.io a standout tool for Livestorm, Benoit highlighted three key features that have made it indispensable to their marketing efforts.1 - First on the list is data integration. Benoit praises the seamless connection between Customer.io and their Customer Data Platform (CDP), Segment. This integration enables Livestorm to map user events and attributes effortlessly, which in turn allows for highly personalized messaging. By leveraging this data, the team can trigger specific campaigns at the perfect moment for each user, ensuring that every message is relevant and timely.2 - The second feature Benoit appreciates is the user experience (UX) and user interface (UI) of the platform. Onboarding new team members has been straightforward, thanks to Customer.io's intuitive design. The visual workflow builder simplifies the process of creating and editing campaigns and emails, making it easy for the entire team to collaborate and execute strategies without unnecessary complications.3 - Finally, Benoit highlights the segment builder as a crucial tool in their arsenal. Managing recipient lists can be a nightmare in many platforms, but Customer.io's approach, with tags and naming conventions, makes it much easier to organize and clean up lists. This feature not only improves efficiency but also ensures that Livestorm's campaigns reach the right audience every time.Key takeaway: Customer.io excels in data integration, intuitive UX/UI, and efficient segment management, making it a powerful tool for personalized marketing campaigns. These features have allowed Livestorm to optimize their messaging and ensure smooth operations across their team.Crafting Revenue-Driving Workflows with Customer.ioBenoit shares a fascinating look at how Livestorm has leveraged Customer.io to create sophisticated workflows, particularly those focused on driving revenue. This year, the team concentrated on revenue-centric workflows, addressing challenges like incomplete subscriptions and payment issues—common hurdles in any SaaS business.One notable experiment revolved around abandoned carts. By integrating Customer.io with their data stack, they tracked users who landed on the billing page but didn't complete their transactions. This e-commerce-in...

What's up everyone, today I have the pleasure of sitting down with Pranav Piyush, Co-Founder and CEO at Paramark. Summary: Pranav guides us out of the labyrinth of multi-touch attribution under the clear sky of incrementality and causality, urging marketers to focus on whether their efforts genuinely drive sales that wouldn't happen otherwise. Early-stage startups can benefit by prioritizing simple methods like geo-based testing over complex attribution models, allowing intuition to guide resourceful experimentation. By understanding the underlying motivations and true causality behind customer actions, marketers can craft campaigns that resonate deeply and drive real results. As businesses grow, balancing intuition with structured analytics becomes crucial. Holdout tests and marketing mix modeling provide actionable insights, ensuring strategies remain effective in a competitive landscape. This approach transforms marketing from a cost into an investment in sustainable growth, making each dollar count.About PranavPranav started his career at well known brands like PayPal and DropboxHe co-founded Padlet, the popular collaboration app to make school less boringHe's former Head of Growth at Magento and Pilot.com before becoming VP of Marketing at BILLHe's also a Reforge Instructor for a new marketing measurement courseAnd in March of last year, Pranav co-founded Paramark to help marketers measure and forecast the impact of their investmentsWhat's More Valuable? Analytical Skills or Creative Taste?Marketing's creative nature often gets overshadowed by the obsession with data. Recently, HubSpot's co-founder Brian Halligan suggested that marketers with good taste are undervalued compared to those with analytical skills. Pranav agrees, arguing that creativity now drives the most significant impact in marketing. We often question the overuse of the term "data-driven" in marketing, suggesting a shift towards being more "creatively driven." Pranav responds, arguing that data-driven and data-informed are all kind of bullshit. Relying solely on being "data-informed" is not sufficient. He emphasizes that without the ability to discern the success of a creative idea through data, creativity alone falls short.Marketers face the challenge of making memorable impressions on people they've never met, and this requires innovation and creativity. While data is essential, Pranav notes that many marketers don't truly understand the depth of analytical skills. True data literacy involves grasping complex concepts like correlation and causation, which are often missing in marketers' education. Pranav points out that the dichotomy between creativity and analytics is overly simplistic. Marketers need to integrate both skills. This blend is crucial not only in marketing but in other business functions like product development. He uses the example of launching a feature and gauging its success. If only 10% of the customer base uses it, understanding the broader impact on adoption, revenue, and retention is essential.Despite recognizing the importance of analytical skills, Pranav emphasizes that good taste in marketing offers a unique advantage. Creativity leads to building compelling campaigns that resonate more profoundly with audiences. This insight suggests that while data provides valuable insights, it is creativity that ultimately distinguishes successful marketing efforts. Pranav further highlights the importance of rigorous testing and measurement. A successful feature or campaign isn't just about positive feedback; it needs to contribute to tangible business outcomes, such as increased revenue or cost savings. Without proper measurement, the value of creative initiatives remains unclear.Key takeaway: To truly excel in marketing, you need to embrace a harmonious balance between analytical skills and creative taste. This means honing your ability to interpret data while also nurturing your creative instincts to craft memorable campaigns. Instead of relying solely on data or creativity, focus on integrating these skills. Use data to measure the success of your creative ideas, ensuring they lead to meaningful business outcomes like increased revenue or customer retention. By blending data literacy with creative insight, you'll develop campaigns that resonate deeply and drive tangible results.Understanding Incrementality in MarketingWe often hear marketers claiming they understand ROI and reporting, yet the concept of incrementality often eludes them. Pranav sheds light on this by differentiating between attribution and incrementality. Attribution, as he explains, is rooted in the idea of cause and effect. However, its usage has been diluted over time, losing its original meaning.Pranav appreciates our provided definition of incrementality: business results from marketing campaigns or channels that wouldn't have occurred otherwise. He elaborates that if a prospect would have purchased a product without the influence of marketing, then that marketing effort isn't incremental. Conversely, if a prospect's decision to buy is directly influenced by marketing, then that effort is incremental.He emphasizes the importance of understanding incrementality beyond traditional marketing channels, especially in B2B contexts. This involves considering scaled sales channels, partner channels, and affiliate channels. The essence of incrementality lies in recognizing the true impact of marketing efforts on sales and other business outcomes.Pranav's insights underscore the need for marketers to move beyond surface-level metrics and understand the deeper implications of their strategies. By focusing on incrementality, they can more accurately measure the effectiveness of their campaigns and make informed decisions that drive real business growth.Key takeaway: Focus on incrementality to truly gauge your marketing impact. Instead of just relying on attribution metrics, assess whether your efforts genuinely drive sales that wouldn't have happened otherwise. By understanding and applying incrementality across all channels, you can refine your strategies and foster real business growth.Unpacking Multi-Touch AttributionMulti-touch attribution (MTA) often gets hailed as the holy grail of marketing measurement. Many believe it's essential to solve attribution by capturing all touchpoints. However, Pranav argues that the obsession with MTA overlooks fundamental issues, particularly around causality.When discussing attribution, we need to understand cause and effect. Pranav illustrates this with a simple example: if someone clicks on a Google link and converts, did that click cause the conversion? Sometimes it does, but other times it doesn't. He emphasizes the need to ask, "What prompted the search in the first place?" Without knowing this, we aren't truly understanding causality. We're merely observing sequences of actions without grasping their underlying motivations.Pranav criticizes the current approach to MTA, which often amounts to behavioral analytics. This method logs sequences like A led to B led to C, but it doesn't clarify if A caused B. This lack of clarity is compounded by pressures on marketing and analytics teams to produce quick results, pushing them towards convenient but superficial solutions.The martech industry, according to Pranav, has profited from building easy, superficial tools rather than delving into the complex but necessary task of understanding true causality. He believes this approach must change for the industry to advance meaningfully. By focusing on more robust methodologies, marketers can gain genuine insights into the effectiveness of their campaigns.

What's up everyone, today we have the pleasure of sitting down with Jacqueline Freedman, CEO and Founder at Monarch Advisory Partners. Summary: Jacqueline straps on her jetpack and invites us to soar through the martech skies, teaching us how to navigate the journey of becoming an independent martech advisor. From hands-on execution tasks strategy and advisory projects and assembling a futuristic composable martech stack, we cover a lot of air miles. We navigate the build versus buy decision in martech, the realities of composable CDPs and embracing user-friendly modern marketing automation tools.About JacquelineJacqueline started her career in Account and relationship management before joining WeWork where she would eventually settle into a Global Engagement Marketing and Operations Manager role as the fifth marketing hire during the company's hyper-growth She later joined an email and lifecycle growth agency as the 2nd team member and built out their NYC office where she worked with startups ranging from seed to series CShe then moved over to Grammarly as the founding Marketing Operations hire where she built out the B2B MOPs team and led their marketing technology stack to support their transition to a B2B2C companyAnd recently Jacqueline strapped on her jetpack and went out on her own as a solopreneur founding Monarch Advisory Partners, a full-stack Marketing Ops and Martech consultancyWhy Introspection is the Secret Weapon for Aspiring EntrepreneursJacqueline, reflecting on her transition from Grammarly to entrepreneurship, reveals the depth of her decision-making process. With a family history rooted in entrepreneurship, Jacqueline always envisioned herself running her own business. Observing her father and grandfather, she felt like she had a front-row seat to an MBA. This early exposure planted the seed of entrepreneurship, but it wasn't until she recognized her unique skill set that she felt truly ready to take the plunge.The decision wasn't impulsive. Jacqueline emphasized the role of introspection and reflection in her journey. She spent a year contemplating the right moment, fueled by her natural tendency to overthink. Through late nights and early mornings, she assessed her career achievements, from scaling WeWork during its prime to steering Grammarly's shift to B2C. These experiences solidified her belief in her capabilities, leading her to recognize that she was ready for the entrepreneurial leap.Jacqueline's courage was also bolstered by her practical approach. While at Grammarly, she had already begun advising several founders, driven by her passion for problem-solving rather than monetary gain. These conversations not only honed her skills but also provided a soft landing into entrepreneurship. By the time she officially launched her business, she had a lineup of clients ready, thanks to her reputation and the support of colleagues and partners who championed her abilities.Her journey highlights the importance of strategic preparation and the value of building a strong professional network. Jacqueline's story is a testament to how a combination of introspection, practical experience, and a supportive community can make a significant career transition smoother and more successful.Key takeaway: Use introspection to identify your unique skills and career achievements. Reflecting on these aspects will not only boost your confidence but also clarify your readiness for major career changes, like transitioning to entrepreneurship.How TV Dramatization Barely Scratches WeWork's RealityWhen asked about the accuracy of the WeWork TV show "WeCrashed" on Apple TV, Jacqueline offered a candid perspective. Having watched all the content related to WeWork, she noted that "WeCrashed" starring Jared Leto and Anne Hathaway, came closest to capturing the essence of the events. However, she emphasized that the series only scratched the surface of what truly transpired.Jacqueline explained that while the series contained a kernel of truth, the actual events at WeWork were far more intense. Everything depicted in the show was amplified tenfold in reality. This amplification was very much in line with WeWork's brand, known for its high-energy and sometimes chaotic environment. She described her experience of watching the dramatization as somewhat PTSD-inducing due to its accuracy in portraying the underlying ethos of WeWork.Despite the dramatization, Jacqueline found it fascinating and somewhat validating to see the story unfold on screen. The series succeeded in conveying the core truth of WeWork's journey, even if it couldn't fully encapsulate the extremities of the real-life scenarios. For Jacqueline, revisiting those memories through the show was a mixed experience, balancing between validation and the resurfacing of intense memories.Her insights underscore the dramatic nature of WeWork's history and how media adaptations, while engaging, often have to simplify or condense reality. For viewers, it's a reminder that behind the scenes, the stories of such companies are often more complex and multifaceted than any series can fully capture.Key takeaway: Jacqueline noted that while "WeCrashed" captured the essence of WeWork, it only scratched the surface of the true events, which were far more intense. The dramatization, though somewhat accurate and PTSD-inducing, validated the chaotic environment of WeWork. However, she emphasized that media adaptations often simplify the complexities of real-life scenarios.How to Become a Martech AdvisorBalancing Hands On Execution Projects vs Strategic AdviceJacqueline addresses the nuanced demands of clients in marketing operations (MOPs). While she shares a passion for every facet of MOPs, she acknowledges a point in her career where hands-on tasks like copywriting and sending emails no longer align with her long-term vision. This shift towards focusing on advisement and strategy is something she enjoys, and it's about setting clear expectations from the start with clients.Each client's needs vary, which Jacqueline finds exciting. However, it necessitates clear communication about what she offers. When clients require extensive lifecycle or demand generation email execution, Jacqueline is upfront about her role. If it's a short-term need, she might handle it, but for long-term commitments, she refers them to trusted partners. She mentions firms like Modular Marketing and Ragnarok, highlighting her strong relationships with these agencies. This symbiotic partnership ensures clients get top-notch service while allowing Jacqueline to concentrate on strategic advisement.By focusing on strategy, Jacqueline can provide high-level insights and direction that impact her clients' overall marketing operations. She values the ability to step back from the minutiae and look at the bigger picture, helping businesses navigate their marketing landscapes more effectively. This approach not only suits her professional growth but also ensures her clients receive specialized, high-quality execution from her partners.Jacqueline's journey exemplifies the importance of evolving in one's career and recognizing when to delegate tasks that no longer fit one's vision. It's about leveraging strengths and building a network of reliable partners to deliver comprehensive solutions. Her ability to set expectations and offer strategic guidance is a testament to her experience and foresight in the marketing operations field.Key takeaway: When transitioning to a more strategic consulting role, clearly communicate your focus and delegate hands-on tasks to trusted partners. This allows you to leverage your strengths, provi...

What's up everyone, today we have the pleasure of sitting down with Simon Heaton, Director of Growth Marketing at Buffer. Summary: Simon helps us explore Buffer's martech journey, highlighting their shift from traditional tools to a product-led approach driven by data and server-side analytics. We unpack their use of Customer.io for automation and hold out testing, Redash for data insights, and their agile sprint model that fosters continuous innovation. Discover how Buffer's small team thrives with efficient, data-driven strategies.About SimonSimon started his career in the agency world at Banfield in Ottawa, CanadaHe later moved over to Shopify where he would spend nearly 7 years, first as a content Marketing Manager and later as the Senior Growth Lead, AcquisitionSimon's also worn a part-time teaching hat for over 5 years, he was an Instructor with Telfer School of Management at UofO as well as a Professor at Algonquin CollegeHe's a startup mentor for founders that are part of the Singapore-based equity fund at AntlerToday Simon is Director of Growth Marketing at Buffer, the world-renowned social media management platformBuffer's Marketing Tech Stack and Why it Doesn't Include a CRMBuffer's marketing strategy is unique. They don't use a traditional CRM like HubSpot or Salesforce. Simon explains that Buffer is a product-led company without a dedicated sales team. This means they don't need typical CRM functionalities like lead routing and scoring. Instead, Buffer relies heavily on data and product analytics to drive their marketing efforts.The core of Buffer's operations is their data warehouse, with Segment acting as their Customer Data Platform (CDP). This setup allows Buffer to integrate various tools and centralize crucial information. Mixpanel, their product analytics tool, is pivotal in this system. It gathers both product usage and marketing data, providing a comprehensive view of user interactions.Simon highlights the importance of server-side tracking and integrating data from diverse sources such as AdWords, Customer.io, and Pendo. This integration helps Buffer understand the user lifecycle and measure the impact of marketing efforts beyond basic website metrics.Tools like Customer.io are also essential for Buffer. It manages most user communications, making it a critical component of their stack. The combination of Mixpanel, Customer.io, and other integrated tools ensures that Buffer can seamlessly track and analyze user behavior.Key takeaway: Not all B2B companies need a CRM or a sales team. A product-led approach, using robust data and product analytics tools, can effectively drive your marketing efforts and provide comprehensive insights into user behavior.The Power of a Visual and Intuitive Automation Flow InterfaceSimon loves working in a smaller team like Buffer, where he can get hands-on with their tools daily. He highlights how Buffer uses Customer.io for their marketing automation, a tool he's familiar with from his previous experience at Shopify. Unlike Shopify, which eventually switched to Salesforce Marketing Cloud for more enterprise-level needs, Buffer continues to thrive with Customer.io.Buffer relies on Customer.io to manage email marketing, push notifications for mobile apps, and various communication programs. Simon appreciates how the tool handles both marketing and transactional communications, offering a unified view of user interactions. This integration ensures consistency in messages, whether they're marketing emails or product notifications.Simon praises Customer.io's user-friendly interface, especially the journey mapping functionality and the WYSIWYG editor, which make it accessible for non-technical team members. Despite its ease of use, the platform also boasts deep technical capabilities, allowing for extensive customization through HTML and API integrations. This flexibility has been crucial for Buffer's needs.The integration with Segment, Buffer's Customer Data Platform (CDP), is particularly valuable. Simon emphasizes that having all data in Segment and seamlessly integrating it with Customer.io enables precise data handling. This setup ensures accurate and timely data flow, essential for personalized and effective marketing automation workflows.Key takeaway: Even as a small team, you can effectively manage complex marketing automation needs by choosing user-friendly tools like Customer.io that offer both simplicity and deep customization. This approach allows your non-technical team members to contribute meaningfully while ensuring your technical needs are met, enhancing overall efficiency and personalization in your communications.Experimentation and Holdout Testing at BufferExperimentation is a cornerstone of Buffer's approach, and Simon is particularly enthusiastic about the capabilities provided by Customer.io. He explains that the platform's holdout testing functionality is essential for validating new programs and comparing campaign performance. Unlike some tools, Customer.io counts a delivery for the holdout group, simplifying the tracking process over time.The integration with Segment and Mixpanel is a game-changer for Buffer. This setup allows them to surface Customer.io data in Mixpanel, creating unique reports and dashboards to support their experiments. Tracking differences in behavior between groups becomes straightforward, thanks to the detailed delivery events logged for both test and holdout groups. This level of detail ensures that Buffer can effectively measure the impact of their campaigns.Simon also highlights the ease of A/B testing within Customer.io. Whether at the message level or within workflows, the platform's randomization logic allows for extensive testing. Buffer can run tests on content, sequencing, and other variables, ensuring they continually optimize their marketing efforts. The ability to branch workflows and test different variants simultaneously is particularly valuable, enabling ongoing experimentation.Key takeaway: Leverage holdout testing and detailed event tracking within your marketing automation tools to gain deeper insights into your campaign effectiveness. This approach allows you to validate new programs, compare performance, and optimize your strategies based on precise, data-driven insights.Testing Journeys and Templating Language with QA Draft ModeSimon praises Customer.io's QA draft mode, a feature he finds invaluable for Buffer's marketing automation. This functionality allows the team to build complex workflows, trigger off specific data points, and test the entire process in a production environment without actually sending emails. It's a unique capability that Simon has not found in other tools, making it a standout feature of Customer.io.Simon highlights how QA draft mode lets them see real users qualifying for different branches of the workflow while emails remain in draft. This means they can verify that users are correctly segmented and the emails look as intended, all without prematurely sending any messages. This testing phase is crucial for catching errors that might not be evident during initial previews.Buffer has used this feature for several initiatives, such as new onboarding iterations and product notifications. Given the high frequency and volume of these emails, ensuring everything works perfectly before going live is essential. Simon appreciates that once the testing phase is complete, it only takes a click to start sending the validated emails to users.This capability saves time and reduces the risk of errors in live campaigns. It allows Buffer to maintain high st...

What's up everyone, today we have the pleasure of sitting down with Ashleigh Johnson, Marketing Technologist at Microsoft. Summary: Ashleigh gives us a glimpse into the enterprise world of martech, and it might not be what you're expecting. She emphasizes embracing the unexpected by seeking diverse roles and rotational programs. Building a personal network within large organizations like Microsoft is crucial for navigating corporate silos. Curiosity and people skills, including shadowing colleagues and effective communication, are paramount. Ashleigh highlights the need for robust documentation and the strategic use of AI for routine tasks to boost productivity. Finally, she advocates for marketers to lead AI deployment, ensuring flexibility and innovation by empowering tool owners to make technology-driven decisions.About AshleighAshleigh started her career at Trend Micro, a global cybersecurity company as a Sales and Marketing Associate with rotations as a Lead Qualification Rep, then a Marketing Coordinator and finally a marketing Ops and Automation associateEventually she would get promoted to Marketing Automation Manager where she was responsible for all things building, QA and campaigns across a variety of martechShe then took on the role of Senior Marketing Operations Manager at Cornerstone OnDemand, a talent experience platform where she rolled out a Content Intelligence tool and a Webinar engagement platformToday Ashleigh is Marketing Technologist at Microsoft on their Platform Operations team where she strategizes and consults on how the martech stack is used across different workstreams of the businessEmbracing Openness in Marketing CareersAshleigh highlights the significance of being open-minded in the marketing industry. She reflects on her early career, noting that she had no idea what martech was when she started. College had prepared her for traditional marketing roles—branding, PR, content management—not martech. She envisioned a straightforward path in these areas but ended up somewhere entirely different.Her entry into martech came by chance, thanks to a rotation program at Trend. This experience unveiled a whole new side of marketing she hadn't considered. Ashleigh stresses that there's much more to marketing than what college teaches. She urges young professionals and students to stay open to various roles and experiences.Ashleigh advises against the narrow approach of targeting only specific job types based on college education. She encourages a broader perspective, exploring different facets of marketing, and being receptive to opportunities that might initially seem outside one's defined path. This openness can lead to surprising and rewarding career paths, as it did for her.Her journey exemplifies the benefits of keeping career options open and exploring the full spectrum of the marketing industry. By stepping outside conventional boundaries, one can discover new and exciting opportunities in martech and beyond.Key takeaway: Embrace the unexpected by diversifying your job search beyond traditional roles. Actively seek out rotational programs or internships that expose you to different facets of marketing. This strategy will help you uncover hidden opportunities and potentially lead to a more fulfilling and dynamic career path.Navigating Martech Silos at Giant CorporationsWorking at a behemoth like Microsoft offers a unique perspective on martech operations. Ashleigh, who has been with the company for two and a half years, admits that the scale still overwhelms her. Coming from smaller enterprises where she handled marketing operations for the entire company, the shift to Microsoft's segmented structure has been significant.At her previous companies, Ashleigh was part of small, global marketing ops teams, typically ranging from three to seven people. These teams managed the martech stack across the entire organization. In stark contrast, Microsoft's martech environment is vast and compartmentalized. Multiple teams handle different aspects, and Ashleigh often finds it challenging to keep track of all the players and their roles.Ashleigh's current role focuses on supporting enterprise cloud products and services, specifically in a pre-sales capacity. There are separate teams for post-sales, gaming, hardware, and other areas, each with their own martech stacks and operations. The sheer size of the company means that even after years, she doesn't know all the teams or their specific functions.Adjusting to this environment has required a significant mindset shift for Ashleigh. She's accustomed to having a comprehensive view of martech operations, working closely with marketing and sales, and understanding the big picture. At Microsoft, she's had to accept a more siloed view, focusing on her specific area and recognizing that she won't have visibility into all parts of the company. It's a continuous learning process, and embracing this limited scope has been a significant adjustment.Key takeaway: When transitioning to a larger organization, prioritize building a personal network within your company. Regularly schedule coffee chats or brief meetings with colleagues from different teams to understand their roles and how they intersect with yours. This will help you navigate the segmented structure and foster a more collaborative and informed working environment.Why Microsoft's Fast-Paced Culture Beats the Slow Corporate MythAshleigh values the collaborative culture at Microsoft. One of her favorite aspects is working with diverse teams and individuals. In such a large organization, there's a role for everything, which means constantly interacting with new colleagues. This variety keeps her projects dynamic and introduces her to smart, creative minds across different domains.When addressing common criticisms of enterprise environments, Ashleigh counters the notion that things move slowly. Contrary to the stereotype, she finds Microsoft's pace anything but sluggish. There's always a project in motion, and new initiatives constantly arise. This fast-paced environment ensures that her work remains engaging and ever-evolving.Another positive is the breadth of experience she gains. Unlike the narrow focus some might expect, Ashleigh's work spans various aspects of martech. Her background in events has expanded to encompass broader martech roles, offering her new perspectives and skills outside her previous specialization. This variety keeps her job interesting and allows her to grow continuously.The enterprise environment at Microsoft provides Ashleigh with both depth and breadth in her career. She appreciates the chance to collaborate with a wide range of professionals and tackle diverse projects, all while maintaining a fast-paced, stimulating work environment.Key takeaway: To maximize your growth in a large organization, actively seek out cross-functional projects that require collaboration with different teams. This approach will not only broaden your skill set but also help you build a diverse professional network, keeping your work dynamic and your career development continuous.Why Curiosity Outranks Experience in Martech CareersCuriosity has been a cornerstone of Ashleigh's career in martech. She attributes much of her success to her insatiable curiosity and willingness to figure things out on her own. Unlike traditional roles with clear guidelines, martech often lacks a roadmap. This absence of predefined instructions demands a curious mindset, constantly seeking to understand how tools and technologies work.Ashleigh enjoys shadowing senior team members, a practice she values dee...

What's up everyone, today we have the pleasure of sitting down with Siobhan Solberg, data privacy consultant and advisor. Summary: Siobhan takes on a behind-the-scenes look at the hidden mechanics of data privacy, ethical marketing practices, and effective data management. Marketers often overlook the importance of data privacy, but the increase in data breaches shows that people do care about their data. To address this, marketers should experience tools from the customer's perspective, implement regular data reviews, and foster collaboration between marketing and compliance teams. By breaking down the user journey into distinct phases, they can attribute value more effectively while minimizing data collection. Focusing on key metrics and regularly auditing for dark patterns will enhance user experience without deception. Prioritizing ethical practices and transparency builds trust and leads to more informed decisions and stronger customer relationships.About SiobhanSiobhan started her career as a classical musician in NY where she had various teaching roles, specializing in violin and violaSiobhan later moved abroad and pivoted to a content role at a media agency where she would spend almost 4 years working her way up to CRO Manager and later Head of BI & Optimization and finally CMOShe completed her Certified Information Privacy Manager and joined an accelerator programOn the back of this experience, Siobhan founded Raze a niche agency specializing solely in the measurement and optimisation of marketing data – which she ran for 5 successful yearsShe's also the co-host of Marketing Unfucked, a podcast about all things data, ethics and privacy for marketing She's currently studying towards an Advanced Masters of Laws in Privacy, Cybersecurity and Data ManagementToday she's working as a data privacy consultant and advisor to tech startups who want to get it right from the startPrivacy Concerns and Cultural Differences in Data HandlingSiobhan dives straight into the issue of privacy and its varying levels of importance across different regions. She highlights a stark contrast between the United States and the European Union regarding privacy regulations and cultural attitudes. In the US, the adoption of stringent privacy measures lags significantly, partly due to cultural differences and the absence of comprehensive regulations. This has allowed some companies to exploit these gaps by selling data products that would be deemed illegal in many other parts of the world.When asked about the prevalence of tools that exploit privacy laws and whether people genuinely care about their personal data being resold, Siobhan points out an interesting dichotomy. She references studies, particularly from the Netherlands, showing that while many people claim to care about privacy, their actions often tell a different story. There is a significant gap between expressing concern for privacy and taking concrete steps to protect it.Siobhan believes that at a deeper level, everyone does care about their privacy. She mentions the common justification of having "nothing to hide" as a coping mechanism for the lack of control individuals feel over their personal data. This helplessness leads many to adopt a nonchalant attitude towards privacy. However, as incidents of data misuse and the ramifications of lost privacy become more apparent, even those previously indifferent are beginning to take notice.In the European Union, the implementation of strict privacy regulations has fostered a culture of awareness and proactive measures. This early adoption has forced companies and individuals to prioritize privacy. Conversely, in the US, the conversation is only now gaining momentum, driven by emerging state regulations and the increasing misuse of personal data through advanced technologies like AI. This growing awareness is slowly shifting the cultural landscape towards a more privacy-conscious mindset.Key takeaway: Challenge the notion that people don't care about privacy. Actively take steps to protect your data and demand transparency from companies, as the growing awareness and incidents of data misuse show that everyone values their privacy more than they might admit.Why Marketers Must Rethink Privacy and Ethical PracticesSiobhan gets straight to the heart of ethical marketing. Marketers often face the challenge of using tools that skirt privacy laws. The advice she offers is simple: put yourself in the customer's shoes. She believes this empathetic approach is crucial. It's a lesson we teach kids about bullying—how would you feel if it happened to you? Marketers should apply the same principle to their practices.When asked about using questionable tools, Siobhan emphasizes the need to consider personal feelings. How would you feel if your email was shared without consent? Or if your personal information was used to cold email you? Most people wouldn't appreciate it. Marketers need to step back and think about the human impact of their actions.Siobhan points out a fascinating contradiction: many marketers use ad blockers themselves. They don't want to see ads, yet they're creating them for others. This highlights a disconnect. By putting themselves in the recipient's shoes, marketers can make more ethical decisions. This approach doesn't just make legal sense—it's about making the right choice morally.Cultural differences also play a role. Siobhan recalls a trip to Korea, where CCTV cameras are ubiquitous. What's normal there might feel invasive elsewhere. Marketers must consider these cultural nuances. By understanding the context, they can make choices that respect privacy across different regions. The goal is to balance legality and ethics, making marketing more humane.Key takeaway: Evaluate your marketing tools by experiencing them as a customer first. Before deploying any tool, use it on yourself to understand the privacy implications and emotional impact. This practice helps you make more ethical and customer-friendly decisions.Avoiding Creepy Data Practices in Personalized MarketingMarketers often face the challenge of balancing necessary data tracking with personalization without crossing into creepy territory. Siobhan addresses this by acknowledging the delicate nature of data collection. Marketers need data to do their jobs effectively, but they must avoid overstepping boundaries. She recalls her time in measurement and technical marketing, describing it as a playground where data was plentiful, and the possibilities were endless. However, she emphasizes that what was once fun and innovative can now be seen as invasive.When asked about maintaining this balance, Siobhan suggests that marketers must be mindful of consent. If a user willingly shares their data and understands the implications, marketers should feel free to use it. However, it's crucial to ensure that the user is genuinely aware of what they are agreeing to. The key is transparency and clear communication about data usage.Siobhan also highlights the importance of being selective with data. Instead of collecting everything just in case, marketers should focus on the data they will actually use. This approach not only respects user privacy but also makes data management more efficient. Aggregated data can provide valuable insights without compromising individual privacy.Finally, Siobhan acknowledges that balancing ethical considerations with business needs is not easy. Marketers must navigate regulations and user expectations while striving to achieve their goals. The challenge lies in finding creative solutions that respect privacy and deliver personalized experience...

What's up everyone, today we have the pleasure of sitting down with Sam Oh, VP of Marketing at Ahrefs. Summary: Sam takes us on a masterclass covering SEO fundamentals, evolving search behaviors, AI in content marketing, refreshing attribution thoughts and work-life balance strategies. He advises sticking to proven SEO fundamentals and understanding search intent to meet audience needs. As search behavior evolves with tools like ChatGPT, he highlights the need for a diversified strategy across multiple platforms. He advocates for thoughtful AI integration to enhance research and streamline content creation. Finally, Sam shares Ahrefs' approach of prioritizing product quality and user-centric content over detailed attribution models, focusing on broad success indicators for effective decision-making and a fulfilling professional life.About SamAs a fresh Toronto grad out of University, Sam started a service based ecommerce site and got into black hat SEOHe grew traffic to this site and eventually sold it, this led Sam to “retire” – briefly – before experimenting with niche sites – he had one of those also acquiredHe also built an Amazon and Ebay business, where he would buy pallets of return goods from big merchandise stores and started a refurbishing center and reselling those goods online while sharpening his SEO skillsHe founded Money Journal where he published long form guides to help entrepreneurs grow their traffic and drive revenueThis naturally led Sam to co-founding a successful SEO and digital agency… but after a while, he was on kid number two and realized he wanted to leave the hustle lifestyleHe tried to get Ahrefs as a client for his agency by applying for a job and trying to turn it into a contract basis but in the end they won out and turned Sam into an employeeHe started without a title and was just asked to create educational videos and he turned that into as Director of Product Education and today he's Sam is VP of Marketing at AhrefsWhy Entrepreneurs Need to Rethink Work Life BalanceSam's path to Ahrefs was anything but traditional. Instead of following the common route of balancing entrepreneurial ventures with full-time roles, he fully immersed himself in starting businesses. From e-commerce to marketplace experiments, he thrived on innovation and problem-solving. But the relentless grind eventually took its toll, especially after a significant setback with Google's Penguin update on his first e-commerce site.As he clocked in 16-17 hour days, the birth of his second child prompted a shift in priorities. The thought of missing out on his children's lives pushed Sam to rethink his approach. Was he destined to work endlessly or could he find a way to balance family and career? This question became pivotal as he sought more meaningful work-life integration.Sam's connection with Ahrefs began as a client pursuit. After months of discussions with Tim Soulo, they decided to collaborate. Initially, Sam held onto his agency, unsure of the future. However, the move to Ahrefs proved to be an excellent match. The company offered him full autonomy and creative control, backed by substantial budgets and resources.At Ahrefs, Sam feels a strong sense of ownership. The company's culture of trust and freedom aligns perfectly with his entrepreneurial spirit. This environment allows him to apply his skills effectively, achieving professional success without sacrificing personal fulfillment.Key takeaway: Entrepreneurs often face the challenge of overcommitting to their ventures at the expense of personal life. Reassess priorities and seek roles that align with your values and lifestyle. Find work that offers autonomy and creative freedom so you can prioritize professional success and personal fulfillment. SEO Experts Need to Stop Obsessing Over Algorithm UpdatesSam addresses the constant flux in the SEO world. His advice is refreshingly simple: focus on what works. Many SEO consultants, like the one asking the question, find themselves overwhelmed by the relentless updates and algorithm changes. Sam suggests that if your current strategies are effective, there's no need to chase every new development.For those engaging in practices clearly against Google's guidelines, staying updated is crucial. However, for most people working on technical SEO—handling internal linking, crawling, and similar tasks—the updates can be more noise than necessity. The key is to concentrate on proven methods and adjust only when a significant change directly impacts your work.Sam likens this to the hype around ChatGPT, where exaggerated claims cause unnecessary panic. He points out that this noise can lead to irrational fears, such as interns doubting their career choices. Instead of getting caught up in every new trend, it's better to stay grounded and focus on tangible results.Ultimately, Sam's approach is to avoid the hysteria surrounding new updates and technologies. He emphasizes the importance of sticking to solid SEO practices and avoiding the distractions that come with every new development.Key takeaway: Focus on what works and avoid getting caught up in every SEO update. Don't let every minor change disrupt your workflow. Concentrate on proven strategies and adapt only when necessary. SEO Is Here to Stay Despite AI and Algorithm ChangesSam doesn't believe SEO is dying anytime soon. The need to sort and index information isn't going away. Whether it's Google, YouTube, Pinterest, or Reddit, every platform with a search feature relies on SEO. Despite the industry's perennial claims of its demise, SEO remains crucial for organizing and optimizing content across the internet.He addresses the divide within the SEO community: those who adhere to white hat tactics and those who dabble in black hat methods. The latter often tarnish the industry's reputation. Despite this, the fundamentals of SEO—technical optimization, quality content, and understanding search intent—continue to hold strong. Sam compares the scenario to the stock market, with pessimists always predicting crashes. He attributes some of the criticism to frustrations with search results often filled with copycat content, which he sees as a consequence of optimizing for search intent.People tend to blame SEOs when they see repetitive content in search results. Sam explains that this is a result of everyone trying to match search intent, which can lead to similar content being ranked. He acknowledges that this might cause users to think SEO is at fault, but he views it as part of the game. SEOs are tasked with demonstrating to Google that their page is the best result for a query, often within the constraints of Google's guidelines.Sam is confident that SEO won't be replaced soon. While AI and other technologies might change aspects of the industry, the core need for SEO remains. The industry will continue to evolve, but the fundamental skills and strategies of SEOs will stay relevant.Key takeaway: SEO remains essential as long as search engines exist. Technical optimization, quality content creation, and understanding search intent are timeless strategies that remain effective despite algorithm changes and AI advancements.How Content Marketers Can Stay Relevant with AISam argues that SEO and content marketing are here to stay, even with the rise of AI. The key to thriving lies in effort, experience, and experimentation. Ryan Law's article on this topic resonates with Sam, who emphasizes these principles for standing out in a crowded field.Effort is paramount. Understanding your audience and delivering precisely what they need sets you apart. ...

What's up folks. We've got a fun episode today. If you're a regular listener, you've heard me mention an article that's been living rent free in my head for a while now. Casey Winters, the former CPO at Eventbrite and an Instructor at Reforge, wrote an article titled “The Problems With Martech, and Why Martech is Actually for Engineers”. I've asked a lot of recent guests what their thoughts were on some of the arguments raised in the article. So today we're going to respond to his claims.Summary: Should you buy a 3rd party martech solution or build your own in-house tool, the answer is almost always buy. Let your in-house engineers focus on product and data while leveraging the cutting-edge solutions and support offered by specialized martech vendors. Unless you're planning on building a martech company, leave the martech to the experts. Homegrown tools aren't appealing to marketers, they're hard to scale, most have a shitty UI and it's not a recognisable martech tool you can add to your resume. Not only are homegrown martech tools not appealing to marketers, they are even less appealing to engineers. Engineers can't stand the chaos of marketing and effective martech implementation requires collaboration between engineers and marketers, highlighting the need for cross-functional translators and disproving the claim that martech is actually only for engineers.Martech Has Continued to Explode as a CategorySo the article we're debating was written in 2019, that's 5 years ago. That's a boatload of time in martech so we can't fault the author too much and I respect his bold claims. He starts off by stating: “I hate martech, and think martech will decline as a category, and most martech businesses will not be very successful.” Now we could spend a whole episode disproving this prediction… but obviously we have 5 years of hindsight. But it is worth mentioning that he made this prediction on the year (2019) where the martech landscape exploded past 7,000 tools. Pretty bold to claim that it will decline as a category given the meteoric rise of tools up from only 350 in 2012. Scott Brinker recently released the state of martech in 2024 report which his team says they've seen the “largest number of new apps added to the martech landscape in the 13 years they've been curating it: net new growth of approximately 3,000 new tools.”We've crossed 13,000 tools, nearly doubling the landscape from 2019 when Casey made his “bold prediction” that martech will decline as a category. Number of tools isn't the only way to evaluate whether martech has declined or not. I'm not a big fan of Gartner reports but if that's a more trusted source for you, they reported that in 2023 client organizations spent over 1/4 of their marketing budgets on technology. In terms of VC investments, LUMA reported a steady rise in martech acquisitions in Q3 of 2023, averaging over 40 per quarter, alongside substantial capital inflows into new ventures. This financial backing underscores confidence in the industry's future​​.Okay… so Casey was wrong about martech declining as a category. But he did have some interesting arguments about why. His main thesis is that: Martech faces decline due to in-house engineers who are increasingly handling tailored solutions in-house, and the success of vendors hinges primarily on serving those engineers, not marketers.I've asked 8 recent guests on the podcast to read Casey's article and share their thoughts.What's your take on this? Is martech actually for engineers?Homegrown Marketing Technology Isn't Attractive for Marketers or EngineersMartech Just Isn't that Appealing for Most EngineersVish Gupta, Marketing Operations Manager at Databricks shared her perspective on whether martech is truly designed for engineers, challenging pretty much every single one of Casey's viewpoints. She started by expressing her disagreement with the idea that martech will decline due to competition from in-house engineers and platform limitations. "I don't think martech is the sexiest thing for an engineer to do," she noted. Vish argued that talented engineers building martech are more likely to work for CRM companies to enhance their products rather than find in-house martech development appealing.Vish explained that building a CRM in-house is often not the best approach. She emphasized that knowing popular systems like Customerio, Marketo, and HubSpot adds more value. She questioned the practicality of finding the right talent for in-house solutions, given the complexities and specialized skills required.Regarding the idea that successful martech companies cater primarily to engineers, Vish disagreed. "Martech teams are actually part engineer, part product marketer, part IT person, part biz ops," she said. She believes the value of an operations professional lies not in owning and maintaining tech but in resolving business problems by aligning the right people, technology, and tools to accelerate pipeline generation. The engineering work in martech spans across data, data engineering, IT, and business operations, but this is just one aspect of a martech professional's role.Vish also questioned the notion that the rise of in-house engineers creating tailored solutions for their companies will lead to a decline in martech. "Just because you can, should you?" she asked. She emphasized the importance of a good quantification model and total cost of ownership (TCO) analysis when comparing in-house engineering teams to martech solutions.She highlighted the challenges of integrating customer and product data in a compliant manner, which often requires a holistic approach. "It's not just your martech stack; where's your customer data living? Where is your product data living?" Vish noted. These challenges often make martech an operational project rather than just a marketing function.Ultimately, Vish believes that martech will never be just for engineering. The value of a martech professional lies in understanding what marketers want to achieve and enabling them to get there. "The value is being able to see this is what the marketer wants to do, and here's how we can enable them to get there and measure success," she explained. This holistic view is crucial for martech to function effectively, a perspective she feels engineers alone may not fully capture.Key takeaway: In-house martech development is off-putting for most seasoned marketers. The preference is usually with popular systems like Customerio and HubSpot. Also, Martech just isn't that appealing to engineers. So martech can't just be for engineers, it requires a blend of skills from marketing, IT, and operations. The real value of martech lies in enabling marketers and measuring success, a role not easily filled by engineers. Engineers Can't Stand the Chaos of MarketingSo far we've uncovered two themes: Marketers don't find homegrown tools that appealing and engineers don't find martech sexy. But why? Why isn't martech appealing for engineers?Let's hear from the legendary Sara McNamara, former Senior Manager, Marketing Operations at Salesforce.. Her answer stemmed from the complexities and cultural challenges of integrating engineering into marketing operations.Sara began by acknowledging the trend of engineers becoming more involved in creating custom solutions for marketing. However, she expressed skepticism about marketing operations teams becoming predominantly composed of engineers. She explained, "A lot of the engineers I've worked with cannot stand the chaos of marketing." Engineers typically prefer clear requirements and stable projects, while marketing often involves rapid changes and freque...

What's up everyone, today we have the pleasure of sitting down with Vish Gupta, Marketing Operations Manager at Databricks. Summary: This episode with Vish is jam packed with advice for marketers making their way through the martech galaxy. We touch on the pitfalls of Frankenstein stacks and the perks of self-service martech. Vish explains why martech isn't just for engineers and highlights the efficiency of customized Asana intake forms. We also tackle the dangers of over-specialization for senior leaders. Additionally, we explore the intersection of martech and large language models (LLMs), providing insights on how to stay ahead in the evolving landscape.About VishVish started started her career as a Business Analyst in sales ops at Riverbed, a network management companyShe later joined Redis Labs – a real time data platform – as a Marketing Coordinator and got her first taste of analytics and reporting covering social, paid and eventsShe had a short contract at Brocade where she was Marketing Ops specialist and worked closely with their data science team to develop marketing reporting using BIShe then joined VMware, the popular virtualization software giant just before they were acquired by Broadcom. She was both a marketing analyst and later shifted to Growth Analyst where she focused more on Go to market strategyToday Vish is Marketing Operations Manager at Databricks, a leader in data and AI tech valued at more than 40BInfluences from a Tech-Infused ChildhoodVish's upbringing in a tech-savvy household shaped her career path significantly. Her parents, immigrants from India, transitioned into tech for better opportunities, despite initial dreams of cricket and architecture. This drive for a better lifestyle through technology was a core narrative in her family.Interestingly, Vish initially rebelled against this tech-centric world. She pursued psychology, striving to carve out her unique path. However, practicality led her back to tech, aligning her career with her desired lifestyle. This shift wasn't romantic but highlighted her adaptability and strategic thinking.Her parents' relentless upskilling and enthusiasm for technology left a lasting impression. Their constant engagement with new tools and innovations inspired Vish to embrace learning and staying current with tech trends. This mindset proved invaluable in her role at Databricks, where technological adeptness is key.Growing up in Silicon Valley provided Vish with a unique network and role models in tech. This environment, combined with her parents' stories and actions, underscored the importance of tech as a vehicle for advancement and success.Key takeaway: Vish's tech-centric upbringing, driven by her immigrant parents' pursuit of better opportunities, significantly shaped her career. Despite initially rebelling by studying psychology, practicality led her back to tech, showcasing her adaptability. Her parents' continuous upskilling inspired her commitment to learning, crucial in her role at Databricks.Why Your Frankenstein Martech Stack is Sabotaging Your SuccessA Frankenstein martech stack is like a tech monster stitched together from mismatched parts, always on the brink of chaos. Avoiding the creation of a Frankenstein stack is challenging for any marketing operations team who is trying to stay on top of new tools. Vish's mantra is that tools are not problem-solvers on their own; people and processes are the real drivers of solutions.She's a big proponent of understanding the role each tool plays within the organization. It's crucial to ask, "What is this tool doing?" If a tool isn't effectively serving a business purpose or hasn't been adopted well, it might be time to retire it. Simplification is key before automation. An overly complex or constantly changing process isn't a good candidate for automation.Vish points out a common misconception: the belief that automating everything is the ultimate solution. In reality, automating a clunky or inefficient process can exacerbate issues rather than resolve them. The focus should be on simplifying processes first. Only after streamlining should organizations consider tools that enhance efficiency.In practice, this means critically assessing each tool's contribution to the business. If a tool no longer serves its purpose or complicates processes, it's time to reconsider its place in the stack. Automation should follow simplification, ensuring that processes are as straightforward as possible before adding layers of technology.Key takeaway: Simplification should precede automation. Marketers must critically evaluate their tools and processes, focusing on streamlining before leveraging automation. This approach prevents the creation of a cumbersome, Frankenstein-like martech stack—a tech monster stitched together from mismatched parts, always on the brink of chaos.Empowering Campaign Ops with Self-Serve ModelsSetting up self-service models for campaigns is like to an all-you-can-eat buffet, where the food is already prepared, and you simply pick and choose what you want. In the realm of campaign operations, enabling self-service means providing users with the right tools and training, allowing them to be effective without the need for constant support.One such tool, Knak, plays a pivotal role in this self-service approach for Databricks. Vish explains that Knak allows users to create emails independently without needing to delve into their automation platform. This system keeps users out of the intricate details of their MAP, reducing the burden on the marketing operations team while still enabling efficient email creation. By using Knak, the process is streamlined: users work within Knak, sync their work to their MAP, perform quality assurance, and then execute their campaigns. This seamless integration not only simplifies operations but also enhances efficiency.Vish highlights the potential pitfalls of a full self-service model, where multiple users could potentially create chaos within their MAP. Instead, she advocates for a balanced approach, where specific components of the campaign process are made self-service. This method provides a win-win situation for both the operations team and the front-end users. The key is finding tools that allow for this partial self-service model, thereby maintaining control while empowering users.Knak was introduced to replace a previous tool that failed to meet expectations. Vish was part of the decision-making process, although the team had several champions for Knak and a supportive leader confident in their ability to select the right vendor. This collective decision-making and confidence in the tool have led to a successful implementation, demonstrating the importance of team involvement and leadership support in adopting new technologies.Key takeaway: Empowering users with the right self-service tools like Knak can streamline campaign operations and reduce the burden on the marketing team. A balanced approach to self-service can prevent chaos while maximizing efficiency.Why Martech Shouldn't Cater Exclusively to EngineersWhen asked if martech is really geared towards engineers, Vish provided a nuanced perspective. She finds the notion that martech should cater exclusively to engineers rather unsettling. For Vish, her expertise lies in mastering popular systems like Marketo and HubSpot, not engineering. She raises a compelling point about the value of specialized martech knowledge, emphasizing that the real worth of a martech professional is their ability to understand and implement what marketers need, not merely to build systems from scratch...

What's up everyone, today we have the pleasure of sitting down with Carmen Simon, Chief Science Officer at Corporate Visions and Brain Science Instructor at Stanford CS. Summary: Carmen takes us on an adventure exploring the wonders of brain science and how to sustain attention through contrast. We cover embodied cognition, deviating from expected patterns and avoiding the sea of sameness in AI content. We also take a detour into the speculative future of neuroscience and making data impactful through context. About CarmenCarmen has spent her career in multimedia design, writing books, creating and selling companies, and more recently conducting brain science research. She wrote ‘Impossible to Ignore' – A groundbreaking approach to creating memorable messages that are easy to process, hard to forgetShe started (and still is) at Stanford Continuing Studies teaching several brain science coursesAnd today she's Chief Science Officer at Corporate Visions where she runs neuroscience research to help businesses increase their persuasive powerShe also recently published another book called Made You Look – a full-color image packed guide on developing persuasive contentEmbodied Cognition in MarketingCarmen highlights the rising trend of embodied cognition in neuroscience. This concept suggests that our brain's attention, memory formation, and decision-making are influenced by the interaction between the brain, body, and environment. It's not just mental processes but physical engagement that shapes our cognitive functions.She offers practical advice for marketers: involve your audience physically. For example, during a sales presentation or team meeting, encourage note-taking. This simple act engages multiple parts of the body, enhancing memory and focus. In Carmen's studies, participants who took notes during sessions retained information better than those who just listened.The key is to move beyond passive engagement. Traditional methods often required participants to stay still, but advancements in neuroscience now allow for physical involvement without compromising data accuracy. So, telling your audience to write things down can make a significant difference in how well they remember and engage with your content.This becomes more challenging in remote settings like Zoom. The temptation to type notes digitally is strong, leading to potential distractions. Carmen's research shows that while digital note-takers wrote more, those who handwrote their notes retained and synthesized information better. Handwriting forces individuals to summarize and critically engage with the content, enhancing the quality of their notes and memory retention.Carmen's insights suggest that integrating physical activities into your marketing strategies can create a more immersive and memorable experience for your audience. This approach not only boosts engagement but also helps in building stronger connections and better information retention.Key takeaway: Encourage physical involvement in your marketing efforts. Simple acts like note-taking can enhance engagement and retention, leveraging the principles of embodied cognition for more effective and memorable interactions.Enhancing Virtual Engagement with Body CuesCarmen discusses an intriguing neuroscience study comparing brain activity when showing products through slides versus using a whiteboard. She emphasizes that using a whiteboard engages people more effectively. The physical act of drawing grabs attention and creates a dynamic visual experience. When the audience is encouraged to draw along, this engagement deepens even further.Encouraging participants to draw along creates a shared physical activity, reinforcing memory retention. This technique leverages embodied cognition, where physical movement aids cognitive processes. Carmen's study showed superior recall effects for those who engaged in drawing versus those who only watched slides. After 48 hours, participants who drew remembered more, highlighting the power of active involvement.In a virtual setting, applying these principles requires creativity and discipline. For instance, you can ask participants to take control of the mouse during a demo or encourage them to use a digital whiteboard. Despite the challenges of remote interactions, these physical cues remain crucial for memory retention. Carmen's research indicates that handwriting notes leads to better retention than typing, emphasizing the need to integrate physical activities in digital environments.Carmen urges marketers to rescue the practice of whiteboarding, even in virtual settings. The visual and physical engagement it provides can significantly enhance memory and decision-making. By reintroducing these techniques, marketers can create lasting impressions and foster better audience connections.Key takeaway: Integrate physical activities like whiteboarding in virtual settings to enhance engagement and memory retention. Encouraging your audience to draw along or take notes by hand can lead to more effective and memorable interactions.Sustaining Attention Through ContrastCarmen dispels the myth of shrinking attention spans, emphasizing that humans are capable of sustained focus if the stimulus is engaging enough. She notes that from a biological and evolutionary perspective, our ability to concentrate hasn't diminished. The key is to make the content interesting and relevant. As an example, think about how many hours people can spend binge-watching TV shows when they're captivated.Carmen challenges marketers to think about how to capture and hold attention. The competition for focus is fierce, and at any moment, people can easily switch to something else. To stand out, marketers need to make their offerings compelling and distinct. This involves creating engaging experiences that resonate with the audience on a deeper level.One effective technique Carmen mentions is using contrast to create a noticeable difference between your content and that of others. The brain needs at least a 30% difference to perceive something as distinct. For marketers, this means clearly differentiating their solutions from the competition. It's not enough to claim that your product is better; the contrast must be perceptible and significant.She highlights the importance of making your marketing content unique and memorable. In a crowded field, ensuring that your message stands out is crucial. This can be achieved by presenting information in a way that is markedly different from others, creating a strong and lasting impression.Key takeaway: Create engaging and distinct content to capture and maintain attention. Use contrast effectively to differentiate your offerings, ensuring they stand out in a crowded market. This approach helps in making your marketing efforts more impactful and memorable.Deviate From Expected Patterns and Create Memorable ImpactCarmen highlights a significant distinction between human and AI-generated content: the power of human touch. She emphasizes that for the brain to perceive distinctiveness, it must first recognize patterns. This means that not every aspect of your marketing needs to be unique. Instead, marketers should identify areas of sameness and then have the courage to deviate from those patterns to create a memorable impact.One compelling example Carmen shares involves Krispy Kreme's daring marketing approach. They ran an ad with the headline, "Donuts are bad for you," a stark contrast to their usual “Donuts are life” messaging but also the typical health-centric marketing messages. This distinctiveness, paired with a c...

What's up everyone, today we have the pleasure of sitting down with Michael Rumiantsau, Co-Founder and CEO at Narrative BI. Summary: This episode delves into the future of Business Intelligence, highlighting AI's role in democratizing data for marketers, automating insights with LLMs, and the importance of anomaly detection. Michael's on a mission to make data insights accessible and useful for everyone, not just experts, by leveraging AI to provide tailored, easy-to-understand insights that boost decision-making. The episode also discusses how proprietary data gives companies a competitive edge in the AI market by refining models and creating tailored solutions, while well-structured data sources enhance natural language query tools. Anomaly detection is crucial for quickly identifying issues and uncovering new opportunities, with tools like Narrative BI automating alerts for unusual patterns, reducing the need for constant monitoring, and enabling more strategic decisions. Michael explains how Narrative BI, an augmented analytics platform, not only presents data but also provides context, explains trends, and suggests actionable steps, helping marketers focus on significant changes and improve performance.About MichaelMichael started his career as an electronics engineer and then a backend software engineer where he dived into web dev, db management and API integrationsHe later took on the challenge of being CTO at an IT startup called Flatlogic based in BelarusHe then moved to San Francisco and founded a web and mobile dev consultancy which he ran alongside co-founding a natural language search startup called FriendlyData with a mission of democratizing access to data He went through 500 Startups, a VC seed fund acceleration programFriendlyData was acquired by ServiceNow in less than 3 years and Michael went on to join the company in a central product role to help develop their Natural Query Language AI toolHe's also an investor at founders.ai, a startup platform for disruptive SaaS productsHis latest entrepreneurial endeavor is Narrative BI, a generative analytics platform that helps growth teams turn raw data into actionable narrativesDeciding When to Commit Fully to Your StartupStarting a business varies greatly depending on personal circumstances. Michael explains that while it might be easier for a young, single entrepreneur to take the plunge, it's a different story for someone with a family. Despite these differences, one thing is clear: at some point, you must go all in. Without full commitment, building something substantial is unlikely.Michael highlights the need to have "skin in the game." This means demonstrating serious commitment, which can convince others to support you. Investors, for example, are more likely to back someone who has shown they are fully invested. For Michael, this commitment meant leaving a secure, high-paying job and investing his own money into his venture, Narrative BI.Michael's story shows the kind of dedication required. He left behind a seven-figure salary to pursue his startup. This kind of personal risk can be a powerful motivator and a strong signal to potential investors and team members. Making the transition from a stable job to a startup isn't just a career move; it's a significant life decision that requires careful thought and total commitment.Key takeaway: Aspiring founders need to move from part-time dreamers to full-time entrepreneurs. Taking this leap is crucial for success. Without it, the foundation of your startup may remain weak. It's about believing in your vision enough to put everything on the line.Encouraging Entrepreneurial Spirit in EmployeesMichael isn't on his first entrepreneurial venture. He believes expecting startup employees to match a founder's dedication is unrealistic. Founders often work around the clock due to their significant equity stakes, but employees with smaller shares shouldn't be pressured to do the same.Michael values his employees' time and boundaries. He doesn't track how many hours they work, focusing instead on their contributions. This approach creates a healthier work environment, where employees feel appreciated for their results, not just their hours.He also encourages side hustles. For Michael, these ventures aren't distractions; they're sources of valuable experience that can benefit the company. His small team of eight includes individuals with diverse entrepreneurial backgrounds, with many already engaged in other income-generating activities. Michael sees this diversity as an advantage, bringing fresh ideas and perspectives to the company. This is a refreshing perspective coming from a founder and not shared by everyone. Shopify CEO for example is well known for discouraging side hustles and expects unshared attention from his team.Michael takes pride in his employees' entrepreneurial efforts. If someone leaves to start their own company, he sees it as a success and supports them fully. By fostering an entrepreneurial spirit, he believes his team becomes more innovative and motivated.Key takeaway: Supporting employees' side hustles and respecting their work-life balance can lead to a more innovative and motivated team. Encouraging entrepreneurial efforts within the team benefits both the company and the individuals, fostering a culture of mutual growth.Future of Business IntelligenceBI is here to stay. Michael points out that despite its $30 billion market size and growing influence, BI tools are still primarily designed for data specialists. In even the most advanced tech companies, adoption rates hover around 20-25%, leaving a vast majority of knowledge workers without direct access to valuable data insights.Michael sees a significant opportunity in democratizing BI. He believes every knowledge worker should access data insights, regardless of their technical background. This can be achieved through automated or AI-generated insights, making data more accessible to those who make critical business decisions but lack deep data expertise.Discussing dashboards, Michael notes their static nature as a limitation. Traditional dashboards rely on predefined metrics and queries, which can miss the nuances of a constantly evolving business environment. The static approach often results in overlooked insights that could be pivotal.Michael envisions a future where BI tools are dynamic, AI-powered, and user-friendly. This would allow real-time insights tailored to specific roles and individuals, enhancing decision-making processes across all organizational levels. By enabling a broader audience to harness the power of data, the potential impact of BI could be far greater than ever imagined.Key takeaway: The future of BI lies in making data insights accessible and actionable for all employees, not just data experts. Embracing AI-powered, dynamic tools can help businesses stay ahead by providing real-time, personalized insights, fostering a culture of informed decision-making.AI's Role in Democratizing Data for Knowledge WorkersMichael acknowledges that while BI tools are a boon for data enthusiasts, their complexity often hinders wider adoption among knowledge workers. Even with advanced natural language query tools, users need to understand database structures, table names, and relationships. This level of data literacy is uncommon among marketers and executives, creating a significant barrier.AI offers a promising solution to this challenge by proactively generating insights. Instead of waiting for users to ask specific questions, AI can analyze data trends and patterns to provide pers...

What's up everyone, today we have the pleasure of sitting down with Michele Nieberding, Director of Product Marketing at MetaRouter. Summary: Michele takes us on a broad journey across job hopping, learning technical martech products, preparing for the cookie apocalypse and diving deep into the world of server side data processions and tag management. Her transition from sales to product marketing sparked new growth, blending her enthusiasm for learning technical martech products with practical strategies to improve sales outcomes. She emphasizes the importance of ethical marketing practices, like enhancing first-party data and focusing on consent management, crucial for building consumer trust. Michele also explores the benefits of server-side data processing, such as using systems like MetaRouter for real-time data handling, which improves site performance, data security, and compliance. This technical shift supports her broader view on the integration of marketing with data science, stressing the need for solid data management to navigate the complexities of modern marketing and data privacy laws effectively.About MicheleMichele started her career in sales at Cvent, a meetings and events management software provider She later had a short stint as a marketing consultant at Fishbowl a restaurant platform And then joined a CRM company called Merkle as a Digital Marketing Manager where she wore a variety of marketing hatsThis made her boomerang back to Cvent, but this time as a Product Marketing Manager where she would spend another 2 years with the companyShe later took on the role of Senior PMM at Qualtrics, an online customer experience management platformThis led her to an exciting role leading Solutions Marketing at Iterable, where she was eventually promoted to Director of Product MarketingMichele is also an Executive Mentor at Cornell UniversityToday she's Director of Product Marketing at MetaRouter, a Customer Data Infrastructure startup Why Job Hopping Can Be a Green FlagWhen asked about the recent commentary from a CEO criticizing frequent job changes and claiming that you need to stay at a company at least 4 years to achieve anything worthwhile. Michele offered a compelling counterpoint that challenges old school views on career progression. Her journey in the tech industry illustrates the value of embracing various roles across different companies, especially in wild sectors like martech. Michele believes that the innevitably rapid advancements within tech demand adaptability and a willingness to tackle new challenges, which often means moving between jobs.Michele argued that the notion of needing several years to make a significant impact in a company might indicate deeper issues with the hiring or role alignment process. In her experience, impactful contributions don't necessarily require long tenures. She shared an anecdote from her last position where she was promoted twice within just 12 months, underscoring her ability to drive meaningful change swiftly. Her success stories reflect her high performance and dedication to progress every day she's at work.This perspective brings into question the disparity in the traditional view of loyalty, highlighting that while businesses often tout long tenures as signs of allegiance and even liken their teams to families, they frequently fail to uphold their end during challenging times, opting instead to cut numerous lower-level positions rather than making reductions at the top. Michele highlighted that nowadays the real value lies in how much an individual can accelerate growth and bring about change, rather than how long they remain in a position. This approach benefits the companies that embrace such high-performing individuals.Her stance suggests that companies should rethink their hiring strategies and the attributes they value in employees. The focus should shift towards flexibility, quick adaptation, and the ability to deliver results efficiently—qualities that are crucial in a sector as fluid as technology.Key takeaway: Companies need humans that can adapt quickly and make significant impacts in relatively short periods, not half a decade. Michele's experience shows that job mobility can be a sign of a high-performing individual capable of driving innovation and growth who's looking out for themselves and owning their career paths. Companies should value flexibility and quick adaptability as much as, if not more than, long-term tenure.Making the Leap From Sales to Product MarketingMichele's career shift from sales to product marketing at Cvent is a perfect example of how adaptable skills can propel your career forward. Starting in sales, Michele thrived by meeting challenges head-on and solving customers' problems effectively. Her success wasn't unnoticed; she was a top sales rep, deeply involved in every aspect of the products she sold. However, Michele knew she wanted more from her career. Unable to transfer from sales to marketing internally, her ambition to explore beyond sales led her to an agency role where she broadened her marketing expertise.Despite enjoying the creative rush at the agency and wearing all of the hats, Michele felt something was missing. She could suggest marketing strategies but rarely saw how they played out, missing the direct impact of her work. This gap led her back to Cvent when a product marketing role opened up. It was a new territory, but she knew the product inside out from her sales days, which gave her a unique edge.Stepping into product marketing, Michele fell in love with the strategic and creative elements of the role. She was right back at solving problems, but this time she was crafting the narrative and directly influencing the product's market journey. It was different from sales but used many of the same skills in new ways.Today, Michele can't see herself doing anything else. Her story isn't just about a job change; it's about finding your niche where you can use your talents to the fullest. She took her in-depth product knowledge from sales and seamlessly integrated it with the marketing skills she honed along the way, proving that the right move at the right time can redefine your career.Key takeaway: Michele's switch from sales to product marketing shows how valuable it is to apply your skills in new contexts. For marketers looking to keep their careers vibrant and impactful, consider how your current skills can open new doors within your field. It's not just about climbing the ladder; sometimes, it's about stepping onto a completely different one.What Do Sales and Product Marketing Have in Common?It's not always intuitive, but one fundamental commonality between sales and product marketing is the requirement to deeply understand your product. Michele's strategy for mastering new martech tools showcases just how critical this understanding is, not only for personal growth but also for making significant contributions to her team and the broader company objectives.When Michele joins a new company, she immediately seeks to connect with colleagues from sales, customer success, and technical teams such as solution architects. These relationships are crucial as they provide a wealth of insights into the product's real-world applications, an invaluable resource for anyone in product marketing. Michele's early days in any role are spent actively engaging: participating in calls, attending demos, and using the tools herself as much as possible. This hands-on experience allows her to view the product through the eyes of a user, which is essential for crafting messages that resonate with potential customers...

What's up everyone, today we have the pleasure of sitting down with Angela Cirrone, Senior Director, Marketing Operations at Optimizely. Summary: Angela brings a fresh perspective to marketing operations, a key theme throughout the conversation is curiosity and how it helps boost your confidence and be a key lego block to a successful career. What makes her a unique leader is her experience being part of over a dozen acquisitions which came with over a hundred platform migrations and integrations. She's developed a framework for platform migrations and a knack for evaluating software and building a stack with martech minimization in mind. We also navigated the convergence of martech and analytics in MOPs and pondered whether MOPs should report into GTM?About AngelaAngela started her career as a dental assistant before moving to academic advisory and then trying out dental salesShe moved over to marketing – playing social media and community roles for various companiesEventually she found her way into Marketing Ops at Skill-soft where she learned Marketo and got her certificationShe later freelanced at CS2She then joined a proposal automation software company that would later get acquired by Upland Software, a portfolio of 25+ cloud apps, where she would eventually get promoted to Director of Marketing OperationsShe later took on the role of Senior Director of Marketing Ops and Demand Gen at Sauce Labs, a continuous test and error solution where she transformed the Ops function for enhanced efficiency and alignment with sales and GTMToday she's Senior Director of Marketing Operations at Optimizely, an enterprise digital experience platformBoosting Confidence by Embracing CuriosityAngela reflects on her initial days at Optimizely, surrounded by experts in marketing operations. She didn't start out knowing all the answers. Instead, she focused on moving challenges forward, a method she credits for easing her entry into a field filled with experienced professionals. Angela quickly realized the power of not knowing everything but having the skills to find out.She champions the idea of empowerment through curiosity within her team. This approach shifts the emphasis from having instant solutions to developing the ability to explore and tackle problems efficiently. Angela believes that when a marketer faces a new issue, the goal shouldn't be to solve it immediately but to start unraveling it bit by bit.Angela suggests that anyone can build confidence by being inquisitive and resourceful. This means enhancing one's skills in using tools like AI and Google, and tapping into a network of knowledgeable peers. This skillset turns daunting challenges into a series of smaller, more manageable tasks.She openly shares her moments of doubt, reassuring us that even seasoned professionals feel uncertain at times. What matters is how they handle these moments—by seeking solutions and learning from the process.Key takeaway: Angela's journey teaches us that true confidence in marketing operations comes from cultivating curiosity and resourcefulness. Marketers can future-proof their careers by learning to decompose complex issues and steadily work through them, which not only builds individual confidence but also enriches team dynamics.The Challenges and Opportunities of Numerous Migrations and IntegrationsWhen Angela joined Upland Software, she found herself right in the middle of a tidal wave of acquisitions—14 in total during her time there. Each of these mergers, including one with her former company Kubity, thrust her into a role that tested her skills and confidence. Her task was to merge different technologies and operational cultures into Upland's existing framework, and in some cases she had just six months to make it happen. This period marked a significant leap in her career, filled with both challenges and substantial learning.Angela's experience at Upland was filled with managing logistics but it also presented an opportunity to shape the company's future. With no formal marketing ops team in place and the function previously outsourced to an agency, Angela saw a gap. She proposed and established a dedicated team, shifting the company's approach from external reliance to internal strength. This move was about building a foundation that was robust and could handle the complexities of future growth.Each acquisition brought different practices and technologies to the table. Angela emphasized the importance of understanding the reasons behind each company's methods. She saw this as more than just integrating new tools into Upland's tech stack but a chance to think critically about what improvements these new elements could bring to the company.Reflecting on her time at Upland, Angela highlights the formation of the marketing ops team as a key achievement. Her approach shows how tackling immediate challenges with a strategic mindset can lead to lasting advancements within a company.Key takeaway: Dealing with acquisitions in martech requires strategic foresight and the courage to drive change. By viewing each migration and integration project as a stepping stone for improvement, marketers can capitalize on the opportunities these changes bring. Architecting a Framework for Platform MigrationsWe asked Angela to unpack how her first few integration projects looked liked compared to her 13th and 14th acquisitions. She started by sharing details on the evolution of the process for merging data from new acquisitions into existing systems. Initially, the process was somewhat indiscriminate, with an emphasis on transferring as much data as possible, regardless of its immediate value or relevance.Over time, Angela and her team developed a more nuanced strategy, likening it to "packing a suitcase, not the whole house." This approach meant being selective about which data and tech assets to integrate, focusing on quality and relevance rather than quantity. They established clear criteria for what to include, such as activity levels and the strategic value of certain accounts or campaigns. This method allowed them to streamline the integration process and avoid cluttering their system with unnecessary data.Naturally, when two companies merge, two tech stacks also need to merge. A key part of refining their approach involved making tough decisions about existing contracts and technologies. Angela encountered scenarios where newly acquired companies had recently entered into multi-year contracts for technologies that were not part of her company's preferred tech stack. Deciding whether to honor these contracts, transition to preferred technologies immediately, or find a middle ground was a complex challenge that required strategic thinking and careful negotiation.By the time of the later acquisitions, Angela's strategy had matured significantly. The team had moved from a lenient approach to a more standardized method, focusing on aligning new acquisitions closely with operational standards. This shift not only improved the efficiency of the integrations but also ensured that new additions could seamlessly contribute to the company's overall strategy.Key takeaway: By focusing on what truly adds value and aligning new assets with established standards, marketers can enhance the efficiency and effectiveness of their tech stacks and data strategies. This strategic integration ensures smoother transitions during acquisitions and can significantly boost a company's capabilities in the competitive martech landscape.How to Pick Between Similar Martech Solutions?Angela often faced a common scenario: deciding whether ...