Podcasts about Martech

How much of your marketing technology budget is quietly underperforming, not because the software is flawed, but because your teams can't, or won't, fully adopt it?Because real agility was never about buying faster tools. It's about having an operating model that can actually turn a tool's potential into results, and keep doing it as the tools keep changing.Today we're digging into the phase that quietly decides whether any martech investment pays off: what happens after the contract is signed with things like implementation and adoption. We'll get into:- Why rollouts stall — and why the real cause is usually the operating model, not the tool.- What it takes to move a team from "trained" to genuinely changed.- How to measure real value without fooling yourself with usage metrics.- And what shifts once the platform starts doing some of the work itself.To help me discuss this topic, I'd like to welcome, Kate Dalbey, Chief Client Officer at Qualified Digital.About Kate DalbeyAs CCO, Kate leads client management and growth initiatives at Qualified Digital, bringing over 20 years of digital marketing experience from both client-side and agency-side roles. She's responsible for driving organic and net new growth by leading multi-disciplinary teams who turn light-bulb ideas into fantastic outcomes for the brands QD works with. Kate is guided by the client philosophy that "we grow because they grow." Kate has consistently delivered year-over-year growth in her portfolio within fast-paced, high-growth start-up environments. She passionately believes that digital experiences can change people's lives for the better and works diligently to see these outcomes arrive in real time. In her daily life at QD, Kate enjoys what she calls "the relentless pursuit of better business results" and takes pride in building the teams that can create them, from idea to strategy to plan to execution and measurement. Because what's next isn't enough, it's what's north that really gets her excited. Kate's career experience is deeply rooted in healthcare, across provider, payer, and life sciences. The client roster she's managed includes category powerhouses CVS Health, CommonSpirit Health, Mayo Clinic, Kaiser Permanente, Cigna, Aetna, Sunrise Senior Living, Gelesis, UNCH, Jefferson Health, Cedars-Sinai, Spaulding Rehabilitation, UHS, and Wedgewood Pharmacy. She's also led digital transformation for AmeriGas, Hitachi Vantara, Thomson Reuters, ScanSource, U of Pennsylvania, and the Am. Board of Internal Medicine. When Kate isn't delivering her unique brand of magic at QD, she's with her husband and 2 sons. She loves cheering on Philly sports teams, coaching youth soccer with her husband, and traveling with her family.Kate Dalbey on LinkedIn---------- Resources ---------- Qualified DigitalThe Agile Brand podcast is brought to you by TEKsystems.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!Reach your customers with Reddit. Spend $500 in ad spend, get $500 back in ad credit!Chaser is the only Slack-native project management platform that helps teams turn messages into tracked tasks, automate follow-ups, and maintain team-wide visibility, without adopting another tool. Now integrated with Claude and other GenAI tools. Use code AGILEBRAND for a 3-month free trial (normal trial is 14 days).The most influential minds in software, AI, and engineering leadership will be at WeAreDevelopers World Congress North America, September 23-25 in San Jose. Start building your own apps with Replit and get $20 off.Enjoyed the show? Tell us more at and give us a rating so others can find the show.Connect with Greg on LinkedInDon't miss a thing: get the latest episodes, sign up for our newsletter and more.Check out The Agile Brand Guide website with articles, insights, and Martechipedia, the wiki for marketing technology.The Agile Brand is produced by Missing Link. Hosted on Acast. See acast.com/privacy for more information.

Demandbase's Vice President of Product explains why they deleted a fully-approved AI architecture two months before launch — and how the rebuild surpassed some of their customer's highest expectations.Topics Include:AWS's Achint Naveen introduces Demandbase's VP of Product, Chad HoldorfDemandbase unifies sales, marketing, and revenue data into one viewNovember's architecture used many specialized agents, all committee-approvedThat design failed constantly — only a 30% conversation pass rateOn May 11th, the team deleted the entire architectureRebuilt in May with AWS Strands: one simpler, flexible agentPass rate leapt from 30% to 94% almost overnightWeek two retention rose from the low 20s to upper 80sWeekly active users grew 45% week-over-week after launchReal customer interviews play, calling the new AI a "dream"One user cut an hour-long report down to fifteen minutesCustomers now trace ad impressions directly to closed dealsHoldorf's advice: delete and rebuild when architecture gets too complexAWS's Naveen walks through Bedrock, AgentCore, and StrandsAgentCore Memory highlighted as Demandbase's next area of explorationParticipants:Chad Holdorf – Vice President of Product Management, DemandbaseAchint Naveen – Sr Account Manager, Amazon Web Services See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

What's up everyone, today we have the pleasure of sitting down with Kelsie Dube, Director of Marketing Operations and Automation at Unanet.(00:00) - Intro (01:09) - In This Episode (05:31) - Why New Marketing Ops Leaders Should Audit Before They Act (10:09) - How to Run a Marketing Ops Audit When You Join a Company (16:04) - How to Balance a Full Audit Against Your Boss's Priorities (19:00) - How to Spot a Process Problem Disguised as a Tool Problem (23:41) - How to Surface Shadow Processes and Duplicate Tools in an Audit (31:08) - How to Choose a New Martech Tool With a Tiger Team of Power Users (35:30) - How to Turn a Marketing Ops Audit Into a Prioritized Roadmap (41:20) - How to Align Your Team on a Measurement Philosophy (44:22) - What Happens to Junior Marketing Ops When AI Eats the Entry-Level Work (49:26) - How to Turn Marketing Ops From Ticket-Takers Into Business Partners (52:40) - How to Use One Interview Question to Screen for Team Fit (56:57) - How a Marketing Ops Leader Decides What Deserves Her Energy Summary: Kelsie Dube joined Unanet and did the one thing most new ops leaders are too nervous to do: nothing, at least at first. In this episode she breaks down the 30-day audit she runs before changing a single tool, how she sorts 30-plus problems into big rocks, quick wins, and parked FY27 headaches, and why she'd rather build a "digital twin" to argue with than buy another platform. She gets into the tiger-team playbook that makes tool replacements actually stick, the measurement fight every team should have out loud, and what happens to junior marketers when AI eats the entry-level rung. It's a full field guide to walking into a new company and earning trust before you change anything, plus the interview question she uses to know if you'll thrive on her team.Kelsie's Marketing Operations Assessment Framework: https://drive.google.com/file/d/1x3IJf9tHku4-fASS9AQE_F6sJ1FLK3PN/view?usp=sharingLiza Adam's Digital Twin: https://www.linkedin.com/pulse/smartest-ai-teammate-youll-ever-build-liza-adams-c7rnc/About Kelsie DubeKelsie Dube is the Director of Marketing Operations and Automation at Unanet, where she joined in 2026 to rebuild the company's measurement and reporting foundation. Before that she spent 7 years at Sophos, climbing 5 roles from Marketing Operations Specialist to Director and leading the team through much of that run. She started her career in data entry, scrubbing lead lists and learning the VLOOKUPs she still uses most days, and that ground-floor view shapes how she thinks about the craft.Outside of work she's a mom of 2, an amateur basketball player, and a snowboarder who guards the hours between 5 and 7 for her kids.Why New Marketing Ops Leaders Should Audit Before They ActThe first 90 days at a new company come with a quiet dare. Ship something. Plant a flag. Prove they were right to hire you. Most new marketing ops leaders answer that dare by ripping out a tool they never liked and installing one they used at their last job, all inside the first 2 weeks.Kelsie did the opposite when she joined Unanet. Her first move was to change nothing.The reasoning was twofold. Without a real map of how work gets done, any change you make is a guess, and you'll probably aim it at the wrong target. And Unanet had said in the job description that they wanted someone who'd slow down and understand the business first, which is part of why she took the role. For a marketer who came up through ops and now leads it, that patience is the whole point. You have to understand what's happening well enough to be dangerous, she says, before you can tell anyone what to actually fix.The harder version of this is resisting your own experience. A new CMO walks in and wants a different marketing automation platform because they used one at the last company. Kelsie feels that pull too, since she's learning a few systems here for the first time. Her answer is to make the existing stack work before spending a dollar to replace it. Right now she's rebuilding how campaigns get captured and tagged to campaign members, and she's solving it with a Salesforce workflow or Power Automate instead of a purchase. Replacing the tool would cost more and probably solve less.Then comes the part nobody warns you about, the clock. Listening mode has a shelf life, and everyone, including you, is quietly counting the days until you produce something. Kelsie gave herself a hard deadline of 30 days to finish the audit, then engineered small wins into every week so the learning never looked like stalling. New hires have one thing veterans don't, an empty calendar, and she guarded it. A recurring block every Friday at 2:00 to turn that week's discoveries into something usable. One of those blocks became a 30-minute campaign taxonomy diagram she walked the leadership team through, a quick and visible proof that better structure meant better reporting down the line.The instinct to ship in week one is the most expensive habit in operations, because a fast fix aimed at the wrong problem still has to be undone later. The operators who compound value are the ones who can sit in not-knowing long enough to find the actual bottleneck.Key takeaway: Give yourself a fixed audit window, 30 days is a reasonable default, and block a standing hour each week to turn what you've learned into one small, visible win. Keep a running log of quick wins as you find them so you always have something to ship while the deeper work is still in progress.How to Run a Marketing Ops Audit When You Join a Company"Do an audit" is the most repeated and least defined phrase in marketing ops. Everyone nods along. Almost nobody can tell you what's actually in one, which funnel stages it covers, or where it starts on a Monday morning.Kelsie's version starts before day one. The moment she accepted the Unanet offer, she began mapping ownership lines: what marketing ops owns, what rev ops owns, what IT owns. She wrote out the questions she had and sent them to her leader ahead of her start date, partly out of genuine excitement and partly to get a head start on the RACI.From there it's a series of conversations that snowball. She interviews everyone from her own team to her peers to the level above to her business partners, and she ends every conversation the same way: who else should I talk to? The list never stops growing, but the patterns start to show. Along the way she confirms the systems in her swim lane against the job description, asks what she's missing, and books dedicated working sessions where someone walks her through a live task like a lead import. She records those sessions, then feeds the transcriptions to an LLM to pull out the patterns, a tip she picked up from a mentor that turns hours of shadowing into a usable roadmap.She also runs the work herself.Joining a much smaller team than she was used to, she asked people to hand her a lead import and a campaign creation task so she could run them personally. Part of it was capacity, since a director who can still execute is extra hands when the team is slammed. Part of it was fluency. As she says, a director isn't really a "do-rector," but being right there in the work is how you understand it well enough to change it later.Data privacy rides shotgun through all of this. Coming out of the cybersecurity world, she asks about data retention and opt-in policies early, then files them under "needs struct...

Clean data beats clever algorithms in AI marketing. Katrina Wong, Chief Marketing Officer at New Relic, brings 20+ years of enterprise go-to-market experience to the data-versus-AI debate. She argues AI functions as an operating system, not a standalone tool, becoming the intelligence layer powering interconnected agent workflows. Wong stresses that AI output quality depends entirely on data hygiene, making clean data infrastructure a prerequisite for effective AI-driven decision-making.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Clean data beats clever algorithms in AI marketing. Katrina Wong, Chief Marketing Officer at New Relic, brings 20+ years of enterprise go-to-market experience to the data-versus-AI debate. She argues AI functions as an operating system, not a standalone tool, becoming the intelligence layer powering interconnected agent workflows. Wong stresses that AI output quality depends entirely on data hygiene, making clean data infrastructure a prerequisite for effective AI-driven decision-making.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Marketing teams keep paying for tools they no longer need. Katrina Wong, Chief Marketing Officer at New Relic, explains why AI is replacing entire categories of MarTech software. Her team canceled a competitive intelligence subscription after building roughly 85 AI agents to gather and organize the same data. The output now feeds one-pagers and an interactive Gemini gem, giving sales real-time answers without waiting on a team or logging into a clunky dashboard.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Marketing teams keep paying for tools they no longer need. Katrina Wong, Chief Marketing Officer at New Relic, explains why AI is replacing entire categories of MarTech software. Her team canceled a competitive intelligence subscription after building roughly 85 AI agents to gather and organize the same data. The output now feeds one-pagers and an interactive Gemini gem, giving sales real-time answers without waiting on a team or logging into a clunky dashboard.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Rising AI costs are quietly eroding marketing's bottom line. Katrina Wong, Chief Marketing Officer at New Relic, has led seven successful exits and now factors AI spend directly into cost of goods sold. She breaks down the buy-versus-build decision for AI agents, explains why New Relic won't automate end-to-end campaigns yet, and shares how her team is orchestrating agents across marketing handoffs to control costs.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Rising AI costs are quietly eroding marketing's bottom line. Katrina Wong, Chief Marketing Officer at New Relic, has led seven successful exits and now factors AI spend directly into cost of goods sold. She breaks down the buy-versus-build decision for AI agents, explains why New Relic won't automate end-to-end campaigns yet, and shares how her team is orchestrating agents across marketing handoffs to control costs.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

AI adoption is upending marketing budgets. Katrina Wong, Chief Marketing Officer at New Relic, brings 20+ years leading marketing and go-to-market strategy across enterprise tech companies including Twilio Segment, Hired, Zuora, Salesforce, and SAP. She discusses experimenting with OpenAI's ChatGPT app program despite unproven ROI, treating emerging AI platforms as a budget hypothesis rather than a guaranteed channel, and rethinking SEM investment as LLMs become a default search interface.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

AI adoption is upending marketing budgets. Katrina Wong, Chief Marketing Officer at New Relic, brings 20+ years leading marketing and go-to-market strategy across enterprise tech companies including Twilio Segment, Hired, Zuora, Salesforce, and SAP. She discusses experimenting with OpenAI's ChatGPT app program despite unproven ROI, treating emerging AI platforms as a budget hypothesis rather than a guaranteed channel, and rethinking SEM investment as LLMs become a default search interface.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

AI development costs won't outpace developer salaries by 2028. Katrina Wong, Chief Marketing Officer at New Relic, brings 20+ years of enterprise marketing leadership and AI-driven go-to-market expertise. She predicts market competition and open models will keep AI tooling affordable, while token costs won't scale to $250,000 per developer per year. Wong also points to one-to-one personalized marketing and selling as the next frontier AI will unlock.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

AI development costs won't outpace developer salaries by 2028. Katrina Wong, Chief Marketing Officer at New Relic, brings 20+ years of enterprise marketing leadership and AI-driven go-to-market expertise. She predicts market competition and open models will keep AI tooling affordable, while token costs won't scale to $250,000 per developer per year. Wong also points to one-to-one personalized marketing and selling as the next frontier AI will unlock.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 Kathleen Schaub, Author, Strategist, and Advisor in Marketing Management and Organizations.We cover:(00:00) - Intro (01:19) - In This Episode (04:45) - Why Marketing Behaves More Like Weather Than a Machine (08:49) - The Four Mindsets Marketing Leaders Need for Complex Markets (14:06) - Why ROI Doesn't Work as a Marketing Measurement (18:19) - What Causal AI Can Actually Tell You About Marketing (28:37) - Why Your Marketing Budget Works Like an Investment Portfolio (34:21) - What Marketers Should Actually Be Held Accountable For (38:49) - The Surrogation Trap Behind Single Marketing Metrics (44:09) - Why Marketing Managers Should Create Conditions Instead of Commands (50:00) - How Pace Layering Makes a Marketing Budget Adaptable (57:16) - How Intention Decides What Deserves Your Energy Summary: Marketing has spent a century pretending it's a machine you can feed cash and read like a receipt, and Kathleen Schaub is here to take that apart. She makes the case that markets behave more like weather than vending machines, walks through her 4 mindset shifts for leading in the chaos, and explains why a single north-star metric quietly wrecks your decisions. Along the way there's a butterfly in Brazil, a cucumber garden in Canada, a poker champion, and a COO who begged for the book on a cruise. If you've ever had to defend marketing ROI in a boardroom and felt the ground move under you, this conversation names what's really going on.About Kathleen SchaubKathleen Schaub is an author, strategist, and advisor focused on marketing management and organizations, working through KathleenSchaub.com. She spent 9 years leading IDC's CMO Advisory practice, where she advised hundreds of technology marketing leaders, and she's a longtime contributor to leading martech publications including CMSWire. Her work argues that markets are complex adaptive systems rather than predictable machines, and her book lays out 4 mindset shifts, investor, navigator, statistician, and ecologist, for leading marketing in a volatile world. These days she splits her time between writing, advising, passion projects, and being a grandmother of 2.Why Marketing Behaves More Like Weather Than a MachineEvery marketing leader has sat across from a finance executive who wants one thing. Put a dollar in, know what comes out. Budgets get built on that promise. Forecasts get defended on it. And every year, the results wander off somewhere the model never predicted.Kathleen has spent more than a decade explaining why that keeps happening. Her line is that marketing is not a vending machine. A vending machine is controllable and predictable. You put your money in, you press the button, you get the exact thing you chose. Executives, she says, would give almost anything for marketing to work that cleanly. Marketing never has.The weather comparison is a humbling one. We carry supercomputers in our pockets, we have decades of atmospheric data, and we still can't say for sure whether it'll rain tomorrow. Marketing runs on something messier than the atmosphere, which is people. Buyers, brands, influencers, partners, and the economy, all reacting to each other at once. Kathleen calls the result a complex system, the kind scientists study, where every interaction feeds back into the next and quietly introduces unknowns into every situation.That's the part most measurement frameworks skip over. Marketers, salespeople, and customer experience teams all work at the edge of the company, the seam where the controllable inside meets the uncontrollable outside. Their whole job is to manage, predict, and measure a world that refuses to hold still. No amount of dashboard polish changes the fact that half the inputs live outside the building.Kathleen keeps the parts of the old factory toolkit that still earn their place. The shift she wants is smaller and harder to swallow. Accept that markets are what the military calls VUCA, volatile, uncertain, complex, and ambiguous, then adopt measurement practices built for that reality instead of pretending the reality is something tamer. The methods already exist. Other fields use them every day. Marketing just hasn't bothered to translate them yet.The uncomfortable implication is that a lot of the dashboards marketing teams present with total confidence are measuring a machine that was never really there. The teams that win the next decade will be the ones who stop apologizing for uncertainty and start building for it.Key takeaway: Audit your current reporting for any number you present as a guarantee. Rewrite each one as a range or a probability, and rehearse saying "here's what's likely and here's what could move it" before your next budget review. Present every forecast as a weather report, a set of ranges you can actually defend.The 4 Mindsets Marketing Leaders Need for Complex MarketsYou can buy a new attribution platform, restructure the team, bolt on a dozen dashboards, and still land exactly where you started. Kathleen thinks she knows why. You changed your operations without changing the thing that steers them, which is your mindset. She treats mindset as the director of every action a team takes. Leave it untouched, and every operational upgrade delivers roughly the same results you've always had.Her favorite way to explain this comes from Buddhism. Your mind is the ox, and the cart is everything the ox drags behind it, every outcome your marketing produces.The leverage is quieter than it looks. Change your mindset and the dozens of small decisions you make every day start bending, even slightly, and over enough decisions you end up miles from where the old direction would have taken you. That's why the mindset has to move first. The 4 she recommends all come from worlds that are genuinely volatile and complex, but they're worlds anyone can picture, and each one maps onto something marketing leaders already wrestle with.Investor: stop treating the budget like a cost center you spend down, and start treating it like a portfolio you risk for a better future return., Navigator: change the relationship between your plan and your measurement, adapting like a pilot or a sailor who reads the conditions in front of them instead of clinging to the route., Statistician: give up the hunt for certainty and accept that everything in the human and natural world runs on probability. Kathleen calls this the hardest of the 4 because our brains hate it., Ecologist: manage the conditions people work in, because behavior arises from the intersection of an individual and the context around them, so managing the person by themselves only covers half of it.Read them together and a pattern shows up. Every one asks you to trade the illusion of control for the ability to adapt. That trade is where most transformation efforts quietly die, because swapping tools is easy and swapping beliefs is not.Key takeaway: Before you approve the next platform or reorg, write down the belief driving it in one sentence. If that belief still assumes marketing is predictable and controllable, fix the belief before you spend the money. Pick one of the 4 mindsets and name the single daily decision it would change for you this quarter.Why ROI Doesn't Work as a Marketing MeasurementAsk a room of marketers what keeps them up at night and ROI lands near the top every time. It's the question waiting in every board meeting. What drove revenue last month, and how much will this next bet add? Kathleen has been chasing that question longer than most. Running IDC's CMO advisory practice for 9 years, she kept asking leaders whether they were actually getting ...

AI is helping marketers move faster, but not always smarter. Katrina Wong, Chief Marketing Officer at New Relic, explains how her team turns raw data into decisions leadership can trust. She covers using AI to analyze recorded sales calls for unbiased win-loss insights, deploying real-time in-product signals to personalize the self-service funnel, and building a human-in-the-loop fact-checking process to catch AI drift before it erodes trust in the data.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

AI is helping marketers move faster, but not always smarter. Katrina Wong, Chief Marketing Officer at New Relic, explains how her team turns raw data into decisions leadership can trust. She covers using AI to analyze recorded sales calls for unbiased win-loss insights, deploying real-time in-product signals to personalize the self-service funnel, and building a human-in-the-loop fact-checking process to catch AI drift before it erodes trust in the data.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Summer Remix: 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

Most marketing campaign workflows will disappear within three years. Brendan Farnand, Co-founder and Chief Evangelist at Knak, spent the past year talking with over 100 enterprise marketing teams—including OpenAI, Google, Stripe, and AT&T—to learn where AI helps campaign production and where it breaks. He explains what separates companies experimenting with AI from the ones actually shipping better marketing, and how campaigns should function in the AI era.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Most marketing campaign workflows will disappear within three years. Brendan Farnand, Co-founder and Chief Evangelist at Knak, spent the past year talking with over 100 enterprise marketing teams—including OpenAI, Google, Stripe, and AT&T—to learn where AI helps campaign production and where it breaks. He explains what separates companies experimenting with AI from the ones actually shipping better marketing, and how campaigns should function in the AI era.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

AI removed the campaign bottleneck, but volume alone won't win. Brendan Farnand, co-founder and chief evangelist at Knak, spent the past year studying how 100+ enterprise teams—including OpenAI, Google, and YouTube—build AI-native marketing campaigns. He breaks down OpenAI's workflow that starts with an unstructured Slack message, uses AI agents to build a structured brief in Linear, then generates production-ready assets through an MCP server. Farnand also explains why campaigns should function like factory production lines, how to apply Goldratt's single-constraint theory to marketing throughput, and where humans stay in the loop to protect taste and relevance.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

AI removed the campaign bottleneck, but volume alone won't win. Brendan Farnand, co-founder and chief evangelist at Knak, spent the past year studying how 100+ enterprise teams—including OpenAI, Google, and YouTube—build AI-native marketing campaigns. He breaks down OpenAI's workflow that starts with an unstructured Slack message, uses AI agents to build a structured brief in Linear, then generates production-ready assets through an MCP server. Farnand also explains why campaigns should function like factory production lines, how to apply Goldratt's single-constraint theory to marketing throughput, and where humans stay in the loop to protect taste and relevance.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Most conference speakers turn their session into a sales pitch. Brendan Farnand, co-founder and Chief Evangelist at Knak, has spoken at Adobe Summit, Salesforce Connections, and the MarTech Conference. He explains why a full product pitch on stage falls flat, and how to make your talk relevant enough that the audience leaves with something they can actually use at their organization.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Most conference speakers turn their session into a sales pitch. Brendan Farnand, co-founder and Chief Evangelist at Knak, has spoken at Adobe Summit, Salesforce Connections, and the MarTech Conference. He explains why a full product pitch on stage falls flat, and how to make your talk relevant enough that the audience leaves with something they can actually use at their organization.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Summer Remix: Album 8 Track 9: Accelerating Your Career: Think Two. Act One. w/Kristen FischbeckBrand Nerds, we are back in the building! Today, we are diving deep into what it takes to achieve professional growth as we sit down with Kristen Fischbeck. If you are a marketer looking to "compress the timeline" between where you are and where you want to be, this episode is your blueprint. Kristen's rise is nothing short of meteoric: she joined a boutique agency as an entry-level account coordinator and, in just seven years, navigated every level of the organization to become Managing Partner. Now, she leads strategy for an expansive and impressive portfolio including BMW, Rolls-Royce, and Land Rover. In this conversation, Kristen breaks down what we are coining the "Think Two. Act One." strategic mindset of thinking two steps ahead while acting on one to master the job you want before you even have the title. We explore the grit required to thrive in your career, the "Ruh-Roh" moments that lead to massive growth, and how AI is currently slashing production costs in half for luxury brands. Key Takeaways:The 2-1 Rule for Career AccelerationMimic the MasteryThe Space to FailHigh-Octane BrandingAI as a Production ToolDon't forget to subscribe, rate, and share with a fellow Brand Nerd!Instagram | LinkedIn

Marketing teams struggle to make AI work in real campaign production. Brendan Farnand, co-founder and Chief Evangelist at Knak, spent the past year talking with over 100 enterprise marketing teams—including OpenAI, Google, Stripe, and AT&T—to learn where AI helps and where it breaks. He explains what separates companies experimenting with AI from those actually shipping better marketing, how campaigns should function in the AI era, and how to deliver value to an audience without turning it into a sales pitch.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Marketing teams struggle to make AI work in real campaign production. Brendan Farnand, co-founder and Chief Evangelist at Knak, spent the past year talking with over 100 enterprise marketing teams—including OpenAI, Google, Stripe, and AT&T—to learn where AI helps and where it breaks. He explains what separates companies experimenting with AI from those actually shipping better marketing, how campaigns should function in the AI era, and how to deliver value to an audience without turning it into a sales pitch.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Welcome to the Health Marketing Collective, where strong leadership meets marketing excellence.On today's episode, Scott Brinker joins Sara Payne for a candid discussion on the accelerating pace of marketing and the impact of marketing technology and AI on today's business environment. Widely known as the “Godfather of MarTech,” Scott Brinker brings his nearly two decades of expertise through his Chief MarTech platform and numerous bestselling books to help us navigate the challenges and opportunities at the intersection of speed, strategy, and creativity in modern marketing.Is marketing really moving faster, or does it just feel that way? That's the key question Sara and Scott unpack, digging into the effects of digital transformation and AI on content creation, expectations, and, importantly, the human cost of relentless urgency in the field. They explore the implications for marketing leaders, the hidden costs of always-on activity, and how to build sustainable rhythms that foster both creativity and strategic impact, especially in healthcare.Join us as we examine how marketers can balance agility and discipline, use technology as a force for focus rather than just acceleration, and reclaim space for deep thinking to build brands rooted in trust and authenticity.Thank you for being part of the Health Marketing Collective where strong leadership meets marketing excellence. The future of healthcare depends on it.Key Takeaways:The Double-Edged Sword of Marketing Velocity: Scott underscores that the rapid pace of marketing goes far beyond AI, it's rooted in years of digital transformation and an explosion of touchpoints and technologies. While these innovations enable marketers to do more, faster, they introduce significant costs, particularly by eroding critical time for reflection and strategic thinking. The challenge: can the human mind keep up with technology's pace? (04:24)The Cost of Speed: Creativity, Strategy, and Burnout: Both Sara and Scott warn that constant urgency often leads to a shortcutting of the creative and strategic process, resulting in decision fatigue and burnout. Marketing effectiveness isn't just about reaction time; it's sustained by discipline, iteration, and making space to revisit projects with fresh eyes. Short-term responsiveness should not eclipse long-term impact. (06:21)Discipline and Cadence Trump Perpetual Chaos: Adapting concepts from agile development, Scott advocates for operating rhythmic sprints, structured backlog, and focused delivery cycles to help teams juggle changing priorities without succumbing to perpetual interruption. Sarah Payne echoes the need for discipline, emphasizing the importance of being intentional about what merits urgency, and communicating clear priorities across organizations. (12:30)More ≠ Better: Activity vs. Impact in the Age of AI: The proliferation of AI and automation threatens to amplify “activity for activity's sake.” Scott urges marketers not to simply fill newfound time with more execution but to protect it for higher-order thinking and true innovation. Drawing parallels to software development, he notes that an avalanche of new features or campaigns rarely translates to better outcomes if it's not grounded in value and customer impact. (24:31)Scarcity of Trust and Attention: The New Differentiators: Looking ahead, Scott predicts that as technology further reduces the friction of activity, human attention and trust will become the scarcest and most valuable assets for brands. The organizations that excel will be those who invest in building genuine relationships and deliver consistently on customer-centric outcomes, focusing less on technology for its own sake and more on understanding and serving their audiences with authenticity. (27:01)Mentioned in this episode:Health Marketing Collective is Powered by InprelaThe Health Marketing Collective is powered by Inprela: a communications firm built for health brands determined to lead, not follow. We partner with marketing innovators who aren't just chasing attention—they're building movements. Connect with the audiences shaping the future of care and lead the conversations that move your market. Ready to rise above the noise? Visit inprela.com. Let's create something that moves the market.Inprela Communications

Most marketing teams experiment with AI but never ship better work. Brendan Farnand, Co-founder and Chief Evangelist at Knak, spent the past year interviewing 100+ enterprise marketing teams—including OpenAI, Google, Stripe, and AT&T—to learn what separates AI experimentation from real output. He explains how marketing campaigns should function in the AI era, where AI actually helps versus where it breaks, and how to build on-brand campaign assets at scale without code or developer support.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Twenty years of digital marketing created something of a monster: companies poured enormous investment into analytics teams, MarTech stacks, media capabilities, and data infrastructure—and then watched all those functions march off into their respective silos to work really, really hard at producing activity rather than impact. Rusty Rahmer, founder of Starize AI and author of Working As Designed, joined Michael, Julie, and Val to dig into why that happened, why it's still happening, and what it actually takes to flip the shovel over and use the right end. Along the way, Rusty—who Val correctly identified early as a spontaneous analogy machine—explained why customer journey maps on walls are basically the statistical average American life that literally nobody lives, why waffle fries are structurally superior to ridged chips (and what that has to do with cross-functional team design), and why the most important question a marketing leader can ask a room full of executives is also the one most likely to be met with complete silence. This episode is brought to you, in part, by our sponsors, Stape and Prism from Ask-Y. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Most marketing teams experiment with AI but never ship better work. Brendan Farnand, Co-founder and Chief Evangelist at Knak, spent the past year interviewing 100+ enterprise marketing teams—including OpenAI, Google, Stripe, and AT&T—to learn what separates AI experimentation from real output. He explains how marketing campaigns should function in the AI era, where AI actually helps versus where it breaks, and how to build on-brand campaign assets at scale without code or developer support.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

AI made campaign creation easy, so the new bottleneck is knowing what to ship. Brendan Farnand, co-founder and chief evangelist at Knak, spent the past year studying how enterprise teams like OpenAI, Google, and YouTube build AI-native campaigns. He breaks down OpenAI's agent workflow that starts with an unstructured Slack message, builds a structured brief in Linear, then passes assets to a production platform for a human to add taste. He also explains applying Goldratt's Theory of Constraints to find the single bottleneck in your go-to-market process, and why speed to market can mean millions more customers reached.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

AI made campaign creation easy, so the new bottleneck is knowing what to ship. Brendan Farnand, co-founder and chief evangelist at Knak, spent the past year studying how enterprise teams like OpenAI, Google, and YouTube build AI-native campaigns. He breaks down OpenAI's agent workflow that starts with an unstructured Slack message, builds a structured brief in Linear, then passes assets to a production platform for a human to add taste. He also explains applying Goldratt's Theory of Constraints to find the single bottleneck in your go-to-market process, and why speed to market can mean millions more customers reached.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this month's episode of Trade Show Talk, TSNN's Danica Tormohlen speaks with Kate Spellman, Chief Commercial Officer of the newly combined Emerald and Questex, which were both purchasedby global alternative asset manager Apollo-managed funds with the sales officially closing July 14. Spellman shares how she's approaching the integration, why she sees enormous growth potential in the merger, and how AI, data, and year-round engagement are changing the way the industry sells and delivers value.  Spellman breaks down three major organic growth opportunities: event extensions, digital products, and deeper year-round content programs. She also explains why consultative selling and stronger ROI reporting are becoming essential for modern event businesses.  The conversation then turns to Apollo's investment in live events, the role of first-party data, the importance of personalization, and how AI is already accelerating sales and marketing performance across the portfolio.  The episode concludes with an advocacy update from Tommy Goodwin, President and CEO of the Exhibitions and Conferences Alliance (ECA) on tariffs, industry policy, and new initiatives designed to keep professionals connected and engaged year-round.  Highlights from the podcast:  Why the Emerald x Questex combination is a "once-in-a-lifetime opportunity:  How integration can remove silos and unlock scale  Why one-to-one meetings and personalized outreach are here to stay  How AI SDRs are generating faster responses and measurable revenue  Why event tech, martech, and data should function as one connected stack  The latest updates on industry advocacy and tariff pressure  Timestamps:  00:00 - Introduction to Kate Spellman and her expertise in digital transformation 00:45 - Kate's career highlights and impact on enterprise value at Penton and Informa 01:35 - Overview of her current role as Chief Commercial Officer at QuestX and Emerald post-merger 02:28 - Excitement around the Emerald and Questex merger and industry growth opportunities 03:21 - The industry's shift towards year-round connection and data-driven ROI  04:01 - Lessons from past integrations at UBM and Penton on building capabilities and organic growth 05:24 - Strategic focus on market knowledge, vertical expertise, and partnership building 06:18 - Leveraging talent and data to accelerate growth and scale shows 07:06 - The integration approach for Emerald and Questex, including the role of data and leadership tours 08:25 - Managing siloed structures and creating unified, scalable event portfolios 09:42 - Expansion of digital pharma and biotech events, and the importance of large trade shows 10:33 - Emphasizing strategic thinking over siloed operations for bigger, more impactful events 11:02 - New market opportunities from the industry merger and what it means for customers 11:58 - Industry investment in live events by Apollo funds and the focus on building trust and relationships 13:20 - How the combined company will enhance customer experiences in the next 12 months 14:09 - Rebranding strategies and new offerings to clients via the merged entity 15:29 - Organic growth opportunities including event extensions, digital products, and full-year programs 16:46 - The emergent importance of year-round engagement and personalized content strategies 17:15 - Evolving sales strategies towards high-touch, consultative approaches and larger client relationships 18:13 - The industry's move toward data-driven ROI and how event tech is converging with Martech 20:06 - The deployment of AI for sales, marketing, and personalized attendee experiences 21:26 - Successful AI integration at QuestX and Emerald, and future potential 23:16 - AI's measurable impact on revenue, responsiveness, and client engagement  24:29 - Building communities and continuous content sharing outside of event periods 25:24 - Strategies to keep databases fresh and maximize year-round outreach 27:25 - The shift in sales conversations toward strategic partnerships and high-value clients 29:13 - How industry relationships are deepening among large companies and new client acquisition 33:47 - Emerging trends underestimated by organizers, such as one-to-one marketing and sophisticated reporting 34:33 - The importance of creating memorable, experience-driven events and personalized journeys 35:02 - Personal interests and travel essentials of Kate Spellman 36:23 - Memorable first shows and recent events attended 36:53 - Travel plans and upcoming listening tours  Advocacy Update with Tommy Goodwin, ECA  37:21 - Tommy Goodwin joins for an advocacy update from the Exhibitions and Conferences Alliance 37:46 - Update on the OMB proposal and the industry's response 38:08 - More than 500,000 comments submitted on the proposal 38:32 - Follow-up conversations with the White House and OMB 39:47 - New tariffs affecting imports from multiple countries and the ongoing uncertainty 41:12 - Why tariff pressure matters for 2027 planning 42:45 - New ECA programs designed to keep advocacy active year-round 43:12 - Returning ECA Votes program ahead of the 2026 election 44:25 - Upcoming appearances at the ASA annual meeting and SISO Leadership Conference 44:53 - Closing thoughts and thanks from Danica and Tommy  Guest bio: Kate Spellman, Chief Commercial Officer, Emerald+Questex  Kate Spellman is a senior commercial operating executive known for driving enterprise value creation across B2B information services, with deep expertise in monetizing data, digital, and event-led platforms. She has led P&L and go-to-market functions across businesses ranging from $20M to $800M+ in revenue, operating within private equity, public company, and founder-influenced environments. Her work consistently centers on accelerating revenue growth, expanding margins, and scaling platforms through both organic and M&A-driven strategies.  Leadership Scope  Functional leadership across Sales, Marketing, Product Marketing, Data, Digital, Events, and Customer Experience   Experience leading global, cross-functional teams across the U.S., Europe, and Asia   Team sizes ranging from ~25 to 150+ across centralized and business unit structures   Oversight of multi-channel revenue engines spanning events, subscriptions, data products, and digital media   Currently, Ms. Spellman serves as Chief Commercial Officer at Questex, where she leads monetization strategy across events, data, digital, and content. She is responsible for commercial execution, product monetization, and go-to-market optimization, directly supporting scalable growth and EBITDA performance across the portfolio.  Previously, as Chief Marketing Officer at Questex, she built and led a centralized Centers of Excellence model spanning products, data, events, digital, content, and customer experience. This operating structure enabled more efficient cross-platform monetization, drove record revenue and EBITDA performance, and materially expanded digital and event-based revenue streams.  Ms. Spellman was a member of the Executive Committee at Penton, where she played a key role in tripling enterprise value, culminating in a $1.67B sale to Informa. Following the acquisition, she was promoted into Informa's Executive Leadership team, where she founded and scaled the global Informa Engage business unit, driving over $200M in new product launches and revenue growth.  Earlier in her career at UBM, Ms. Spellman launched new business lines, expanded international operations, and built high-performing commercial teams across the U.S., Europe, and Asia, further establishing her track record in scaling global platforms.  Ms. Spellman brings deep experience operating in acquisition-driven environments, including M&A and exit experience, integration, commercial transformation, and organizational scaling.   In addition to her operating roles, Ms. Spellman has served on multiple boards and advisory councils, providing strategic oversight and governance across B2B media, data, and information services platforms. Her expertise is sought after across the events and media industry, and she has won multiple awards for her contributions.   

Summer Remix: 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

Heather Macaulay, co-founder of MadConnect, joins Joe Zappa and Eric Franchi to discuss building a company after 40, balancing motherhood and leadership, and turning a career setback into a new opportunity. She also explains how MadConnect solves connectivity challenges across AdTech and MarTech, why experienced founders can make better decisions, and why you can have it all, just not all at once. Plus, Heather challenges Adam Epstein to a five-mile run, and Joe puts his 20 chin-ups claim on the record.

In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss the flaws behind AI detection tools and how creators can protect their reputation while using generative writing assistants. You’ll discover why these detection tools misread human writing and how to stop false accusations from damaging your reputation. You’ll learn simple steps to preserve original drafts and voice recordings as undeniable proof of your authorship. You’ll explore ethical disclosure practices that build trust with your audience while keeping your creative process transparent. You’ll gain confidence in navigating AI ethics so you can create content without fear of unfair judgment. 00:00 – Introduction 02:15 – The AI detector dilemma 06:40 – Katie shares her newsletter workflow 11:20 – Why detection tools consistently fail 16:50 – Protecting your authorship with proof 21:30 – Navigating ethical AI disclosure 26:45 – Call to action Watch the video here: Can’t see anything? Watch it on YouTube here. Listen to the audio here: https://traffic.libsyn.com/inearinsights/tipodcast-the-problems-with-ai-detectors.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, let’s talk about AI detectors, one of my personal favorite subjects to rant about. But Katie, before I foam at the mouth for 30 minutes, let’s have you foam at the mouth about it. Katie Robbert: It’s such an interesting topic and obviously very polarizing right now. AI detectors in a nutshell are meant to help someone determine whether or not AI was used in any kind of writing. Now our good friend Anne Hanley pointed out, oh sure. So these AI detectors that were trained on human authors’ writings without their consent are now meant to tell these people that they didn’t write the things that the model was trained on. I’m paraphrasing, but it was basically that was the gist. And last week when we published the weekly Inbox Insights newsletter, we had a reader provide some very unpleasant feedback. This reader felt, in their opinion, that they had determined that the post I had written about “if you don’t know what AI can do, just ask it” was completely written by AI and that I should be fired. That I was lying about the use of AI in terms of it wrote it for me, that it was AI slop, that this person was going to write their own blog post about how I, the CEO of a company called Trust Insights, can’t be trusted. So that was the feedback this person had for my contribution to the newsletter last week. This week, if you subscribe to Inbox Insights, I fully disclose my use of AI in writing the newsletter and writing in general. I’m going to give you a spoiler because there’s no secret. I write the newsletter myself. I then use various AI tools to hopefully clean it up. Because the feedback I got when I was in college in my creative writing class is that I write the way that I talk. And it’s kind of a stream of consciousness. Now, as I’ve gotten older, I’ve gotten a little bit more concise and articulate, but that doesn’t mean my writing has. And so it still kind of comes out as a stream of consciousness, which I think for any writer that’s doing draft one is you just get it out. It’s why it’s called the ugly first draft, and then some people… I used to have John, our head of business development and our partner, read through and edit my posts for me. This was prior to having tools like Hemingway or AI editors. I had a human editing it. Now John’s busy making sales. He’s still happy to edit my posts, but it’s not the best use of his time. And so now I use a tool called Hemingway, which a lot of people use. Hemingway has a lot of really great features for grammar and sentence structure. I’m not trained, and I don’t have a degree in writing or English. My grammar is really bad sometimes. Sometimes I overuse passive voice. Sometimes my sentences aren’t structured well. It’s helpful to have a tool that can clean up the thing without losing the intent and sentiment of the writing. I also use our Ask the ICP skills in our cloud environment to make sure that the post that I’m writing resonates with our audience. Because if it doesn’t, why am I writing it? So I use those various tools. So the point of the newsletter this week that I dive into is, yes, I use AI to supplement and clean up my writing. No, AI does not write for me. I’ve got 10 fingers, one with a bandage, so it goes a little slower. And I type with my thumbs, typing very slowly. So sometimes I use an audio recording of me speaking something. Chris, this is something you do. But, yes, I painfully type all of my newsletters very slowly. And then AI helps me clean them up to be more concise. I don’t think that’s an uncommon practice, especially among people. This is true of, I think, Ann even posted in her newsletter this past week. Christopher S. Penn: Week. Katie Robbert: Total anarchy if you’re not subscribed. How she uses AI with her writing as well. And she said she gives it explicit instructions: read through it, review it, don’t edit anything, tell me what the edits are supposed to be. So she’s also someone who we know and love, who is a very fantastic writer, finding ways to use these tools to help enhance the writing. It can be cost prohibitive to have a human editor on your team. You may not have access to a copywriter, or you may not have a team of people who are really great at editing. There’s a lot of… So AI can fill that role for you. I’ll say it like this: I wrote the newsletter. AI helped me edit it, so it was coherent. So unfortunately for this reader, I will not be firing myself. I would appreciate you not trying to destroy my credibility, but should you choose to do so, we will deal with it at that time. Christopher S. Penn: I’m surprised you didn’t bring this up because this is the heart of the matter to me. If we think about these AI detectors, why are you using them? Why do you care? What is the purpose of an AI detector by the 5P Framework by Trust Insights? Of course. Katie Robbert: Well, the five P’s are in this week’s newsletter, so you can certainly get your healthy dose of the 5P Framework by Trust Insights. But you’re absolutely right, Chris, and that’s a miss on my part because I am human and not a sentient machine. I missed the mark on calling out that the 5P Framework by Trust Insights is a great place to start. Why are you using these AI tools? So, for me, my purpose is to edit the grammar and spelling of my content so that it’s coherent. I’m also checking with our ICP to make sure it resonates with the people I’m writing it for. But our ICP is the people part of it that really matters, because I’m not writing it for myself. I’m writing from my experience and my expertise, but I’m writing it for… For our ICP so that they get something educational out of it. I outlined my process in this week’s newsletter of how and when I use the tools and platforms. It depends. I might write it in a document, I might create an audio file, and then I’ll bring it into the large language model. I might use Hemingway. I definitely use the skills that we’ve created. And then the performance is, do I have a piece of content that I wrote and AI helped me edit that gets people to respond to the newsletter? Christopher S. Penn: It is the 5P Framework. From the perspective of the people who are using or advocating for AI detectors, what is their purpose? Because this is where I have the biggest problem I see. Yeah, no, no. From the AI detector perspective, what is your purpose in the case of this particular reader? Is your purpose just that you have a burr up your ass and you need to yell at somebody? Like, okay, you don’t need an AI detector for that. You can be a jackass. Regardless, in the case of its use in academia, the purpose is very often for academic integrity, which makes these tools very dangerous because of their false positive rate. Pangram, which is the tool that Substack most famously just implemented, has a false positive rate of 0.02 percent. If you fed every college student’s papers in America to it and said, run disciplinary proceedings, you would flag 200,000 students a year with false accusations. In the corporate world, if you’re using these tools to enforce contracts, again, that false positive rate—particularly for business-related content, which is what a lot of these tools have been trained on—is going to have a fairly high false positive rate. So the first thing people need to be very clear about is why are you using an AI detector? And is your purpose a good use of the technology? Spoiler, there really isn’t a great use of the technology for AI detection. And we’ll talk about why the technology itself is so flawed on this week’s live stream, which you can tune into Thursdays at 1 PM Eastern Time at TrustInsights.ai YouTube. But going back to the 5P Framework by Trust Insights, my biggest issue with these tools is that very often the purpose people are using them for is deeply flawed. Katie Robbert: And that, you can sort of generalize and say that, well, people don’t want AI-written content. They want content written by a human. So you could say that’s the purpose. So if this particular reader decided, I don’t want AI-written content, but this content is written by AI, this particular reader could have just moved along. But they decided to try and pick a fight. By the way, screenshots last forever. And it was a very unprofessional feedback session from this person, just as an FYI. And you know, if this person decided, okay, I feel like this is written by AI, let me put it through the detector and determine if this is written by AI. They could have just said, you know what? I don’t care for this. I don’t want this. Christopher S. Penn: Yeah, that’s what I always come back to is like, if you don’t want this, great, here’s the door. It’s like if people complain, oh, well, you didn’t write this fiction novel the way I wanted, well, then write your own damn novel. Right? No one’s stopping you from writing the novel you want to read. If you didn’t like the way I did it, go write your own and you’ll probably use AI to do it. This was the rather harsh commentary I had about Substack. Things like, we don’t really care if it’s human-written or AI-written. We care if it’s worth reading, right? If you’re publishing something that’s worth reading, there’s one Substack I subscribe to that is 100 percent AI-written. No editing passes. It is 100 percent Claude. You know it’s Claude because of Claude’s particular mechanisms. And I don’t care because the information is genuinely useful. I read it and go, I learned something. I don’t care who wrote it. I learned something. Katie Robbert: But that’s you and I, and I don’t disagree. People should be looking at it from that lens. But a lot of the general population is still stuck in the, AI is bad. It’s very black and white. Humans are good, AI is bad, don’t give me AI-written content. And so that’s still the challenge that we’re trying to overcome in the conversation that we’re trying to change. And so if their purpose is, was it written by AI, yes or no, then that’s what we have to work with, because that’s their purpose, not ours. Our opinion of their purpose is very similar to this reader’s opinion of my use of AI. As the old saying goes, opinions are like… well, you can fill in the blanks if, I won’t say it on the podcast. It’s very rude. But the point being is that you do need to figure out why you care if it was written by AI or not. And then you can go ahead and determine, was it high quality? Did I learn something? Was it useful? And then go back to the purpose, like, does it matter if it was written by AI? Now it brings up the bigger conversation, which Chris and I have talked about: AI disclosures and why those are important. And so in your newsletter, you do a very good job every week of disclosing. Here’s how much of this is AI. Here’s how I used AI. And I want to say thank you to the person who called me out because it reminded me this is a good opportunity to start doing my own AI disclosures so that hopefully we don’t continue to find ourselves in the situation of being called names. Christopher S. Penn: And so you cannot rely on them. I will give you a very solid example this week in my personal newsletter. I said, It’s 90 percent written by human. There’s 10 percent written by Claude. And I mark the section: This is what Claude said. And then just for giggles, I put it through the detector. And it said, Congratulations, it’s 100 percent human. I’m like, well, you clearly missed the part where I labeled it this is AI. So anyway, just more ranting about the tooling. The disclosures are important. And I do understand from some perspectives. There are some folks who correctly say they have problems with the ethics of AI companies or the environmental impact of AI. Totally get that, totally fair, completely reasonable. But again, it goes back to what you were saying, which is if we label it—which we all, everyone should be doing—and you are still mad, go read something that isn’t. There is an infinite amount of content out there that’s video or audio. Where I do have a problem and I think is very relevant to the conversation on the topic of AI detection is when it is not labeled or when it is intended to deceive. There is no shortage, for example right now on Instagram and TikTok, of various politicians making faked videos and photos. And thankfully they’re not doing it very well. But, okay, clearly that’s not a… that doesn’t work. But they are. The intent is to deceive. So if we go back to the 5P Framework by Trust Insights, their purpose is deception, right? And therein lies one of the valid reasons to want to use AI detectors to say, is this entity or person attempting to deceive me? Katie Robbert: I’m going to be, I’m going to challenge you on that for a second. Okay, so let’s say I’m a politician and I’m going to use AI. I can almost guarantee I’m not going to state that my purpose is deception. I’m going to state that my purpose is engagement, my purpose is attention. My purpose is oh gosh, anything probably except deception. So it’s interesting because like we can say as an outside observer, well, they’re trying to deceive us. They’re going to say with that lack of self-awareness, this is the way that I saw this thing happen. So, you know, I’m using the tools to reenact it or recreate the way that I see this. So it’s really an educational tool or whatever. So I do feel like it’s interesting that we’re saying their purpose is deception. They’re saying, no, that was never my purpose. Why would I ever want to deceive you? I’m totally honest. I’m showing you what’s possible. I’m showing you the way that I see things. Christopher S. Penn: And this gets us into the extremely deep and sticky morass known as AI ethics, which is again going back to the 5P Framework by Trust Insights. What is the purpose and is the purpose that you think you have aligned with the audience and the goals you’re trying to achieve? Because yes, attention can be a goal, but what’s the purpose behind that attention? Is it to garner more votes? Is it to beat the social media algorithms that are gatekeeping various viewpoints? What is the purpose of creating something that you know is not real? Katie Robbert: You are giving these fictional politicians a lot of credit for that deep thinking and self-awareness, but it does. You brought up AI ethics and Inbox Insights in the same issue this week coming up, where I talk about my process for using AI tools in my writing. You conclude a four-part series on responsible AI using our RAFT framework, and part four being transparency, which is really timely for what we’re talking about. One of the things that you bring up in that four-part series, and it’s brought up in a few of the different issues, is so companies whose mission statement is, and I’m paraphrasing—I apologize, Chris—something along the lines of companies who state out that they’re going to do bad things and they also are doing them, are technically following their own code of ethics. And so it’s the “do as I say, not as I do” or no, it’s the “here’s what: you do what you say and you say what you do, right?” So they do that. So therefore they are following a code of ethics. And that’s where, again, it gets really tricky. But I want to bring that up. Because responsible AI is not black and white. Ethics is not black and white. Christopher S. Penn: So no, and the reason for that is because ethics and morals are often conflated. They are different; they are completely different philosophical disciplines. But in the utilitarian ethics that a lot of the business world works on, “I do what I say and I say what I do” are essentially sort of the heart of that. So going back to the purpose of things like AI detectors, if you say this is real and it’s fake, that is unethical. If you say this is fake and it’s fake, that is ethical, right? It may or may not be moral. That is a different question because morals are based on the culture of the person and the culture that it occurs in. But from an ethics perspective, if I say this is fake and this is fake, I am behaving in an ethical manner. And so where this loops back around is to say, on the part of publishers and creators, we have an ethical obligation to be transparent and disclose. And on the part of AI detectors and the people using them, you have an obligation to be clear about what your purpose is. If your purpose is you just want to feel morally superior to someone else and you say that’s fine, you’re, I think you’re a jerk, but at least it’s clear. If you say that you’re trying to preserve the environment or what have you, but you really just want to feel morally superior, that is itself unethical because you’re not doing as you say and you’re not saying what you do. And so it is incumbent upon everybody using these tools in whatever capacity to disclose why you’re doing it and disclose how the results are going to be used. This is especially true for academia, for law, and for contracts. You have to be clear and say, we are using these tools for this purpose. And here is how we will measure the success of these tools. The performance, the fifth P in the 5P Framework by Trust Insights. You have to declare that, and if you don’t, yourself may have an ethics problem. Katie Robbert: I recently submitted an academic paper, and it was very clear in the instructions that I had to do a very large AI disclosure section on how AI was used to assemble the paper. And in that paper, if I recall correctly, I used AI to do the deep research. I then culled through the deep research to find the relevant parts for writing the paper for which I had a hypothesis. I drafted the paper. I used AI to help me clean up the paper and make it a more coherent story. And then I had to create two images, a graph and another supplemental image, and disclose what parts I used AI on. Here’s the question, though. So back to where we started, what do you do in the situation where you, the human, created the thing the detectors say, no, you didn’t? It’s AI and everybody believes the machines and not you. Like that’s not a matter of ethics anymore. That’s your reputation. Christopher S. Penn: And therein lies the problem with a lot of these detectors. The detectors are pattern matching. And again, we’ll talk about the mathematics of it this week on the live stream. But fundamentally, they’re looking at probabilities. And so if what you are creating, which academic papers in particular have a very specific kind of language to them that is highly formulaic, a pattern matching system—even if it’s 100 percent human-written—is still likely to pick it up. The example I often give is there’s a quote from Star Wars, from The Empire Strikes Back, where Yoda says, “For 800 years have I trained Jedi. My own council will I keep on who is to be trained.” Right? That’s Yoda. If you… if Yoda was to dictate that and then AI was to clean up the grammar, it would say, “I have trained Jedi for 800 years. I will keep my own council on who is to be trained.” Exact same words. AI’s just rearranging the word sequence, which dramatically changes the probabilities. And that second quote, which is still substantially the same as the first one, but with a different word order, will be flagged as AI or more likely be flagged as AI. Because in the process of editing, AI assembles things to the highest level of probability. And so for anybody, if you were doing that—as we often recommend—taking your phone out, doing a voice memo, and then having AI transcribe it and rearrange it, unless you know how to prompt it to preserve your word order, it’s going to change the language and it’s going to get flagged by AI. Even though you have proof from the voice memo itself that what you created was original. So a big part of what creators may want to think about, and this is the prescriptive part, is that I’ve actually talked about this with our friend Carrie Gorgon, who’s a lawyer. You may want to have a system where you preserve or even publish the work product that led to the final work product. I have done this with several of my books now where I publish the absolutely awful-to-listen-to voice recordings, like as I’m driving down the road. And you know, that’s usually in the deluxe edition, if you want to hear me yelling at people in traffic like, get out of the way, jackass. As part of the recordings, you can. But it also provides that provenance and lineage to say, here’s what the final product was manipulated by AI. Yes, here’s the original work product that proves that it’s a human original. Katie Robbert: But I think that also goes back to again, where we started. And you know, the commentary we referenced from Ann is that these tools are word prediction machines that have been trained on human words. We are the ones who taught it. Here are the predictable patterns that we use when we write and when we speak. Therefore, these machines, well or not well, are mimicking the way that we talk and the way that we write. Therefore, those AI detectors are detecting patterns that we taught as humans on our writing. Like it’s very… I feel like you go round and round forever. But the point being is that these tools are dangerous and can be very damaging if used incorrectly, which most people… Are using them incorrectly because they have the wrong purpose. Right? So if their purpose is to, I am angry and want to lash out at the world and I want to tear someone down today, congratulations. You are accomplishing your purpose with your performance. If your purpose, yeah, if your purpose is to like really just understand, then you know it’s going to be a while before these tools get more sophisticated. They’re not very good. Christopher S. Penn: No. And they never will because they’re always going to be reactive to whatever the latest models are capable of doing. It’s interesting. This actually inspires me as part of our upcoming AI for Writers course that we’re assembling for the Trust Insights Academy. But also maybe something that we should include is a skill that can assist people in creating stuff that sounds more like their human version. There are deterministic measures to do that, and maybe we’ll talk about that a little bit on the live stream as well. But if you’ve got some thoughts about AI detectors and their use or misuse, and you want to share them or your own experiences of dealing with them, post in our Free Slack Group. Go to TrustInsights.ai analytics for marketers where you and over 4,700 other marketers are asking and answering each other’s questions every single day. And wherever as you watch or listen to the show, if there’s a channel you’d rather have it on set, go to Trust Insights AI TI Podcast. You can find us at all the places fine podcasts are served. Thanks for tuning in. Talk to you on the next one. Speaker 3: 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 Robert 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. Trust Insights 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 and 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 LA. Trust Insights provides fractional team members such as 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 Live Stream webinars and keynote speaking. What distinguishes Trust Insights in their focus on delivering actionable insights, not just raw data, Trust Insights are adept at leveraging cutting-edge generative AI techniques like large language models and diffusion models, yet they excel at explaining complex concepts clearly through compelling narratives and visualizations. Data storytelling this commitment to clarity and accessibility extends to Trust Insights 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’re 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.

Connected TV is becoming a performance marketing channel. Alison Clark, CTV and Go-to-Market Strategy Lead at AdRoll, breaks down why CTV is merging with digital advertising. She explains how video fits inside a unified digital strategy, why omnichannel buys across TV, display, and social work as one plan, and how brand perception now feeds AI-driven marketing outcomes.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Connected TV is becoming a performance marketing channel. Alison Clark, CTV and Go-to-Market Strategy Lead at AdRoll, breaks down why CTV is merging with digital advertising. She explains how video fits inside a unified digital strategy, why omnichannel buys across TV, display, and social work as one plan, and how brand perception now feeds AI-driven marketing outcomes.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Connected TV is becoming a performance channel, not just a brand play. Alison Clark, CTV and Go-to-Market Strategy Lead at AdRoll, explains how video fits inside a unified digital strategy. She breaks down why marketers should stop separating CTV from digital advertising, how omnichannel buying across television, display, and social works as one strategy, and why brand perception now shapes AI-driven discovery.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Connected TV is becoming a performance channel, not just a brand play. Alison Clark, CTV and Go-to-Market Strategy Lead at AdRoll, explains how video fits inside a unified digital strategy. She breaks down why marketers should stop separating CTV from digital advertising, how omnichannel buying across television, display, and social works as one strategy, and why brand perception now shapes AI-driven discovery.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Connected TV is becoming a performance marketing channel. Alison Clark, CTV and Go-to-Market Strategy Lead at AdRoll, brings 20 years of media experience across programmatic, CTV, digital, and linear. She explains why video will fold into digital strategy rather than stay siloed, how omnichannel buying spans television, display, and social in a single plan, and why brand perception now shapes performance in an AI-first world.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Connected TV is becoming a performance marketing channel. Alison Clark, CTV and Go-to-Market Strategy Lead at AdRoll, brings 20 years of media experience across programmatic, CTV, digital, and linear. She explains why video will fold into digital strategy rather than stay siloed, how omnichannel buying spans television, display, and social in a single plan, and why brand perception now shapes performance in an AI-first world.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Summer Remix: Album 8 Track 6 - Step Up. Speak Up. Move Up. w/Shawna HausmanBrand Nerds, get ready to take some serious notes! On this episode of Brands, Beats and Bytes, hosts Darryl "DC" Cobbin and Larry "LT" Taman sit down with retail and digital marketing powerhouse Shawna Hausman. From her scrappy early days in the Gap Inc. universe to driving a massive 300% sales increase as CMO of FSA Store, Shawna has built an incredible career by stepping up, speaking out, and never letting fear dictate her next move.Shawna takes us behind the scenes of some of the most iconic retail brands, sharing hilarious and anxiety-inducing stories, like the time she told retail legend Mickey Drexler that his marketing wasn't working when she was just a 22-year-old intern! We also dive deep into the modern marketing landscape, discussing everything from the rise of AI to why heritage brands like Birkenstock are winning by refusing to compromise their identity.Whether you are looking to climb the corporate ladder, pivot into consulting, or simply understand the psychology of retail sales, this episode is packed with "Triple C" leadership advice: Clarity, Conviction, and Courage.What You'll Learn in This Episode:The Mickey Drexler Story: How a bold critique from a young intern led to an unexpected seat on the corporate jet with the "Merchant Prince" himself.Avoiding the "Mushy Middle": Why brand overlap (like the historical dynamic between The Gap and Old Navy) can eat your own market share, and why you must carve out distinct lanes.The Power of Executive Buy-In: Shawna gets vulnerable about her biggest career "F-up" involving an unapproved $40,000 app at West Elm, and why you absolutely need skin in the game from your key overlords.Embracing AI: Why marketers must lean into artificial intelligence tools rather than fearing them, and how it is revolutionizing the way we work today.The Birkenstock Strategy: How "winning ugly," maintaining scarcity, and leaning unapologetically into comfort and heritage is keeping Birkenstock at the top of the footwear game.Fearless Career Growth: Why you should never stay in a miserable job just for the money, and how taking calculated risks leads to the real magic.Don't forget to subscribe, rate, and share with a fellow Brand Nerd!Instagram | LinkedIn

Most marketers still treat CTV as separate from digital. Alison Clark, CTV and Go-to-Market Strategy Lead at AdRoll, brings 20 years of programmatic, CTV, and digital media experience to make the case for CTV's performance era. She explains why video belongs inside your digital strategy, not beside it, and how omnichannel buying across television, display, and social works as one strategy. She also covers why brand perception now shapes AI-driven discovery and outcomes.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Most marketers still treat CTV as separate from digital. Alison Clark, CTV and Go-to-Market Strategy Lead at AdRoll, brings 20 years of programmatic, CTV, and digital media experience to make the case for CTV's performance era. She explains why video belongs inside your digital strategy, not beside it, and how omnichannel buying across television, display, and social works as one strategy. She also covers why brand perception now shapes AI-driven discovery and outcomes.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Connected TV is becoming a performance marketing channel. Alison Clark, CTV Go-to-Market Strategy Lead at AdRoll, brings 20 years of media experience across programmatic, CTV, digital, and linear. She explains why video strategy is merging into digital strategy instead of standing apart. Learn how omnichannel buying across television, display, and social works as one campaign, and why brand matters as much as tracking in an AI-first world.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Connected TV is becoming a performance marketing channel. Alison Clark, CTV Go-to-Market Strategy Lead at AdRoll, brings 20 years of media experience across programmatic, CTV, digital, and linear. She explains why video strategy is merging into digital strategy instead of standing apart. Learn how omnichannel buying across television, display, and social works as one campaign, and why brand matters as much as tracking in an AI-first world.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Connected TV is shifting from a brand awareness play to a performance channel. Alison Clark, CTV Go-to-Market Strategy Lead at AdRoll, brings 20+ years across programmatic, CTV, digital, and linear media. She explains why video belongs inside your digital strategy instead of being managed separately, how omnichannel media buying works across TV, display, and social as one strategy, and why brand perception now feeds AI-driven performance.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Connected TV is shifting from a brand awareness play to a performance channel. Alison Clark, CTV Go-to-Market Strategy Lead at AdRoll, brings 20+ years across programmatic, CTV, digital, and linear media. She explains why video belongs inside your digital strategy instead of being managed separately, how omnichannel media buying works across TV, display, and social as one strategy, and why brand perception now feeds AI-driven performance.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.