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This episode is the bonus round to Brian and Andrew's four forces webinar. They ran out of time on the live session, so they saved the best part for here: where all four trends are actually pointing and what it means for how research gets done.
Andrew lays out the clearest version of the webinar's thesis: capital, AI, and the data quality crisis are not three separate things. They are converging forces pushing the industry toward methodologies that are more transparent, more respondent-friendly, and more operationally feasible than what came before.
From there, the conversation gets specific on async qual, AI-led conversational interviewing, and agentic research. Andrew makes a sharp argument that the next step change in automated research will not come from software companies selling AI tools. It will come from agencies building proprietary workflows trained on their own data and methodological history. The agencies that do that work now will have a moat that an off-the-shelf product cannot replicate.
The episode closes with Brian's take on four things the disruption narrative tends to get wrong, including why qual is not dying and why the trust crisis will not be solved by more technology.
Key Takeaways:
Why the four trends are a single converging story, not four things happening in parallel
What AI-led async qual does better than scheduled IDIs and why it matters for panel health
Why agentic research workflows will be built by agencies from the inside, not sold to them as products
Why qual is not dying and why AI quant cannibalises quant budgets, not qual budgets
Why the trust crisis is a culture problem, not a technology problem
If you loved the episode, have comments, or want to appear on the show, connect with us down below!
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ROI Rocket
In this special episode, Brian and Andrew bring their live webinar to the podcast feed. Drawing from recent conferences, client conversations, and industry reports, they break down four forces reshaping how research gets done: Capital Influx, the Data Quality Crisis, AI Disruption, and Methodology Reframe.
Brian's core argument is that these are not four separate trends. They are one larger story with feedback loops accelerating each other, and the industry does not get to choose whether the shift happens, only whether it leads or follows.
The episode also features a live Q&A, including a sharp exchange on whether there are research categories where AI should not be used yet, and a direct answer to how you sell quality to a client who thinks $12 CEOs are fine.
Key Takeaways:
Why OpenAI and Anthropic’s launch of deployment consulting firms is a competitive threat the insights industry needs to take seriously
What the latest GDQ benchmarks reveal, including a 59.6 percent post-survey removal rate in B2B
Why the biggest fraud risk is not bots but humans using AI to fake qualifications and game incentives
Why synthetic data still needs proof, and why every credible synthetic platform still anchors to a verified human sample
Why the qual and quant divide has not just blurred, it has effectively disappeared
If you loved the episode, have comments, or want to appear on the show, connect with us down below!
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ROI Rocket
In this quick-hit episode, Brian and Andrew debrief fresh off the conference circuit. Brian just landed from Washington, D.C. and comes in hot with takeaways from two back-to-back events: the Insights Association Ignite Data Quality and the GreenBook IIEX conference at the Ronald Reagan Building.
The first stop is data quality. The Global Data Quality Initiative unveiled its latest benchmarks at IA Ignite, and the numbers are hard to ignore. Post-survey removal rates of 46.5% in B2B and 30% in healthcare patient research paint a picture of an industry with serious work to do. Brian and Andrew also dig into findings from Verisol, who analyzed 50 million survey clicks and found that the biggest threats are not true bots, but humans armed with AI using VPNs and location spoofing to game incentives.
Then it's on to IIEX, where Brian played a little game with Andrew: name the companies. Out of roughly 30 AI companies with booths or presentations, Andrew recognized maybe two. Outset, Neurons, Dialogue AI, ConvoTrack, Riley AI, and dozens more are flooding the market, and Brian makes the case that nobody can keep up with all of them. The second mouse gets the cheese.
The episode closes with a plug for the Signal and Noise webinar on May 12th at 2 PM Eastern, where Brian and Andrew will go deeper on trends, AI, and everything they held back from this one.
Key Takeaways:
Why the IA Data Quality Day may be the single most important gathering in the industry right now
What the GDQ benchmark numbers actually reveal about the state of B2B and healthcare research sample
Why the biggest fraud threat is not bots but humans with AI using proxies and spoofed locations
The overwhelming volume of new AI companies entering the market and why being strategic matters more than being comprehensive
Why the second mouse gets the cheese when it comes to evaluating early-stage AI tools
If you loved the episode, have comments, or want to appear on the show, connect with us down below!
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ROI Rocket
In this episode, Brian and Andrew sit down with Mike Courtney, founder and principal of Aperio Insights and a practicing futurist. Mike brings a rare perspective to the Signal and Noise table, equal parts market researcher and strategic foresight practitioner.
Mike kicks things off with his "Land Man oil analogy," framing AI not as something happening to us but as a new drilling tool for human knowledge and intelligence. Just as early oil pioneers could not have imagined the thousands of uses petroleum would eventually unlock, we are likely only scratching the surface of what AI makes possible.
From there, the conversation goes deep on what futurists actually do, why exponential growth is so hard for humans to comprehend, and what the five to ten-year picture actually looks like.
Key Takeaways:
Why the right frame for AI is not what it will do to us, but what we will be able to do with it
How futurists think about possibility and change management rather than prediction
The barbell effect coming for knowledge workers and why AI fluency is not optional
Why lowering the floor does not automatically raise the ceiling
What will be genuinely scarce and therefore valuable in an AI-abundant world
Why the Michelangelo of market research will be the person who asks the right question, not the one who executes the fastest
If you loved the episode, have comments, or want to appear on the show, connect with us down below!
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Connect with Mike Courtney:
In this episode, Brian and Andrew sit down with Jase Bumgardner, a 25-year partner at The Link Group, a healthcare-focused market research consultancy. Jase leads complex, multi-year research work streams in neuroscience and new product planning, most notably alongside Eli Lilly, following products from early concept all the way through FDA approval and launch.
Jase brings a grounded, refreshingly calm perspective to a conversation the podcast usually approaches with a bit more urgency. Where Brian and Andrew often find themselves in the AI doom spiral, Jase comes in as a self-described pragmatist. He estimates AI has changed roughly 10 to 15 percent of what his team actually does day to day, and he sees it primarily as amplification, not replacement. The real disruption, in his view, is still mostly theoretical for firms doing elite, high-stakes consultative research.
The conversation covers how The Link Group made AI a formal priority years ago through a structured task force, a five-year strategic plan, and ongoing sentiment checks to see if it's actually moving the needle with clients. Jase also pushes back thoughtfully on the rush to adopt, citing data showing only 13 percent of brand-side clients are satisfied with generative AI results, and warns against what he calls the "great de-skilling," where reflexively outsourcing thinking to AI erodes the very capabilities that make great researchers irreplaceable.
Key Takeaways:
How The Link Group built a deliberate, mission-aligned AI strategy rather than chasing every new tool
Why the "any benefit" mindset around AI adoption is a problem, and how to think about net benefit instead
The risk of de-skilling as reading, writing, and independent thinking get offloaded to AI tools
Why market research is still fundamentally a talent and relationship game, and why that is not changing anytime soon
If you loved the episode, have comments, or want to appear on the show, connect with us down below!
Connect with us:
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Connect with Jase Bumgardner:
The Link Group
In this episode of Signal and Noise, Brian and Andrew sit down with Erin Sowell, owner and principal consultant at Thoughtful Research. Erin brings a background that is genuinely uncommon in the insights world, starting in environmental science and entrepreneurship before discovering market research through the product development process and going on to earn her master's degree from the University of Georgia's highly regarded MMR program, where she now serves on the advisory board.
The conversation digs into what it actually looks like to run a small, independent research consultancy built around integrated insights, bringing together qual, quant, and existing client data to answer business questions rather than just execute studies. Erin walks through a real project where a B2B client had a product that customers asked for and then refused to buy, and how a phased qual-to-quant approach helped uncover that the problem was not the product but the positioning and targeting strategy around it.
Brian and Andrew also explore one of the more underappreciated challenges in the industry: working with clients who have never done primary research before. Erin talks candidly about what it means to not just sell a study but to introduce an organization to research itself, the white-glove education involved, the sticker price shock, and why getting that first impression right matters so much for the long-term relationship a client develops with insights as a function.
Key Takeaways:
How Erin built Thoughtful Research around integrated insights and a consultative, business-first approach rather than a methodology-first one
The unique challenge and opportunity of working with clients who are brand new to primary research
How Erin is using AI for qualitative analysis and building toward always-on forecasting and leading indicator capabilities
If you loved the episode, have comments, or want to appear on the show, connect with us down below!
Connect with us:
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Connect with Erin:
Thoughtful Research
In this episode of Signal and Noise, Brian and Andrew ditch the agenda and go full rant mode, recording from Andrew's hotel in Atlanta with no guest, no script, and no filter.
The topic is AI anxiety. Not the doom spiral variety, but the very real, day-to-day frustration of trying to stay current with a technology that moves faster than any organization can evaluate, approve, or implement. Andrew frames it as trying to build a robot underwater with one arm tied behind his back, in a wave pool, while the water keeps changing.
The conversation gets honest about what this looks like in practice, from juggling a growing personal stack of AI tools to navigating the very different constraints that come with using AI inside a company holding PII, client data, and SOC 2 compliance obligations. They land on a practical and surprisingly calming framework: stop chasing the best model and start building your processes in a model-agnostic way so your work survives the next wave of change regardless of which tool wins.
The episode ends with both hosts arriving at genuine excitement rather than dread, and an open invitation for listeners navigating the same thing to come on the show and talk through it.
Key Takeaways:
Why AI anxiety is a real and shared experience for market research professionals right now, and why the pace of model releases makes organizational adoption feel nearly impossible to time correctly
The case for being model agnostic and building AI workflows that do not depend on any single tool or provider, so your work survives the next wave of change
Why the Anthropic report on AI exposure by industry means market research professionals should be excited, not threatened
If you loved the episode, have comments, or want to appear on the show, connect with us down below!
Connect with us:
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ROI Rocket
In this quick-hit episode of Signal and Noise, Andrew catches up with Brian fresh off the floor of SampleCon 2026, recording from the Delta Sky Club in Seattle. No studio setup, no guests, just a real-time debrief from one of the industry's most dedicated annual gatherings.
Brian shares his firsthand impressions of a conference that felt noticeably different this year. SampleCon is evolving. What once centered on panel standards and supplier partnerships is now leaning hard into technology, AI implementation, and a wave of new faces and companies that would have felt out of place at the event just a few years ago. Brian compares the vibe to a smaller IIEX, and that is not a small compliment.
The conversation covers the headline moment of the conference, a point-counterpoint keynote debate between Patrick Comer and Melanie Courtright on human versus synthetic respondents, the growing industry consensus shifting from "should we use synthetic?" to "prove to us that it works," and a standout session from Walmart's research team making a public case for better respondent care and panel investment.
Key Takeaways:
How SampleCon is evolving from a supplier networking event into a technology and innovation conference
What one keynote debate revealed about where the industry stands on synthetic research
Why the conversation around AI and synthetic data has shifted from "should we?" to "prove it works"
Why conferences held at resort-style venues create a different and arguably more productive networking environment
If you loved the episode, have comments, or want to appear on the show, connect with us down below!
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ROI Rocket
In this episode of Signal and Noise, Brian and Andrew sit down with Lenny Murphy, one of the most recognized voices in the market research industry. As the founder of GreenBook, co-founder of the Insight Innovation Exchange (IIEX), and a Gen2 Advisors partner with deep roots in M&A and investment, Lenny brings a perspective that is equal parts historical lens and boots-on-the-ground reality.
The conversation covers the accelerating collision between artificial intelligence and the market research industry. Lenny reframes AI not as an apocalypse, but as a restructuring, drawing parallels to the printing press, the automobile, and the industrial automation of the 1980s. The discomfort is real, the displacement is real, but so is the opportunity.
The trio digs into where the industry has already been commoditized and where it went wrong, why the real asset in research has always been the connection to consumers, and how agentic AI is already reordering business models faster than most companies can respond. Lenny also shares a candid take on why many established firms are caught in the crosshairs, not because of a lack of talent, but because of a failure to adapt before the wave arrived.
The episode also touches on the future of live events and in-person connection, the upcoming IIEX conference in Washington, DC, and a new IIEX West launch in San Francisco, with Lenny making the case that human gatherings become more valuable, not less, as automation takes over routine work.
Key Takeaways:
Why Lenny views AI as a restructuring event comparable to the printing press and industrial automation, not an ending
How the research industry commoditized its own most valuable asset and what that means now
Why the shift from process-based pricing to impact-based pricing is both necessary and overdue
What the "reckoning still to come" looks like for established firms that have not adapted fast enough
Why live events and in-person connections are poised to become more critical in an AI-driven world
If you loved the episode, have comments, or want to appear on the show, connect with us down below!
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Connect with Lenny:
In this episode of Signal and Noise, Brian and Andrew sit down with Tim Matthews, who heads up the in-person research and support team at ROI Rocket. Tim brings over 20 years of marketing experience, starting from tactical brand activations at the Winston Cup Series to building a research firm rooted in creative, human-centered consumer engagement.
The conversation centers on a growing challenge in the research industry: the erosion of trust in online quantitative data, the difficulty of reaching low-incidence and niche populations, and why in-person recruiting is anything but old-fashioned.
Tim reframes the concept of the "intercept" entirely. Forget the clipboard in the mall. His team operates more like a creative, agile engagement deployment squad, going where consumers live, work, shop, and play to find respondents that online panels simply cannot reach. From private golf clubs to luxury dinners at the Playboy Mansion, Tim shares the strategies and stories behind some of his most memorable and creatively ambitious recruiting projects.
The episode also features a live "Can You Find Them?" game, where Brian and Andrew throw out increasingly niche audience targets, and Tim explains how his network and methodology could actually reach them, from nuclear plant operators to doomsday bunker owners.
Key Takeaways:
Why online panels fall short for low-incidence and hard-to-reach populations
How Tim's team uses experiential incentives (not just cash) to recruit elusive respondents
The value of storytelling over transactional survey-taking
What the "six degrees of Kevin Bacon" has to do with finding niche research targets
Why stated vs. actual behavior gaps make in-the-moment observation so powerful
If you loved the episode, have comments, or want to appear on the show, connect with us down below!
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Connect with Tim:
LinkedIn
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