In this episode of Signal and Noise, hosts Brian and Andrew are back with a fresh dose of industry insights, hot takes, and personal stories, diving into three major topics shaking up the research world. They kick things off with the Qualtrics and Pure Spectrum partnership, exploring whether this could be the turning point for synthetic data in market research, the strengths and weaknesses of the approach, and the likely future of hybrid panels. Next, they spotlight the rebrand of Azure Knowledge to Mavericks, debating why the change was made and whether it works, while having some fun with its pronunciation and branding implications. Finally, they break down the recent IRS decision to raise the 1099-K reporting threshold from $600 to $2,000, discussing what it means for research participants, particularly those in healthcare and qualitative studies.

If you have thoughts on synthetic data, rebranding in the insights space, or want to join the conversation, Brian and Andrew want to hear from you!

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In this episode of Signal and Noise, hosts Brian and Andrew hit the ground running - literally - fresh off a multi-city client tour. They break down the recurring (and alarming) theme they heard at nearly every stop: data quality is in a full-blown crisis.

Brian and Andrew unpack why some researchers are tossing out nearly half of their data, how bots and disengaged respondents are wreaking havoc and why middle-tier sample market might be on its last legs. The episode ends with some must-hear rants, including Andrew’s thoughts on why terms like “proprietary” and “verified” need serious industry-wide clarity.

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Welcome all to the debut episode of Signal and Noise, hosted by marketing research veterans Brian Lamar & Andrew DeCilles. Aiming to bring you honest conversations from industry experts, ranging from trends to breaking news to ugly conversations that others won’t touch; no subject is off limits.

In today’s episode we go over where we’ve been and what we’ve been up to since our last podcast for those that aren’t new here. We also discuss what old and new listeners in the Marketing Research space can expect from us moving forward. Marketing Research has never been in such a season of change and outcry - we’ll help you separate the signal from the noise.

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In this fiery episode, hosts Brian and Andrew tackle one of the most pressing and frustrating issues in market research: data quality. After weeks (more like years) of conversations with clients, researchers, and suppliers, the hosts dive deep into why data quality feels like it’s getting worse, why the industry keeps masking the problem, and whether brands should even care.

From the massive waste caused by fraud prevention and data cleaning to the commoditization of sample providers, Brian and Andrew don’t hold back in asking the hard questions. Does a poor-quality sample matter if agencies clean it all up before it reaches brands? And if not, what’s the long-term cost to the industry?

If you have thoughts on Data Quality (rants or solutions), or are interested in being a guest on the show, Brian and Andrew want to hear from you!

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In this episode of Signal and Noise, hosts Brian Lamar and Andrew DeCilles sit down with Craig Alter, an experienced consumer insights leader at Perfetti Van Melle, to explore how consumer behavior, impulse buying, and innovation research intersect inside the world of candy, gum, and mints.

Craig shares his nontraditional path into market research, explaining how early experience in finance, marketing, and brand management shaped his ability to connect subtle consumer insights to measurable business outcomes. He discusses why many professionals discover research later in their careers and why diverse business backgrounds are a strength for the insights industry.

Craig also discusses innovation and product testing as one of the most rewarding areas of consumer research. He walks through central location tests, flavor development, texture evaluation, and how research can serve both product refinement and selling stories with retail buyers. Throughout the discussion, he highlights how qualitative and quantitative methods increasingly blend together to solve real business problems.

The episode concludes with a thoughtful discussion on the role of artificial intelligence in research. Craig offers a pragmatic perspective on where AI can add speed and efficiency, such as summarization and early screening, and where human nuance remains irreplaceable, particularly in humor, taste, emotion, and impulse-driven behavior.

Key Takeaways:

• Impulse-driven categories like candy are difficult to research because consumers often cannot explain why they buy in the moment.

• Observational and in-context research is critical for understanding real shopper behavior, especially at the shelf or checkout.

• Consumer behavior changes significantly by channel, so insights must be tailored for grocery, convenience, club, and digital environments.

• Innovation research works best when qualitative and quantitative methods are combined to refine products and tell compelling business stories.

• AI can improve efficiency in research, but human judgment is still essential for understanding emotion, taste, humor, and nuance.

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In this episode of Signal and Noise, hosts Brian Lamar and Andrew DeCilles welcome Ellen Houston and Jordan Harper from Qualtrics Edge, marking the first time the podcast has featured guests from Qualtrics. The conversation dives into the future of AI, synthetic data, and the evolution of modern research inside one of the most influential insights platforms in the world.

Ellen, who leads the Edge Center of Excellence, outlines how her team focuses on the intersection of market research and artificial intelligence, particularly in developing synthetic respondents and next-generation research tools. Jordan, a senior principal thought leader, brings a scientific and strategic perspective shaped by his background in astrophysics, engineering, technology, and agency leadership. Together, they explain how Qualtrics Edge is working across product, engineering, delivery, and customer teams to establish a rigorous foundation for AI in research.

Throughout the episode, the conversation highlights the opportunities and challenges of AI, including research design, niche audience modeling, accuracy signals, and the role of synthetic respondents in uncovering deeper truths and exposing issues in survey construction. Both guests share examples of experiments, such as priming tests and concept evaluations, that reveal how synthetic respondents behave compared to humans and how these differences can expand the insight landscape.

Key Takeaways:

• Qualtrics Edge is focused on using AI to advance market research, especially through synthetic respondents.

• Synthetic respondents are meant to support human research, not replace it.

• The Qualtrics model is trained on decades of real survey data, giving it a unique advantage.

• Synthetic respondents help reveal issues in survey design and respondent behavior that humans may hide or overlook.

• Future developments include niche synthetic audiences and expanded AI tools across the entire research process.

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In this episode of Signal & Noise, Andrew and Brian are joined by pollster Jeremy Zogby for a deep dive into the state of American politics, the growing power of independents, and what the future might hold for voters caught between two increasingly polarized parties.

Jeremy shares his perspective as Managing Partner of John Zogby Strategies, where he has led groundbreaking work on independent voter behavior, including his role as lead pollster for RFK Jr.’s 2024 presidential campaign. With a historian’s lens and decades of polling experience, he unpacks how political violence, economic uncertainty, and global shifts are reshaping the electorate.

Key Takeaways:

• The Rise of Independents - Why unaffiliated voters made up over a third of the electorate in 2024 and how they may shape the next cycle
  

• Polarization & Violence - How rising rhetoric and high-profile acts of violence could impact voter sentiment and long-term party alignment
  

• Third-Party Hurdles - Why structural barriers make it nearly impossible for a viable third-party movement, despite a strong public appetite
  

• Global & Economic Pressures - How shifting power toward the East, BRICS alliances, and U.S. economic instability could influence voter priorities
  

• The Next Generation’s Concerns - Housing affordability, retirement security, and job uncertainty as unifying issues across political lines
  

Jeremy also reflects on lessons from history, generational cycles, and his own family’s legacy in polling to frame today’s turbulence within a broader context.

🔗 Learn more about John Zogby Strategies & The Zogby Report podcast: johnzogbystrategies.com

🔗 Connect with Jeremy on LinkedIn: Jeremy Zogby

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In this episode of Signal & Noise, Howard Fienberg, Senior VP, Advocacy at Insights Association, returns for a wide-ranging conversation on the policies shaping the insights industry. With over 25 years of government affairs experience, Howard has been named a Top Lobbyist by the National Institute for Lobbying and Ethics and continues to be one of the strongest voices advocating for research professionals in Washington, D.C.

In this episode:

• The Privacy Patchwork - Why 20 states now have their own privacy laws, how California and Washington are setting the pace, and why a federal standard remains critical

• What Counts in Census 2030 - How upcoming tests, government shutdown risks, and funding gaps could impact the next decennial count and why it matters for research professionals

• AI in the Crosshairs - The latest on state and federal AI regulations, transparency requirements, and how the Insights Association’s Code of Standards is evolving to cover new technologies

• Independent Contractors & Incentives - The ripple effects of state-level attempts to redefine independent contractors and even mandate minimum payments for research participants

• Practical Takeaways for Researchers - Why compliance depends on where respondents live, the risks of pseudonymous data, and how companies can prepare for shifting definitions of privacy

Learn more about us, the Insights Association, and Howard down below!

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In this episode of Signal & Noise, Andrew and Brian take you behind the curtain again on one of the most buzzworthy topics in market research: synthetic panels. After meeting with four different providers in a single day, they share candid reactions, surprising truths, and why the future may not be what you think.

But first, Brian gives a quick recap of his trip to CrimeCon in Denver, a subculture of true crime enthusiasts that had eerie parallels to how niche communities form in market research.

This episode is part myth-busting, part roadmap, and part rallying cry for researchers curious (and cautious) about synthetic data. Tune in now to filter out the noise!

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In this episode of Signal & Noise, Andrew and Brian sit down with David Butler, President of PureSpectrum, to unpack the company’s newly expanded partnership with Qualtrics and what it means for the future of synthetic data in market research.

David shares insights on:

• His journey at PureSpectrum and transition into the role of President.

• The collaboration with Qualtrics to enhance synthetic respondent capabilities.

• How PureSpectrum is leveraging micro-surveys and longitudinal data to fine-tune synthetic models.

• Opportunities and challenges in using synthetic panels for sensitive research, difficult-to-reach populations, and faster iteration.

• The ongoing importance of human data in grounding AI-driven insights.

The conversation also covers broader industry themes like data quality, the shift toward shorter, more engaging surveys, and how synthetic insights could reshape research practices in the years ahead.

To lighten things up, the episode ends with a round of rants from the headaches of time zones to the value (or lack thereof) of conferences.

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In this episode of Signal and Noise, hosts Brian Lamar and Andrew DeCilles sit down with Brandon Richard, Senior Vice President at The Link Group and a long-time AI enthusiast who has been leading multiple AI initiatives across qualitative and quantitative research. Together, they unpack what is actually happening in the research industry as companies race to understand and apply artificial intelligence.

The episode also explores the limits of AI-generated synthesis, the need for trust and human verification, the challenges of capturing nuance in qualitative work, and why the industry must avoid falling into the trap of faster and cheaper at the expense of true insight. Brandon highlights the importance of friction in the research process, explaining that many of the valuable ideas and breakthroughs come from the messy and human parts of research, not simply the final deliverable.

Key Takeaways:

• Where AI synthesis supports analysts and where it still falls short

• Practical examples of AI being used before and after qualitative work

• A balanced view of synthetic samples, digital twins, and personas

• Why accurate forecasting and real-time insight remain difficult for AI

• The risks of creating research that is fast and cheap but not meaningful

• Why friction in research often produces the best insights

• What the future of human plus AI collaboration should look like

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In this episode of Signal and Noise, hosts Brian Lamar and Andrew DeCilles talk with Lindsay Zaltman, Chief Executive Officer and Partner at Olson Zaltman, the firm known for creating the widely respected ZMET qualitative insight methodology. Together, they explore how deep psychological structures influence the way people think, feel, and make decisions, and why traditional research methods often miss these hidden drivers.

Lindsay explains how deep metaphors guide human behavior at a subconscious level and how they reveal the emotional stories people use to make sense of the world. He shares how Olson Zaltman uncovers these underlying meanings through imagery, personal narratives, and symbolic thinking. The discussion highlights how these insights help brands uncover motivations that consumers cannot easily verbalize and how they lead to more effective strategies, stronger creative ideas, and clearer paths for innovation.

Key Takeaways:

• Why traditional research struggles to reveal emotional truth

• How ZMET identifies the subconscious patterns that shape behavior

• The role of imagery and storytelling in uncovering hidden needs

• Examples of deep metaphors that changed brand strategy

• Why emotional meaning is the foundation of consumer decision making

• How deep metaphors support creative development and positioning

• The value of psychological depth in a fast-moving and automated world

• What it means to understand the stories behind customer choices

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In this episode of Signal & Noise, hosts Brian Lamar and Andrew DeCilles speak with Ben Cortese, Vice President of Decision Sciences and Innovation at KS&R, to explore how custom AI chatbots are reshaping the way research insights are accessed, shared, and expanded beyond traditional deliverables.

Ben explains how his team is combining qualitative and quantitative research with secure AI systems to build proprietary chatbots that allow clients to interact naturally with their own data. These tools help stakeholders ask new questions, explore nuances, and identify early opportunities without re-fielding studies or relying solely on static reports.

The discussion covers how KS&R structures these models to remain accurate, safe, and aligned with proven research findings. Ben also walks through the technical evolution of the tool, including early failures, the role of system guardrails, the importance of loading structured data, and why transparency and validation matter more than speed or novelty.

Key Takeaways:

• What it means to extend insights beyond traditional deliverables

• How custom chatbots are powered by proprietary qualitative content

• Why guardrails are essential to prevent drift, hallucination, and off-topic responses

• The process of grounding AI output to match known research narratives

• How AI can support ideation, early concept testing, and faster client exploration

• Where AI can accelerate the workflow versus where human judgment remains irreplaceable

• How researchers may evolve into curators, validators, and strategic translators

• The future role of AI in tracking, longitudinal analysis, and blended data environments

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In this episode of Signal & Noise, hosts Brian Lamar and Andrew DeCilles welcome the team from Verisoul, a company redefining fraud detection in market research. The guests include Henry LeGard, Founder and CEO, Joey Maddox, Chief Strategy Officer, and Erinn Taylor, who joins the conversation to explore how Verisoul uses banking-grade technology to detect and eliminate fraud while keeping real respondents in the data set.

Henry and Joey explain how Verisoul’s background in cybersecurity and fintech enabled them to develop invisible fraud-prevention tools that identify bots, VPN spoofers, and fraud rings in real time. The team discusses how their system detects human behavior through device patterns, network signals, and even physics-based methods like latency and impossible travel analysis, all without disrupting survey participants.

Brian and Andrew dive into how legacy fraud detection tools often over-block legitimate respondents, creating bias and frustration. The Verisoul team outlines how their approach balances protection with precision, reducing false positives and improving data integrity across the research industry. They also share insights from Verisoul’s large-scale fraud study that analyzed more than 50 million sessions, revealing global fraud trends and the role of device types in fraud rates.

Key Takeaways:

• How Verisoul applies banking-level fraud detection to market research

• The global scale of organized fraud farms and location spoofing

• The impact of false positives on respondent experience and data quality

• Privacy compliance across global markets

• Insights from Verisoul’s fraud research and data quality report

• The concept of real-time fraud and value scoring

• The growing importance of authenticated AI agents in fraud prevention

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In this no-filter episode of Signal & Noise, hosts Brian and Andrew dive into one of the most pressing issues in market research: the misuse of fraud detection platforms. They unpack how digital fingerprinting tools, while valuable, are often implemented in ways that damage data quality and block legitimate respondents.

Brian and Andrew explain how overly-aggressive fraud settings can create non-response bias, limit sample diversity, and frustrate real participants. They reveal why using multiple fraud detection tools or relying solely on automation can lead to distorted data and wasted resources.

They share lessons from industry research, stories of clients who turned off their fraud filters and saw better outcomes, and practical insights into balancing data protection with respondent experience. The conversation builds toward Brian’s “Eight Steps to Winning,” a clear framework to improve quality, restore trust, and move the industry forward.

Key Takeaways:

• Why misusing fraud detection tools can do more harm than good

• How false positives block real people and skew your data

• The hidden consequences of using multiple fraud platforms

• The Eight Steps to Winning framework for better data quality

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In this episode, Brian and Andrew sit down with Isaac Rogers, CEO of Sago Health, for an in-depth conversation about the rapidly changing world of healthcare research.

Isaac shares his path from technology entrepreneur to leading one of the most respected names in healthcare insights. Together, they explore how qualitative and quantitative research are merging, how artificial intelligence is shaping the future of patient and physician studies, and why the healthcare sector is becoming one of the most innovative areas in the research industry.

• Isaac’s Journey: How a single lunch meeting with Jim Bryson set the stage for an unexpected and rewarding career in market research.

• Sago Health’s Mission: What the company’s new independent structure means for clients and the healthcare research community.

• Hybrid Research: Why integrating qualitative and quantitative methods provides a more complete view of both patient and physician experiences.

• AI and Synthetic Data: How technology is helping researchers reach hard-to-find audiences and improve efficiency in healthcare studies.

• Industry Trends: How pharmaceutical companies, medical device manufacturers, and healthcare systems are adopting new methodologies faster than ever before.

Stay tuned until the very end of the episode to hear blends of expertise, humor, and practical insights!

Connect with Isaac Rogers on LinkedIn: Isaac Rogers

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In this episode of Signal & Noise, Brian Lamar sits down with Dan Foreman, one of the most influential voices in market research, to reflect on a 30-year career that has shaped the industry’s evolution from clipboards to AI. From launching global operations at FocusVision to investing in next-gen insight startups like Zappi, Dan has always been on the leading edge of innovation.

Dan shares his fascinating career path - starting as a researcher at Research International, then moving through marketing, consulting, and entrepreneurship - culminating in advisory roles across more than a dozen companies. He also dives deep into the founding of the ESOMAR Foundation, created to support researchers in crisis zones, and the impact of building community-driven change in a global industry.

The conversation explores Dan’s investment philosophy, how he evaluates new ventures using a mix of “science and X-factor,” and his latest venture into biotech and longevity through initiatives like The Infinite Games. With stories that span continents, boardrooms, and industries, this episode is a masterclass in staying curious, connected, and committed to meaningful innovation.

Key Takeaways:

• Career Longevity & Reinvention - How Dan’s career evolved through constant curiosity and boundary-pushing.

• ESOMAR Foundation Origins - The moving story behind founding a global nonprofit supporting researchers in need.

• Entrepreneurial Insight - What Dan looks for when investing: purpose, innovation, and a positive impact on the industry.

• M&A and Industry Shifts - His perspective on the Qualtrics-Press Ganey-Forsta merger and what it signals for the future.

• Biotech & Longevity Crossover - How Dan’s new ventures explore the intersection of human health, data, and innovation.

  
  

🔗 Connect with Dan Foreman on LinkedIn: Dan Foreman

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In this episode of Signal & Noise, Andrew and Brian are joined by Alex Millet, CEO of Brandtrust, for a thought-provoking conversation on the intersection of emotion, insight, and innovation. Alex explains how Brandtrust helps companies uncover the deeper psychological and emotional forces that shape consumer behavior, what they call “Human Truth.”

The discussion dives into how brands can balance data-driven decisions with empathy-driven understanding, especially in an era increasingly dominated by automation and AI. Alex shares his perspective on how human-centered storytelling, narrative research, and empathy-based strategy can transform how organizations connect with customers and build loyalty.

From uncovering the subconscious motives behind purchasing behavior to redefining what authentic branding means in a digital-first world, this episode is a reminder that even as AI advances, emotion remains the ultimate differentiator.

Key Takeaways:

• The Role of Emotion in Insight - Why understanding emotional motivation creates stronger, more resonant brand connections.

• Human Truth as a Competitive Edge - How Brandtrust’s approach helps organizations move beyond surface-level data to uncover deeper meaning.

• Empathy in a Digital Age - The importance of integrating humanity into strategy, storytelling, and leadership.

• AI Meets Emotion - How technology can support, but not replace, the human side of research and decision-making.

• Leading Through Story - Alex’s reflections on how great brands leverage emotional truth to inspire change from the inside out.

🔗 Learn more about Brandtrust: https://brandtrust.com/who-we-are/

🔗 Connect with Alex Millet on LinkedIn: Alex Millet

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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

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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

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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

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In this episode of Signal and Noise, Brian and Andrew sit down with Tom Anderson and Spencer Imel, co-founders and partners at The Langston Co, a quant-focused consumer insights firm known for deep category expertise and rigorous research standards.

Tom and Spencer share the origin story behind Langston, from their early days working together at a fast-growing Denver startup to building a research firm rooted in reliability, trust, and methodological discipline. What began as two social scientists exploring how to understand consumers evolved into a firm now operating at the intersection of AI, category intelligence, and scalable insights.

The core of the conversation centers on a bold idea: AI has made speed cheap, but trust is still expensive.

Langston describes its journey from early skepticism about AI to building a sophisticated internal Insights Assistant that sits on top of category-level survey ecosystems. Instead of treating AI as magic, the team invested heavily in understanding how large language models actually work, including context windows, tool calls, and failure points. By combining structured survey data, industry context, and documented research methodologies, they created a system that accelerates analysis without sacrificing rigor.

The episode includes a live walkthrough of their AI-powered Insights Assistant, demonstrating how a brand manager could instantly explore brand performance across age groups within a facial skincare category. The conversation then zooms out to tackle bigger questions about the future of research, including:

• Will chat-based AI become the new dashboard?

• How should firms balance automation with human interpretation?

• What happens to the role of the researcher in an AI-forward world?

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Brandon Richard returns to Signal and Noise for his second appearance, joining Brian and Andrew in person at The Link Group’s Durham, North Carolina, office. The conversation picks up where their previous AI discussion left off, diving deeper into what has actually changed in the past few months and what has not.

As an AI enthusiast and healthcare research leader, Brandon shares how The Link Group approaches AI pragmatically. Rather than chasing every new tool, the team focuses on understanding core AI categories such as conversational surveys, synthetic data, knowledge management, and generative productivity tools. The number of vendors may be exploding, but the foundational capabilities remain relatively stable.

The episode also explores a bigger existential question for the research industry. If AI can generate longitudinal synthetic respondents and analyze business questions directly, what role does market research play? Brandon argues that the value of research lies not just in answers but in the collaborative process. The refinement of business questions and the strategic intuition researchers bring to the table are difficult to replicate with a single AI prompt.

Key Takeaways:

• AI tools are multiplying fast, but the core research use cases have not changed much.

• Synthetic data still makes the most sense as augmentation, not replacement.

• The magic of research is in the process, not just the answer.

• AI is most powerful as a thinking accelerator.

• If research becomes “question in, answer out,” the industry is in trouble.

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In this special in-person episode of Signal and Noise, the hosts sit down with Beth Finn, CEO, and Jason Ebbing, COO of The Directions Group, for a wide-ranging conversation on the future of insights leadership.

Beth and Jason share their career paths, how The Directions Group approaches integrated intelligence, and what it means to move beyond siloed research toward clearer signals that drive real business action. The discussion also explores data quality, speed to insight, pricing research based on value, and how artificial intelligence should support rather than replace human thinking.

This episode offers a candid look at modern leadership in the insights industry and how organizations can stay relevant as decision-making accelerates and expectations rise. 

Key Takeaways:

• Clients are overwhelmed with data but still struggle with clarity and decision-making

• Integrated intelligence works best when multiple data sources are planned together from the start

• Research teams gain influence when insights are tied directly to business actions

• Data quality must be usable, credible, and actionable to create real value

• AI should amplify human judgment, not replace it, especially in strategy and leadership

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In this episode of Signal and Noise, Brian Lamar sits down with Frank Kelly, one of the most experienced voices in panel management, sampling, and respondent engagement, to unpack what is actually broken in online research and how the industry can fix it.

Frank reflects on nearly four decades working across every major panel model, from postal and telephone panels to online access panels at Nielsen, Kantar, Ipsos, and now Virtual Incentives. He explains why today’s fraud and data quality challenges are not new problems, but the result of incentives, engagement, and trust being systematically undervalued for years.

A central theme of the conversation is compensation. Frank makes the case that low incentives drive fraud, disengagement, and professional respondents, while fair and meaningful incentives expand the pool of real people willing to participate. He challenges the assumption that higher incentives automatically increase fraud and explains why the opposite is often true.

The discussion also explores how conversational AI, video, and smarter profiling can radically improve panel quality if paired with the right incentive strategy. Frank outlines a future where premium panels support deeper qualitative work, smaller samples, and AI-powered synthesis, all while maintaining higher standards of validation and trust.

Key Takeaways:

• Low incentives shrink the respondent pool and invite fraud

• Fair compensation expands access to real, engaged participants

• Incentive strategy is as important as fraud detection technology

• Conversational AI and video can improve quality when paired with better pay

• Premium panels will be essential as big qualitative research grows

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In this episode of Signal and Noise, Brian Lamar and Andrew DeCilles are joined by leaders from CASE4Quality for a candid and deeply informed conversation on the state of data quality in market research.

The discussion features Mary Beth Weber, founder of CASE4Quality, alongside Tia Maurer - Data Quality Guru, Efrain Ribeiro - Godfather of Sampling, and Karine Pepin - Data Fairy. Together, they unpack how the industry arrived at its current data integrity challenges and why progress has been slower than many expected.

The episode explores the realities of online sampling, fraud, and professional respondents, including how the promise of unlimited and inexpensive sample has distorted incentives across the ecosystem. The guests explain how aggregation, lack of transparency, and pressure for speed and cost reduction have quietly undermined confidence in research outputs.

The conversation also addresses the growing tension between AI-driven research and poor-quality input data. The panel warns that synthetic data and advanced analytics cannot solve quality problems if the underlying data is flawed. Throughout the episode, the group emphasizes the need for transparency, accountability, and brand-led standards to restore trust and long-term viability to the research industry.

Key Takeaways:

• The industry operates under the false assumption that unlimited high quality sample exists

• Speed and low cost have consistently been prioritized over data integrity

• Fraud and professional respondents remain widespread and often undetected

• Aggregated and opaque sampling practices make validation nearly impossible

• AI and synthetic data amplify risk when built on compromised data foundations

• AI can improve efficiency in research, but human judgment is still essential for understanding emotion, taste, humor, and nuance.

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In this episode of Signal and Noise, hosts Brian Lamar and Andrew DeCilles sit down with Samuel Cohen, Ph.D., CEO of Fairgen, to explore how generative AI and advanced statistical modeling are reshaping the way consumer research is conducted, validated, and scaled.

Samuel shares his international academic journey, from studying mathematics and synthetic data research at Oxford to working with AI in industry labs before launching Fairgen. He explains how rising costs and declining data quality in traditional market research led him to build a platform focused on generating reliable, usable insights from limited samples.

The conversation breaks down the difference between partial simulation and full simulation, clarifying how Fairgen uses statistical models to amplify real survey data rather than replacing it outright. Samuel walks through real-world applications, including how enterprise clients use data amplification to unlock granular insights across small or hard-to-reach segments without dramatically increasing budgets or field time.

The hosts and Samuel also discuss where AI works well and where it falls short, particularly in high-stakes research, governance-driven projects, and complex quantitative methods like advanced conjoint analysis. The episode closes with a forward-looking perspective on how budgets, decision risk, and organizational governance will shape the future role of simulated data in consumer research. 

Key Takeaways:

• Generative AI can amplify small samples into enterprise-level insight without multiplying cost or field time.

• There is a critical difference between simulating data and strengthening real data, and most people get it wrong.

• Fairgen’s approach shows how math and models can reveal patterns humans cannot see at scale.

• Not all research should use AI, especially when decision risk and governance are high.

• The future of insights may be fewer surveys, smarter modeling, and faster strategic confidence rather than bigger sample sizes.

• AI can improve efficiency in research, but human judgment is still essential for understanding emotion, taste, humor, and nuance.

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In this special New Year episode of Signal and Noise, Brian Lamar and Andrew DeCilles return with a candid conversation about what 2026 may hold for the market research and insights industry. Drawing from months of conversations with researchers, technology leaders, and clients, the hosts share a grounded but optimistic view of an industry entering a period of economic repositioning, technological acceleration, and rising expectations for data quality.

The discussion opens with reflections on personal and professional goals before shifting into a wide-ranging outlook on volatility, global and political uncertainty, and how those forces shape research budgets and decision-making. Brian and Andrew explore why market research is well positioned to benefit from artificial intelligence, even as pricing pressure, consolidation, and competition continue to intensify.

Key Takeaways:

• The economic and political factors shaping research budgets in 2026

• Why artificial intelligence may reduce cost and time while raising expectations for quality

• The rising importance of verified and high-quality online samples

• The growth of synthetic data and hybrid research approaches

• How the role of the researcher is shifting toward insight and strategy

• Industry consolidation and what it means for agencies and panels

• Why innovation and experimentation will define competitive advantage in 2026

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