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Research Quality Lives in People, Not Binders

DWG Admin on June 22, 2026

What a clean ISO 20252 audit actually proves.

Most quality audits end with a list. The auditor walks the floor, reviews the records, sits with the team, and then hands over a tally: a nonconformity here, an observation there, an “opportunity for improvement” that everyone nods at and files away. The list is the point. It is, in a way, how an audit proves it did its job.

This year, our list was empty.

L&E Research completed its first ISO 20252:2019 surveillance audit with zero nonconformities and zero areas of note. Nothing flagged. Nothing to fix. The audit was conducted by CIRQ, the Insights Association’s accredited certification body for ISO 20252, and the auditor’s closing remark was longer than the list of findings: “I am very pleased and impressed with what I have seen. I have no concerns.”
That is a bigger deal than it sounds, and it is worth explaining why.

What the standard actually measures

For anyone outside the certification weeds: ISO 20252 is the international quality standard for market, opinion, and social research, including insights and data analytics. It governs the full arc of a research project, from design and sampling through data collection, processing, analysis, and reporting, and it applies across qualitative and quantitative work alike. It was built by the global research industry through ISO, with input from professional bodies including Esomar, precisely so that research buyers would have a consistent benchmark for judging how rigorously the work behind a result was actually done.

Certification is not a logo you purchase. It is a system an auditor inspects, and then keeps inspecting.

That last part matters more than it first appears. Earning a certification is one thing. A surveillance audit, the check that happens between full recertification cycles, asks a harder question. Not “can you pass on your best day,” but “is this genuinely how you operate a year later, while running live work across multiple sectors in the middle of ongoing change?” One is a performance. The other is a habit.

And a clean surveillance audit is rare. Anyone who has sat through a decade of them will tell you that findings are nearly a given. A minor nonconformity or two becomes so routine it can start to feel like proof the auditor was paying attention. James Wilson, a CTO consultant with more than 20 years in the industry, said it best: “I’ve been involved with ISO surveillance audits for over 10 years, and I’ve never had one without some sort of finding. I just assumed that’s how the auditors prove their worth. Turns out not true, and the L&E team behind this did a truly amazing job.”

So what produces a result like that?

Not a binder.

It is tempting to credit the documentation, because documentation is what an audit appears to examine. But a clean audit is not really a verdict on your paperwork. It is a verdict on whether the behavior behind the paperwork is real. And behavior comes from people.

It is the account manager who spends the extra time understanding what a client actually needs before a scope is set. It is the recruiter who double-checks a response that does not quite add up. It is the project manager who catches a small detail and picks up the phone before it becomes a large problem. It is the data team member who validates the file one more time when the deadline says they could stop. And in at least one memorable case, it is the facility manager who spends hours shredding diapers, making sure nothing from a confidential study ever leaves the building. (Yes, that is a real thing. Quality work is not always glamorous work.)
None of those moments live in a process document. They are choices, made by individuals, usually when no one is auditing them. The standard describes what good looks like. People are what make it true.

Why this matters to the person commissioning the research

For the insights professionals who buy research, this is the part worth sitting with. Process rigor is invisible in a proposal. You cannot see, on paper, whether a recruiter re-screened a borderline respondent or whether a data set was validated once or three times. You find out later, in the quality of what comes back: in whether the people in the room are who the screener promised they would be, and in whether the data holds up when you build a decision on top of it.

A certification does not guarantee that any single project will be flawless. No honest standard claims that. What it signals is that the organization behind the work has built quality into how it operates, rather than improvising it study by study. A clean surveillance audit is evidence that the benchmark is being met not just on the day of the test, but on the ordinary days in between. We are not going to pretend a clean audit means the work is never hard or never messy. Real research is chaotic by nature. Schedules compress, respondents cancel, scopes shift mid-field. The value of a quality system is not that it removes the chaos. It is that it holds under it.

That, more than the certificate on the wall, is what we are proud of. Not that we passed, but how we passed, and who made it possible. The standard was met by the same people who meet it every day when no auditor is watching.

If you want to talk about what research quality looks like in practice, not on a checklist, start a conversation with L&E Research.

“Why Is My Photocopy So Blurry?” Why AI Is Running Out of Human Truth, and How You Can Protect Your Brand

Brett Watkins on June 19, 2026

By Brett Watkins, CEO, L&E Research

Most of us are mulling the future of the insights industry and the impact of AI and synthetic data on helping brands predict human behavior. AI and synthetic data are promising the next “cheap insights, even faster!” As a qualitative research guy, I feel like I’ve seen this movie before. But this time the pitch is more seductive than ever, given the omnipresence of artificial intelligence in our world today.

And then it hit me: this is analogous to the problem with photocopies.

Oddly enough, what got me thinking wasn’t something from within the industry — it was a question asked directly to Sam Altman, CEO of OpenAI. Lenny Murphy, a well-respected industry expert, recently posted in his Insight Innovations Substack about an OpenAI event where the question was posed: what happens to AI models when there is no training data left? The answer wasn’t reassuring. By current estimates, the global supply of ground truth human-generated data — the real, verified, first-person human content that trains AI systems — could be exhausted somewhere around 2030.

Lenny framed it well: “Primary research has always sold itself as ‘access to human truth.’ For a generation, that value proposition was under pressure from secondary data, synthetic data, and passive behavioral data. Now those pressures are converging with an active supply deficit that makes the industry’s core product — structured, validated, first-person human data — more strategically valuable than it has been in decades.”

The AI revolution runs on human-generated data — the words, opinions, behaviors, and experiences real people have produced and shared over decades. Every large language model you’ve used — ChatGPT, Gemini, Claude, Perplexity — was trained on an enormous corpus of human-written text. The problem is that corpus is finite, and the models are eating it faster than we can produce it.

Epoch AI estimates the effective stock of quality human-generated public text at roughly 300 trillion tokens, with full utilization projected somewhere between 2026 and 2032. Elon Musk declared at CES that AI has essentially exhausted available real-world training data. Dario Amodei, CEO of Anthropic, has publicly acknowledged data scarcity as a meaningful risk to continued AI scaling.

So what does the AI industry do when it runs out of human truth? It turns to synthetic data. And that is where the photocopy analogy comes into play.

The Photocopy Problem

What happens when you photocopy something over and over again? By the fifth or sixth generation, the text is blurry, the details are fading, and what started as a crisp original has become a smeared approximation of itself.

That is exactly what happens when AI trains on AI-generated data.

In July 2024, Oxford University researchers published a peer-reviewed paper in Nature that rattled the AI world. When AI models are trained on synthetic data — content generated by other AI models — subsequent generations degrade. Not subtly. Dramatically. Rare knowledge disappears first. Outputs drift toward bland, averaged generalities. Diversity collapses. The researchers called this model collapse. Some academics have gone further, calling the recursive version — training AI on AI that was trained on AI — “Model Autophagy Disorder.” The models, quite literally, begin eating themselves.

By April 2025, an estimated 74% of newly created webpages already contained AI-generated text. The web that future AI will scrape for training data is increasingly a web that AI already wrote.

The 2025 GRIT Insights Practice Report found that data quality concerns among insights professionals have surged 40% year-over-year, driven specifically by anxiety over synthetic respondents, AI bots masquerading as real people, and the integrity of the data supply chain. As one GRIT respondent put it plainly: “Bad data amplified by AI erodes trust faster than ever.”

The photocopy machine is running on fumes — and the industry knows it

What This Has to Do With Your Brand

For several years, synthetic data has been promoted as a faster, cheaper alternative to primary research. Why recruit real consumers when AI can simulate what they’d say? Why run a focus group when a synthetic persona can model the response in minutes?

The pitch is seductive. Research teams using synthetic data report high satisfaction — 87% express positive feedback, according to GRIT — and a 2025 Qualtrics study found 62% of market researchers used synthetic data in the previous six months. Adoption is real and accelerating.

But here is the uncomfortable truth the adoption numbers don’t tell you. The same researchers watching AI models collapse from a diet of synthetic data have identified what they call hyper-accuracy distortion — a tendency for synthetic responses to produce answers that are too clean, too consistent, and too confident. In other words: platitudes and generalizations. Not insights. Not human.

Carnegie Mellon researchers studying AI-generated interview responses found a consistent pattern: while AI can sound plausible and articulate, it fundamentally lacks real-world context and authentic lived experience. That’s not a software bug to be patched. That’s an ontological reality. AI has never stood in a grocery aisle, held a product, and felt the flicker of hesitation before putting it back on the shelf. It has never sat at a kitchen table and felt the quiet relief of finally finding a solution to a problem carried for months.

Brands make eight, nine, and ten-figure decisions based on research. Synthetic data drifting from reality as it compounds on itself is not an adequate foundation for those decisions.

The Scarcity Paradox: Why Human Data Has Never been More Valuable

Here’s where I want to reframe the conversation entirely.

The same dynamic threatening the long-term quality of AI models is simultaneously making verified, structured, first-person human data the most strategically valuable commodity in the insights industry. Don’t take my word for it — OpenAI and Google have signed licensing deals with major publishers and human-first content creators. The hyperscalers are not doing this out of nostalgia for human authorship. They’re doing it because human-generated ground truth data is becoming scarce, and without it, their models degrade.

Without ongoing human research, synthetic models lose their connection to how real people actually think, feel, and behave. Even Qualtrics — one of the more bullish voices on synthetic data’s potential — acknowledges that human respondents remain the irreplaceable source of truth anchoring all synthetic models. Which raises a question worth asking, brand leaders: when exactly did Qualtrics assume ownership of the data it collected on your behalf to build its models and grow its valuation?

The 2025 GRIT report is clear: the insights industry faces a trust crisis, and the solution isn’t a technology fix. It’s a return to authentic human understanding. The firms pulling ahead are those combining AI-native tools with genuine human expertise — not those replacing one with the other.

Your customers — real, verified, ID-validated people who can tell you what they actually think, feel, want, and do — are the exact resource the entire AI industry is running low on. That is not a crisis for primary research. That is a mandate.

The Bottom Line

Synthetic data has a role to play. Used appropriately — as a complement to human research — it is a useful tool. I’ve said it before and I mean it. Heck, I’m an investor in it.

But as a replacement for real human voices? The science says no. The engineering says no. The GRIT data says no. And four decades of watching brands make decisions based on shortcuts in the research process says no.

Sam Altman’s team is worried about running out of human truth. Your competitors are quietly hoping you’ll settle for synthetic substitutes while they invest in getting closer to their actual customers.

Don’t let them.

At L&E Research, we have been building toward this moment for a long time — not because we predicted the AI data crisis, but because we never stopped believing that the foundation of better understanding humans is creating a healthy ecosystem where brands and their customers can engage. Our panel of over 1.6 million ID-validated US consumers, patients, and medical professionals isn’t just a recruiting asset. In the world we are now entering, it is a strategic one.

The magic of what we do — the reason brands keep coming back after 40 years — is simple. We bring companies and people together to talk. Real people. Real conversations. Real truth. That’s where smarter decisions get made.

We’re not giving you fifth and sixth generation photocopies you can barely read. We’re giving you crystal clear insight into how to move the needle on your brand.

Brett Watkins is the CEO of L&E Research, a research solutions firm that has connected brands with their customers since 1984. L&E delivers high-quality, US-based insights by bringing together ID-validated panel, purpose-built technology, research facilities, and talented people — because smarter decisions start with real conversations with real humans. If you’re a brand leader or the agency behind one, we are the people for you.

L&E Research Passes First ISO 20252:2019 Surveillance Audit With Zero Findings

DWG Admin on June 19, 2026

RALEIGH, N.C. — June 17, 2026 — L&E Research, a trusted partner connecting companies with people to make meaningful conversations happen, today announced it has completed its first ISO 20252:2019 surveillance audit with zero nonconformities and zero areas of note. The audit was conducted by CIRQ, the Certification Institute for Research Quality, an accredited certification body and a subsidiary of the Insights Association. The result confirms the company’s continued certification to the international quality standard for market, opinion, and social research.

ISO 20252 governs the full arc of a research project, from design and sampling through data collection, processing, analysis, and reporting. A surveillance audit is the independent check conducted between full recertification cycles, and it tests whether a certified organization maintains the standard during live, day-to-day operations rather than only at the point of initial certification. Audits of this kind commonly return at least minor findings; a result with none is uncommon.

“A certification proves you can meet a standard. A clean surveillance audit, a year later, proves you live by it,” said Brett Watkins, CEO of L&E Research. “This result did not come from a policy binder. It came from people who do the work right when no one is watching. I could not be prouder of our teams.”

The audit reviewed L&E’s operations across multiple research sectors during a period of active client work. Company leadership attributed the outcome to the behaviors that sit beneath the documentation: account managers who clarify client needs before scoping, recruiters who re-screen borderline respondents, project managers who surface small issues early, and data teams who validate results before delivery.

L&E Research also holds ISO/IEC 27001 certification for information security management, placing it among a small group of research providers worldwide certified to both standards.
For research buyers, ISO 20252 certification offers a consistent, independent benchmark for evaluating the rigor of a research provider’s processes. L&E Research maintains the certification across its operations.

Press contact:
Kelli Hammock, Director of Marketing, khammock@leresearch.com

About L&E Research

L&E Research is a trusted partner connecting companies with people to make conversations happen. Since 1984, we have helped the world’s leading brands understand their customers through the power of human connection and innovative recruitment and research solutions. We serve a wide range of industries, including healthcare, consumer goods, legal, biotech, and more, delivering trusted insights that help clients make smarter, more meaningful decisions. Learn more at leresearch.com.

The Room Where It Happens: Why In-Person Qualitative Research Still Matters

DWG Admin on April 23, 2026

By Brett Watkins, CEO, L&E Research

Grab your coffee (or your beverage of choice, no judgment here), because I want to talk about something that’s been on my mind as I watch our industry sprint headlong into the age of AI, synthetic data, and remote-everything research.
In-person qualitative research is still the most powerful tool brands have for understanding their customers. And I worry we’re talking ourselves out of using it.
Let me explain why that matters, and why a book recommended to me by a client in one of the largest brand companies in the world makes the case better than I ever could.

The Mystery No Dashboard Can Solve

David Scott Duncan’s The Secret Lives of Customers opens with a deceptively simple problem: a fictional café chain called Tazza is losing customers, and nobody can figure out why. They have the data. They have the metrics. They have the dashboards. And yet the answer eludes them, right up until someone does something radical.

They actually go talk to their customer.

Duncan’s central insight, rooted in the “jobs to be done” framework pioneered by the late Clayton Christensen at Harvard Business School, is this: customers don’t buy products. They “hire” products, services, and brands to do a specific job in their lives. And when that job goes undone, or when a competitor does it better, customers fire you. Quietly. Without a survey response, a complaint email, or a single data point to warn you it’s coming.

That’s the mystery. And here’s the uncomfortable truth for insights leaders: no amount of behavioral data, no synthetic persona, and no AI-generated summary can fully crack it. Not yet. Maybe not ever.

Because the job a customer is hiring your product to do isn’t always the job you think it is.

What “Jobs to Be Done” Really Demands

The “jobs to be done” framework is brilliant in its simplicity, but it’s deceptively hard to execute well. The reason? You cannot identify the real job — the functional need, the emotional driver, the social context — from a survey alone.

Think about it this way. If Tazza had sent a questionnaire asking “Why did you stop coming in?”, they would have gotten answers. Probably logical, coherent, reasonable answers. “Prices went up.” “Location wasn’t convenient.” “I found somewhere closer.”

But what they would have missed is the real story: the feeling, the context, the moment. The fact that Tazza used to feel like a neighborhood living room, and now it feels like an airport terminal. That’s not a multiple-choice answer. That’s a conversation.

The jobs-to-be-done framework demands what Duncan calls “market detective work”: observation, curiosity, and the willingness to follow a thread wherever it leads. And for that, you need to be in the room.

The Case for the Room

I’ve been in this industry for over 30 years. I’ve watched research evolve from phone surveys to online panels to AI-assisted synthesis. Every evolution has brought real value. I’m not here to relitigate any of that.

But every time we move further from the physical room, we give something up. And I think we’ve started to forget what that something is.

When a consumer sits across from a moderator in a well-designed focus group facility, things happen that cannot be replicated on a Zoom call, and certainly cannot be inferred from passive behavioral data. A participant holds a product, and her grip tells you something. Another person starts to answer a question and then hesitates, and a skilled moderator follows that hesitation into the most important insight of the entire session. And don’t get me started on sensitive subjects, where I have watched grown men cry because of a solution they wish existed as they provided care for an ailing parent or child.

No algorithm catches those moments. No transcript captures what they mean. Only a human in the room — curious, present, and trained — could make that call.

These are the moments that change product roadmaps. These are the moments that save brands from launching the wrong thing to the wrong people for the wrong reasons.

The AI Argument Is Real. It’s Just Incomplete.

I want to be fair here. The argument for AI-assisted research, remote qual, and even synthetic data is not wrong; it’s just incomplete.

AI is extraordinary at synthesis. It can process hundreds of open-ended responses in a fraction of the time a human team could. It can identify patterns across datasets that would take weeks to surface manually.

Remote qual has expanded access in ways that matter: geographically, logistically, economically. We use it. We believe in it. And we’ve built technology to do it well. But Synthesis and access are not the same things as insight.

Synthetic data can model what people may do based on what they’ve done before. But it can’t predict what they will do. No one yet has cornered that outcome, but great qualitative research, conducted in real time, with real humans, in the real world, is still the closest thing I have seen to achieving it.

Duncan’s Tazza eventually figures this out. The breakthrough doesn’t come from better data analysis: it comes from going out and listening. From being present. From having actual conversations and following the threads that no algorithm thought to pull.

What This Means for Insights Leaders

If you’re leading an insights function, I’d ask you one question: when was the last time you or your team actually sat behind the glass?

Not reviewed a transcript. Not read an AI summary. Sat. Behind. The glass.

Because here’s what I know after four decades of watching the best researchers in the business work: the magic doesn’t happen in the report. It happens in the room. It happens when a brand-side researcher watches a real customer struggle to open their packaging and suddenly, viscerally, understands the problem 27 pages of quant data failed to communicate.

That moment of human-to-human understanding is the foundation of every great insight. And it’s available to you. It’s one conversation away.

Customers have secret lives. David Scott Duncan is right about that. They have needs they can’t fully articulate, contexts they’ve never been asked about, and jobs they need done that your brand may not even know it’s competing to fill. The only way to uncover those secrets is to get close. To be present. To create the conditions for real conversation that no survey or synthetic persona can come close to matching.

If you aren’t sure, ask yourself when the real insights in your own life transpired with the people who matter most to you. I’m told the younger generations love their phones, but I’ve watched my nieces’ and nephews’ faces light up when I leaned in, when their grandparents leaned in. The screen didn’t do that. Presence did. Humans are still most revealing when engaged in person. We are a social species. We don’t make decisions in a vacuum. Qualitative research is the psychological tissue that connects the dots on sociological behavior, and the best of it still happens in person, in the room, face to face.

That’s why our motto is: we bring brands and people together to talk. That’s where the magic happens. That’s where smarter decisions get made.

The room still matters. More than ever.

Brett Watkins is the CEO of L&E Research, a qualitative research firm that has connected brands with their customers since 1984. L&E operates research facilities across the United States and maintains a proprietary panel of 1.6 million ID-validated US consumers, patients, and medical professionals.

Inside L&E New York: Five Research Suites in the Heart of Midtown Manhattan

DWG Admin on April 22, 2026

New York City is the most concentrated qualitative research market in the country. The legal community, the healthcare sector, and the consumer brands headquartered up and down Manhattan all rely on facilities that can support complex, high-stakes research at the pace the city demands.

L&E Research operates a five-suite qualitative research facility at 28 West 44th Street in Midtown Manhattan, steps from Bryant Park. The facility is purpose-built for the kind of work that defines New York research: large-format jury studies, multilingual consumer groups, healthcare professional interviews, and the full range of qualitative methodologies that require physical space, professional infrastructure, and a team that knows how to make it work.

This is not a facility on the way. It’s here. It’s operational. And it’s designed for the research that matters most.

Five Suites, Each Built for Flexibility

The New York facility houses five focus group suites, each named for a Manhattan landmark: Landmark, Broadway, Grand Central, Central Park, and Wall Street. The naming isn’t just aesthetic. Each suite includes a dedicated conference room, a private client viewing room, and a client lounge, giving every session its own self-contained environment.

What distinguishes the New York suites is their size. The rooms are among the largest in the L&E network, which makes them especially well-suited for jury research and large-group methodologies. Mock trial work, deliberation studies, and co-creation sessions all benefit from rooms that can comfortably seat larger participant groups without the cramped, artificial feeling that smaller spaces create. For the legal research community, in particular, this matters: juror behavior changes when people feel confined. L&E’s New York rooms give participants space to interact naturally.

The Landmark and Broadway suites are hardwired for connectivity, meaning a presentation or stimulus shown in one room can be viewed live in the other. This overflow capability is valuable for large studies where stakeholder teams need separate observation space, or when two concurrent sessions need to share materials without duplicating equipment.

Technology That Supports, Not Replaces, the Room

Every suite in the New York facility is equipped with high-definition video recording and streaming capabilities, available through L&E’s HD video streaming platform and accessible via our secure client portal. Stakeholders who can’t be on-site can observe sessions in real time from anywhere, with the same video and audio quality as the viewing room.

The facility also provides on-site translation equipment for multilingual research, a significant asset in a market as linguistically diverse as New York. Cable pass-through between conference and viewing rooms supports custom A/V configurations, so research teams can set up stimulus displays, product demonstrations, or prototype walkthroughs without retrofitting the space.

The technology is designed to extend the reach of in-person sessions, not replace them. Streaming and recording make it possible for a broader stakeholder team to participate in the research, even when they can’t all be behind the glass.

The Team Behind the Space

A facility is only as good as the people who run it. L&E’s New York team manages every operational detail: participant check-in, room configuration, catering coordination, A/V setup, and the real-time problem-solving that live research inevitably requires. Clients consistently cite the New York team’s responsiveness and professionalism as what sets the experience apart.

That operational support is backed by L&E’s national recruitment infrastructure, a proprietary panel of 1.6 million ID-validated participants across the United States. For New York studies, this means access to the full diversity of the metro area’s population, whether the study calls for healthcare professionals in the tristate area, bilingual consumers in specific boroughs, or high-income decision-makers in Manhattan. The facility and the recruitment engine work together: the space is where the conversation happens, and the recruitment team ensures the right people are in the room.

Research That Belongs in New York

Certain research methodologies are especially well-served by the New York facility’s combination of size, location, and infrastructure:

Jury and litigation research benefits from the large room configurations, the proximity to New York’s legal community, and the ability to recruit from one of the most diverse jury pools in the country. Mock trials and deliberation studies need space that allows natural group dynamics, and L&E’s New York suites deliver that.

Healthcare professional research takes advantage of both the facility’s central location (accessible for physicians and clinicians across the metro area) and L&E Health’s specialized recruitment for patients, caregivers, and medical professionals.

Consumer research in the New York metro draws on one of the largest and most diverse consumer populations in the United States. For brands testing products, messaging, or concepts, the ability to recruit targeted consumer segments in New York and host them in a professional, well-equipped space is a significant advantage.

Large-scale qualitative programs that require multiple sessions over several days benefit from the five-suite layout, which allows concurrent or sequential sessions without competing for space.

Across all of these methodologies, the facility’s Midtown Manhattan location contributes to consistently strong show rates. Accessibility matters for data quality, and participants don’t need to navigate an unfamiliar part of the city to reach 44th Street.

L&E’s New York facility is open, operational, and ready for your next study. If you’re planning qualitative research in the New York metro, contact our team to show you the space and talk through how it can support your methodology.

Qual vs. Bot: A Study So Real, It’s Artificial

DWG Admin on October 23, 2025

The research world is buzzing about synthetic respondents, but the question remains: can AI-driven panels deliver the same nuance, insight, and emotional depth as real people? As synthetic panel technology matures, researchers are grappling with when – and if – it makes sense to replace human participation with machine-generated responses.

Join L&E Research as we unveil the results of a brand-new case study designed to put synthetic respondents to the test. In this session, we’ll compare real and AI-generated participants across several research tasks, revealing surprising insights about where synthetic data delivers, where it doesn’t, and what that means for the future of research. Along the way, we’ll highlight a few innovative platform features that made this experiment possible.

This isn’t just a theoretical discussion. We’ve built synthetic panels using retrieval-augmented generation (RAG) models and compared them to real participants recruited via Condux’s self-serve capabilities. The result? A compelling, unbiased look at when synthetic works, when it fails, and how researchers can smartly deploy it.

Whether you’re skeptical, curious, or already testing AI in your research stack, this session will help you understand what’s hype – and what’s real.

During this webinar, we’ll explore:

What we tested: An overview of the research design, including how we structured parallel studies with synthetic and real respondents.
How responses differed: Key findings on where synthetic participants aligned with, or diverged from, human data.
Methodological implications: What our results suggest about the strengths and limitations of using AI-generated respondents in various research scenarios.
Workflow considerations: A look at how survey logic, branching, and object detection influenced participant experience and outcomes.
Practical takeaways: Where synthetic inputs can realistically support qualitative and quantitative goals, and where caution is still warranted.

From Race to the Bottom to Rise of AI

DWG Admin on October 10, 2025

Each year, the Future Trends webinar gives us an opportunity to pause, reflect, and take stock of where the future of market research is headed. This year’s discussion was especially striking. Artificial intelligence (AI) is no longer a distant prospect on the horizon; it is here, shaping how we work, think, and deliver value.

As with every wave of innovation, AI forces us to reckon with what we’ve learned from the past. The insights industry has already lived through its own growing pains. For years, the “race to the bottom” drove down costs but left behind an enduring problem with data quality. That legacy continues to shape how we approach the work ahead.

The challenge before us now is simple in statement but complex in execution: how do we ensure that new tools like AI serve as a force for higher-quality insights, not just faster and cheaper outputs?

The Legacy of the Race to the Bottom

The story of the last decade in research is, in many ways, the story of a marketplace caught in a cycle of underbidding.

To win projects, companies slashed costs, often at the expense of participant incentives. That decision may have been expedient in the short term, but the long-term consequences were significant.

Participants became fatigued, undervalued, and, in some cases, disengaged altogether. Fraud crept in through the cracks. The result was an erosion of trust in the data itself, the very foundation of our work.

At L&E Research, we saw this problem emerging early and took it seriously. We invested in “research-on-research,” asking participants directly about their experiences, not just with us but across the industry. How did incentive levels affect their willingness to participate? How quickly did they expect to be paid? How did they feel about moderation and engagement styles?

These weren’t academic questions; they were existential.

When participants don’t feel valued, the quality of insights deteriorates. That’s why we aligned ourselves with industry-wide initiatives through the Insights Association and built fraud mitigation into our processes well before it became the industry’s headline concern.

The race to the bottom is part of the research industry’s legacy, but it is not our future. Having acknowledged how we got here, we now have the opportunity to move forward with stronger footing.

Data Quality in the Age of AI

Today, the conversation about speed and cost has been reignited by AI. Procurement departments push for faster, cheaper research. Sales teams feel pressure to deliver. And once again, quality risks being left behind.

However, the tools themselves are not the problem; it’s how we use them. AI can accelerate processes, but it can also strengthen outcomes if we put quality at the center of our applications. The choice is ours.

At L&E, we’ve seen firsthand how AI can be deployed to improve accuracy while also saving time. A recent case study with our CondUX platform is a powerful example. A client asked us to analyze nearly 200 photos submitted by participants. Traditionally, this would have taken a team of humans more than 18 hours to review and categorize. Using CondUX’s object detection capabilities, we reduced the process to just two and a half hours, including setup and quality control.

The time savings alone were impressive, but even more importantly, the AI surfaced errors that the human reviewers had missed. By flagging low-confidence images for human verification, CondUX didn’t replace human oversight; it enhanced it.

This shift is significant. Qualitative research has long relied on asking participants to describe their behaviors and environments. Object detection allows us to observe instead. Rather than asking what’s on a kitchen counter, we can see it directly. Observation has always been at the heart of qualitative work, and AI now gives us new tools to scale it without losing authenticity.

The lesson here is clear: AI doesn’t have to perpetuate the mistakes of the past. If used wisely, it can reverse them. Instead of cutting corners on quality, AI can elevate it.

The Human Factor: Training, Oversight, and Storytelling

Yet even as we embrace new tools, one truth remains unchanged: humans are central to research. AI may be, as one panelist described it, “the best intern you’ll ever have.” But even the best intern still needs a manager.

AI can synthesize information, but it cannot think critically. It does not problem-solve. Left unchecked, it can amplify errors rather than resolve them. The risk of over-trusting AI is the risk of making high-stakes business decisions on faulty insights, a mistake no brand can afford.

That is why human-in-the-loop oversight is non-negotiable. Researchers must continue to bring context, domain expertise, and discernment to every AI-assisted output. AI may help answer “what,” but humans must still interpret “why.”

This balance between technology and humanity is not just relevant for today’s practitioners; it also defines the training of tomorrow’s researchers. Academic institutions play a critical role here. Just as earlier generations learned math without calculators, students today must learn the fundamentals of research without over-relying on AI.

If researchers don’t understand the basics, AI becomes nothing more than a “yes-person,” agreeing, generating, and emulating without questioning. Only those who have mastered curiosity, empathy, and storytelling will know when the machine is wrong, and more importantly, how to use it responsibly.

The future of market research belongs to those who can balance both: the efficiency of AI and the empathy of human interpretation.

Looking Ahead with Optimistic Caution

The insights industry is entering a period of remarkable transformation. Investment in AI and other technologies is accelerating, and the potential to make research faster, more scalable, and more accessible is undeniable.

Optimism must be paired with caution. If we lean too far into speed and cost, we risk repeating the mistakes of the past and recreating the very data quality challenges we’ve worked so hard to overcome.

The way forward is not about rejecting efficiency. It is about balance. AI should help us achieve all three points of the triangle: speed, cost, and quality, without sacrificing one for another. That balance is not easy, but it is possible. And it is necessary if we want our work to remain meaningful, relevant, and impactful.

What gives me confidence is the spirit of this industry. Time and again, researchers have shown the ability to adapt, innovate, and lead. We are not passive recipients of technology; we are active shapers of how it is applied. If we keep people – participants, clients, and researchers – at the center of our work, then tools like AI will not just make us faster or cheaper. They will make us better.

Shaping the Future of Market Research

The future of market research is not defined by technology alone. It is defined by how we choose to use it. The race to the bottom taught us that neglecting participant experience and data quality comes at a high cost. AI gives us the chance to learn from that history and write a different story, one where speed and cost efficiencies are balanced with quality, and where human expertise guides every technological advancement.

At L&E Research, we believe the path forward is not about replacing people but empowering them. With the right balance of tools and talent, the future of market research can deliver insights that are not only faster and more efficient, but also deeper, richer, and more reliable. That is the future we should all be working toward.

L&E Research and Qrious Insight Partner to Advance Behavioral Data Integration for Smarter Research

DWG Admin on October 1, 2025

Raleigh, NC: September 22, 2025 – L&E Research, a trusted partner in qualitative research recruitment and insights since 1984, launched a strategic partnership with Qrious Insight, experts in behavioral data and insights.

The collaboration integrates Qrious Insight’s passive metering technology into L&E’s panel apps and websites. This integration combines traditional qualitative and quantitative research with real-time behavioral data. Researchers and brands can now enrich surveys and qualitative insights by tracking app usage, website visits, ad exposure, search activity, and more.
For L&E, this partnership enables dynamic profiling of panelists based on actual behaviors, improving targeting and recruitment while unlocking new research capabilities and product offerings. It also creates a better consumer research experience through less intrusive engagements that offer passive income opportunities for consumers and patients, addressing data quality issues pervasive in the insights industry

L&E Research Perspective

“We are excited to partner with Qrious Insight to offer research solutions that will disrupt the insights industry. Research began as an anthropological study of human behavior: we will now be able to offer brands and researchers alike the opportunity to both observe and ask consumers and patients about their brand experiences.
“Meanwhile, the number one complaint from consumers in qualitative research is the exhaustive questioning of their demographics and behaviors that rarely leads to opportunities to engage brands. This partnership will virtually eliminate this challenge. Brands are responding by focusing their data collection. Panel companies must do the same by investing in better solutions. This partnership is a win/win for everyone: Qrious, L&E, brands and consumers alike.”

Qrious Perspective

“Market research has long relied on what people say, but behaviors provide a complementary, fuller view that helps close the say/do gap,” said Andrew Moffatt, CEO of Qrious Insight. “By building an always-on behavioral data network, we are creating a foundation for smarter research, strengthened analytics, and AI applications across the industry.”

About L&E Research

Founded in 1984, L&E Research is the leading expert in qualitative research and insights, trusted by top brands and agencies to create meaningful conversations between people and the brands they love. With a reputation for excellence via our 95% “highly recommended” ratings by clients post project, L&E continues to set the standard for brand research in the U.S.

About Qrious Insight

Qrious Insight is a leader in behavioral data, providing advanced technology that captures and translates digital behaviors into actionable insights. By partnering with organizations that have established, first-party audiences, Qrious builds a network of behavioral data that empowers companies to better understand and serve their customers.

Security and Quality Aren’t Perks. They’re Prerequisites.

DWG Admin on September 15, 2025

When it comes to choosing a research partner, trust isn’t a luxury.

It’s the baseline.

That’s why two questions should always be front and center:

How do you protect my data?
How do you make sure nothing gets missed?

At L&E Research, we believe that security and quality are non-negotiable for ISO certified market research.

That’s why we’ve invested in dual ISO certifications: one for information security and one for research quality.

Very few partners hold both. Fewer still bake them into every project the way we do.

What It Means To Hold Both Certifications

At L&E, we understand that trust in ISO certified market research comes from two places: data security and process quality.

These two ISO certifications work together to cover both.

ISO/IEC 27001:2022 is the international standard for information security management. It ensures that your data is protected through formalized policies, risk assessments, employee controls, and encryption practices.
ISO 20252:2019 is the international standard for managing market, opinion, and social research. It ensures that every research project is executed with consistency, documentation, and methodological rigor across all phases.

Holding both means that we don’t just protect your data or deliver your research well.

We do both, every time.

Fewer Than Five Firms Hold This Dual Certification

The Insights Association, through its audit body CIRQ, has certified L&E Research to both ISO standards.

Fewer than five companies hold both certifications for ISO certified market research.

The dual status is rare and difficult to achieve. It represents a deep investment in systems training, oversight, and continuous improvement.

When you work with a partner that holds this distinction, you choose a level of excellence that goes beyond standard vendor relationship.

Why ISO Certified Market Research Matters To You

When you partner with an ISO certified market research firm that holds both standards, you gain tangible benefits across security, quality, and operational efficiency:

Peace of mind for IT and compliance teams. ISO 27001 certification assures that every layer of your project data, from client records to video files, to survey data, is protected by one of the most respected security standards in the world.
Confidence in research integrity. ISO 20252 certification ensures your qualitative and quantitative research is managed with consistent documentation, governance, and methodological accuracy.
Faster onboarding, fewer surprises. Auditable standards reduce friction in vendor approval processes, especially in healthcare, financial services, and tech where security and governance matter most.
Proof of excellence, not just promises. These certifications are independently verified, maintained through regular surveillance audits, and publicly listed through CIRQ. They reflect an organization that holds itself accountable.

Trust Is Earned

When we say we’re built for your peace of mind, it’s not just a promise.

It’s a process.

One that’s been extremely audited, globally validated, and continually improved to meet the ISO certified market research standards you deserve.

Looking for a partner that holds itself to the highest global standards? Let’s talk.

8th Annual Future Trends of Market Research and Technology

DWG Admin on September 10, 2025

Join us for our 8th annual Future Trends of Market Research and Technology roundtable, our most anticipated discussion of the year. Industry experts will share their perspectives on the future of qualitative insights, exploring how technology, authenticity, and shifts in information access are shaping the way we connect with people and deliver meaningful understanding.

With AI adoption accelerating, the rise if synthetic respondents, and major changes in how people search for information, the conversation will cover the issues most important to researchers today. This session will provide guidance on where qualitative research is headed and how to prepare for what’s next.

During this webinar, we will discuss:

A clear perspective on the trends that will shape qualitative research in the year ahead
Practical examples of how AI can enhance insights work while keeping people at the center
Guidance on protecting data integrity and ensuring genuine respondent voices are heard
A better understanding of how new search behaviors are influencing the way research is shared, discovered, and valued