Signal and Noise

After a small break, Brian and Andrew are back. Both came with independent lists, sat down, and went back and forth for an hour on something they have been doing together for over a decade: running brand tracking studies the right way.Between them, they have overseen the in-field transition of more than ten large continuous tracking programs, launched dozens more, and spent years studying exactly how panel bias shows up in longitudinal data in ways that most researchers never catch. This episode is the playbook they wish existed when they started.The conversation covers how to think about blending panels for a tracker, why your anchor panel is the most important decision you will make, how inherent panel bias gets built in through recruiting practices that panels will never volunteer to you, why over-engineering the blend is its own form of data corruption, and why NPS in a tracker is a trap waiting to spring.If you run a tracker, manage a tracker, or are about to set one up, this one is worth a full listen.Key Takeaways:Why your anchor panel is the single most important structural decision in a blended trackerHow panels develop inherent brand bias through their own recruiting, and why they will never tell you about itWhy NPS is dangerous in a tracker and how to use it without blowing up your trend lineIf you loved the episode, have comments, or want to appear on the show, connect with us down below!Connect with us:LinkedInYouTubeROI Rocket

No guest, no agenda, no notes. Brian and Andrew just riffed for an hour on one of the biggest questions in the industry right now: what does sampling look like in 5 years?Brian is presenting on the future of sampling at the Future of Insights Summit in Athens, Georgia, and this episode is the unfiltered, longer version of that talk. The current model is broken and nobody serious is arguing otherwise. The real question is what replaces it, and who wins when it does.They work through where today's panels fall short, what synthetic data can and cannot actually do right now, and why the first truly useful synthetic products will likely be built inside brands, not sold to them. P&G, Google, and Meta are sitting on behavioral data sets that dwarf anything a panel company owns. That has consequences.The conversation also gets into why the brands that build proprietary synthetic tools will have a moat that nobody can buy, why psychological data will never fully be replaced, and why the next 5 years might be the most interesting and terrifying stretch in the history of this industry.Key Takeaways:Why the current online panel model is broken and what the industry is not doing about itWhy the first useful synthetic products will be built by brands using their own data, not by research suppliersWhy human panels are not going away, and what role they play in a world increasingly run by synthetic modelsIf you loved the episode, have comments, or want to appear on the show, connect with us down below!Connect with us:LinkedInYouTubeROI Rocket

Andrew flies solo and sits down with Joey Maddox and Sebastian Babis from Verisoul, fresh off a $9M Series A and the most creative go-to-market run market research has seen in years.Times Square billboards. A Reds game with hundreds of attendees. Branded cigarettes at a European conference. None of it is random. Verisoul mapped their top 200 prospect companies, identified the 10 to 15 buyers at each, plotted where they all live, and built activations around them. Strategic chaos.The conversation covers how a team from banking and identity fraud disrupted a market that had been hearing the same messaging for years, why in-person trust-building is non-negotiable when your product is fraud prevention, and what it looks like to run go-to-market across wildly different verticals at once. Also, all three of them are newly married or about to be, and the wedding vendor pricing rant is worth the listen alone.Key Takeaways:How Verisoul built a geographic database of prospects and designed its entire events strategy around itWhy an outside-in approach to fraud detection is beating well-funded incumbents head-to-head on accuracyThe marketing ideas that did not make the cut, including blowing up a building with a competitor's logo on itIf you loved the episode, have comments, or want to appear on the show, connect with us down below!Connect with us:LinkedInYouTubeROI RocketConnect with Joey:LinkedInConnect with Sebastian:LinkedIn

Brian and Andrew sit down with Karine Pepin of The Research Heads and Andrew Gordon of Prolific to break down one of the most important data quality studies the industry has produced. They analyzed 5,200 respondents across 10 platforms and the findings will surprise you.AI agents are not in your data. Outside of MTurk, detection rates were below 0.5% across every platform type. And the things getting flagged on MTurk? Old-school bots, not LLMs. When they ran actual AI agents through the same survey, those agents outperformed real human respondents on nearly every quality measure.The actual crisis is your human respondents and the platform you are buying them from.Key Takeaways:Agent infiltration is not the crisis the industry thinks it isWhat is actually getting flagged as bots on MTurk, and what it really meansWhy the human quality gap between direct panels & marketplace platforms is the story nobody is tellingWhy the cheapest sample per click is often the most expensive data you will ever buyLink to the study "AI Agent Prevalence and Data Quality Across Multiple Online Sample Providers"If you loved the episode, have comments, or want to appear on the show, connect with us down below!Connect with us:LinkedInYouTubeROI RocketConnect with Karine Pepin:LinkedInConnect with Andrew Gordon:LinkedIn

Brian and Andrew sit down with Angela Chavez, Insights Manager at Dig Insights and UGA MMR graduate, ahead of her first-ever conference presentation at the Future of Insights Summit in Athens this August.Angela's talk is called "Learning Research in a Rapidly Changing World," and this episode is a preview of exactly that. She walks through what it has actually been like to enter the industry as AI was exploding, going from hesitant early adopter to someone who opens ChatGPT as a reflex, all while growing from analyst to manager.The conversation also gets into Dig Insights' tech-forward approach and what Angela's early career experience reveals for senior leaders trying to figure out how to onboard, train, and develop the next generation of researchers right now.Key Takeaways:What it is actually like to learn research and AI at the same time, in real timeHow Angela balances keeping up with new tools while still doing the workWhere the gap between academic foundation and real-world practice still shows upWhy early career researchers have a perspective that senior leaders should be paying attention toIf you loved the episode, have comments, or want to appear on the show, connect with us down below!Connect with us:LinkedInYouTubeROI RocketConnect with Angela Chavez:LinkedInDig Insights