239: Personalization is a creativity problem not a data problem, with Christina Garnett

What's up everyone, today we have the pleasure of sitting down with Christina Garnett, Fractional Chief Customer and Communications Officer at Neuemotion.(00:00) - audio-Christina (01:19) - In This Episode (05:37) - Why Your Tech Stack Cannot Fix Siloed Customer Teams (11:10) - Why Getting the Name Right No Longer Counts as Personalization (18:08) - Why A/B Testing Programs Ignore Qualitative Customer Data (24:14) - How Brands Build Core Memories Customers Cannot Buy (29:55) - How B2B Brands Build Core Memories Without a Budget (35:46) - What to Do When Transactional, Behavioral and Feedback Data Disagree (42:12) - Why Spotify Wrapped Works and What Gen AI Took Away (49:17) - Why Personalization Feels Predatory Even When You Have Consent (53:58) - Where Influence Ends and Manipulation Starts in Marketing (58:57) - Why Audiences Are Going Back to the Humanities in the AI Era Summary: Christina spent 5 years teaching math before she ever wrote a subject line, and it shows in how ruthlessly she takes apart the personalization playbook. Getting someone's first name right used to be impressive and now it just proves you didn't get fired, which leaves marketers chasing hooks and tricks while customers quietly learn to read the pattern. She makes the case for core memories a brand cannot buy, walks through what actually happened when Spotify Wrapped got the AI treatment, and introduces earned context, the idea that having someone's data and having the right to use it are 2 completely different things. Along the way she calls CX and brand the same job, refuses to bet her life on NPS, and explains why the B2B move nobody is making costs almost nothing. If you have ever shipped a perfectly segmented campaign that landed with a thud, this one will tell you why.About Christina GarnettChristina Garnett is a fractional Chief Customer and Communications Officer at Neuemotion and the founder and principal at Pocket CCO, where she builds customer trust systems for agencies and SaaS companies. She's the author of Transforming Customer-Brand Relationships, which won the Independent Press Award and the International Impact Book Award and was a Foreword INDIES finalist, and she's currently writing a second book built on the Customer Trust Equation she created.Before going independent she built customer advocacy at HubSpot, growing the HubFans program from 0 to 37,000 members and more than 4,000 active advocates, and she led social and customer strategy at global scale through ICUC. She's a contributing writer at Campaign US, was previously a byline at Adweek, and she started her career as a teacher.Why Your Tech Stack Cannot Fix Siloed Customer TeamsEvery few years a software category shows up promising to end the silo problem. The CRM was going to do it. Then the customer data platform. Then the customer 360, the composable stack, and whatever the warehouse-native vendors are calling it this quarter. Marketing, support, social, and CX all get wired into the same tables, and everyone assumes shared data will produce shared behavior. Buy the integration, get the alignment.Christina has been on enough of those teams to know how that ends.She came into marketing sideways, an English major who taught math for 5 years, including a stretch at a school built for kids with learning differences where she trained in the Orton-Gillingham method. That method exists to move information from short-term into long-term memory. Marketers have a word for the same thing and call it brand recall. Her husband told her early on that she should go into advertising because she couldn't watch an ad without rebuilding it in her head, tweaking the copy, cutting the music, fixing whatever was broken. She went and took every course, read every book, and kept the teacher's instinct the whole way through: make the hard thing make sense, find the right words for the room you're in.Then she sat at basically every table that claims part of the customer, working as a social listening strategist, a social media creator and a social media strategist, and putting time into support, CX, community and advocacy. What she kept finding was the same organizational failure repeating under different logos, and no amount of shared tooling moved it.Here's the argument that runs under her whole book. Nobody is solving customer experience alone, because nobody is the only person reaching the customer. Support talks to them, so support gets blamed for the relationship. But your UX team is shaping what the customer can and can't do, whether they think of that as CX work or not. Your legal team is writing the fine print the customer reads at the worst possible moment. Finance sets the refund window. All of it builds the relationship, and most of it never appears on anyone's CX dashboard.The result is a company that's genuinely excellent in one place and quietly hostile in another, and it shows.That's why the material became a book rather than a framework or a course. A framework asks you to already agree with its premise before you'll use it. Christina wanted the thing she'd been hunting for on shelves and never found, written for the people at all of those different tables at once. Her words on it: "I think we all wind up writing the books that we wish already existed." The structure follows the problem in 3 moves:Every moving piece that actually builds a brand relationship, most of which sits outside the CX team., Community as the silo killer, the thing that finally forces those teams into the same room., What happens when something lands that you had no way of seeing. A brand crisis, an acquisition by a company your customers hate, or AI arriving and throwing the whole operating model in the air.That third one is where most companies are living right now, and it's the least rehearsed. The martech buying cycle keeps funding integration projects because integration is something you can purchase, and cross-functional accountability is something you have to negotiate. Until one person owns the customer relationship end to end on paper, a new platform just gives 4 teams a shared place to file work they still refuse to coordinate.Key takeaway: List every team that shapes your customer's experience, including the ones that never speak to a customer. Legal writes the cancellation language, UX decides how buried the downgrade button is, finance sets the refund window, and none of them get counted. Put all of them on one page and mark who currently owns the customer's experience of each moment. The blanks are your real CX roadmap, and no platform purchase will fill them in for you.Why Getting the Name Right No Longer Counts as PersonalizationAccuracy in a lifecycle program has never been cheaper. You can segment by behavior, by lifecycle stage, by predicted churn, by what someone hovered over last Tuesday, and the tooling will do all of it on a mid-tier plan. Ask a marketer whether their email is personalized and they'll show you the merge fields and the branching logic and say yes.Ask the person receiving it and you get a different answer. Christina's position is that martech made accuracy so cheap that creativity started to look like a nice-to-have, and customers noticed long before marketers did.Her frame for the whole industry is the Jeff Goldblum line from Jurassic Park, the one about scientists so preoccupied with whether they could that they never stopped to ask whether they should. We're living inside that meme, she says, running on a lot of we could so we can. And the cost shows up somewhere marketers rarely look, which is in what we've trained people to expect.Conditioning is real, and it doesn't require a marketing degree. Somebody w...

What's up everyone, today we have the pleasure of sitting down with Aditya Vempaty, VP of Marketing at Coram AI.(00:00) - Intro (01:07) - In This Episode (05:05) - Why Expansion Revenue Beats New Logos When Channels Are Saturated (06:07) - Why Customer Empathy Means Knowing What Gets Your Buyer Promoted (12:38) - How to Tell If Your Case Study Makes the Customer the Hero (18:16) - Why Single Channel Attribution Hides the Journey That Closed the Deal (22:00) - How to Find Real Customer Problems by Paying for 30 Minute Interviews (30:29) - The 3 Levels That Connect Marketing Strategy to Tactical Execution (36:32) - Why Implementation Speed Is the Real Answer to a Migration Objection (42:12) - The ABM Play You Can Build From Your Closed Won List Today (48:46) - How Marketing Leaders Get a Team to Actually Adopt an AI Tool (53:26) - How Marketing Leaders Decide What Deserves Their Energy Summary: Aditya has built marketing functions and named categories from nothing at Synthego, Amplitude and Nutanix, and he shows up here to argue that the loud top of funnel work is now the cheaper half of the job. He takes apart the make your customer the hero cliche with a test you can run on any case study in about 4 seconds, then explains why he pays customers $100 for 30 minutes before he will even look at the product he was hired to market. There's a story about harvesting a competitor's free tier badge off customer websites, a telco onboarded in 6 weeks, and a VP of marketing spending 15 minutes making a poster so his team would actually use AI. He also has a very short answer for what your ChatGPT persona document is worth. Stick around for the part where 95% product parity turns into the only argument that reliably wins a migration deal.About Aditya VempatyAditya Vempaty is the VP of Marketing at Coram AI, an AI physical security platform running across more than 1,500 locations. Before that he spent 3 years as VP of Marketing at MoEngage, where the company grew from $58M to $100M in ARR. Earlier in his career he built the marketing function and named the category at Synthego, Amplitude and Nutanix, work that spans 2 IPOs and several unicorns.He also invests as an angel, mentors at First Round Capital, and is known for 2 rules he repeats often: market the problem first, and distribution is the strategy.Why Expansion Revenue Beats New Logos When Channels Are SaturatedEvery marketing team has a number on the board for new logos. Far fewer have one for what happens to a customer 6 months after the contract gets signed. That made sense when acquisition was cheap and a paid dollar reliably bought you a lead. Channels are crowded now, budgets are flat, and the math has moved.Aditya has spent his career at the loud end of marketing. He helped name the product analytics category at Amplitude. He helped define the agentic customer engagement platform at MoEngage. Those are top-of-funnel plays, the kind where you plant a flag and get the industry to repeat your words back to you. So it's a fair question why the category creation guy now spends his time talking about heroes, lifecycle and retention.His answer is arithmetic.For a marketer defending a budget, the second half of that sentence matters more than the first. Cheaper is the obvious part. Easier to show impact is the part that should change how you plan. Every acquisition attribution fight you've ever lost, where the CFO wants to know which of your 6 channels made the lead buy, goes away when the account is already in the building and you can see exactly what they did and didn't adopt.The shape of the products matters too. Amplitude and MoEngage are both multi-product suites. Customers land on one thing, get value, and then expand into the rest. So the second, third and fourth sale are already sitting inside your customer base, and nobody has to be convinced you exist. Aditya points to HubSpot's version of this, where the funnel is a loop rather than a line, and treats the loop as the actual revenue machine instead of a diagram in a deck.Here is the uncomfortable version. Most B2B marketing orgs are staffed and measured around the most expensive, least provable part of the job. If expansion is where the margin actually is, the demand gen team should carry a retention or adoption number, and most demand gen teams would fight you hard on that.Key takeaway: Pull the last 4 quarters of revenue and split it into new logo, expansion and renewal. If expansion is the bigger line and nobody in marketing carries a number against it, claim it before the next planning cycle starts. Pick the one product line your existing customers adopt second and build the campaign for that.Why Customer Empathy Means Knowing What Gets Your Buyer PromotedCustomer empathy is the most repeated phrase in B2B marketing and the least examined one. It shows up in every kickoff deck, every messaging workshop, every values page. Ask what it produced and you usually get a persona document nobody has opened since it was made.Aditya spent years on the vendor side of exactly this, at 2 companies that sit in the middle of the funnel where marketing ops and lifecycle people live. He saw how the sausage gets made, and he came out of it with a low opinion of the word.What replaced it is much more specific and much more useful. Sitting inside those companies taught him that the thing worth understanding about a buyer is their job justification. How does this person prove they were worth their salary this year? How do they get promoted? Your product either helps them say that sentence out loud or it does not.At Amplitude the answer was retention. Product managers in B2C couldn't track what they were doing and couldn't justify their own existence and investment. The industry was obsessed with mobile acquisition at the time, so the question that actually kept a PM up at night was how to keep the users they had already paid for and how to show the product was giving those users value. Amplitude built the whole marketing motion around that metric because that metric was the PM's career.At MoEngage the pain had moved. Retention was table stakes by then and everyone was already on mobile and web. The problem had become execution across channels, and the version Aditya describes is painfully familiar to anyone who has run campaigns at a big company. You have every channel available to you and no ability to say what you actually did. He describes marketers who legitimately can't come back and report which campaign hit, where it hit, and which users it reached across the full cycle. Teams operated as channel owners rather than as one coordinated effort.Then he gives the number that makes it real. One customer took 6 weeks to launch a campaign, because getting the segments required 20 people on a SQL query team pulling across 5 databases. 6 weeks. For a campaign. That's the daily texture of the job for the person you're selling to, and no amount of empathy language on a website touches it.Here is the payoff. When your product lets someone explain their value in a simple way that other people understand, they stop being a customer and start being an advocate. As Aditya says, they will rave about you because you made their life easier and their job explainable.Most vendor positioning is aimed one level too high. It addresses the company's pain, churn and efficiency and cost, while the person signing the order form has a smaller and more urgent problem, which is that they can't prove what they did last quarter. That mismatch is why so much martech messaging reads as true and lands as nothing.Key takeaway: Write down the exact sentence your champion would say in ...

What's up everyone, today we have the pleasure of sitting down with Mary Keough, Fractional Demand Gen for B2B at DemandLoops.(00:00) - Intro (01:12) - In This Episode (04:30) - How to Write LinkedIn Posts That Hit a Nerve Without AI (06:39) - How to Run an Honest Goal Setting Conversation With Your Founder (14:46) - Why Marketing Always Catches the Scope Creep at Startups (18:39) - How New Marketing VPs Establish Credibility in Their First Month (28:30) - How Women in Marketing Leadership Get Out of the Marketing Girl Box (33:49) - How to Tell if a Founder Who Doesn't Get Marketing Will Trust You (36:54) - What a VP of Marketing Job Description Should Actually Say (39:12) - When to Fight for a Broken Marketing Role and When to Leave (44:43) - Why Fractional Marketing Leadership Works as a Stopgap and Fails Long Term (49:53) - How to Vet a Marketing Role by Talking to People Who Left (53:17) - How to Use a Family Value System to Decide What Deserves Your Energy Summary: Mary wrote a LinkedIn post listing every fear a senior marketer has about taking a VP of Marketing job, and it hit a nerve loud enough to become this entire episode. We take the fears apart one at a time: the goalpost that moves the week after your team clears it, the executive dinner that quietly becomes 6 more events, the launch strategy your boss never opens. Then we build the other side of it, including the 3 sentence job description she'd sign tomorrow and the written SLA that stops sales from eating 4 days of your designer's week. She also explains why the fractional model everyone is rushing toward is a stopgap, and why her own contracts are designed to end. Stick around for the performance review where nothing went wrong and it still nearly took her out.About Mary KeoughMary Keough is a fractional demand gen marketer at DemandLoops, where she builds B2B demand programs that are designed from day one to be handed back to a permanent hire. She has spent 15 years across B2B SaaS and industrial manufacturing marketing, most recently as Director of Demand Generation at CoLab Software, and before that as Head of Marketing at Map My Customers and Senior Marketing Strategist at Gorilla 76.Her roots are in industrial and manufacturing demand gen, a niche she cut her teeth on at Spraying Systems Co. and still speaks about at events like the Industrial Marketing Summit. She's built an audience of roughly 30,000 on LinkedIn writing candid, fundamentals-first posts, and she co-hosts the Purposeful Marketing Podcast.How to Write LinkedIn Posts That Hit a Nerve Without AIYou can spot them before you finish the first line. Same hook shape, same clipped one-line paragraphs stacked into a wall, same closing question nobody answers. B2B LinkedIn has gotten very good at producing posts that read like posts, and the feed is worse for it.Then something like Mary's shows up. Her post about VP of Marketing roles was a stacked list of fears, one after another, written against the line founders keep repeating about not being able to find good candidates. It went around because a lot of senior marketers had been carrying those fears for years without the words for them. That feeling of reading your own thought in someone else's sentence is rare, and it's almost never something a hook formula produces.Originality is the entire filter for her, and applying it kills most content calendars on contact. Mary doesn't pre-plan posts. An idea sits with her for a while, usually something that's been bothering her that she can't quite name yet. Then a conversation does it: a marketer venting, a thread she can't scroll past, a call with a potential client. Something tips her over the edge and the post writes itself.Not a single one of her posts has been written with AI. She says it flatly, and you can tell from the drafts: the scar tissue is right there on the page, and the sentences go where an editor would have smoothed them. The cost of that is inconsistency. She posts when she has something, and only then. The return is that when she does post, it carries the one thing a language model cannot manufacture, which is the specific irritation of a person who has actually lived the problem.The volume play is finished. When any competitor can generate a competent, on-brand, keyword-aligned post in 30 seconds, competence stops being a differentiator and originality becomes the only moat left. Most B2B content operations are structurally incapable of producing it, because they're built to hit a cadence rather than to publish the thing only their company could say.Key takeaway: Run every idea on your content calendar through Mary's filter before it gets assigned: if 10 other companies in your category could publish the same piece, kill it. Replace the slots you clear with a standing prompt to your team, asking what has annoyed them at work this month that they can't fully explain yet. Those are the posts that travel.How to Run an Honest Goal Setting Conversation With Your FounderMarketing targets in most startups get set the way weather forecasts get set in a bad novel, which is to say somebody decides what would sound good and then everyone agrees to act surprised when it doesn't happen. The CMO needs a board-friendly story. The investor update needs an AI angle. Almost none of it starts from historical numbers, and the marketing leader gets handed the result and asked to commit.Mary's diagnosis starts a layer above the number. Companies keep saying they need a great VP of Marketing, an awesome VP of Marketing, an amazing director of demand gen. Very few of them are willing to do the work that makes a great one want the job. And the work starts with a company vision that has actual business goals underneath it.The version she wants runs down a ladder. There's the grand vision, the thing that got the company funded in the first place. Under it sits a 1-year and a 3-year picture of what changes in the market if the company wins. Under that sit the business goals that get you there, segmented by department, so product, marketing, and sales each know what they own.She walks through it with an attribution example, mostly because it's easy and partly because she can't resist. Say the company vision is to get founders, CEOs, and marketers to start caring about attribution. Fine. Now what does product build in the next 12 months to make that true? What does marketing publish? What does sales say on calls? Every function can answer that question, and the answers can be checked against each other.That ladder is almost completely gone from the startups she sees. What's left is the revenue multiple, which is a wish, and a set of quarterly targets that get reverse-engineered from it. Marketing is usually the first function asked to sign for the gap.The line that stuck with me is her framing of the whole discipline: everything about marketing is simple and fundamentals driven, and simple has nothing to do with easy. The hard part isn't figuring out what to do. The hard part is that you're doing it inside politically driven motivations, shifting strategies, and goalposts that move whenever the board asks a new question.How to Push Back When Product Wants to Change the ICPAnyone who has worked at a startup knows the move. You spend a year building a content engine around marketers, the quarter goes well, product decides the real opportunity is salespeople, and suddenly your entire library is pointed at the wrong buyer. Product changes a few things in the roadmap. Marketing starts over, and the results of that restart won't show up for 12 months.Mary's honest about the limits here. Preventing the shift is difficult, so you mitigate it...

What's up everyone, today we have the pleasure of sitting down with Julie Beynon, Head of Analytics at Augment Code.(00:00) - Intro (01:07) - In This Episode (04:13) - Breaking Into Data Without A Computer Science Background (06:05) - Why AI Made Building Cheap But Maintenance Expensive (09:25) - How To Push Back On AI Projects Without Killing Momentum (12:28) - Building AI Agents That Multiply A Two Person Data Team (16:29) - When Not To Reach For AI At Work (22:23) - Running A Lean Data Team As A Force Multiplier (27:28) - The Spreadsheet Test For Keeping Your Data Stack Simple (31:49) - How To Prove The Value Of Invisible Data Work (39:14) - Why Data Analytics Is Becoming GTM Operations (41:47) - What Part Of The Data Analyst Job AI Is Replacing (47:15) - The Data Skills AI Can't Replace (52:07) - How To Decide What Deserves Your Energy Summary: Julie Beynon came into data sideways from content marketing, got cut down to 2 words by a CEO, and turned that into a 15-year career running lean data teams. In this episode she breaks down how she cloned her best analyst into an AI agent named JimBot, why she pushes back on AI projects without ever saying no, and how she gets companies to fund the invisible foundation work nobody claps for. She makes the case that AI knocked down the SQL wall, so the real bottleneck moved to the data model underneath, and that simple is now the hardest skill in the room. There's a spreadsheet test, a team of 2 that runs like 10, and a surprisingly hopeful take on AI making us more human. Stick around for the part where she explains why the boring option takes the most nerve.About Julie BeynonJulie Beynon is the Head of Analytics at Augment Code, an AI coding assistant company, where she runs a lean data team and builds AI agents that let the whole company self-serve trusted answers. She's spent roughly 15 years in data and go-to-market analytics, previously leading data at Census and analytics at Clearbit, with earlier stops at Customer.io and other startups.She's self-taught and came into data sideways from content marketing, with no computer science background. Alongside the day job she writes a series of short essays on data, AI, and the discipline of knowing when not to reach for a tool.Breaking Into Data Without A Computer Science BackgroundMost people assume the path into data analytics runs through a computer science degree or at least a few years buried in SQL. Julie's route looked nothing like that. She started as a content marketer, and by her own account she was bad at it. Her CEO once edited a piece of her writing down to 2 words.That kind of feedback breaks a lot of people. It did the opposite for her. Getting cut down that hard built a habit of raising her hand for whatever nobody else wanted to do, and the thing nobody wanted to touch was data. The real turn came at Customer.io, where a new tool called dbt showed up and someone offered to train her on it. She figured saying yes would be silly to pass up, and within a few sessions the whole job changed shape.The moment she describes is the one every self-taught analyst recognizes. You take a pile of raw rows nobody trusts, run it through a model, and suddenly you're holding something a whole company can use. She calls it realizing what power she had just yielded. The intuition that makes her good now got built out of the failures that came first, then an open door she was willing to walk through. Coming at data from content rather than engineering is why she reads the business side so well, because she learned the questions before she learned the syntax.Key takeaway: Volunteer for the messy, unowned work on your team, especially the data nobody wants to clean. Pair it with one modern tool you can learn hands-on, like dbt, and get a colleague to walk you through a real project rather than a tutorial. The reps you build on work nobody else will do become the skill set that's hardest to replace later.Why AI Made Building Cheap But Maintenance ExpensiveAI has made it trivial to spin something up. A dashboard, a workflow, a scrappy internal tool, all of it now takes an afternoon and a few prompts. The problem is that the fun part and the expensive part were never the same part. Julie's been making this argument since before AI showed up, in a build versus buy post she wrote 5 years ago, and the tooling change only sharpened it.Here's the trap she watches teams fall into. Someone builds a slick dashboard because they can, everyone's impressed, and then 6 months later sales walks up asking why a number moved. There's data drift, nobody remembers how the thing was wired, and the person who built it isn't the one who has to answer for it. She's the one who answers for it. So before anything gets built on her watch, she runs it through a short set of questions:Is this mission-critical, or just fun to make?, Who owns it and who maintains it when it breaks?, Is there an off-the-shelf tool that costs less per month than the tokens it takes to build and run this?That last one lands hard. You can burn $1,000 building something that replaces a tool costing $5 a month, and feel productive the whole time. The cheap build is a real cost hiding as a win. Maintenance never got cheaper, which means the discipline that matters now is refusing to build the thing you're perfectly capable of building.Key takeaway: Before you build anything with AI, price the maintenance, not the build. Ask who owns it in 6 months, whether it's mission-critical, and whether a paid tool would cost less than the tokens you'll spend building and running your own version. If the honest answer is that you're building it because it's fun, buy the tool instead.How To Push Back On AI Projects Without Killing MomentumOps and data people carry a reputation as the team that says no. Every shiny new tool, every "we should build this," runs into someone whose job is to point out that you already own 2 things that do the same job. That instinct matters more than ever now that anyone can build anything. It also curdles fast into being the person nobody wants to bring ideas to.Julie's answer is to almost never say no at the door. There's a real constraint underneath her patience, since on the data side you have an actual duty to protect the data and the security around it, so some requests genuinely can't fly. Outside of that, she lets people run.That quote comes from a specific win. One of her engineers built a proof-of-concept dashboard for a new product. It worked. Instead of telling him to stop, she treated it as a starting pad and let him take the first pass as far as he wanted. AI helped him productize and visualize what he was thinking. Then, when the question became how to make it sustainable, she stepped in and rebuilt it as a stable dashboard in their BI tool with observability and role-based access control baked in. The engineer knew every data point and how it was tracked, so she pulled the context straight out of his code instead of extracting it from him in a meeting. She calls it one of the most productive data cycles she's had. Letting someone go a few steps before you take the wheel turns pushback into a handoff, and the person feels seen instead of shut down.Key takeaway: When someone brings you an AI-built prototype, resist the reflex to kill it. Let them take the first pass all the way, then offer to productize it yourself, pulling the logic and context out of their code rather than dragging it out of a meeting. Reserve your hard no for genuine security and data-protection lines, and treat everything else as a draft you can finish.Building AI Agents That Multiply A Two Pers...

What's up everyone, today we have the pleasure of sitting down with Stéphane Hamel, Founder and Product Architect at MANTIS.(00:00) - Intro (01:07) - In This Episode (04:07) - How To Audit Which Trackers Are Firing On Your Website (07:00) - Why Nobody On Your Team Owns The Tags Firing On Your Site (11:22) - Why Your Consent Banner Does Not Match What Your Site Actually Does (16:45) - Does Server Side Tagging Actually Improve Privacy Governance (22:30) - Why Loading A Third Party Script Is Already A Privacy Risk (27:30) - What Happens When You File A Privacy Complaint In Canada (36:42) - Why AI Output Is Useless Without Domain Expertise (41:58) - Is AI Removing The Training Path For Junior Marketers (44:16) - When Vibe Coding Works And When It Falls Apart (47:56) - Why Marketing And IT Still Fight Over Who Maintains The Stack (52:02) - How To Decide Which Projects Deserve Your Energy Summary: Stéphane Hamel built the first web analytics QA tool back in 2006, watched an ad blocker quietly borrow his logic, and spent the next 20 years learning that tracking got harder to see every year while the industry got better at documenting it. Now he's building MANTIS, a privacy observability platform that watches what a website actually does instead of what its policy claims. Along the way he audited his own credit bureau account after a breach, found trackers from companies that no longer exist sitting on the page displaying his credit file, and spent 2 years fighting to get them removed. He also coined the term vegetative AI, sold his house and furniture after one good vacation in the Rockies, and will tell you your consent banner is a receipt for a transaction nobody actually agreed to. Wait until you hear what a third party script collects before it fires a single tag.About Stéphane HamelStéphane Hamel is the founder and product architect of MANTIS, a privacy observability platform built to show what a website actually does at runtime rather than what its policy claims. He's spent 35 years across the full arc of digital analytics, building WASP in 2006 as the first web analytics quality assurance tool, publishing the Digital Analytics Maturity Model in 2009, and creating Da Vinci Tools, which was later acquired by Supermetrics.He teaches MBA and EMBA students at Université Laval and advises privacy tech startups including Supermetrics, Caden, and Masthead Data. He's currently writing his first book on digital analytics concepts, and having been a victim of 2 of Canada's largest data breaches, he treats privacy as a trust problem rather than a legal one.How To Audit Which Trackers Are Firing On Your WebsiteOpen the network tab on your own company's homepage and count the outbound requests. Most marketers who try this land somewhere between 40 and 100 calls going to domains nobody on the current team approved. In 2006 that number was small enough to check by hand, and the only question worth asking was whether your analytics tag fired on the right page at the right moment.That's the question Stéphane built WASP to answer. He was on the technical side back then, implementing trackers on client websites, and nobody in the room was talking about privacy or where any of this data ended up. The tool checked whether tags fired when they were supposed to and whether they collected the right information. It was quality assurance work, and it was the first tool of its kind.That shift wasn't academic. Stéphane got hit by data leaks more than once, watched fraud follow, and spent 35 years consulting and teaching through every generation of the tracking stack. MANTIS is what came out the other side, and it asks a very different question than WASP did.The new question has 3 parts:What is actually loading on this website in terms of trackers, Whether any of those trackers fire without consent, What kind of data each one collects once it doesThe hard part is the chain. Websites include third party scripts that load other scripts, a pattern Stéphane calls piggybacking, and every hop moves further from anything a marketer ever approved. Fingerprinting rides along in the same traffic. By the time a script 4 hops deep does something it shouldn't, nobody on the marketing team can name what triggered it or say where the data went.So MANTIS is built for people who don't read network waterfalls for a living. Marketers, decision makers, privacy specialists, and the technical folks stuck doing QA on tags all need to see the same picture, and right now they each see a different slice of it. The industry spent 20 years getting very good at deploying tags and almost no time getting good at watching them. That gap is why most privacy programs audit documents instead of traffic, and why the documents keep passing while the traffic keeps failing.Key takeaway: Run your own homepage through a network inspector before you click anything on the consent banner, and write down every third party domain that already received a request. Compare that list against the vendor list your consent management platform declares. Any domain in the first list that's missing from the second is a gap you own right now.Why Nobody On Your Team Owns The Tags Firing On Your SiteAnyone can inspect a page now. Right click, open the debug console, watch the calls go out live. That was exotic in 2006 and it's table stakes today, which raises a reasonable objection to the whole category of tag surfacing tools. If the browser already shows you everything, what's left to build?Stéphane's answer is that the console shows you the calls and tells you nothing about who authorized them. Working with technical people for 35 years, he's watched the gap widen. The traffic is visible. The accountability is gone.There's a story from the WASP years he still turns over. Someone messaged him saying the tool should block the tags it found. He said no, that's not the purpose, the purpose is quality assurance. Shortly after, ad blockers took off, and he found some of his own logic sitting inside one of the very first ones. He had no way to prove it and no means to enforce anything. He was one guy solving his own problem, and the industry took the idea somewhere he hadn't intended.20 years on, the reason tags go unowned has less to do with technology than with how many people handle a single pixel on its way to production. Stéphane walks through the cast:The marketer, who asks for something and moves on, The software engineer, or the data engineer, depending on which fancy name the org uses this year, Legal, who reviews the words and doesn't get the technical constraints, The consent management platform vendor, whose position is that they provide a tool and don't provide legal adviceThat's 4 groups, and not one of them can describe the whole system. That's before you count the agency your marketing lead handed tag manager access to, the one that said trust us, we know what we're doing, we're just going to put a tag on your website. Then somebody runs an audit 2 years later and finds tags firing that nobody recognizes.Here's the part that should bother you more than it probably does. Every single tag is a privacy risk and a security risk at the same time. The moment you put third party JavaScript on your site, you've given someone else write access to your users' browsers, and that script can change tomorrow without telling you. It might start recording keystrokes. It might start fingerprinting. Stéphane notes that vendors coming out of the US tend to be particularly greedy about collection, and none of that requires a new contract or a new conversation.What MANTIS does about it is draw a timeline. You got consent at t...

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...

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 ...

What's up everyone, today we have the pleasure of sitting down with Sharon Gai, author, keynote speaker, and educator.We'll cover:(00:00) - Intro (01:21) - In This Episode (05:20) - How AI Moves Marketing Creativity Up the Abstraction Layer (09:08) - Why Taste Is No Longer a Durable Human Skill (15:33) - What Human Work Looks Like After AI Learns Taste (20:41) - How to Codify Taste Into Your AI Systems (27:20) - Why Hands-On Execution Still Builds Judgment AI Can't Copy (36:48) - How to Build a Personal AI Strategy and Learn How to Learn (39:31) - Why Seeing Your Job as Tasks Rather Than a Role Future-Proofs Your Career (48:12) - Why You Should Tinker With AI Before You Cut Back on Meetings (54:13) - How Students Can Adapt to Graduating Into an AI Economy (01:02:13) - How to Decide What Deserves Your Energy Summary: Sharon Gai wrote a book telling everyone that taste and judgment were the durable human skills AI couldn't touch, then went on record to take half of it back. In this episode she walks through why taste is now codifiable, why originality still belongs to humans, and how she pulled a McKinsey-grade deck out of Claude by feeding it her own best work. We get into the lost generation of junior executors, the beekeeper mindset that separates orchestrators from busy bees, and a token-maxing hot pot dinner that made her swear off wasting agents. She even hands over a deathbed test for deciding what deserves your energy. If you've ever wondered which of your skills actually survive the next few years, this one is a map.About Sharon GaiSharon Gai is an author, keynote speaker, and educator who helps professionals future-proof their careers in an AI-driven economy. She teaches on Maven and speaks to audiences around the world about how AI is reshaping creativity, work, and the roles people play inside their companies. Her latest book uses the image of busy bees and beekeepers to argue that the future belongs to the people who orchestrate AI rather than execute every task themselves.Before writing and speaking full time, she spent years in enterprise tech, starting out helping IT directors and CIOs build data centers at the dawn of the cloud era. That hands-on background shows up throughout her work, especially in how she thinks about the difference between doing the work and orchestrating it.How AI Moves Marketing Creativity Up the Abstraction LayerWhen cameras got cheap, painters thought they were finished. Why spend weeks rendering a face in oil when a machine could capture it in a fraction of a second? Plenty of people called photography mechanical, soulless, artless. The threat was real, and the outcome was stranger than anyone expected. Freed from copying the world exactly, painters walked through a door cameras couldn't follow, into Impressionism, Cubism, and everything that made modern art feel alien at first. Sharon sees the same door swinging open for marketers right now, and the word she keeps returning to is abstraction.Walk through any art museum and you can watch this happen on the walls. The 1800s rooms are full of precision: portraits rendered to the eyelash, battle scenes with every horse in place, oceans and landscapes you could almost step into. Then you reach the modern wing, and some people stop and say "I could have done that." The work got harder to read. You have to stand there a moment, wonder who the artist was and why they picked this particular black over a lesser one. The craft survived by climbing a level, from rendering reality to deciding what the piece should mean.Sharon's marketing version is concrete. A few years ago you drew up a Facebook ad yourself, designed the banner, and loaded it into the platform's back end by hand. Now that whole chain can run on its own. So what does the marketer actually do? The real decisions look different now. You choose whether to test one ad or several hundred, each personalized to the person about to see it, whether the creative should be a flat image or a video, and if it's video, what belongs on screen. The manual work shrinks and the number of real decisions explodes. That's the abstracted layer, and it's where the job is heading whether marketers are ready or not.Over the next 2 years, the marketers who struggle will be the ones who still measure their worth by the execution those tools just swallowed.Key takeaway: Write down every part of your last campaign that was pure execution: building the banner, resizing creative, loading it into the platform, pulling the report. Hand those tasks to AI on your next campaign and pour the reclaimed hours into the layer above them. Decide which audiences, how many variants, what format each one takes, and what the creative is actually trying to make someone feel.Why Taste Is No Longer a Durable Human SkillFor about a year, the safe career advice sounded identical everywhere. Let AI do the work, but hold onto taste and judgment, because those are the human skills a machine can't reach. Tech CEOs repeated it on every stage. Sharon believed it too, and wrote it into her book. A few months later she started taking half of it back.Her reasoning is uncomfortable if you've built a career on your eye. What is taste, really? For an expert artist it's roughly 10,000 hours of seeing the bad versions and the good versions until they can tell the difference on sight. That makes the taste expert something close to a mini LLM, a person pummeled with enough examples to develop a reliable read on quality. And if taste is just a very large training set, there's no obvious reason you can't hand those examples to a model.Sharon is careful about where she draws the new line. In AI time, she points out, a single day can feel like a year, so any strong opinion has a short shelf life. She'll grant that judgment might still belong to humans, but taste she no longer counts in that column. Her position in June of 2026 is that taste is codifiable, and that alone knocks it off the list of things only people can do.Where Originality Still Separates Humans From AIShe used to open talks with a slide that read: creativity does not equal originality. The words sound like twins, and they describe 2 different things. AI can be creative. It can paint in an impressionist style and produce something that would look at home in a modern gallery. Originality means something genuinely novel, something that hasn't appeared anywhere before, and everything a model makes was pre-trained on what already exists.The gap shows up most clearly in how humans move between domains. Narrow AI, the kind we mostly use today, is trained on one field. General intelligence takes a principle from physics class and applies it to biology, or borrows something from construction and uses it while cooking. People do this instinctively from childhood. Machines still struggle with the leap, which is why originality, for now, stays on the human side of the ledger even as taste crosses over.If taste is now a training asset, the marketers still selling "good taste" as their moat are pricing a skill the market is about to commoditize.Key takeaway: Stop treating your taste as something locked inside your head. Start capturing it instead. Save the emails, decks, and campaigns you consider excellent right next to the weak ones, label what makes each good or bad, and feed both to your AI tools so the model learns your specific standard rather than a generic one.What Human Work Looks Like After AI Learns TasteEvery few months someone publishes a confident map of what work looks like in 2030. Ask Sharon and she starts by lowering the temperature. Most of it is prediction, and prediction is ch...

What's up everyone, today we have the pleasure of sitting down with Michele Martin, Senior Director of Global Brand and Integrated Marketing at Ticketmaster.Summary: Most career advice still hands you a ladder and tells you to climb. Michele makes the case for a lattice instead, the crisscross path of sideways and diagonal moves that built her range across banking, retail, a startup, and now Ticketmaster. Along the way she breaks down why the call center job she almost refused changed everything, how mentorship and sponsorship are 2 different engines, and why communication beats coding as the skill that survives the AI era. She even walks through what a genuinely good AI session looks like on her marketing team. If you've ever felt boxed in by the straight climb up, this one rewires how you think about your next move.About Michele MartinMichele Martin is the Senior Director of Global Brand and Integrated Marketing at Ticketmaster, where she leads brand strategy and ties together the channels that reach fans across sports, music, and the arts. Her career is a working example of the lattice she advocates: 11 years at TD Bank moving through corporate sponsorships, communications, a contact center, and sales strategy, then brand and customer roles at L.L.Bean and a stretch at a growth-stage startup.A first-generation college graduate, she builds communities everywhere she lands, from the Kind/Red marketing collective to Live Nation Women. She's also an avid traveler, an amateur golfer, and a self-described nonfiction reader who gets her fiction through Netflix and TikTok.What A Lattice Career Means And Why It Beats The LadderMost career advice still runs on a single image: the ladder. You start as a specialist, become a manager, then a senior manager, then a director, then a VP, climbing one predictable rung at a time. It's clean, it's legible on a resume, and it quietly convinces a lot of good marketers that any move which isn't straight up is a step backward. Michele has spent 2 decades proving the opposite, and she has a better picture in mind.Walk into any hardware store and find the fencing section. The lattice is that crisscross panel of wood, the one you'd nail under a porch for a little privacy. That shape is the whole philosophy. A lattice career moves diagonally, sideways, sometimes down for a stretch, and then back up from a completely different position than where you started.The freedom in that reframe is the part people miss. When you stop treating vertical promotion as the only valid direction, you give yourself permission to chase the work you're actually curious about. You might take a role that pays the same and reports to the same level because it teaches you something your current lane never will. A year later that detour is the reason you can do a job nobody on the straight-up track is qualified for. The lattice isn't a slower ladder. It's a wider map of where a career can go.The marketers who'll be hardest to replace over the next decade are the ones who collected range on purpose, because range is the thing no single promotion can hand you.Key takeaway: Stop scoring every potential move by whether the title goes up. Draw your own version of the lattice instead: list the 3 skills or domains you most want to understand, then look for roles that hand you those, even laterally. The diagonal move you resist now is usually the one that makes you uncopyable in 5 years.How To Decide If A Sideways Career Move Is Worth ItEvery marketer has a moment where someone dangles a role that feels wrong. Wrong department, wrong direction, wrong vibe for the brand you're trying to build for yourself. The instinct is to protect the climb and say no. Michele almost did exactly that, and the role she nearly turned down ended up shaping everything that came after.She spent 11 years at TD Bank, a place that treated career growth as a contact sport. The internal logic there was simple: if you want to grow, try a little bit of everything, because that's how you actually learn how the business makes money and how decisions land on customers and employees. So when a contact center role came up, it fit the bank's culture even though it terrified her. She'd never pictured herself there. She didn't know what the work even was beyond the frontline.What tipped her over was a mentor named Matt Chevalier, who passed away young and whose advice she still repeats. He'd watched her get comfortable, and comfort was the thing he refused to let slide. His argument wasn't that her current job was bad. It was that she'd convinced herself the fun she was having couldn't exist anywhere else, and that staying put meant never testing herself in the ways a harder room would. That landed.Inside the contact center she learned phone systems, quality programs, and the guts of customer technology she'd never have seen from a marketing desk. The next jump, onto a sales strategy team, was scarier still, because now she was building an incentive platform alongside genuinely technical people while feeling like she knew nothing. The relief came from a small realization that's stuck with her since. If you can explain a complicated system in plain words, you actually understand it.The roles people resist hardest tend to be the ones carrying the steepest learning curve, which is exactly why avoiding them keeps so many careers thin.Key takeaway: The next time a role feels like a sideways or scary move, separate the fear from the data. Ask what specific skill or exposure it would hand you that your current seat never will. If the honest answer is "a lot," treat the discomfort as a signal you've found a real growth edge, not a reason to pass.Why Integrated Marketing Is A General Contractor RoleMarketing invents job titles faster than anyone can define them, and "brand and integrated marketing" is one of those phrases that means something different at every company. At Ticketmaster, Michele uses a metaphor that finally makes the term concrete. Integrated marketing is the general contractor of a campaign.Think about what a general contractor actually does on a build. They don't pour every foundation or wire every outlet themselves, but they understand each trade well enough to know when something's off, and they're the one person responsible for making all of it connect into a house someone can live in. That's the role. You need real fluency across the components of a campaign, whether that's CRM, paid media, organic, or social, and then you need the rarer skill of wiring those parts together.Here's where the lattice pays off in a way no straight-line career could. Because Michele spent years jumping into unfamiliar functions and learning new technology on the fly, she walks into an integrated role already understanding most of the trades she's coordinating. That changes the quality of the work. Without that range, the job quietly degrades into project management, chasing status updates and herding stakeholders. With it, she comes to the table with a real point of view on every channel because she's actually done the work in them.The integrated marketer who can only schedule the trades gets treated like overhead, while the one who understands the trades gets treated like a leader, and the difference is almost always hands-on range.Integrated Marketing Versus Omnichannel MarketingPeople lump integrated marketing and omnichannel together constantly, and Michele doesn't fight that too hard. Where she sits, the 2 work almost the same way. The job starts with a business challenge for a given category, then asks how marketing can support it, then defines a single concept grounded in data and fan insight. Only after that does the work fan out to the channels.The discipline is in what stays constant ...

What's up everyone, today we have the pleasure of sitting down with Amanda Natividad, Chief Evangelist at SparkToro and co-author of Zero Click Marketing.We'll cover:(00:00) - Intro (01:14) - In This Episode (06:37) - Why Attribution Breaks Down in a Zero Click World (16:09) - What the Alligator Graph Means for Ops Teams (22:46) - How to Run a Zero Click Launch Week You Can Actually Measure (32:35) - How Incrementality Testing Works at Enterprise Scale (38:09) - What Audience Listening Adds to the Marketing Ops Stack (42:50) - What Content Leaders Need From Marketing Ops (47:59) - How to Turn Audience Research Into an Operational System (52:00) - How AI Visibility Changes Zero Click Marketing (58:36) - Setting Boundaries to Protect Your Energy and Focus Summary: zero click marketing won the strategy war, and now nobody can prove it's working. Amanda has spent over a decade building marketing that lives where the audience already is, and in this episode she takes apart the measurement crisis that creates. We get into why your attribution dashboard is quietly lying to you, how a viral story about HubSpot losing 80% of its organic traffic actually hid record revenue, and what a 25 million dollar ad blackout taught Dropbox about the gap between credit and cause. She also shows how to turn audience research into an operational system and why winning AI visibility comes down to writing genuinely good stuff. Stick around for the launch-week playbook and the overslept-webinar story that completely reframes how she guards her time.About Amanda NatividadAmanda Natividad is the Chief Evangelist at SparkToro, the audience research startup, and the founder of Zero Click Marketing, a podcast and consultancy built around the framework she co-created with Rand Fishkin in 2022. She spent 4 and a half years as SparkToro's VP of Marketing, where she launched a newsletter that reaches more than 60,000 subscribers at a 35% open rate and built Office Hours, a webinar series that pulls as many as 1,200 registrants a show.She's keynoted at AdWorld, Content Marketing World, and MozCon, and guest lectured at Columbia, Cornell, and Stanford. A Le Cordon Bleu-trained chef and former journalist, she now teaches Content Marketing 201 on Maven.Why Attribution Breaks Down in a Zero Click WorldEvery marketing ops team runs on a dashboard that hands out credit. This lead came from paid search. That demo came from a LinkedIn ad. This signup traces back to the nurture email. The numbers look authoritative, and leadership treats them that way. The trouble is the data underneath has been eroding for years, and most teams still read the output like scripture.Amanda has spent more than a decade building marketing programs that don't depend on the click. Her take on measurement starts from an uncomfortable place. Attribution was never as precise as the industry sold it, and every year it gets less precise.4 separate forces have chipped away at what attribution can actually see, and they stack on top of each other.Third-party cookies barely function. Only about 30% of users accept them, and Safari rejects them by default., Ad blockers hide a huge share of traffic. Somewhere between 20 and 60% of people run one, and among tech-savvy B2B audiences that number climbs toward 60%., The multi-device journey is untrackable pre-login. People average 3.6 devices each, so stitching a single human across all of them is mostly guesswork., Privacy regulation makes persistent tracking impractical. GDPR, CCPA, and LGPD mean what's legal in the US often isn't legal anywhere else, a real burden for any team with a global audience.None of this means you rip attribution out of the stack. In a mature organization it's already there, already wired into the reports leadership reads, so ignoring it would be its own kind of malpractice. The shift Amanda argues for is one of posture. Go in knowing exactly where the model goes blind, then ask the more useful question of what you can measure next to fill the gaps. That's where incrementality, media mix modeling, geo-testing, and holdout tests start to earn their place. The teams that keep their budgets in a down market are the ones who stopped presenting attribution as ground truth and started presenting it as one flawed witness among several. A single confident number is easy to attack. A converging set of imperfect signals is much harder to argue with.Key takeaway: Audit where your attribution model goes blind before your next leadership review. Write down how much of your traffic Safari blocks, how many of your B2B visitors run ad blockers, and how many touchpoints happen before anyone logs in. Bring that context into the room so a drop in tracked conversions reads as a gap in measurement, not a failure in marketing.Why Dark Social Traffic Shows Up as DirectOpen Google Analytics on any given week and a fat slice of your traffic sits in a bucket labeled direct. The polite interpretation is that all those people typed your URL straight into the address bar. Almost none of them did. Most of that direct traffic is dark social, the shares that happen inside messaging apps and closed platforms where the referral information never makes it back to you.SparkToro put real numbers on it. About 2 years ago the team ran an experiment, sending more than 1,100 visits across 11 social networks and then checking what Google Analytics reported. For TikTok, Slack, Discord, WhatsApp, and Mastodon, every single visit landed in direct.Amanda has a theory about why, and it follows the money. The platforms can see the organic referral string. They keep it invisible, because the moment you pay to join their ad network, that traffic suddenly becomes visible and measurable. Organic reach stays in the dark so paid reach looks like the only reach worth buying. And it goes well past the obvious suspects. Facebook Messenger strips the referral about 75% of the time, Instagram DMs about 30%, and even LinkedIn hides it roughly 14% of the time. A share is a share whether it happens in a feed or a private message, but only some of them ever get counted.The practical lesson for an ops team is to stop treating the direct channel as a junk drawer. When word of mouth and private sharing drive a real share of pipeline, a measurement model that files all of it under direct is quietly erasing your best-performing channel. The brands that figure this out start asking where conversations about them actually happen, instead of waiting for a clean UTM that the platform was never going to hand over.Key takeaway: Run your own dark social test before you trust the direct bucket. Push a known batch of clicks through TikTok, Slack, and a few DM channels, then watch how your analytics file them. Use the gap to set expectations with leadership, and lean on post-purchase survey questions like "where did you first hear about us" to recover the attribution the platforms refuse to share.What the Alligator Graph Means for Ops TeamsThere's a chart making the rounds that content marketers have started calling the alligator graph. Impressions climb while clicks to your website fall, and the 2 lines drift apart until they look like an open set of jaws. For a content team this reads as proof the strategy is working, because more people are seeing the brand. For a marketing ops team staring at the same chart in Google Analytics, it reads as failure, because the dashboard they own is built to count clicks and the clicks are going down. The measurement layer is undercutting the exact thing the content layer is producing.Amanda's first move is to reframe the problem. The j...