If you blinked, you might’ve missed it—The Market Research Event 2025 flew by in a blur of big ideas, packed sessions, and hallway conversations that went late into the night.
What actually stood out?
We asked both client- and agency-side attendees to share their biggest takeaways.
AI IS EVERYWHERE, BUT WHERE’S THE STRATEGY?
Jenny Reece, Senior Research & Insights Manager, and AI Expert at Microsoft, was surprised by how much AI dominated the event. But the solutions tended to cluster around only two use cases, AI moderation and knowledge management. There was very little content that pushed the envelope on where AI could take the industry next:
- “I expected it to be important, but I didn’t realize just how much every company would be talking about AI. Beyond the sheer presence of AI, the ways it was being used seemed to be either AI-enabled qual or some kind of knowledge management/analysis tool. While these applications are impressive, I believe there’s still a vast range of AI use cases in market research that haven’t been discovered (or maybe just aren’t ready for a conference yet).”
Jenny also noted that we are only at the beginning of how AI is changing our industry, and we need to be prepared to adapt:
- “Many speakers stressed that humans remain essential throughout the market research process, and while I agree—and even spoke about this in my presentation—I think the impact of AI is still being underestimated. AI will continue to reshape roles and processes in market research, and its capabilities will only grow. This is something we need to acknowledge and prepare for.”
Stacy Tholking, VP Analytics & Insights at Procter & Gamble, talked about how the industry has put the cart before the horse when it comes to AI:
- “We are inundated with new AI solutions every day. It’s overwhelming. We need to identify what problems we’re actually trying to solve.”
VF’S TAKE:
It’s no surprise that AI stole the spotlight this year, but much of what we saw echoed familiar themes. With so many similar solutions on display, the question becomes—what’s next? We think it’s time to move beyond tech capabilities and focus on defining use cases.
THERE IS A NEW SKILL SET FOR RESEARCHERS
Ryan Leonard, Market & Customer Researcher, and Katie Ruiz, Senior Manager, Research & Market Intelligence at Cox Automotive, discussed the researchers’ new skill set:
- “Future researchers must blend technical fluency with business acumen and empathy. Soft skills—storytelling, stakeholder management, and ethical judgment—are what make research indispensable. The “last mile” of research—translating findings into business action—remains a human domain.”
Amy Anderson, Research Director and Owner of Solutions Through Research, talked about the importance of craft in working with AI:
- “The new frontier for researchers seems to be in curating inputs, labeling data, and designing the frameworks for AI to run within. The differentiator is now in how we determine what to feed AI, how we train it, and how we validate its outputs. One presenter reframed the familiar “garbage in, garbage out’ as “gold in, gold out”. Defining what counts as “gold” is the key to success.”
In a keynote session, Pamela Forbus, SVP, Global Chief of Insights & Analytics at Mondelez International, agreed—the key skills researchers need today are “business acumen, commercial understanding, and curiosity.”
VF’S TAKE:
A new era of research is here. As AI automates more of the process, the next generation of researchers will stand out not for what they can code, but for how they connect—synthesizing, interpreting, and telling stories that drive real decisions.
THE LINE BETWEEN QUANT AND QUAL ARE BLURRING. WHAT DOES THAT MEAN?
AI Moderation platforms like Listen Labs and Outset.ai represent a new methodology, and a great example of what AI can bring to our industry:
- “AI moderation enables qualitative research with unprecedented breadth, leading researchers to hypothesize that conversational AI qual tools could eventually replace quant research as we currently know it. One panelist said: ‘The only reason we do quant is because we can’t currently quantify qual.’” – Ryan Leonard & Katie Ruiz
Kevin Stocker, Senior Marketing Research Manager at Microsoft, spoke about how AI is enabling them to conduct 4-6,000 15-minute qual interviews, globally, in a week:
- “The most important benefit from this is speed. I can turn this around to my stakeholders in 1-2 days after getting the results.”
VF’S TAKE:
AI tools now make it possible to scale qualitative insights from a small number of respondents to hundreds or even thousands, uncovering themes and emotions at a depth we’ve never seen before. It’s an exciting evolution, but we think the focus needs to be on “what problem does this solve?” instead of “what features does this platform have?” Rather than create our own tech platform, we’ve chosen to build products using the best tech solutions, like our Qual-at-MASSIVE-Scale solution.
CLIENTS ARE NOW IN THE WEEDS WHEN IT COMES TO DATA QUALITY
Monika Mandrakas, Manager of Customer Insights from Mutual of Omaha, noted how data quality has become a key client concern and that insights leaders still struggle to get a seat at the table with executive leadership. Data quality is an open secret that clients have to actively engage with:
- “TMRE was a little bit of a support group for all of us client-side people as the data issues are not even an elephant in the room anymore. It was an open secret, and it was there in almost every session that I went to—how big a problem it is, and what are we going to do about it? The question to us is, are you willing to invest a little bit more to guarantee that the data is good? Maybe you need fewer completes, but of higher quality. We can’t just all be about quantity only anymore.”
VF’S TAKE:
Clients used to trust their research partners to control data quality—not anymore. We’ve had clients move work to us because they’ve finally gotten a seat at the table with senior stakeholders, only to be picked apart over suspicious verbatim responses. Our industry can’t afford for clients to be put in positions where they have to constantly defend their data. We’ve moved to using verified sample (e.g. through LinkedIn) for B2B, and programmatic checks + extensive human checks for B2C. The industry needs to be open with clients about the challenges with data quality and what we’re doing to address it.
AI PERSONAS: THE BEST OPPORTUNITY FOR SYNTHETIC DATA
Jason Kramer, Chief Research Officer at Vital Findings, noted that “a consensus is starting to emerge that the best use case for synthetic data is AI Personas, especially for hard-to-reach audiences. The cost and time of reaching these populations make synthetic data especially attractive.”
Charitie Dantis-Gayo, Corporate VP at New York Life, gave a great example of Hispanic small business owners:
- “They’re really expensive to reach, research takes a long time, if I can do a concept test with synthetic data, it lets me do research I couldn’t have done before.”
Romani Patel, Director of Data Science at Microsoft, talked about how the company started with AI personas for lower-hanging fruit like SMBs (small business owners) and then moved to hard-to-reach target CISOs (Chief Information Security Officers).
VF’S TAKE:
The challenge with synthetic data is that it’s a black box, and researchers hate black boxes. The benefit of AI personas is that they fit into the “explainable AI” paradigm—you can review what they say and “gut check” it. We think there’s strong potential here, but have yet to see a platform that fully delivers on this opportunity.
Traditional quant methods for creative testing are built for speed and scale, but the voice of the customer can be lost in a sea of metrics. Traditional qual methods give the customer a voice, but are time-consuming and challenging to scale. But what if you could do Qual at MASSIVE scale? 4000+ interviews, across multiple countries, in one week? And do it with engaging voice surveys that respondents love? That’s exactly what Microsoft and Vital Findings did, reshaping their research approach and finding a better, faster, AI-enabled way to evaluate creative.
This session will show you how Microsoft is using Vital Findings to bring back depth, emotion, and storytelling to creative testing research using Qual-at-MASSIVE-scale. We’ll explore how this new approach is changing how Microsoft approaches ad testing, and what it could mean for the future of research.
