Topics
June 23, 2026
June 23, 2026
When Mamie Dayan Vogel came to Dscout for an RFP, she had a tall order to fill. As a Product Strategy User Researcher at Affirm, she needed to understand how a massive variety of users engaged with "Buy Now, Pay Later" financial products—and on a tight timeline to boot.
Affirm’s C-suite had long been pushing for a large-scale benchmarking study to map this particular competitive landscape. The recurring request had been circulating in various forms since 2018, yet it remained notoriously difficult to execute. Previous attempts had stalled due to resource constraints, narrowed scopes, and vendor limitations.
The mandate was clear: deliver a robust view of the customer experience at a scale that could influence product, design, and strategic business units. Here's how Vogel and Dscout made it happen.
This article is adapted from the webinar “Turning Research into Results”. You can watch it in its entirety here.
The path to the “Buy Now, Pay Later” insights was paved with logistical and ethical hurdles that had bested previous vendors. Beyond the sheer volume of data required, the team had to navigate the delicate intersection of research and real-world financial stakes on a tight timeline.
The project demanded answers at or near statistical significance across 75 distinct user cohorts. This was not a simple survey! It required finding and managing approximately 1,500 participants to ensure the data was representative of the broader U.S. landscape.
Unlike studies that use hypothetical prototypes, this initiative required participants to make real financial transactions. That meant researchers had to capture and protect Personally Identifying Information (PII) with intention and thoroughness, creating ethical stakes for data protection.
"Because the nature of this particular quantitative study requires PII and user-sensitive data, we had to be very thorough about getting and capturing that in a very protected way that didn't put our users' data in jeopardy. It became very expensive to get those quantitative metrics,” Mamie emphasized.
As the scope of leadership’s requests grew, a small, focused team from Strategic Finance and UXR needed to rise to the occasion.
Previous iterations of the study were purely quantitative, providing Affirm with static numbers but no narrative. Without a qualitative component, the team lacked an understanding of why users behaved in certain ways and had no clear direction on what Affirm could actually do about it.
"We didn't have the why,” said Vogel. “We had these static numbers around people's financial lives, but we didn't have any kind of story leading up to that moment in the customer's financial life...The quant was powerful; it told us a lot about the volume of these different segments, but it didn't tell us what could happen and what Affirm could do about it.”
Affirm didn't just need a software tool. They needed a partner capable of handling massive-scale quantitative data alongside rich, human-centered qualitative insights in a single study. They required a collaborator who could manage the logistics of real-world transactions while co-designing the research in real-time.
The "aha" moment for the team was realizing that if they were already investing in getting 1,500 people through checkout flows, they should also capture the qualitative "why" behind every click. This realization transformed the project from a standard benchmarking exercise into a foundational, transformative research initiative.
To succeed with a lean team, Affirm needed a partner to take over participant management and the heavy lifting of logistics. This would allow their researchers to focus on what they do best: analysis, storytelling, and strategic influence.
"We were already investing in getting 1,500 people through real checkout flows,” said Vogel. “The realization was: why aren't we doing more with that time and investment? Let's actually talk to users about their experiences."
While Affirm was in the process of evaluating a few different vendors, Dscout ran a mini pilot unprompted.
"We had narrowed it down to three different vendors at the time, and we were torn between two—Dscout and one other,” said Vogel.
“[Dscout] showed that they could do the work…We had launched it again with a different vendor who ultimately couldn't give us the accuracy of the quantitative data that we needed for it to succeed.”
The speed and initiative of the study surprised and delighted the Affirm team, sealing the deal for their work together.
From the start, Dscout brought researchers, account directors, and leadership into the room—rather than just sales representatives. This ensured that everyone understood the definition of the "quant question" and the immense responsibility of handling sensitive user data.
The collaborators designed a four-activity diary study that allowed participants to walk through multiple end-to-end digital shopping moments. This iterative approach started with a pilot, moved to a small-scale test of key questions, and finally launched the full 1,500-person study, with each phase informing the design of the next.
Using both proprietary and partner panels, Dscout screened 7,887 unique participants to find the 1,500 needed for the 75 distinct cohorts. The platform captured 7,468 distinct responses, providing the "abundance of questions" and volume required for statistical confidence.
Dscout handled the massive administrative burden of messaging participants and fielding hundreds of questions. They were even able to reassign merchants to participants on the fly if field circumstances changed, keeping the study alive and responsive.
Vogel used Dscout’s AI filtering and clustering tools to navigate the sheer scale of the qualitative data. The AI helped surface patterns faster and pulled cited quotes at scale, acting as an analytic partner that reduced manual burden, while still requiring human reflection for final validation.
Dscout was not just a "yes" person; the team pushed back on scope and flagged where completion rates might suffer. By being realistic about what could be asked of participants, they co-created solutions that ensured the study's ultimate success.
The result of the partnership was a landmark initiative that restored Affirm’s C-suite confidence and created a permanent resource for the entire organization.
Insights from the study are currently informing product roadmap decisions across multiple departments. "It's being used in strategic decision-making around product roadmap,” said Vogel. “And it's being used in strategic decision-making around research projects, where we need to go deeper, and where we can use this as a springboard or a complement."
Strategic decisions around CTAs, interaction design, and value propositions are now grounded in this massive dataset.
The team adopted a drip strategy, sharing insights throughout each wave of the study rather than waiting months for a final deliverable. "We had the ability to not feel like we had to wait until the end to start socializing the insights,” said Vogel. “We had this opportunity to drip insights along the way and say, 'This is what we're seeing. This is the level of confidence that we're seeing it—both statistical and emotional and emphatic confidence'—and set the tone that this is really an evolving, breathing research initiative."
A research team of just six people pulled off a feat that previous teams double that size couldn't land. Dscout’s participant management and AI tools made a dataset of over 7,400 responses navigable for a single researcher, freeing them to focus on high-level storytelling.
The study is no longer a "one-and-done" report but a living repository that Vogel continues to slice by cohort and merchant type. The data serves as a springboard for new research projects and continues to ripple across product, design, and sales departments.
“We're still bringing it to different product partners.
We're still socializing it with different strategic parts of the business that are setting the roadmap over the coming quarters... this is not just your typical usability study of what went well and what friction can we minimize.”
By combining the "what" of quantitative benchmarking with the "why" of qualitative storytelling, Affirm achieved a nearly impossible feat: a 1,500-participant study across 75 cohorts on a tight timeline. This project didn't just provide answers for the C-suite; it fundamentally changed how Affirm’s design, product, and strategy teams think about their users.
For other practitioners looking to bridge the quant-qual gap, Vogel’s advice is to embrace the discomfort of new methodologies. "Don't be afraid of quant," she suggested, as long as you find a partner who understands the power of human voices.
When you move beyond transactional vendor relationships toward true co-design, you don't just get a report—you get a living repository of human voices that can guide your organization for years to come.
