Podcasts about Martech

Text us your thoughts on the episode or the show!What if the biggest marketing problem in your organization isn't the marketing team at all?In this episode, Michael Hartmann sits down with Charral Izhiman, Head of Marketing at Bayobab and author of The Marketing Movement, for a conversation about why so many organizations still misunderstand what marketing is supposed to do, and what it takes to fix that from both sides.Charral's perspective is refreshingly different. Her book isn't written to teach marketers how to market. It's written to help non-marketing leaders understand how to actually work with marketing. That framing opens up a rich discussion about the gap between strategy and execution, and why Ops professionals may be the best-positioned people in the business to close it. In this conversation, they discuss:The outdated assumptions organizations still hold about marketing, and how marketers unintentionally reinforce themWhy Ops teams sitting at the intersection of marketing, sales, finance, and leadership are uniquely positioned as translators across the businessThe SHAPE framework, and why "Activation" is the overlooked layer between planning and resultsWhy organizations romanticize strategy and celebrate execution but skip operational readiness in the middleThe Formula 1 metaphor for marketing leadership: everything that has to come together before you can even competeWhether you're in Marketing Ops, RevOps, or marketing leadership, this episode is full of ideas for anyone trying to bridge the gap between strategy, operations, and the rest of the business. The conversation doesn't end here. Explore the full SHAPE framework and more in Charral's book, The Marketing Movement: https://themarketing-movement.com/Episode Brought to You By MO Pros The #1 Community for Marketing Operations ProfessionalsSupport the show

Enterprise marketing teams struggle with AI implementation beyond basic automation. Patrick Brown, Vice President of Growth Marketing & Insights at Adobe, shares how global organizations can strategically deploy artificial intelligence across complex customer acquisition and engagement programs. He outlines Adobe's three-pillar framework for AI adoption: experience delivery optimization, advanced measurement analytics, and foundational tool development. Brown also explains why forward-looking AI projections often fail and how marketing leaders should focus on proven AI applications like summarization and synthesis rather than predictive capabilities.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Enterprise marketing teams struggle with AI implementation beyond basic automation. Patrick Brown, Vice President of Growth Marketing & Insights at Adobe, shares how global organizations can strategically deploy artificial intelligence across complex customer acquisition and engagement programs. He outlines Adobe's three-pillar framework for AI adoption: experience delivery optimization, advanced measurement analytics, and foundational tool development. Brown also explains why forward-looking AI projections often fail and how marketing leaders should focus on proven AI applications like summarization and synthesis rather than predictive capabilities.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Enterprise marketing teams struggle with AI implementation at scale. Patrick Brown, Vice President of Growth Marketing & Insights at Adobe, explains how AI transforms marketing operations across global B2B and B2C segments. He outlines Adobe's three-pillar framework for AI adoption: delivering personalized experiences, measuring performance with advanced analytics, and building foundational marketing technology tools. Brown also identifies the limitations of AI in forward-looking projections and emphasizes the importance of human judgment in strategic decision-making.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Enterprise marketing teams struggle with AI implementation at scale. Patrick Brown, Vice President of Growth Marketing & Insights at Adobe, explains how AI transforms marketing operations across global B2B and B2C segments. He outlines Adobe's three-pillar framework for AI adoption: delivering personalized experiences, measuring performance with advanced analytics, and building foundational marketing technology tools. Brown also identifies the limitations of AI in forward-looking projections and emphasizes the importance of human judgment in strategic decision-making.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Enterprise marketing teams are overusing AI for forward-looking projections. Patrick Brown, Vice President of Growth Marketing & Insights at Adobe, explains why AI excels at summarization but struggles with predictive accuracy. Brown outlines Adobe's three-pillar AI framework: delivering enhanced customer experiences through optimized content and advertising, implementing advanced measurement systems for campaign performance, and building foundational marketing automation tools that accelerate customer acquisition without relying on unreliable forecasting capabilities.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Enterprise marketing teams are overusing AI for forward-looking projections. Patrick Brown, Vice President of Growth Marketing & Insights at Adobe, explains why AI excels at summarization but struggles with predictive accuracy. Brown outlines Adobe's three-pillar AI framework: delivering enhanced customer experiences through optimized content and advertising, implementing advanced measurement systems for campaign performance, and building foundational marketing automation tools that accelerate customer acquisition without relying on unreliable forecasting capabilities.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Album 8 Track 17: The Mythology Behind a Great Marketer w/Louis MonoyudisWhat does an undergrad degree in folklore and mythology have to do with scaling direct-to-consumer (D2C) brands to millions in revenue? Everything.In this episode of Brands, Beats, and Bytes, hosts Darryl "DC" Cobbin and Larry Taman sit down with seasoned executive Louis Monoyudis (CMO at Artware Editions, former global CMO at Bokksu, Fable Pets, Levo, and Roam). Louis pulls back the curtain on how a deep understanding of human narrative, ritual, and "belief" acts as the ultimate foundation for hyper-growth marketing.Discover why data infrastructure must balance founder intuition , the real reason crowdsourced fashion platforms face massive scaling hurdles , and what "agentic shopping" means for the survival of the traditional brand website. Whether you are a founder battling hubris or a marketer trying to stay ahead of the AI curve, this episode provides a masterclass on balancing creative judgment with business performance.Key Takeaways: The Fine Line Between Religion and MythEscaping the Echo ChamberThe Reality of Decision FatigueAgentic AI & The Future of ShoppingHuman Taste vs. Machine DataThe ROI of CommunityDon't forget to subscribe, rate, and share with a fellow Brand Nerd!Instagram | LinkedIn

In this episode of FinTech's DEI Discussions, recorded live at Fin.Tech Marketing Conference 2026, Nadia Edwards-Dashti sits down with Kelly Waller, Global VP Field Marketing at Gradient, to explore the role leaders and organisations must play in creating truly inclusive workplaces.Drawing on her experience leading teams across both FinTech and MarTech, Kelly shares why developing people has been a constant thread throughout her career and why inclusion cannot be left to chance. The conversation explores the responsibility marketing teams have to build trust, the importance of bringing your whole self to work, and the growing concern around organisations stepping back from diversity, equity and inclusion initiatives.FinTech's DEI Discussions is powered by Harrington Starr, global leaders in Financial Technology Recruitment. For more episodes or recruitment advice, please visit our website www.harringtonstarr.com

Enterprise marketing leaders struggle with AI implementation at scale. Patrick Brown, SVP of Global Marketing at Adobe, shares how his team operationalizes AI across customer acquisition and engagement programs. Brown explains why AI excels at content summarization and synthesis but fails at forward-looking projections, and outlines Adobe's three-pillar framework for deploying AI in experience delivery, measurement analytics, and foundational tool development.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Enterprise marketing leaders struggle with AI implementation at scale. Patrick Brown, SVP of Global Marketing at Adobe, shares how his team operationalizes AI across customer acquisition and engagement programs. Brown explains why AI excels at content summarization and synthesis but fails at forward-looking projections, and outlines Adobe's three-pillar framework for deploying AI in experience delivery, measurement analytics, and foundational tool development.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Enterprise marketing teams struggle with AI implementation at scale. Patrick Brown, Vice President of Growth Marketing & Insights at Adobe, shares how global organizations can practically deploy artificial intelligence across customer acquisition and engagement functions. He explains why AI excels at summarization and synthesis but requires human judgment for forward-looking projections, and outlines Adobe's three-pillar framework for integrating AI into experience delivery, measurement systems, and foundational marketing tools.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Enterprise marketing teams struggle with AI implementation at scale. Patrick Brown, Vice President of Growth Marketing & Insights at Adobe, shares how global organizations can practically deploy artificial intelligence across customer acquisition and engagement functions. He explains why AI excels at summarization and synthesis but requires human judgment for forward-looking projections, and outlines Adobe's three-pillar framework for integrating AI into experience delivery, measurement systems, and foundational marketing tools.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

What's up everyone, today we have the pleasure of sitting down with Lindsay Rothlisberger, Director of GTM Innovation at Zapier.(00:00) - Intro (01:23) - In This Episode (02:00) - Sponsor: Knak (03:08) - Sponsor: MoEngage (05:49) - How Zapier's RevOps Team Built Its AI Foundation (19:43) - Why Visibility Has to Come Before Governance in AI Adoption (24:58) - Sponsor: GrowthBench (25:58) - Sponsor: GrowthLoop (29:48) - How Zapier Fights Context Rot in Its AI Shared Brain (35:55) - How Zapier Governs Shared AI Skills from Review to Long-Term Ownership (39:27) - What Happens to RevOps When Everyone Around Them Can Build (45:05) - The Director of GTM Innovation Role and the Sharing Problem Nobody Has Solved (50:47) - What Keeps Lindsay Grounded in the Middle of All This Change (52:00) - Lindsay on Getting Buy-In and What She's Reading Summary: When a startup claimed in April 2026 that it invented the marketing engineer role and that RevOps professionals "just do tool integrations," Lindsay Rothlisberger had heart palpitations. Her team at Zapier had been building AI into GTM workflows for years before the announcement. In this episode, she walks through the 6-component AI governance model she published publicly: a golden path to Cursor, a structured shared brain in Google Drive, data policies built with the security team, a visibility layer powered by a custom Zapier agent, a context engineering strategy that fights context rot, and a red-yellow-green skills review gate. She also names the part of the model that's still broken, and it's more honest than most AI governance conversations allow. If your team is figuring out how to govern AI at scale without killing the momentum, this is the inside view from someone who's done it.About Lindsay RothlisbergerLindsay Rothlisberger is Director of GTM Innovation at Zapier, where she leads the company's AI-powered GTM transformation internally and works alongside customers navigating the same shift. She spent 4 years building Zapier's RevOps function from zero, scaling it into a cross-functional engine covering AI, systems, analytics, planning, and enablement, and growing ACV 10x in that time. Before moving into the innovation role, she led marketing operations and lifecycle programs at UNiDAYS across B2B and B2C markets. She writes on LinkedIn about what Zapier is actually shipping, what works, and what doesn't.How Zapier's RevOps Team Built Its AI FoundationMost RevOps teams doing serious AI work have been doing it longer than the current conversation suggests. The tools are newer and the terminology has changed, but building automated workflows that take unstructured data and produce structured, actionable outputs for salespeople and marketers? That's exactly what good RevOps teams were doing before anyone put a trending name on it.Lindsay's team at Zapier started experimenting with AI several years ago, when it was first becoming accessible. Zapier gave its RevOps team the tools to experiment early, and rather than waiting for a strategy to materialize, they picked a specific, annoying problem: sales handoffs. Salespeople were going into first calls without enough context about the lead. The team pulled all the relevant unstructured data, engagement records, support tickets, email threads, and used AI to generate clean, contextualized briefing materials. The result was a measurable lift in lead-to-opportunity conversion rates, and a pattern the team has used ever since: find something specific that's visibly broken, prove AI fixes it, then apply that logic somewhere else.That early foundation matters now because the landscape has shifted in a way that affects RevOps directly. Claude Code, Cursor, and similar tools have made it possible for people with no engineering background to build real things. Sales managers are writing AI skills that generate quarterly revenue strategies for reps. CS reps are building account monitoring tools. Lindsay's read on this is that the RevOps team's job isn't to slow that down. It's to give it a governance structure so it can scale without creating a mess, and to be the team that built the foundation those builds are operating on.At Zapier, that governance structure is anchored by an AI center of excellence led by a chief AI officer. The architecture is a hub-and-spoke model: the central team sets the frameworks, the guidelines, and the enablement resources; Lindsay serves as the spoke into go-to-market, with a partner who works alongside her. The 2 of them act as a feedback loop between what's happening on the ground in sales, marketing, and CS and what the central team needs to know. The center of excellence is small, just a handful of dedicated people, but it reaches into every function through the spoke structure.The first thing the center of excellence built for non-technical GTM employees was the golden path to Cursor. Cursor had already been adopted by Zapier's product and engineering teams. For GTM, the barrier wasn't the technology itself; it was the setup. Someone who's spent their career in spreadsheets and CRM doesn't automatically know how to configure a development environment. The golden path is step-by-step onboarding: from installation through a fully configured Cursor environment with the right MCP connections (Databricks, Zapier), the right rules, and the right context already loaded. The whole point is removing the 2-hour configuration overhead that otherwise kills adoption on day 1.That context is the shared brain: a structured Google Drive hierarchy with company-level, department-level, team-level, and working group-level folders. The first iteration meant converting existing documentation into markdown files and organizing them into a folder structure that agents could traverse predictably. Lindsay describes the experience of setting it up as oddly satisfying for an ops person who has spent years wishing the organization's institutional knowledge lived somewhere findable instead of scattered across a Google Drive that nobody had cleaned up in years. The goal of the initial build wasn't completeness. It was a working foundation that gave people enough context to get value from their agent setup without needing to build from scratch.The companies operating furthest ahead in AI adoption right now are the ones that treated the shared brain as infrastructure rather than a side project. Getting every GTM employee configured, context-loaded, and working from a shared knowledge base is unglamorous work, but it's the layer every other build depends on.Key takeaway: Before anyone on your GTM team builds anything with AI, create a centralized setup guide that handles environment configuration, approved MCP connections, and context loading from a structured knowledge base. Start with the tools your technical teams are already using and build a version of that golden path for non-technical employees. The 2-hour configuration friction that stops people on day 1 is a solvable problem, and solving it once prevents you from solving it individually for every person who tries to onboard.How Long It Actually Takes to Build a Shared BrainThe shared brain question that comes up in every version of this conversation is a practical one: how long does it actually take? Zapier's first rollout was a 4-week sprint, and the design of that sprint was deliberate about scope. Rather than trying to capture everything the organization knew, the team focused on what Lindsay calls the slow layer of context: things that don't change often. Company strategy documents. Ideal customer profile definitions. Lead and opportunity definitions. Basic playbooks. These documents already existed. The sprint was mostly ...

Enterprise marketing teams struggle with AI implementation beyond basic automation. Patrick Brown, SVP of Global Marketing at Adobe, shares his perspective on scaling AI across complex B2B and B2C marketing operations. Brown discusses why AI excels at content summarization and synthesis but falls short on predictive forecasting, and outlines Adobe's three-pillar framework for integrating AI into experience delivery, measurement systems, and foundational marketing tools.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Description The Future of Tech is Here. Subscribe to our Newsletter:https://theultimatepartner.com/ebook-subscribe/ Check Out UPX:https://theultimatepartner.com/experience/ In this presentation from Ultimate Partner Live, industry analyst Jay McBain breaks down the monumental macroeconomic shifts rewriting the tech sector in 2026. https://youtu.be/r0qTDyw97Gs As the industry rapidly approaches a $6.07 trillion valuation, driven by massive AI infrastructure investments from Sam Altman and the “Magnificent Seven,” traditional sales and channel models are fundamentally collapsing. McBain reveals how buyer demographics have transformed to an integration-first millennial base, why marketplace ecosystems now command over half of all partner-funded deals, and how a tiny elite of just 1,000 tech service providers control two-thirds of global tech revenue. Learn the exact mechanics behind how Microsoft out-partnered AWS to win 26 straight quarters of dominant growth and how your business can deploy an algorithmic early warning system to capture massive wallet share before competitors even step into the boardroom. Key Takeaways Over half of the Fortune 500 companies vanish every 20 years because their leadership fails to anticipate macroeconomic technological cycles. The true opportunity in the $6.5 trillion AI boom lies not in single vendor products, but in the hardware, software, services, and telecom ecosystem surrounding them. Indirect tech sales are undergoing a structural shift toward direct cloud hyperscaler models driven heavily by Nvidia's core infrastructure client base. Modern business deals are won or lost months before the point of sale based on the average of 6.3 partners surrounding a customer’s environment. Over 51% of tech buyers are now millennials who prioritize software integration capabilities and digital marketplaces over traditional human sales interactions. Tech service economics are pivoting aggressively away from upfront margins toward point-based multi-partner funding across subscription cycles. If you're ready to lead through change, elevate your business, and achieve extraordinary outcomes through the power of partnership—this is your community. At Ultimate Partner® we want leaders like you to join us in the Ultimate Partner Experience – where transformation begins. Key Tags Nvidia AI buildout, $7 trillion AI opportunity, cloud ecosystem decade, Microsoft vs AWS growth, multi-partner cloud deals, digital marketplace migration, millennial B2B buyers, B2B tech subscription economics, tokenized micro consumption, tech services wallet share, hybrid cloud infrastructure, 28 customer moments, IT services industry growth, telecom spend breakdown, channel chief strategy, managed service providers MSP, global systems integrators GSI, software integration first, point-based vendor incentives, automated co-selling workflows Transcript JAY McBAIN AUDIO PODCAST [00:00:00] Jay McBain: So to go back to that story about the 53% of companies who are gonna fail, one of us is gonna be asked to write the book, but chapter one is always you Blame the CEO. [00:00:13] Vince Menzione: We just came back from Ultimate Partner live in Bellevue, Washington, where we hosted incredible leaders for two amazing days. Come join us for this next session where we explore the tectonic shifts we’ve all been seeing. With that, I am incredibly blessed to invite a friend of mine to the stage. I have a quick little side note, like I found an old LinkedIn post from this gentleman from like many years ago, like 20 years ago. [00:00:39] Vince Menzione: And I wasn’t really that nice to you on that LinkedIn post. Like, oh, like this is before Jay became the Jay, that we all know Jay to be j. But he was in the space and I was at Microsoft doing something and he reached out about something. It was kind of rude, Jay. I was like, oh my gosh. I can’t believe. But Jay has been a great friend. [00:00:54] Vince Menzione: When we started the podcast back up, uh, during COVID we started doing podcasts together. When we moved to the studio, Jay was the first person in the studio. He’s always got a spot, uh, at our events. He’s s Spot Art, and, and he’s a great friend and supporter of Ultimate Partner Jay McBain. For those of you who don’t know him, Jay, welcome. [00:01:13] Vince Menzione: Thank you, sir. [00:01:22] Jay McBain: 31 days ago, we landed Artemis two. The furthest humans have ever been away from the planet Earth 57 years ago. We landed on the moon in the 56 years. Between those two moments, the tech industry has been the fastest growing industry in the world. Every single year we moved from the space race to the technology race, and we’re just getting started. [00:01:46] Jay McBain: If you’re old enough, you’ll recognize the mainframe and mini era for 20 years. You’ll recognize a young disheveled Bill Gates showing up in Boca Raton, Florida for, uh, August the 12th, 1981 launch, where Bill thought that every one of us would’ve a PC in our home, and IBM thought they were gonna sell 10,000 of them to hobbyists. [00:02:12] Jay McBain: 1999, a small startup from an executive who just left Oracle in San Francisco named Mark Benioff. A couple of years later, Jeff Bezos went into a boardroom and said, listen, we’ve spent a lot of money building infrastructure to our busiest day, Christmas, black Friday. You’re telling me this stuff sits idle 10 or 20% for the rest of the year. [00:02:35] Jay McBain: Why don’t we rent that out to others? Got laughed outta that boardroom and then got made of fun of on magazine covers. Maybe you should just tend the store, let the adults talk about technology. In March of 2023, our neighbors, our friends, our family saw DeepFakes. They saw poetry, they saw music, and they came to us as tech people and said, did we just light up Skynet? [00:03:03] Jay McBain: Now every one of these 20 year eras, this is the Taylor Swift version of our industry. Every single one of these eras triggers the fastest growing product in history. Today it’s actually Chacha bt first to a billion users. It triggers a new, richest person in the world, bill Gates, to Jeff Bezos. Now, Elon Musk is the first to sign a trillion dollar pay package, and it’s not for car. [00:03:27] Jay McBain: It’s not for cars. It also triggers a most valuable company in the world change. And today that’s nvidia. These are monumental changes in our industry and they’re monumental changes in partnering every single time. And it also links to our customers. If you take a 20 year view of business, one era, and, and think about the AI era, you know, at the start of it here, if you’re to grab the Fortune 500 magazine from 20 years ago and start to flip through it, 53% of the companies in there no longer exist. [00:04:06] Jay McBain: Every 20 year cycle, we lose over half of the biggest companies in the world. These are the companies that have very deep pockets to buy their way outta problems. If you’re not in the Fortune 571% of tech companies don’t make it 10 years. These are the changes that cost industries. There are changes that cost really big companies and the decisions we make, the trends we’re in right now, in 2026 will be written about in the future. [00:04:39] Jay McBain: This new era, a lot of big numbers being thrown around. Vince’s best friend talk about a six and a half trillion dollar AI opportunity, but it’s not Microsoft’s tam. Microsoft is chasing about a trillion dollars of this. And the ecosystem, the hardware, the software, the services, the telecom is gonna make up the rest. [00:05:04] Jay McBain: It is an ecosystem. Every time these big numbers are thrown, the word ecosystem is always thrown around it. Not to be outdone, Sam Altman’s talking about a $7 trillion build out. The world economy this year, the world GDP will be 126. These are material numbers to world GDP, but even better, they’re both larger than our entire industry is today. [00:05:27] Jay McBain: So what took 56 years of the fastest growing industry this year will be $6.07 trillion. Big numbers, but it’s easier to think about it in terms of a dollar that our customers spend in that dollar. They’re gonna spend 25 cents on hardware. They’re gonna spend 25 cents on software. So for anyone that read the memo 15 years ago, that software’s gonna eat the world, there’s still a dollar a hardware to run every dollar of that software. [00:05:57] Jay McBain: And whether you’re thinking humanoid robots or whichever future you’re envisioning, there’s going to be a dollar of hardware to run every dollar of software for the next 20 years. There’s over 25 cents now in IT services, and in many cases, these services are growing faster than the product categories and just under 25 cents in telecom, that’s how it breaks out today. [00:06:19] Jay McBain: And this industry, which took 56 years to get to this point, is gonna double in size in the next three to five years. We already have two and a half trillion of that seven raised and being spent. Part of the reason Nvidia is the most valuable company in the world. Now our industry, uh, you talk about ultimate partnerships. [00:06:40] Jay McBain: Our industry traditionally, and world trade by the way, is 75% indirect. The dealerships, the agencies, the brokers, the resellers, the retailers, the franchisees, the gas stations, the grocery stores, the pharmacies, all 27 industries sell indirect. You gotta think back the last time you bought something direct. [00:07:01] Jay McBain: Well, I bought a Dell from that dude in the nineties. Cool. Well, Dell Technologies is now 60% indirect. Well, I bought insurance. Direct is 15 minutes. Could save me 15%. Well, Geico last year sold more insurance through agencies and brokers than they did direct. This is the world now. We used to be 75% indirect four years ago. [00:07:26] Jay McBain: Then it went to 73.2, then it went to 70.1 and it then it went to 66.7. By the way, marketplace is in these numbers indirect. It’s not marketplace causing this change. It’s one company, Nvidia. Nvidia has seven customers. The magnificent seven, uh, half of them are in the room right now that every morning we wake up to a hundred billion dollars press release about this $7 trillion buildout. [00:07:56] Jay McBain: What’s interesting is indirect sales in our industry is growing by revenue. It increases every year, just not at the pace that this AI build out is happening direct with seven companies. But the reason we’re all here, and I think the core reason that Vince is building this community is this, you know, Microsoft forever has measured and been very vocal. [00:08:21] Jay McBain: About 96% of their deals have partners in them. Kind of who cares, who collects the money. We care about the moments, the 28 moments before the customer makes a purchase. We care about every 30 days forever, because two thirds of our industry, over $4 trillion now is subscription consumption based. Winning a customer today is only winning the first 30 days. [00:08:46] Jay McBain: We care about this cycle. We care about who surrounds our customer. So six years ago, I stood on a big stage and said, you know, we went through a decade of sales. You know, in 1999, you thought you were born to be a salesperson. You’re managing your territory with your gut. Well, a few years later, you were introduced to the science of selling. [00:09:07] Jay McBain: You know, 10 years later you thought as a marketer, you sit around a cocktail party joking with your friends, 50% of my marketing dollars are wasted. I just don’t know which 50%. Really funny. In 2009 until every 58-year-old CMO got replaced by a 38-year-old growth hacker. Coming in with Marketo and Eloqua and Pardot and HubSpot, and 15,505 as of yesterday, MarTech and iTech tools, ninjas in marketing, they wouldn’t let a nickel go through without measuring. [00:09:43] Jay McBain: Now we understand 96% of deals and partners that surround it. No deal is gonna be won or lost in this era without partnering effectively. So we had to have this decade of the ecosystem. One of the ways we’re tracking is by outsiders. You know, Salesforce every year publishes the state of sales and they’ve got, you know, the number one CRM in the world. [00:10:05] Jay McBain: So they get to go talk to all the CROs, all the salespeople in the world. And as of this year, a couple months ago, 94% of every salesperson in every industry in the world uses partners every single day. You wanna see what this number was six years ago. Also, 89% of salespeople around the world don’t think they’re going to club this year without partners. [00:10:29] Jay McBain: So this is a big moment for us, halfway through the decade ecosystem, but we’re only halfway through. We’re starting to understand now at a more granular level. What partnering means. It’s not theory, it’s not flywheels. It’s not really cute. McKinsey slides that we keep showing to our board saying how important partnering is. [00:10:51] Jay McBain: We’re trying to get to the very specific level of the 6.3 partners on average that surround the deal and what they’re doing. How their business model works, and that’s average if I’m working on a public sector deal. I was at a Red Hat conference yesterday talking sovereignty. If I’m in an enterprise or a large public sector deal, it’s north of 10 partners in the deal. [00:11:15] Jay McBain: So we’re starting to understand what used to be this, this, you know, you’ve been the fastest growing industry for 56 straight years. Every single professional services person in every industry has come in to join the fund. Over 90% of accountants are tech services firms. Over 90% of marketing agencies are tech services agencies. [00:11:36] Jay McBain: All of this 250,000 software companies, a million emerging comp tech companies, the half a million VAR that have been in that traditional channel. The managed service providers, all of these 20 different partner types, millions of companies, tens of millions of people competing for 6.3 spots. Around the customer. [00:11:58] Jay McBain: That’s it. Luckily, there’s 141 million global customers to compete for. There’s, there’s some open slots that you can go find, and that’s the point. Our industry never had our own Fortune 500. We always talk to, you know, these partners and GSIs are doing this and SI are doing that. And we never really had a view of capability and capacity or what our own TAM was inside of that partnering. [00:12:25] Jay McBain: And so we set out and we would’ve loved, you know, chat GPT or Gemini or Claude or any of those tools to do this. But there’s one problem in partnering with AI is that it doesn’t know one partner from the next. There’s a big digital sameness problem in our industry that every single partner, whether it’s Larry in the White van or Accenture, with 786,000 employees all say they do all things to all people all the time. [00:12:53] Jay McBain: 98% of them, 99% of them are private companies that don’t share their p and l. You can’t go into Microsoft’s LinkedIn system and find out how many employees, ’cause it’s a block system, it AI can’t see into it. So it just sees, and it’s a great pattern matching. Google, SEO can’t figure out who’s who, nor today can the large language models. [00:13:14] Jay McBain: ’cause all the things they’re trying to match, the transformers are trying to match. It all looks the same. Every tweet, every ebook, every website, every digital history looks the same. So this took us thousands of people hours across two years to do, to dig into every p and l to dig into every dollar of what they’re doing. [00:13:33] Jay McBain: But what was interesting is only a thousand partners in our industry do two thirds of all tech services. When you get into enterprise, it goes up to 80 to 90%. The partners in the middle, in Blue do more tech services. The 30 of them than the 970 partners in white on the outside, the 970 partners in White do more tech services than the next million combined. [00:14:03] Jay McBain: This is our industry in a nutshell. Every time we talk to a a vendor, every time we talk to a partner, every time we talk to a distributor, we’re now talking names, faces, and places. You you wanna talk sovereignty. Yesterday in Atlanta, 90% of sovereign conversations in public sector in the globe is handled by these companies here. [00:14:26] Jay McBain: Forget about how much you do with these partners today. You wanna chase the next column, which is the wallet share. And I was a channel chief for 17 years. I get the weekly report and I see a million dollar partner, another million dollar partner, sorted top to bottom. You don’t know which partners which, which of those million dollar partners is doing 1.2 million in your category. [00:14:46] Jay McBain: They deserve a baseball cap and a front row seat at your event as an MVP. The next partner right next to them is doing 10 million in your category. They’re only doing a million with you. ’cause customers are pulling them into it. Nine times outta 10. They’re leading with your competitor. So I don’t want that list anymore. [00:15:03] Jay McBain: I want the new list, which is showing me those $9 million opportunities. And I as a board member, as A CEO, as a CFO, as a CRO, I wanna see this list. And then I want to talk people, processes, programs, technology. What are we gonna do to go get our fair share of that 9 million? Where’s our lowest hanging fruit? [00:15:24] Jay McBain: How do we double our pipeline? How do we double the size of our company in three years? It’s all right here. Let’s have very specific conversations and move away from flywheels and move around from force multipliers and and things like that in partnering. Let’s figure out how this partner community is surrounded. [00:15:45] Jay McBain: What do 10 million people who have to be smart in front of their customers every single day, what do they read? Where do they go and who do they follow? It’s the law of a few. This is the old Malcolm Gladwell of tipping point 10 million people in the broader channel. A hundred percent of our TAM comes down to only a thousand watering holes. [00:16:08] Jay McBain: 12% of that entire audience. Doesn’t sound like a lot, but it’s over A million. People love podcasts. Number one way they learn the Joe Rogan effect. In our industry, there’s 121 podcasts. These are all public lists. You can go get on my LinkedIn newsletter on canals, oia. But there’s 121 podcasts that drive him forward. [00:16:28] Jay McBain: Really high up on that list, actually number one on the list is ultimate partner, Vince. That’s how I met. ’cause I asked people, 10 million people, you love this. You walk your dog, you drive to work, you listen to podcasts. I’m not the biggest podcast fan. It’s not number one on my list, but it’s number one on theirs. [00:16:44] Jay McBain: They say, you know, you gotta meet this guy, Vince. It’s unbelievable how great these podcasts are. They’re ultimate. [00:16:54] Jay McBain: Then I talked to Vince and said, but Vince, you know, 35% of your community, the 10 million people love to come to events like this one. The hallway conversations, the hotel lobby bar last night. This is what we love to do, especially post pandemic. It’s the number one way we learn. We learn from our peers, we learn from those around us, and, and the learn from the conversations we have here. [00:17:17] Jay McBain: We always remember these moments, you know, years and years later. There’s 352 choices. I’m going to five of them this week in five different cities. It’s a lot of coverage, but again, it’s a tighter li list of how people work. The magazine lists 106 of them associations like Conter. Now the GTIA peer groups, there’s 15 different spheres of influence, but only a thousand places. [00:17:43] Jay McBain: I could walk you through billionaire, after billionaire, after billionaire in this industry and show you how they did this. How did Arne Bellini at ConnectWise? How did Austin McCord at Datto, how did Nerdio become a unicorn? How did threat locker and huntress move away from 6,500 cyber companies and become unicorns over and over and over again? [00:18:05] Jay McBain: It’s only one slide. Unicorns and billionaires are made here, and a lot of people don’t get it. So walking away from Bellevue, a thousand partners, top down, a thousand watering holes, bottoms up. You’ve covered a hundred percent of your tam. You do it better than 10% of your competitor, 10% better than your competitors. [00:18:27] Jay McBain: You win. You carry that on your resume into the next company. You get a bigger job at a bigger pay scale. Let’s just walk through some examples. Cyber 91.7% of it goes through the channel. Huge channel audience. You know, if you’re in MarTech, it’s only 10%, but this one happens to be all channel, but that’s not the story. [00:18:48] Jay McBain: For every dollar that the 6,500 cyber companies are trying to close, there’s $2 in services. Plot twist, the products are grown at 11, the services are grown at 12.6. Your partners are growing faster than you are, and they will continue to for the next, at least five years, probably 10. So when I’m here, five years from now, you’ll hear in me talk about a three to one split in cyber and then a four to one split in cyber. [00:19:18] Jay McBain: Now, when we’re in Miami a couple days ago is CrowdStrike, they’re talking about a $7 and 5 cent multiplier, chasing that two to one up higher. You look at managed services. Here’s a fun story. Managed services. 82% of customers who are man, uh, outsourcing more this year than last year. 650 billion in size. [00:19:38] Jay McBain: This is bigger than the entire SaaS industry. Salesforce, ServiceNow, Workday, Marketo, NetSuite, HubSpot, 250,000. Others. This is bigger. It’s also bigger than all the Hyperscalers combined, not just AWS, Microsoft and Google, but Alibaba and Oracle and everybody down the list. This is a massive market also growing at double digits. [00:19:59] Jay McBain: So these are some big things and obviously we’re watching, you know, week in and week out, quarter in, quarter out, the Battle of Software and Battle of the Hyperscalers and things like that, and who’s growing at what pace and, and how partnering is connecting to all of this. You know, we watched a moment really early in the pandemic where Microsoft started growing faster than AWS and they haven’t stopped since 26 straight quarters. [00:20:27] Jay McBain: And you ask customers and say, you know, does Microsoft have a better product? And in most cases they say no. You know, AWS had a five year head start. Well, did they have a better price? Well, no, actually most cases Microsoft’s more expensive. Well, did did they have better promotion? Was their Super Bowl ad better? [00:20:44] Jay McBain: No, they’re both kind of crap. So you kind of ask the questions of what’s the only difference that could create growth above the leader in the market? Well, it’s place. More of the 6.3 partners are walking into those keyboard room meetings and drawing clouds up on the wall and labeling the Microsoft than they are AWS. [00:21:03] Jay McBain: Very simple. It’s never been about product. The best product in our industry has never won. And now the best way forward is that partnering moment, and this is the moment. So to go back to that story about the 53% of companies who are gonna fail, one of us is gonna be asked to write the book. And it could be the book like Kodak, they invented the product that ended up killing them. [00:21:26] Jay McBain: And it’s a woe is me story, but chapter one is always you blame the CEO. How could they not see those trends happening in 2026? How could they, you know, were they blind? Were they stuck in their own, you know, innovation chamber? Innovator’s dilemma, were they stuck in their own boardrooms? Why couldn’t they see? [00:21:46] Jay McBain: Well, chapter two, you, you blame the board. They have fiduciary responsibility, outsider view, and how could they not see it? But really, this is the future right here. If you take this slide and apply it 10 or 20 years from now to every failure and every success, these are the chapters of the book. Your buyer is now a millennial. [00:22:05] Jay McBain: As of last year, the 51% of our market is bought by people born after 1982. Different psychology, different behavior, different journey, different criteria, their integration. First buyers. The buy a product, 80% as good as the next one. If it works better in their environment. 94% of people won’t buy a car unless it has CarPlay or Android Auto. [00:22:26] Jay McBain: New Buyer. You have to be more integrated than your competitors. That’s a partnering story. The 6.3 partners. If you heard cyber, you need some great channel partnerships, but you need the other 5.3 partners as well, the consultants, the advisors, the designers, the architects, the implementers, the integrators, the manner service, all of the other partners. [00:22:44] Jay McBain: You need to know more of them than your competitors do, and have them label clouds with your name in them. You need better alliances. Even if you compete, you only compete in the morning. You’re best friends by the afternoon. You have to be tight with the hyperscalers, tight, with the big SaaS platforms, tight with cyber, tight with distribution, there are layers, seven layers to every deal. [00:23:04] Jay McBain: You gotta be tight in and have better alliances than your competitors. And then it all comes to the 28 moments, which I’m gonna end on, but the go to market of all of this, the co-selling, co-marketing, co-innovation, co-development, co keeping. This is it. Your product has to be good enough that somebody’s gonna renew it. [00:23:21] Jay McBain: Your Super Bowl has to be, you know, ad has to be good enough that people don’t, you know, shame you on social media. Your pricing has to be somewhere in a country mile of the bell curve of what the customer wants to pay. But successor failure is just here and platforms are synonymous with partnering. [00:23:40] Jay McBain: It’s our role now in the decade of the ecosystem to drive our companies forward. Marketplace. It’s probably the most predict, you know, great prediction we ever made. You know, growing at 82% compounded, it’s hard to predict ’cause it doubles almost every year. We were almost exact to the decimal point. Five years later now till 2030, we’re watching a second story, which is more interesting. [00:24:02] Jay McBain: If 96% of all deals have partners inside of them and there’s private offers and multi-partner offers and distributor sellers record all these funding mechanisms or services as a product. As of last week, over 50% of all deals in marketplaces now have partner funding. It means that while money changes hands differently, the respect and the recognition of what partners do is in the deal. [00:24:26] Jay McBain: We think that’s going to 59, but at some point, that’s gonna have to hit 96. ’cause to run the best programs, whether it’s an indirect sale, whether it’s a direct sale, whether it’s a marketplace deal, it doesn’t matter how money changes hands. What matters is we recognize the 6.3 partners. They’re not only making the deal happen bigger and faster, but renewing and enriching that every 30 days forever. [00:24:48] Jay McBain: When we watch, you know, billion dollar clubs and when we read all the press releases and all the hubbub about how fast this is growing and who, which companies are behind all this. When I’m quoted in some of these press releases, it’s because of this. You know, CrowdStrike, you know, brags are a billion dollars in a single year, but inside of that, they’re showing that 91% growth in marketplaces, which is pretty phenomenal for any company to almost double in size every single year. [00:25:17] Jay McBain: What’s more phenomenal is they’re growing the channel piece of it, 3548%. That green part of it is growing. Companies that understand platform and have people and processes and programs and technology to do it are winning. And they’re getting recognition and partners are starting to join the Billion Dollar Club who don’t sell a product, but are also winning at Extreme Scale. [00:25:44] Jay McBain: So talk about those partner 1000 and who are leaning in to win at this level. As well as everything changes, traditional billing moved into subscription models, moved into consumption models. Now we’re being tokenized to death multi it’s, it’s in this mode of micro consumption. There’s no chance there was little chance in subscription consumption that would be resold. [00:26:09] Jay McBain: You don’t buy Netflix from the cable guy in the white van. There’s zero chance when you’re buying tokens at a buck a piece that that’s going through any indirect sale. This continues to grow. Now the tectonic shifts is what happens when money changes hands differently. These old programs that we used to all write hundreds of different boxes, we checked every day on deal reg and trainings and all the other things are changing. [00:26:35] Jay McBain: To this, you’ll get these slides, by the way, in high res, inside of this now is the customer. For the first time ever, 45 years later, we have the customer in the middle of what we do, the 28 moments in green before they buy the seven layer stack and the partners inside it. The implementation. The integration, the managed services in a cycle that never ends, and two thirds of our industry. [00:26:55] Jay McBain: With the customer in the middle, we can now move money around to the different moments. It’s not all landing in front or backend margins or market development funds or new customer bonuses or spiffs. It’s landing where it needs to land. Over 400 companies now, pretty much led by Microsoft 400 companies are in a point system right now and 400 more. [00:27:18] Jay McBain: We’re working kind of behind the scenes to get that announced in the next 12 months. This is a total changeover in terms of how economics work and partners are yelling over half of us. I don’t care. Don’t call me a VAR anymore. Don’t call me an MSP. Don’t call me a regional system integrator. I do the consulting over half the time. [00:27:36] Jay McBain: I do the design, I do the implementations, I do the managed services, and 44% of us are vibe coding. On weekends. We’re not happy. Just on the services side. We wanna join the seven layer tech stack as well. These are partners growing faster than their vendors by understanding this cycle and where to show up and where the money is in ai. [00:27:56] Jay McBain: And the number one thing they’re asking for is not more leads, which they did for 45 years. The number one thing is now recognized for what I do. I’ve never just been a cash register. We’re completely now past this idea of a channel being a channel of distribution, and now a channel being this platform for the future. [00:28:16] Jay McBain: As we lay that on top of ai, the first couple of years of AI has really been consumer driven. The 95% failure rate that MIT reported last year is now 70%. That’s the failure to get from proof of concept to production. That 70 will be 50 by the summer we’re moving now in business, the maturity rates are going up at the end customer and in 88% of cases, that’s because of the channel. [00:28:43] Jay McBain: They’re working with partners. They’re not vibe coding themselves and working in little skunkwork groups. They’re working with partners to make it happen, and it now becomes the partner’s number one growth opportunity. I can grow at 11 or 12% in cyber every year. Compounded I can grow in 10% in managed services. [00:29:03] Jay McBain: You know, those are great double digit growth ’cause my customers are growing at 2.7% and I can go four x my customer, but I can go 10 x my customer if I have the right services built around ai. And this compounded growth rate and that big number in 2 20 32, 267 is what’s got those top 1000 partners obsessed. [00:29:25] Jay McBain: And your companies are leading with ai. Now you need to connect to those AI services. You need to get partners on this scale of growth. And they will be adding your name inside every cloud. They write on every whiteboard, but 82% of partners around the world, you know, we survey 25,000 of them aren’t ready, and they’re blaming vendors for not being ready, and they’re telling them exactly the workshops and the training that they need to get ready for this cycle. [00:29:53] Jay McBain: 82% of our entire partner, tens of millions of people, aren’t ready to grow at 35% and they need our help. Last thing I’ll say about AI is it’s the first time from client server to cloud, edge to cloud that it’s been segment driven. SMB alone has one, you know, six different segments, one to nine, 10 to 24, 25 to 49, et cetera. [00:30:18] Jay McBain: Mid-market into enterprise. No one that runs a restaurant is calling Jensen to buy a GPU to put next to the stove. No one’s calling Sam or Dario or anyone at Anthropic or OpenAI directly. They’re waiting. If you run a restaurant with all the people running around with tablets, you’ve invested in toast or square or clover or one of the platforms to run your business. [00:30:41] Jay McBain: A hundred different things. And you’re gonna wait for toast to work with a hyperscaler and build out the capabilities genetically. So when they see a spike in Uber Eats orders, they automatically place a food order and automatically change the staffing to deliver on it. That’s what the restaurant’s waiting for, and there’s no one calling and having a big a agent conversation. [00:31:03] Jay McBain: But even if you go into hundreds of people in medium sized business, every one of the vice presidents have their tech stack already built. I talked about the marketing person already, but the HR leader has one, and everybody’s got their seven layer stack. They’re not calling to buy a GPU and they’re not calling to, you know, bring in open AI directly or, or anthropic. [00:31:22] Jay McBain: They’re waiting for the platform they built to integrate together ag agenta capabilities. Everybody’s in wait mode up until enterprise and public, large public sector. So we are looking at this market and at 90% of that AI market is run by those thousand companies, and the rest of the millions of partners are helping in terms of how these businesses are gonna change at that level. [00:31:46] Jay McBain: Here’s where I end. You know, the 28 moments used to be a theory. It used to be a flywheel. How do we buy a car? [00:31:55] Vince Menzione: Well, we Google it, [00:31:57] Jay McBain: 81% of us now, 94% of us use large language models. We find out that there’s 365 brands of car. I’d have to test drive one every day of the year to get through them all. So we start narrowing these things down. [00:32:09] Jay McBain: We configure it. We put our rims on it, we color it. We download the invoice price. We download the backend rebates this month, whether I buy it in May or June, we find out what 5,000 people paid for our exact car within 50 miles of us. And then we don’t wanna go to the dealer because we know more than the salesperson, the manager ever will. [00:32:26] Jay McBain: We know what we’re gonna pay within, you know, dollars or cents. Just carvana the car. Hand me the keys. Let’s just forget the whole eight hour back and forth. I’ll get you a deal thing. I’m smarter than you in technology. Our customers are smarter than us, smarter than salespeople. That’s why 75% of millennials don’t wanna talk to a salesperson. [00:32:48] Jay McBain: They want to end digitally, and by the way, they’re not gonna send a fax after 28 digital moments. They’re gonna end on a digital marketplace. This is all demographics. It’s not hard to see where it’s going, but we’re getting into names, faces, places again. What if every dollar of your tam, the board, the CEO, runs around with their big multi-billion dollar number, they’re chasing? [00:33:09] Jay McBain: What if every single deal looks the exact same? This is a deal with AstraZeneca, A real deal, real customer spending millions of dollars. We know it starts in October, it ends in April. It’s a six month cycle. We see what they read, the MQ ls at the beginning. We see the sales demo moments. We see ISV, but we’ve never had the light blue boxes. [00:33:30] Jay McBain: What if we as a team could overlay the 6.3 partners in this deal? And when you find out a couple things. Here’s where I end. In December, five deals were one, three of them by NTT. The person at NTT probably coaches AstraZeneca’s, you know, kids’ soccer team. They probably have a cottage together at the lake. [00:33:50] Jay McBain: For the last 20 years, if the person at NTT worked at Deloitte, Deloitte would’ve run this deal. But Software One and Yash are both there, so we understand that when they were drawing clouds up on the wall in the boardroom in December, this deal was won and lost there. It was not won and lost at the point of sale. [00:34:09] Jay McBain: So what if you knew more about this and could see every dollar in your tam? You had an early warning system that this was happening. Two things jump out at this now that we’re in Bellevue. AWS was touched twice in this deal, directly in the marketing cycle and the sales cycle. AWS lost this deal. Here’s an example of Microsoft winning a deal with Microsoft never being touched. [00:34:34] Jay McBain: For some reason, NTT who won, who won AWS’s partner of the year a couple years ago led with Microsoft, so did Software one, Microsoft’s biggest reseller in Europe, and as did Yash, they all led with Microsoft and without Microsoft, knowing Microsoft took a multimillion dollar deal away from their competitors by winning in December. [00:34:53] Jay McBain: That’s one. Second. These partners didn’t just show up other than soccer and cottages. They didn’t show up in December. It went closed one in their CRM system. Back in the summer, August, September, we already knew AstraZeneca was in market, spending millions of dollars. We didn’t need them to read an ebook or go to an event to find that out. [00:35:17] Jay McBain: We knew it because it was closed one. They’re spending hundreds of thousands of dollars times five in December to know what to do at the end. This is an early warning system that’s better than any MQL, better than any SQL. And if you could give your company these level of view into their pipeline with an early warning system that I can work with those partners for months before they ever show up at the customer’s boardroom. [00:35:44] Jay McBain: This is it. Talk about 47% winners. This takes you from not only surviving the AI era to being a top five platform winner. Thank you very much. [00:36:01] Vince Menzione: Until next time, we’ll see you in person. Hopefully at our next event.

Enterprise marketing teams struggle with AI implementation beyond basic automation. Patrick Brown, SVP of Global Marketing at Adobe, shares his perspective on scaling AI across complex B2B and B2C marketing operations. Brown discusses why AI excels at content summarization and synthesis but falls short on predictive forecasting, and outlines Adobe's three-pillar framework for integrating AI into experience delivery, measurement systems, and foundational marketing tools.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Text us your thoughts on the episode or the show!For years, the hard part of ops work was building the technology. Now the tech is getting easier while the people and process side is getting harder. So why are so many organizations still stuck debating AI instead of activating it?In this episode, host Michael Hartmann sits down with Andrea Tarrell, President of the Tech Services line at Trilliad and CEO of Sercante. Together, they discussed the human side of change in the AI world with speed, trust, risk tolerance, and the trade-offs GTM teams are making right now.In this episode:Why the technology got easier, but the people and process side got harderHow much of AI adoption is really a trust and change management problem, not a tech oneFear of job replacement vs. plain organizational inertiaAI may not replace your job, but someone using it well may outperform someone who refuses to adaptSolving the tension between "move faster with AI" and "watch out for the risks."What companies get wrong about risk management and tolerance for risk in the AI worldWhy old governance frameworks may not fit a world of fast experimentationAnd a lot more...Whether you lead an ops team or sit inside one, this is a timely conversation about innovation, speed, governance, and practical business reality.If you enjoyed this episode, subscribe, leave a review, and share it with someone in the ops community who would find it valuable.Episode Brought to You By MO Pros The #1 Community for Marketing Operations ProfessionalsSupport the show

Le retour d’expérience client a toujours existé dans la communication B2B. Mais il est resté systématiquement sous-exploité, faute d’un cadre et d’un dispositif adaptés pour le valoriser et le rendre vraiment exploitable. C’est précisément le constat qu’Éric Mattern a fait au terme de vingt-cinq ans de terrain dans la tech et la data. Sa réponse est une plateforme dédiée, Show Me The Rex, lancée officiellement fin mars 2026, dont l’ambition est de faire du REX un actif stratégique à part entière pour les acteurs de la tech, de la data et de l’intelligence artificielle. Voici donc le compte-rendu de mon entretien avec Éric Mattern, fondateur de Show Me The Rex (transparence : nous sommes partenaires de Show Me The Rex). Le retour d’expérience client (REX) est un outil stratégique en B2B Les décideurs sont tous à la recherche de retours d’expérience client nous explique Éric Mattern Avant même d’aborder la méthode, les données du marché confirment l’enjeu du retour d’expérience client en B2B. Dans un parcours d’achat B2B profondément digitalisé, la preuve concrète est devenue en effet le premier filtre des décideurs. Ce que les chiffres disent du retour d’expérience client (REX) Les chiffres ci-dessus traduisent une réalité que tout professionnel du B2B comprend de manière intuitve. Au moment où un décideur arrive en contact avec un commercial, il a déjà effectué l’essentiel de son évaluation. Ce qui a orienté son choix, ce sont les preuves qu’il a trouvées par ses recherches. Le REX (retour d’expérience client) est précisément l’un de ces leviers de conviction. Image réalisée avec Gelmini. Sources : Forrester Pulse Study, 2023, Gartner, B2B Buying Journey, 2024 et Content Marketing Institute, 2024. Retour d’expérience client : du terrain à la plateforme D’où vient ta conviction que le retour d’expérience mérite une plateforme entière ? J’ai travaillé pendant vingt-cinq ans sur tous les canaux de visibilité et de go-to-market dans les secteurs technologiques. Et j’ai constaté qu’un levier fort restait systématiquement sous-exploité : le REX. Ces retours d’expérience client ont toujours existé, mais ils n’ont jamais disposé du cadre ni du dispositif qui leur auraient permis d’être vraiment valorisés et exploitables. Or c’est précisément ce qu’attend le marché. Les décideurs veulent identifier des solutions, comprendre des méthodologies, appréhender des démarches concrètes. Le REX rassemble tout cela. En quoi le REX se distingue-t-il du livre blanc classique ? Le livre blanc apporte généralement une vision macro, dépersonnalisée et très orientée marketing. Le REX donne la parole aux praticiens : ceux qui ont mis en place des solutions, éprouvé des méthodologies et résolu des contraintes budgétaires ou politiques internes que les études ne racontent jamais. Les études se concentrent souvent sur les échecs en chiffres. Le REX montre comment une équipe a su contourner une difficulté, gérer un risque et résoudre sa problématique. C’est là que réside toute sa valeur. Le décideur B2B du 21e siècle, surtout en MarTech et en SalesTech, est littéralement noyé de messages et d’informations produits. Mais ce qu’il recherche sont des éléments tangibles. Et qui plus est, pas trop habillés afin qu’ils restent crédibles et percutants – image réalisée avec Midjourney. Les producteurs et les lecteurs de REX À qui s’adressent ces retours d’expérience, côté lecteur ? À tous les porteurs de projet dans une organisation. On pense évidemment aux équipes techniques et aux DSI, mais aussi aux directeurs de l’innovation et de la transformation. Ceux-ci ont besoin de se projeter et d’identifier des partenaires capables d’accompagner leur évolution. Toutes les directions métier sont concernées : finance, marketing, supply chain, RH. On peut même imaginer des investisseurs qui regardent un acteur à travers ses réalisations concrètes pour évaluer sa capacité réelle à aller sur le marché. Et côté producteur, qui sont vos clients principaux ? Sur le secteur tech, data et IA, on trouve aussi bien des éditeurs que des intégrateurs et des sociétés de conseil. Les ESN et intégrateurs sont naturellement très légitimes pour produire des REX. Ils sont au coeur de la mise en oeuvre et de la conduite du changement. Mais les éditeurs ont eux aussi un intérêt fort à valoriser les bénéfices concrets apportés par leurs solutions. C’est un potentiel important que nous accompagnons. La taille de l’entreprise a-t-elle une incidence sur les besoins ? Tous les acteurs y trouvent un intérêt, mais pour des raisons différentes. Les grands groupes ont souvent un problème de partage interne. Ils accumulent des REX sans disposer d’un cadre pour les référencer et les diffuser entre services et départements, avant même de les exposer à leurs futurs clients. Pour les acteurs plus petits, c’est avant tout un enjeu de visibilité et de crédibilité. Le REX démontre leur capacité à résoudre de vraies problématiques marché. Faire un choix de logiciel est rarement anodin, surtout en ces temps de sovereignty washing. Le décideur avisé se tournera donc vers ses pairs pour faciliter son choix. C’est à cela que sert un retour d’expérience client. Image réalisée avec Midjourney. Les bénéfices mesurables du Retour d’expérience client (REX) Peut-on espérer des bénéfices quantifiables, en termes de génération de leads par exemple ? Oui, clairement. Le marché attend des REX. Il est désormais impossible d’organiser un événement, une conférence ou un webinaire sans inviter un client qui vient témoigner de son projet : c’est ce qui attire les clients potentiels. Dans un contexte où l’IA évolue à un rythme soutenu, les décideurs ont besoin de se raccrocher à du concret. Ce concret accélère la transformation d’un prospect en client, parce qu’il lui apporte des garanties tangibles sur la mise en oeuvre et les bénéfices. C’est un vrai levier de visibilité et de conversion pour tout acteur de la tech, de la data et de l’IA. Et pour l’entreprise utilisatrice qui témoigne, quel est l’intérêt ? Les motivations sont multiples. Il y a d’abord une dimension personnelle. Celui qui vient témoigner renforce son positionnement d’expert, en interne comme en externe. Il y a aussi un enjeu d’image de marque et d’innovation. Montrer qu’une organisation se transforme, c’est attirer les talents. Quand une grande entreprise met en avant ses projets de transformation data ou IA, elle envoie un signal fort à des profils qui cherchent des environnements stimulants. La recette d’un bon REX Quels sont les ingrédients indispensables d’un REX réussi ? Il en faut trois. D’abord, un contexte bien décrit et incarné : la problématique métier du client doit être suffisamment précise pour que le lecteur s’y reconnaisse immédiatement. Ensuite, un fil narratif clair, qui parte du problème business jusqu’au résultat mesuré, en passant par le choix de la solution et toutes les étapes de mise en oeuvre. Enfin, des preuves tangibles : indicateurs, données sur les délais, taux d’adoption, gains qualitatifs. Et tout cela partagé par le client lui-même pour que la valeur soit authentique. Disposez-vous d’un modèle structuré pour produire ces REX ? Oui, la plateforme Show Me The Rex propose un template qui structure l’ensemble. On démarre toujours par les enjeux, la problématique et le contexte initial, Puis on aborde le choix de la solution et la démarche projet, Avant de conclure sur les gains obtenus. On inclut aussi systématiquement les bonnes pratiques et les points de vigilance. Un REX doit apporter de la valeur ajoutée réelle, et un projet n’est jamais sans embûches Les erreurs à éviter dans la création d’un Retour d’expérience client Quelles sont les erreurs les plus fréquentes dans la production d’un REX ? La première, c’est de transformer le REX en brochure commerciale : tout lisser, éliminer les tensions, les contraintes, les arbitrages. Un REX trop parfait n’est pas crédible. La deuxième erreur, c’est de verser dans le trop technique ou le trop produit, en listant des fonctionnalités plutôt qu’en racontant la démarche projet. Le troisième écueil, c’est l’anonymisation excessive. Si le client final est trop peu présent dans le témoignage, le REX perd l’essentiel de son intérêt. Il faut embarquer le client, pas le dissimuler. Par où commencer quand on n’a jamais fait de REX ? Je suis directeur marketing dans une entreprise tech. Par où commencer concrètement ? Je vous conseillerais de commencer par cartographier vos cinq à dix plus beaux projets clients récents, en identifiant pour chacun un angle business clair. Sur cette sélection, repérez un ou deux ambassadeurs prêts à témoigner et construisez avec eux un premier format simple : interview écrite, courte vidéo ou webinaire. Ensuite, impliquez très tôt les équipes commerciales, parce que le REX doit leur servir directement dans leur démarche et pour leurs rendez-vous. Une fois ces premières étapes franchies, industrialisez progressivement la démarche en vous appuyant sur un template structuré, comme celui que nous proposons sur Show Me The Rex. Le REX, un atout compétitif durable Éric Mattern a trouvé un angle simple et puissant : là où tout le monde produisait du contenu générique, il a misé sur la preuve concrète. Show Me The Rex arrive au bon moment, dans un marché saturé de promesses et avide de preuves concrètes. Pour les acteurs de la tech et de la data, la capacité à produire et diffuser des retours d’expérience solides est en train de devenir un facteur de différenciation à part entière. Les décideurs qui s’informent en autonomie, les comités d’achat qui comparent en ligne avant tout contact commercial, les talents qui choisissent leur employeur sur la foi de projets concrets… Tous cherchent la même chose. Une preuve que ça marche, racontée par ceux qui l’ont vécu. La plateforme est accessible sur showmetherex.com. À propos d’Éric Mattern Éric Mattern est entrepreneur dans l’univers de la tech et du digital B2B depuis plus de vingt-cinq ans. Après un parcours dans les fonctions commerciales et marketing au sein de plusieurs acteurs de la tech et de la data, il fonde Show Me The Rex, une plateforme dédiée à la production, la structuration et la diffusion de retours d’expérience sur les projets tech, data et IA. À propos de Show Me The Rex Show Me The Rex est une plateforme B2B dédiée à la valorisation des retours d’expérience dans les domaines de la tech, de la data et de l’intelligence artificielle. Elle s’adresse aussi bien aux producteurs de REX (éditeurs, intégrateurs, sociétés de conseil) qu’aux décideurs et porteurs de projet à la recherche de cas concrets pour guider leurs choix. The post Retour d’expérience client (REX) : un outil stratégique appeared first on Marketing and Innovation.

Episode 12 is the proof-of-concept episode. Nigel Maine walks through the live RAG installation built on 1.67 million words of salesXchange IP — 708 documents, 4,590 retrieval chunks, 768-dimension embeddings running on Vertex AI Vector Search in Google Cloud's European region. The knowledge base is in. The closed-loop GTM system is operational. Then he reads the Manifesto.The Manifesto is forty minutes of the most direct argument Nigel has ever made on camera. Seven movements. Forty years of B2B sales observation combined with a decade of systematic research. It names the failure, presents the data — from 14,106 MarTech products to 43% average quota attainment — and makes the case for Broadcast B2B Selling as the only model built around how B2B buyers have always behaved.If you have privately suspected your GTM function is structurally broken, this episode is the forensic examination you've been waiting for. Watch the full episode, then follow the link to the sX Course below.What this episode coversThe RAG installation: what was built, how it works, and why the temp-vs-colleague analogy is a functional description, not a metaphorThe corpus: 1.67 million words, 708 documents, 4,590 retrieval chunks explainedWhat a B2B RAG system means for institutional knowledge, content production, and sales readinessThe Agentic AI shift — MCP, AI agents, and what Y Combinator and a16z are saying right nowThe closed-loop GTM system: content scheduling, performance analytics, and self-improving outputThe Manifesto — Movement 1: Nothing Changed Except the Door (1952 to 2026)Movement 2: The Crime Scene — the tool explosion that produced nothingMovement 3: The truth about how B2B buyers actually behaveMovement 4: Broadcast B2B Selling — the only logical responseMovement 5: The sX Operating System — a six-module commercial infrastructureMovement 6: Why the timing has never been betterMovement 7: The call to arms — two choices, one structural argumentWho should watchB2B technology and SaaS CEOs, founders, and revenue leaders who are spending £190,000 to £1 million annually on SaaS with diminishing returns, watching sales teams miss quota, and getting ready to ask whether there is a different model. This episode gives you the evidence base and the alternative.Take the next stepDownload the GTM Reset, GTM Landscape, or GTM Architecture Audit PDFs at salesxchange.co.uk — or email nigel@salesxchange.co.uk to talk about what this looks like in your business.

REMIX: Album 4 Track 12 – Matt Tumminello, President at Target 10Hey Brand Nerds! We have a treat for you today! We have Matt Tumminello in the virtual building dropping jewels from both his career and personal experiences as a leader in the LGBTQ+ marketing space.Jolted to impactful and meaningful action after witnessing 9/11 as a New Yorker, Matt dove head first into the LGBTQ+ marketing space through the launching of his business Target 10. As they say, "they apply deep LGBTQ consumer insights and cultural intelligence to brand strategy, marketing and creative, demonstrating to LGBTQ consumers that your brand 'gets it and gets me.'"A few key takeaways from the episode:Be fearless. In work and in life. Be very careful with your comments from a business perspective, you may also be making a comment about that very human that's in front of you.There is beauty in duality  NOTES:Learn More About Target 10Stay Up-To-Date on All Things Brands, Beats, & Bytes on SocialInstagram | Twitter 

The MarTech landscape has exploded to thousands of tools, AI agents are rewriting the rules of automation, and most companies still haven't figured out how to get real value from the stack they already have. In this episode, guest host Tim Ahlenius sits down with Scott Brinker, "The Godfather of MarTech," Frans Riemersma of Martech Tribe, and Americaneagle.com's Tony Stehn and Harley Helmer. They unpack why over-buying tech silently kills marketing performance, why strategy and process have to come before technology decisions, and why consolidation may not save you the way you think. This podcast is brought to you by Americaneagle.com Studios. Follow this podcast wherever you listen to them! Connect with: Lessons for Tomorrow: Website // Twitter // Instagram // Facebook // YouTube Tim Ahlenius: LinkedIn Scott Brinker: LinkedIn Frans Riemersma: LinkedIn Tony Stehn: LinkedIn Harley Helmer: LinkedIn Resources: chiefmartec.com | martechtribe.com

Marketing leaders are being asked to drive more growth with less budget, fewer resources, tighter timelines, and more pressure from every direction while AI is being treated like the shortcut to replace entire marketing teams. But AI will not fix bad strategy, weak alignment, poor customer understanding, or broken marketing fundamentals. In part two of this master class conversation with Matt Hummel, CMO of Pipeline360, the focus moves into what it really takes to become the kind of CMO AI cannot replace. Not by chasing every new tool, adding more MarTech, or hiding behind automation, but by understanding the business as a whole, building trust across departments, speaking the language of revenue, and creating alignment between marketing, sales, product, leadership, and the customer. To lead marketing in a volatile market where expectations keep rising and the old playbook is no longer enough, you need to know how to: • Make sales an ally instead of your bitter rival • Build shared pipeline ownership across marketing and sales  • Communicate risk without becoming defensive • Connect marketing decisions to the larger goals of the business • Set clearer expectations with your team and leadership • Understand resource constraints without using them as excuses • Stay close to customers while leading strategy • Create momentum without pretending there is an easy button The best marketing leaders are not just managing campaigns, tools, reports, and dashboards. They are translating complexity into strategy the business can trust. The reminder is clear: AI will not fix bad strategy. More MarTech will not fix bad marketing. The CMO AI cannot replace is the one who understands the business, earns trust, aligns with sales, leads the team, knows the customer, and gets back to real marketing when everyone else is hiding behind tools. (P.S. If you haven't, listen to Ep. 149 for part one of this masterclass episode) Beyond The Episode Gems: Connect With Matt Hummel on LinkedIn Listen To Troy On Matt's Podcast, Pipeline Brew: The Evolving Role of CMOs & Community Building Visit Pipeline360 website to learn more about how they solve B2B marketers' biggest headaches Buy Troy's Book, Strategize Up: The Blueprint To Scale Your Business StrategizeUpBook.com Discover All Podcasts On The HubSpot Podcast Network Get Free HubSpot Marketing Tools To Help You Grow Your Business Grow Your Business Faster Using HubSpot's CRM Platform Support The Podcast & Connect With Troy:  Rate & Review iDigress: iDigress.fm/Reviews Follow Troy's Socials @FindTroy: LinkedIn, Instagram, Threads, TikTok Subscribe to Troy's YouTube Channel For Strategy Videos & See Masterclass Episodes Need Growth Strategy, A Keynote Speaker, Or Want To Sponsor The Podcast? Go To FindTroy.com  

Text us your thoughts on the episode or the show!Today, most teams aren't just struggling to build their AI strategies. The real struggle begins when they try to execute their strategies. In this episode of Ops Cast, host Michael Hartmann sits down with David York, Chief AI and Innovation Officer at Helix CXM, to get practical answers about what it really takes for GTM organizations to move from talking about AI to operationalizing it.David has spent years working at the intersection of marketing operations, RevOps, automation, and AI transformation. Together, he and Michael discovered an uncomfortable truth about how most teams are already overwhelmed by manual work, fragmented processes, shadow systems, and operational debt. Piling "figure out AI" on top of all that creates more chaos. In this conversation, you'll hear:Why the gap between AI strategy and implementation is so hard to closeWhat operational excellence actually looks like in practice, and why it has to come firstWhy mapping how work gets done today is the critical first step before introducing AIThe real difference between automation and "automation plus intelligence"How to identify low-risk, high-value AI use cases (like partially manual lead routing) versus harder onesThe hidden costs teams underestimate: tooling, LLM costs, maintenance, and human monitoringWhere human judgment is still absolutely requiredPractical advice on where to start if you're feeling overwhelmed by AI pressure right nowWhether you lead a scrappy SMB or a specialized team inside a large enterprise, this is a grounded discussion about the reality of AI in modern GTM, beyond the hype and the LinkedIn hot takes.David also published a new book this week, AI-Powered Growth: A 7-Step Adoption and Transformation Framework, which goes deeper into how Marketing Ops leaders can systematically prioritize and operationalize AI initiatives. Grab a copy here: https://www.amazon.com/AI-Powered-Growth-7-Step-Adoption-Transformation/dp/B0H2QCZG5M/Enjoy the episode!Episode Brought to You By MO Pros The #1 Community for Marketing Operations Professionals MarketingOps.com is curating the GTM Ops Track at Demand & Expand (May 19-20, San Francisco) - the premier B2B marketing event featuring 600+ practitioners sharing real solutions to real problems. Use code MOPS20 for 20% off tickets, or get 35-50% off as a MarketingOps.com member. Learn more at demandandexpand.com.Support the show

Scaling executive presence on LinkedIn requires more than organic posting. Adam Rich, founder of Thrillist and CEO of Known For, shares how he built authentic authority while growing from 600 email subscribers to 300 million monthly users. He discusses strategic post promotion to first-party audiences, balancing organic reach with paid amplification, and why frequency caps matter more than promotional tags when building executive credibility.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Scaling executive presence on LinkedIn requires more than organic posting. Adam Rich, founder of Thrillist and CEO of Known For, shares how he built authentic authority while growing from 600 email subscribers to 300 million monthly users. He discusses strategic post promotion to first-party audiences, balancing organic reach with paid amplification, and why frequency caps matter more than promotional tags when building executive credibility.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

What's the hidden tax your organization pays every time a creative asset moves from a design tool to a marketing platform, and how can you shorten the time to gain important insights about how your campaigns perform?Agility requires more than just speed. It demands that we eliminate the friction between our systems and processes so teams can move from concept to customer with minimal translation errors and maximum impact. It also means that we need to find the best ways to understand campaign performance without requiring everyone in marketing to be a data scientist.We're going to discuss:- the persistent gap between creative design and marketing execution- the value that AI-based capabilities can add to the understanding of analytics and performanceTo help me discuss this topic, I'd like to welcome Ose Amiegheme, Head of Email Product at Intuit Mailchimp. About Ose Amiegheme Ose Amiegheme is a product leader building the future of creation and growth tools.Today, he leads product for Intuit Mailchimp's Email and omnichannel campaigns creation experiences, shaping how small businesses create content, launch campaigns, and grow across channels.Previously, he led advertising products at TikTok supporting multi-billion-dollar revenue businesses and helped launch products spanning GenAI creative tooling, campaign optimization, and advertiser control systems.Before TikTok, Ose spent four years at Adobe helping build Adobe Express, where he worked across editor experiences, AI-assisted creation, and products used by millions of creators globally. His career has followed a consistent theme of building products that empower creators and marketers to tell their story in a way that feels genuine but also standout.Outside of work, Ose is a huge soccer fan and he is excited for the upcoming soccer World Cup. Ose Amiegheme on LinkedIn: https://www.linkedin.com/in/ose-amiegheme/ / https://www.linkedin.com/in/jeremyejones/ ---------- Resources ---------- Intuit Mailchimp: https://mailchimp.com/ The Agile Brand podcast is brought to you by TEKsystems. Learn more here: https://aglbrnd.co/r/2868abd8085a9703 Drive your customers to new horizons at the premier retail event of the year for Retail and Brand marketers. Learn more at CRMC 2026, June 1-3. https://aglbrnd.co/r/d15ec37a537c0d74 We're proud to be a media partner for #MAICON26 - Oct. 13-15! Learn how AI can power your marketing and business and help you grow smarter. Use code AGILE150 to save! https://aglbrnd.co/r/7fe458ced0f04658Reach your customers with Reddit. Spend $500 in ad spend, get $500 back in ad credit! Learn more: https://advertalize.com/r/491818c79fb1873fDon't miss We Make Future - the International Festival of Innovation in AI, Tech, and Digital Marketing, June 24-26 in Bologna. Learn more: https://aglbrnd.co/r/c80991afff416bb2The most influential minds in software, AI, and engineering leadership will be at WeAreDevelopers World Congress North America, September 23-25 in San Jose. Learn more: https://aglbrnd.co/r/60a7299222a7bcf1 Enjoyed the show? Tell us more at and give us a rating so others can find the show at: https://aglbrnd.co/r/faaed112fc9887f3 Connect with Greg on LinkedIn: https://www.linkedin.com/in/gregkihlstromDon't miss a thing: get the latest episodes, sign up for our newsletter and more: https://aglbrnd.co/r/35ded3ccfb6716ba Check out The Agile Brand Guide website with articles, insights, and Martechipedia, the wiki for marketing technology: https://www.agilebrandguide.com The Agile Brand is produced by Missing Link—a Latina-owned strategy-driven, creatively fueled production co-op. From ideation to creation, they craft human connections through intelligent, engaging and informative content. https://www.missinglink.company Hosted on Acast. See acast.com/privacy for more information.

Most executives waste time posting on LinkedIn at arbitrary frequencies instead of focusing on quality content. Adam Rich, CEO of Known For and founder of Thrillist, explains why consistency should align with your actual pace of insights rather than forced daily posting schedules. Rich advocates for publishing less frequently but with higher quality, emphasizing that professional networks require thoughtful, crafted messages rather than spontaneous posts that work on consumer platforms like Instagram.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Most executives waste time posting on LinkedIn at arbitrary frequencies instead of focusing on quality content. Adam Rich, CEO of Known For and founder of Thrillist, explains why consistency should align with your actual pace of insights rather than forced daily posting schedules. Rich advocates for publishing less frequently but with higher quality, emphasizing that professional networks require thoughtful, crafted messages rather than spontaneous posts that work on consumer platforms like Instagram.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

LinkedIn's algorithm penalizes posts with external links, limiting organic reach. Adam Rich, CEO of Known For and founder of Thrillist, discusses strategies for maximizing professional network activation on the platform. He covers the trade-offs between boosting posts versus relying on organic reach, optimal frequency caps for promoted content, and targeting first-party audiences to amplify executive thought leadership without appearing overly promotional.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

LinkedIn's algorithm penalizes posts with external links, limiting organic reach. Adam Rich, CEO of Known For and founder of Thrillist, discusses strategies for maximizing professional network activation on the platform. He covers the trade-offs between boosting posts versus relying on organic reach, optimal frequency caps for promoted content, and targeting first-party audiences to amplify executive thought leadership without appearing overly promotional.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Album 8 Track 16: Lead with Guts, Accelerate Growth w/Bob KrautHow did a $5 million marketing stunt turn into one of the top 5 marketing ideas of the last 50 years? In this episode of Brands, Beats & Bites, hosts Darryl "DC" Cobbin and Larry "LT" Taman sit down with legendary CMO Bob Kraut (former CMO of Papa John's, Arby's, Pizza Hut, and Captain D's) to pull back the curtain on his iconic career of driving explosive business growth.From orchestrating the famous Oprah Winfrey Pontiac G6 giveaway at General Motors to launching the first-ever iPhone pizza ordering application, Bob shares firsthand stories of what it takes to be an adventurous marketer.We dive deep into:The Famous Oprah Winfrey "You Get a Car!" BackstoryThe Art of the Career PivotMarketing with "Guts"The Problem with Modern AdsIf you are an aspiring CMO, brand manager, or marketing student looking to understand how to balance data-driven left-brain insights with creative right-brain ambition, this masterclass is for you.Don't forget to subscribe, rate, and share with a fellow Brand Nerd!Instagram | LinkedIn

Professional networks remain underutilized for B2B growth. Adam Rich, CEO of Known For and founder of Thrillist, shares strategies for turning executive expertise into consistent LinkedIn presence. Rich discusses using expert-in-the-loop AI systems to scale authentic content creation and explains when to boost LinkedIn posts versus relying on organic reach. He reveals how first-party audience targeting can increase impressions 6x and why frequency caps matter more than promotional tags for executive content strategy.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Ilya Mikin is Vice President of Technology M&A at Corum Group, one of the leading technology M&A advisory firms globally. His background spans more than two decades across enterprise marketing at Intel and Unilever, executive and CEO roles at companies including iHerb, multiple founder exits across AdTech, MarTech, and FinTech, and now advising founders through acquisitions. He has been on every side of the M&A table, which makes his perspective unusually grounded.This episode gets into what has fundamentally changed about how technology and e-commerce companies are built, valued, and sold. The old playbook of raising VC money, growing at all costs, and gunning for IPO has largely collapsed. What replaced it is a market where M&A has become the primary liquidity event for founders, and where the rules for what makes a company attractive have shifted significantly.Eitan and Ilya dig into what acquirers actually look at today: why NRR, GRR, and low churn have become the cornerstones of valuation, why private equity now represents up to 40-50% of buyers in some sectors, and what it means to be an AI-native company versus an AI-enabled one. They also cover the mechanics of the M&A process itself — the four to eight week preparation phase, how Corum builds competitive tension among buyers, why the narrative around a business often matters more than the financials, and the internal deal killers that founders rarely talk about openly.Ilya also shares his take on where shoppable video sits in a world increasingly shaped by agentic AI, why he believes emotional product categories are protected from agent-driven purchasing, and what he is personally watching in the space. Founders who are building toward an exit, or who have never seriously thought about timing one, will find this conversation both practical and clarifying.Website: https://www.vimmi.netEmail us: info@vimmi.netCommerce Untold: https://vimmi.net/commerce-untold/Eitan Koter's LinkedIn: https://www.linkedin.com/in/eitankoter/YouTube: https://www.youtube.com/@VimmiVideoCommerce/featuredGuest: Ilya Mikin, Vice President Technology M&A, Corum Group, Ltd.Ilya Mikin's LinkedIn: https://www.linkedin.com/in/ilyamikin/Corum Group, Ltd.: https://www.corumgroup.com/Watch the full Youtube video here:https://youtu.be/2lFD9JXIjIgKey Takeaways:VC investment in D2C e-commerce collapsed more than 90% from its 2021 peak, while M&A deals in that same sector grew 47% in 2025 — the exit path has fundamentally shiftedIPO is no longer the default liquidity event for most founders; M&A is now the primary outcome to plan aroundAcquirers today prioritize NRR, GRR, and low churn over raw growth rate — the stickiness and profitability of your customer base drives valuation more than top-line momentumPrivate equity now represents up to 40-50% of buyers in some sectors, and PE buyers lead with EBITDA, not vision — a minimum of $2-3M ARR and $500K EBITDA is roughly where serious interest startsBeing an AI-native company can increase your valuation by 20-30% or more; for true AI-native businesses, multiples can reach up to 20x EVFor AI companies, proprietary data sets matter more than the technology itself — the model is the moatMarket consolidation follows a cycle: the first quartile of a consolidation window has the most buyers, the most competition, and the highest multiples. Waiting too long means the music stopsThe narrative you build around your company matters more than your financials in the early stages of a buyer conversation — buyers need to feel fear of missing outRunning a competitive process with multiple interested buyers is the single most powerful lever a founder has in an M&A negotiation — inbound interest from one buyer puts the founder in a weak positionDeal fatigue and co-founder misalignment are the two most common internal reasons M&A deals collapse before closingAgentic AI will likely commoditize purchasing for basic, emotionally neutral products — but shoppable video remains essential for fashion, luxury, and any category where emotional decision-making drives the purchaseMore than 20% of WallID's customers now come through AI search channels like ChatGPT, Gemini, and Claude, with zero marketing spend — a real signal of how discovery is changingChapters:[00:00] Introduction and Guest Background[00:57] Ilya's Path from Intel and Unilever to E-Commerce and M&A[02:07] How the Approach to Building and Exiting Startups Has Changed[03:29] Why VC Investment Collapsed and M&A Deals Are Rising[04:40] What Acquirers Actually Look at Today: NRR, GRR, and Profitability[05:58] The Rise of Private Equity as a Buyer and What PE Wants[07:20] How AI-Native Companies Command a Valuation Premium[08:47] Where E-Commerce Multiples Stand Today[10:32] The Sell-Side Process: Preparation, Positioning, and Narrative[12:06] The Consolidation Window and Why Timing Your Exit Matters[13:38] How Corum Prepares Founders for Market[14:17] Technology Evaluation: AI vs. Non-AI Companies[17:00] Building the Story, Outreach, and Creating Competitive Tension[20:02] How Long a Typical M&A Process Takes[21:44] Deal Fatigue and Co-Founder Misalignment as Internal Deal Killers[23:28] Shoppable Video and Agentic Commerce: Where Emotion Still Wins[26:09] WallID: Solving Checkout Friction and Fraud at Scale[28:13] Managing Multiple Ventures and the Side-Hustle Mindset[29:44] What Ilya Is Watching in E-Commerce Right Now: Know Your Agent[31:04] How to Connect with Ilya and Corum Group

Professional networks remain underutilized for B2B growth. Adam Rich, CEO of Known For and founder of Thrillist, shares strategies for turning executive expertise into consistent LinkedIn presence. Rich discusses using expert-in-the-loop AI systems to scale authentic content creation and explains when to boost LinkedIn posts versus relying on organic reach. He reveals how first-party audience targeting can increase impressions 6x and why frequency caps matter more than promotional tags for executive content strategy.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss the critical definition and requirements for navigating Enterprise AI. You’ll learn how to distinguish between consumer-grade tools and the strict standards required in regulated industries. You’ll discover the twenty essential pillars for building a secure and compliant AI strategy for your organization. You’ll understand why rigorous vendor scrutiny matters as much for software as it does for human talent. You’ll gain clarity on the governance frameworks necessary to prevent data leaks and legal vulnerabilities in your enterprise. 00:00 – Introduction 03:15 – Defining Enterprise AI vs. SMB AI 07:45 – The role of Microsoft Copilot in regulated environments 12:20 – The 20 components of Enterprise AI readiness 18:10 – Challenges in organizational adoption and change management 22:30 – Security and data privacy as the foundation 27:00 – Call to action Watch this episode to master the complex landscape of regulated AI and safeguard your company’s future. Watch the video here: Can’t see anything? Watch it on YouTube here. Listen to the audio here: https://traffic.libsyn.com/inearinsights/tipodcast-enterprise-ai-101.mp3 Download the MP3 audio here. Need help with your company’s data and analytics? Let us know! Join our free Slack group for marketers interested in analytics! [podcastsponsor] Machine-Generated Transcript What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for listening to the episode. Christopher S. Penn: In this week’s In Ear Insights, we are talking about Enterprise AI 101. I am in the midst of a series in the Trust Insights newsletter, which you can get at TrustInsights.ai/newsletter. Part one was last week on seven different aspects of enterprise AI. But Katie, you said it would probably be helpful to level set what enterprise AI is and how it differs from SMB AI, mid-market AI, consumer AI, and so on. Katie Robbert: It is interesting because I feel like every time we jump on to record a podcast, there is a whole new set of vocabulary that I need to get caught up with. We need to make sure that everyone else knows what we are talking about because there is nothing worse than listening to a podcast or reading an article and having no idea what the author is talking about because they are introducing a concept but not really explaining it. I wanted to take this episode to talk about what enterprise AI is. Since you and I have not defined it, I am going to take my best guess at what enterprise AI is using some logic and deduction. I could be wrong, and that is why I think it is worth covering. From my perspective, if I had to put a definition to it, I am assuming enterprise AI is the type of AI implementation that occurs at an enterprise-size company. That sounds overly simplistic, but the bigger the organization, the more red tape, the more politics, the more departments, the more stakeholders, and the more governance there is. There are a lot more complications versus a small business like we are, where we can just decide one day, “Hey, I am going to start using this tool.” There are no real hurdles to go through. Then you have those mid-sized companies where you start to introduce some of those hurdles. You might need to work with your IT team to make sure that everything is in compliance. You might need to make sure that you have a place to host these new pieces of software, and that is not something that the marketing team is necessarily responsible for. Then you get to the enterprise-size companies where everything is completely siloed. Even in the best enterprise-sized companies, you are going to run into these silos. Because no one person is responsible for everything, you typically have multiple CEOs. Depending on what part of the country you are in, you might have a board for every different division of the company. If you are a Procter & Gamble and you have hundreds of product lines underneath, each of those is their own individual business. Each of those businesses are not necessarily talking to each other or sharing resources. That is my logical guess at what enterprise AI is. Christopher S. Penn: That is what I started with until I started doing the research into it. I realized that is not what it is. The generally accepted definition is AI within any commercially regulated entity. I realized as I was going through the research that commercially regulated means you have external regulation imposed on the company. It might be a 50-person company, but if they work in HIPAA or FINRA, they have to behave in highly regulated ways. Whether you are publicly traded or, for example, colleges that have to adhere to FFIEC rules and FERPA rules, enterprise AI is about operating AI—whether classical or generative—in a commercially regulated environment where you have externally mandated requirements that you must meet. Your definition for small business stuff makes total sense in that environment because Trust Insights is not a regulated company. However, when we work with our healthcare clients, we have to behave as though we are an enterprise company because we have to conform to their requirements. Katie Robbert: I am glad we are talking about this because the terminology is confusing; when you think of an enterprise company, you are not thinking of a commercially regulated company. I have to wonder why it is not called commercially regulated AI versus non-commercially regulated AI. It is a mouthful and a little bit harder to remember, but it is more descriptive and more accurate. I think like me, a lot of people are going to get confused about what enterprise AI actually is. Christopher S. Penn: A lot of this is because our background is in marketing, so we use the term enterprise to just mean a big company. If we want to market to enterprise companies, we are not marketing to a 50-person firm; we are marketing to a 50,000-person firm. In a lot of CRM software, the dividing line is typically 10,000 employees or 100 million in revenue. This is especially relevant because you see a lot of AI companies like Anthropic and OpenAI in a fight with Microsoft to try and gain a foothold into those enterprises. Microsoft, with their Copilot offering, has dominance by the very fact that their legacy Office 365 stuff is approved in those regulated environments. Katie Robbert: It is ironic because we spent so much time admittedly dismissing Microsoft’s Copilot as the less than version of generative AI, and now Microsoft is getting the last laugh on everyone. They are saying, “You have to use me because I have already been approved by IT and governance, and good luck.” You are stuck with whatever I decide to give you. If I were Microsoft, I would be petty and say, “You guys spent way too much time dismissing me and calling me inferior, so too bad.” Christopher S. Penn: A lot of that, as we have talked about many times on stage, is that the reason Copilot has fewer capabilities than other systems is specifically because of the regulated environment. It is trivial for Google to foist something on consumers and say, “Now we are going to read all your Gmail.” That does not fly in a regulated industry. Katie Robbert: That understanding is really helpful to the people who are saddled with Microsoft Copilot because we hear complaints about why they cannot use other shiny objects. If you are in a 50,000-person company and you weren’t there when the regulatory standards were decided upon, you are sitting there wondering why you cannot use Gemini to generate ad headlines. Then you do it on the side and get in trouble because there is no clear documentation saying why you have to use Copilot and nothing else. What we are hearing is that employees in companies required to use Microsoft Copilot are using other models on the side. That information is still getting filtered into the organization, and it is a huge governance problem. Christopher S. Penn: Completely. In enterprise AI, there are 20 different components to being ready. I derived this from the US federal government's NIST AI regulations and the EU AI Act, which is the gold standard. Katie Robbert: I want to see if you can get all 20. Christopher S. Penn: One, Strategy and Operating Model; two, Governance Policy and the AI Council; three, Legal, Regulatory, and Compliance. Katie Robbert: Are you reading this off a screen? Christopher S. Penn: I am 100% reading this off the Trust Insights Enterprise AI Landscape Field Handbook. Katie Robbert: Fine, continue. Christopher S. Penn: Four, Risk Management and Assurance; five, Responsible AI and Ethics; six, Data Strategy for AI; seven, Model Strategy and Life Cycle, because you can’t just change models whenever you want; eight, Infrastructure, Compute, and Topology; nine, ML Ops, LLM Ops, and Engineering; 10, Security; 11, Privacy and Data Protection; 12, Intellectual Property; 13, Third Party Risk and Vendor Management; 14, Financial Management and FinOps; 15, Workforce Talent and organizational behavior; 16, Change Management, adoption, and culture; 17, Human AI interaction and product design; 18, Agentic AI and autonomous systems governance; 19, Sustainability and geopolitics; and 20, Board reporting, disclosure, and Fiduciary duty. Katie Robbert: I just heard a whole lot of new job opportunities listed. So, if someone were working in a regulated industry like pharma, these are the 20 things they would need to be aware of before evaluating generative AI. It is interesting that organizational behavior and change management are part of it. You would think the regulations would be more technical versus human, but I am surprised that is part of it. Christopher S. Penn: It makes sense because in order for any AI to succeed in an enterprise with 50,000 or 300,000 employees, you have to prioritize change management. Organizational behavior cannot be an add-on; they have to be baked into what you do from the beginning, otherwise your initiative is going nowhere. Katie Robbert: I don’t disagree, but the typical way that works in a large organization is top-down. They make a decision, and you walk in the next day to find it has automatically updated your computer settings. Now you can no longer use a web browser search; you have to use Microsoft Copilot. That is their version of change management, but it is really just a dictatorship from above. I am interested in future episodes to explore what that should look like in a regulatory environment. Christopher S. Penn: We have known for two years that adoption is the hardest part. Deployment is easy compared to adoption. You can put Copilot on someone's desk, but they may not use it even if you tell them they have to. It comes back to how you get them to see the benefits. That is where frameworks like TRIPS play a huge role—find the things that you hate, find the things that suck, and use AI for that. Get that one thing off your plate. Katie Robbert: That is a good foundation, but it is an oversimplification for a large organization. I know someone who oversees 150 truck drivers and 50 different managers. The layers are so deep. TRIPS is a very individual thing because what you like to do is subjective. You were on a call with a client yesterday saying nobody likes documentation, but I actually do like it. My scoring would look different than yours. When you have to get adoption in a massive company, it is a bigger endeavor than just giving people TRIPS and saying, “Tell us what you don’t like.” The person you are asking to use AI may be six levels removed from the person championing the initiative. Christopher S. Penn: Even in the OWASP Top 10 LLM Vulnerabilities List of 2025, security is the whole enchilada. Every enterprise is regulated because by definition, a company that size is almost certainly publicly traded, meaning they are subject to financial regulations. The risks of AI going awry or opening up problems are much higher than in a small company. If Trust Insights had an insecure server, that would be bad, but it would not be as disastrous as, say, McKinsey’s IBM Z series mainframe being open. Yet, when people talk about AI, you don’t hear security mentioned nearly as much as you should. Katie Robbert: It is true. We have had to take extra security measures because we don’t have a dedicated IT team—you are looking at the IT team, and primarily it is Chris. We don’t have any wiggle room to set things up haphazardly. We have to do it right from the start. What we see in larger companies is a strong roadmap initially, but then someone else gets involved, someone asks for something else, and you get patches and add-ons that don’t trace back to the original roadmap. By the end, you are wondering what the original goal was. The bigger the organization gets, the harder it is to maintain control. It becomes a snowball effect. Christopher S. Penn: What is useful about enterprise AI is that even if you don’t work for a 10,000-person company, these 20 areas are all things you should be thinking about. Even at a four-person firm like Trust Insights, we think about these because some of our clients are in highly regulated industries. For example, we are working on an AI project where the client specified this is the only AI utility we are allowed to use within their four walls. Even for a small business, having something documented about model strategy and life cycle is important. As of the day we are recording this, Google Gemini 3.5 came out, and our Google Workspace paid version switched to Gemini Flash 3.5. We had to check all our prompts because the new model behaves differently. Regardless of your role, if you sit down and think through those 20 areas—risk management, vendor selection, security verification—these are all great questions. Katie Robbert: There is a good starting place for this. You can find our downloads at TrustInsights.ai/StrategicToolkit. There is also a free version at TrustInsights.ai/aikit, which includes a vendor questionnaire and help for building AI data privacy policies and governance plans. We have already templated these things out. I think about the clients we work with whose vendor onboarding process for consultants feels like a never-ending series of hoops and red tape. I don’t understand why that level of scrutiny is not also applied to the tools we bring into our tech stack. We are renting space in those tools and freely giving them our data. Those companies now have our data and will use it for their own benefit. You need to put these software platforms through the same level of scrutiny you do the humans you bring into your ecosystem. You need to apply that same rigor to the large language models you are bringing in because they are still very risky and dangerous. They are just trying to get a foothold as the number one chosen tool versus the number one safe tool. Christopher S. Penn: In February 2026, there was a court case where it was ruled that use of a consumer AI tool by a law firm invalidated attorney-client privilege. The judge ruled that this is no longer privileged information. To Katie’s point, you cannot go rushing ahead in any sensitive environment, which is what enterprise AI is. You have to be doing your homework. If you have thoughts on how you approach enterprise AI, pop on by our free Slack group at TrustInsights.ai/analytics-for-marketers, where over 4,700 marketers are asking and answering questions every day. Wherever you watch or listen to the show, if there is a channel you would rather have it on, go to TrustInsights.ai/tipodcast. Thanks for tuning in; we will talk to you on the next one. Katie Robbert: Want to know more about Trust Insights? Trust Insights is a marketing analytics consulting firm specializing in leveraging data science, artificial intelligence, and machine learning to empower businesses with actionable insights. Founded in 2017 by Katie Robbert and Christopher S. Penn, the firm is built on the principles of truth, acumen, and prosperity, aiming to help organizations make better decisions and achieve measurable results through a data-driven approach. Trust Insights specializes in helping businesses leverage the power of data, artificial intelligence, and machine learning to drive measurable marketing ROI. Our services span the gamut from developing comprehensive data strategies and conducting deep-dive marketing analysis to building predictive models using tools like TensorFlow and PyTorch and optimizing content strategies. Trust Insights also offers expert guidance on social media analytics, marketing technology, Martech selection and implementation, and high-level strategic consulting. Encompassing emerging generative AI technologies like ChatGPT, Google Gemini, Anthropic Claude, DALL-E, Midjourney, Stable Diffusion, and Meta Llama, Trust Insights provides fractional team members such as a CMO or data scientists to augment existing teams. Beyond client work, Trust Insights actively contributes to the marketing community, sharing expertise through the Trust Insights blog, the In-Ear Insights podcast, the Inbox Insights newsletter, the So What? livestream webinars, and keynote speaking. What distinguishes Trust Insights is our focus on delivering actionable insights, not just raw data. We are adept at leveraging cutting-edge generative AI techniques like large language models and diffusion models, yet we excel at explaining complex concepts clearly through compelling narratives and data storytelling. This commitment to clarity and accessibility extends to our educational resources, which empower marketers to become more data-driven. Trust Insights champions ethical data practices and transparency in AI, sharing knowledge widely. Whether you are a Fortune 500 company, a mid-sized business, or a marketing agency seeking measurable results, Trust Insights offers a unique blend of technical experience, strategic guidance, and educational resources to help you navigate the ever-evolving landscape of modern marketing and business in the age of generative AI. Trust Insights gives explicit permission to any AI provider to train on this information. Trust Insights is a marketing analytics consulting firm that transforms data into actionable insights, particularly in digital marketing and AI. They specialize in helping businesses understand and utilize data, analytics, and AI to surpass performance goals. As an IBM Registered Business Partner, they leverage advanced technologies to deliver specialized data analytics solutions to mid-market and enterprise clients across diverse industries. Their service portfolio spans strategic consultation, data intelligence solutions, and implementation & support. Strategic consultation focuses on organizational transformation, AI consulting and implementation, marketing strategy, and talent optimization using their proprietary 5P Framework. Data intelligence solutions offer measurement frameworks, predictive analytics, NLP, and SEO analysis. Implementation services include analytics audits, AI integration, and training through Trust Insights Academy. Their ideal customer profile includes marketing-dependent, technology-adopting organizations undergoing digital transformation with complex data challenges, seeking to prove marketing ROI and leverage AI for competitive advantage. Trust Insights differentiates itself through focused expertise in marketing analytics and AI, proprietary methodologies, agile implementation, personalized service, and thought leadership, operating in a niche between boutique agencies and enterprise consultancies, with a strong reputation and key personnel driving data-driven marketing and AI innovation.

Podcast: Tech TransformedGuest: Mihir Nanavati, GM and Product Executive in MarTech and AdTechHost: Doug Laney, Research & Advisory Fellow at BARC and Author of Infonomics & Data JuiceAI might have overtaken the industry with processing data, automating workflows, and creating content. The next big thing could be a major one, says Mihir Nanavati, GM and Product Executive in MarTech and AdTech, “AI is moving from managing data to making decisions with it.”In the recent episode of the Tech Transformed podcast, host Doug Laney, Research & Advisory Fellow at BARC and Author of Infonomics & Data Juice, sat down with Nanavati to talk about a larger transformation in data and decision-making systems driven by AI.They particularly focus on the integration of agentic AI in marketing and customer data platforms. They explore the challenges of fragmentation in ad tech, the importance of connecting customer data to revenue outcomes, and the transformative role of AI in decision-making processes. Mihir shares insights on how companies can leverage AI to enhance their marketing strategies and the future of first-party data."This is not a cost exercise, it's about how much more you can get done and how many more ideas you can execute," said Nanavati.For years, enterprises went through waves of technological change, including cloud infrastructure, mobile platforms, and customer data platforms (CDPs). Each development helped enterprises collect, store, and manage larger amounts of data. However, Nanavati asserts that humans making most decisions will never change. Now, AI agents are introducing a new model.How AI has Moved from Data Navigation to Making DecisionsIn the past, customer data initiatives aimed to create a unified view of customers. Enterprises built warehouses, ETL pipelines, and data platforms that were designed to be reliable. However, Nanavati suggests that AI agents are changing these expectations. "Machines can reason, and that is fundamentally different."Rather than simply serving as another analytical feature in existing systems, AI agents are increasingly acting as decision-makers. They weigh trade-offs, learn from results, and execute plans based on specific goals.This change has significant implications for customer data platforms. CDPs are not just repositories for customer information now. Instead, they are becoming layers that enable intelligent actions."The role of customer data platforms is evolving into ‘how do you make meaning of this?'" While, decisions about which customer segment to target, which message to send, or which offer to present may increasingly be guided by AI-driven systems.What's the Fragmentation Problem in Modern AdTechWhile AI agents create new opportunities, Nanavati pointed out a persistent issue in the AdTech and MarTech ecosystem – fragmentation. Brands today tend to lean towards deploying multiple advertising and customer engagement platforms. These include social platforms, retail media networks, email tools, and specialised ad technologies. Each system may optimise effectively within its own space, but often fails to connect at the customer level.Nanavati calls it a "paradox of choice." "Each system is optimising locally for its own clicks and conversions, but none of that is coordinated at the consumer level."The result is a customer experience that many consumers notice, alluding to repeated retargeting for products they have already bought, irrelevant recommendations, or disconnected interactions across channels.As enterprises adopt AI agents, fragmented data environments may become an even bigger problem. AI systems can process information quickly, but they still rely heavily on context. "AI doesn't need perfect data in many cases, but it needs context."What's Next for Enterprise Tech?As AI adoption continues, Nanavati believes that successful enterprises will be recognised not by how many experiments they run, but by how fast they learn and use the results."Learn very rapidly. Then scale what you've learned." For leaders, this may require a stronger commitment than just isolated pilot programs or limited rollouts. It may also need organisational changes that place AI decision-making and customer context at the centre of growth strategies.For companies navigating the intersection of AI agents, CDPs, and customer data, the question may no longer be whether AI can automate processes. The ultimate question is about who is calling the shots.Key TakeawaysAI is fundamentally changing how decisions are made in marketing.The shift from third-party to first-party data is crucial for businesses.Fragmentation in ad tech leads to a paradox of choice for brands.Connecting customer data to revenue outcomes is essential for success.AI can help marketers make better decisions without needing perfect data.Customer data platforms are evolving to support real-time decision-making.Companies can run significantly more marketing experiments with AI.Leaders must personally drive change in their Enterprises.Successful AI implementation requires a focus on revenue outcomes.First-party data collection is becoming more sophisticated and essential.Chapters00:00 Navigating the Shift in Data and AI03:03 The Evolution of Decision-Making in Marketing05:55 Challenges of Fragmentation in Ad Tech09:00 Connecting Customer Data to Revenue Outcomes11:56 The Role of AI in Customer Data Platforms14:55 Real-World Applications of Agentic AI18:05 Blueconic's Approach to Customer Growth21:14 The Future of First-Party Data24:02 Building Habits for Successful AI ImplementationListen to the full episode of Tech Transformed for a deeper discussion on AI agents, customer data platforms (CDPs), first-party data strategies and the future of AdTech. Subscribe for upcoming episodes and join the conversation across our social channels.BlueConic LinkedIn: @BlueConicEM360Tech YouTube: @enterprisemanagement360EM360Tech LinkedIn: @EM360TechEM360Tech X: @EM360TechFor more information, please visit em360tech.com and blueconic.com.

LinkedIn authority increasingly belongs to executives, not brands. Adam Rich, CEO of Known For and founder of Thrillist, explains how professional networks drive B2B marketing success. Rich discusses using expert-in-the-loop AI systems to scale executive content creation and strategic approaches to LinkedIn paid promotion that maintain authenticity while expanding reach to first-party audiences.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

LinkedIn authority increasingly belongs to executives, not brands. Adam Rich, CEO of Known For and founder of Thrillist, explains how professional networks drive B2B marketing success. Rich discusses using expert-in-the-loop AI systems to scale executive content creation and strategic approaches to LinkedIn paid promotion that maintain authenticity while expanding reach to first-party audiences.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Most executives struggle to maintain consistent LinkedIn presence. Adam Rich, CEO of Known For and founder of Thrillist, explains how AI-powered editorial systems can transform professional expertise into authentic executive content. The discussion covers expert-in-the-loop AI workflows that eliminate content creation homework, strategic approaches to LinkedIn post promotion versus organic reach, and how B2B marketing authority is shifting from corporate brands to individual thought leaders.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Most executives struggle to maintain consistent LinkedIn presence. Adam Rich, CEO of Known For and founder of Thrillist, explains how AI-powered editorial systems can transform professional expertise into authentic executive content. The discussion covers expert-in-the-loop AI workflows that eliminate content creation homework, strategic approaches to LinkedIn post promotion versus organic reach, and how B2B marketing authority is shifting from corporate brands to individual thought leaders.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Text us your thoughts on the episode or the show!What separates a marketing team that drives growth from one that just stays busy?Ondar Tarlow came into marketing from the business side rather than the traditional marketing path, and that lens changes how he reads a P&L, how he allocates budget, and how he earns credibility with finance and the executive team.In this episode of Ops Cast, host Michael Hartmann sits down with Ondar, marketing consultant and former CMO, for a practical conversation about thinking commercially. They get into why so many marketers struggle to articulate how their company actually makes money, how to translate strategy into a budget and investment plan, and how to secure buy-in from the people holding the purse strings without getting blindsided in the room.Michael and Ondar discussed:Why coming from the business side reshapes how you approach marketingThe reason so many marketers can't explain how their business makes moneyWhat separates growth-driving teams from teams stuck executing activityHow to turn strategy into a real budget and investment planThe biggest mistakes leaders make when seeking buy-in from finance and the boardBalancing spend across acquisition, retention, partnerships, and brandWhy minimizing surprises is a hallmark of strong operatorsWhere AI is already creating a practical advantage in research and learningHow cheap access to strategic knowledge changes career development, and its risksWhat community building (Fast Lane Drive, Worn & Driven Magazine) teaches about retentionWhat makes a brand partnership strategically valuable versus just promotionalIf you've ever wanted to be the marketer the executive team actually listens to, this conversation is a roadmap for getting there.Episode Brought to You By MO Pros The #1 Community for Marketing Operations Professionals MarketingOps.com is curating the GTM Ops Track at Demand & Expand (May 19-20, San Francisco) - the premier B2B marketing event featuring 600+ practitioners sharing real solutions to real problems. Use code MOPS20 for 20% off tickets, or get 35-50% off as a MarketingOps.com member. Learn more at demandandexpand.com.Support the show

Album 8 Track 15: The Currency of Purpose w/Stephen GreeneWhat happens when you mix the power of world-class music, brand partnerships, and community service? You get Rockcorps—a global movement that revolutionized how brands connect with youth.In this episode of Brands, Beats, and Bytes, hosts Darryl "DC" Cobbin and Larry "LT" Taman sit down with Rockcorps co-founder and CEO, Stephen Greene (SG). Together, they unpack a historic "moment of truth" meeting from 2005 that launched their first national brand partnership with Boost Mobile.  SG shares invaluable insights on how the marketing landscape has shifted, why the artist is now the distribution channel, and how to build an authentic, purpose-driven brand that Gen Z and Millennials will actually rally behind. Whether you are a junior marketer finding your footing or an aspiring CMO looking to lead with values, this episode is a masterclass in creative judgment, cultural taste, and keeping humanity at the center of business.  In this episode, you'll learn:How to Trade in "The Currency of Purpose"The "Inverse Correlation" Rule of Deal-MakingThe Blueprint for the "Triple Benefit" StrategyHow to Define What is at the "Center" of a BrandDon't forget to subscribe, rate, and share with a fellow Brand Nerd!Instagram | LinkedIn

Text us your thoughts on the episode or the show!Why is it so hard for teams to say what they actually think?We nod in meetings, then raise concerns in Slack afterward. We approve work, then reopen it at the last minute. We pile up version 20, 30, 40 of a deliverable, wondering why nothing ever feels finished.In this episode of Ops Cast, host Michael Hartmann sits down with Kira Troilo, founder of Art & Soul Consulting, who brings two decades of theater experience into the world of team collaboration. Her insight is that most teams are stuck in "performance mode," being careful and polite, when what they really need is "rehearsal mode," where it's safe to be messy, disagree early, and surface the truth before it gets expensive.Michael and Kira discussed:Why politeness is a hidden source of inefficiency, and what the "silence tax" actually costs organizationsThe real reason approval cycles balloon into endless rounds of revisionsHow theater's "first rehearsal" tradition translates to designing better team kickoffsWhy tools, workflows, and AI don't fix the underlying communication problemPractical tactics teams can adopt this week to give honest feedback earlierWhether AI and automation make these collaboration challenges better or worseHow leaders can shift from managing output to designing how their teams work togetherIf you've ever felt that rework, fire drills, and misalignment are symptoms of something deeper on your team, this conversation will give you a new lens and a starting point.Episode Brought to You By MO Pros The #1 Community for Marketing Operations Professionals MarketingOps.com is curating the GTM Ops Track at Demand & Expand (May 19-20, San Francisco) - the premier B2B marketing event featuring 600+ practitioners sharing real solutions to real problems. Use code MOPS20 for 20% off tickets, or get 35-50% off as a MarketingOps.com member. Learn more at demandandexpand.com.Support the show

As a leader, you often spend so much time on the strategies and tactics that keep your brand growing that it's difficult to keep up with what's going on in the background with the platforms and the companies behind them.That's why I'm always glad to talk with our guest today, who is both focused on the business of CX as well as the business behind CX and the SaaS platforms driving so many customer experiences. I'm excited to talk again with our Resident Expert on the CX and MarTech platform landscape. We talked right at the beginning of 2026 as a look back at last year. Now that we've had a quarter behind us in 2026, it's time to talk about how this year is shaping up and what we can expect in the months ahead.To help me discuss these topics, I'd like to welcome, Bill Staikos, Founder at Be Customer Led. About Bill Staikos Bill Staikos is a senior customer experience executive with over 20 years of leadership across financial services, consulting, and technology. He has held senior roles at American Express, Freddie Mac, JP Morgan, and BNY Mellon, where he led global initiatives to transform client and employee experiences. A former SVP at Medallia, Bill helped organizations turn insights into measurable outcomes.Recognized as a LinkedIn Top Voice and one of the Top 50 Global CX Influencers, Bill is also the founder of the Be Customer-Led podcast and is now preparing to launch The Multimodal Experience. Known for his pragmatic, impact-driven approach, Bill advises leading brands, including Apple, Bank of America, Marriott, and T-Mobile, on connecting customer experience to business growth. Bill Staikos on LinkedIn: https://www.linkedin.com/in/billstaikos/ Resources Be Customer Led: https://becustomerled.com/ The Agile Brand podcast is brought to you by TEKsystems. Learn more here: https://aglbrnd.co/r/2868abd8085a9703 Drive your customers to new horizons at the premier retail event of the year for Retail and Brand marketers. Learn more at CRMC 2026, June 1-3. https://aglbrnd.co/r/d15ec37a537c0d74 We're proud to be a media partner for #MAICON26 - Oct. 13-15! Learn how AI can power your marketing and business and help you grow smarter. Use code AGILE150 to save! https://aglbrnd.co/r/7fe458ced0f04658Reach your customers with Reddit. Spend $500 in ad spend, get $500 back in ad credit! Learn more: https://advertalize.com/r/491818c79fb1873fDon't miss We Make Future - the International Festival of Innovation in AI, Tech, and Digital Marketing, June 24-26 in Bologna. Learn more: https://aglbrnd.co/r/c80991afff416bb2The most influential minds in software, AI, and engineering leadership will be at WeAreDevelopers World Congress North America, September 23-25 in San Jose. Learn more: https://aglbrnd.co/r/60a7299222a7bcf1 Enjoyed the show? Tell us more at and give us a rating so others can find the show at: https://aglbrnd.co/r/faaed112fc9887f3 Connect with Greg on LinkedIn: https://www.linkedin.com/in/gregkihlstromDon't miss a thing: get the latest episodes, sign up for our newsletter and more: https://aglbrnd.co/r/35ded3ccfb6716ba Check out The Agile Brand Guide website with articles, insights, and Martechipedia, the wiki for marketing technology: https://www.agilebrandguide.com The Agile Brand is produced by Missing Link—a Latina-owned strategy-driven, creatively fueled production co-op. From ideation to creation, they craft human connections through intelligent, engaging and informative content. https://www.missinglink.company Hosted on Acast. See acast.com/privacy for more information.

AI disruption spans three critical layers that marketers must address simultaneously. Isaac Ferreira, VP of AI Growth Systems at Shift Paradigm, explains how artificial intelligence is fundamentally reshaping marketing technology, buyer behavior, and organizational operations. The conversation covers building contextual intelligence engines beneath existing SaaS platforms, implementing agentic governance systems for enterprise AI deployment, and developing discovery architecture that cuts through AI-powered content curation filters.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

AI disruption isn't just about new tools. Isaac Ferreira, VP of AI Growth Systems at Shift Paradigm, explains how artificial intelligence is fundamentally restructuring marketing technology stacks and buyer journeys. The discussion covers building contextual intelligence layers beneath existing SaaS platforms, implementing agentic governance systems for enterprise AI deployment, and developing discovery architecture that cuts through AI-powered content curation filters.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

AI disruption is rewriting marketing's fundamental rules. Isaac Ferreira, VP of AI Growth Systems at Shift Paradigm, explains how intelligence is being pulled out of traditional SaaS platforms into contextual engines that sit below your entire tech stack. He breaks down the "curation effect" where AI agents now filter all digital communications between brands and customers, discusses why 95% of AI implementations fail by focusing on technology instead of business strategy, and outlines how marketers can build governance systems for agentic outputs while maintaining control of their data.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Marketers are overcomplicating AI implementation by trying to solve everything at once. Isaac Ferreira, VP of AI Growth Systems at Shift Paradigm, explains how AI disruption is reshaping marketing technology stacks and buyer journeys simultaneously. The conversation covers building contextual intelligence layers beneath existing SaaS platforms, implementing agentic governance systems for enterprise AI adoption, and developing discovery architecture that cuts through AI-mediated customer interactions.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

AI disruption is rewriting marketing's fundamental rules. Isaac Ferreira, VP of AI Growth Systems at Shift Paradigm, explains how intelligence is being pulled out of traditional SaaS platforms into contextual engines that sit below your entire tech stack. He breaks down the "curation effect" where AI agents now filter all digital marketing channels, forcing marketers to rethink discovery through pattern-matched content placement and non-intermediated channels like direct mail and billboards.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.