June 29, 2026
June 29, 2026
When Product Strategy User Researcher Mamie Dayan Vogel came to Dscout for an RFP, she was already under a lot of pressure to get this study right.
Affirm's C-Suite wanted to understand the competitive landscape for Affirm at scale—including how prospective and current users were applying “Buy Now, Pay Later” features.
Between resource constraints, a narrowed scope, and previous vendors falling short, prior rounds of research had only provided a glimpse into the broader market. And after six months of waiting, the C-Suite was ready for answers.
Affirm’s research team needed to deliver, make sure the results spoke to specific markets as well as the broader marketplace, and do it quickly.
In addition to time constraints, the team faced several challenges to this particular study, including:
While still in the exploration process before signing, Dscout understood the volume and scale of this project presented an unusual challenge. The team wanted to be sure they could pull it off before moving forward, so Dscout launched a pilot version of the study within four days that surprised and delighted Affirm's team.
“When [Dscout] had run a successful pilot version and had gotten quality answers, we were very delighted and surprised—and particularly surprised with the speed at which [they] executed the project.
Over three to four days, we'd gotten really quality answers, both qualitative and quantitative. We were impressed and delighted that there was that much upward initiative.”
After seeing the quality answers Affirm could get with Dscout in such a short period of time, they signed on the dotted line and quickly went into launch mode. The collaborators decided that a diary format gave the greatest optionality for activity and launched a study with 1,500 participants.
Even better, Affirm didn't have to wait until the end of the study to drip insights across different departments and invest in storytelling early. The sheer volume of participants also required Affirm to prioritize data for impact. They had to ask themselves, what were the most actionable and powerful insights they could take away from this study?
Dscout’s AI features created breathing room as an analytic partner. It helped surface patterns faster, cluster open-ended responses, and reduce manual burden. But Affirm didn't rely solely on AI for their analysis. They made sure all findings were thoroughly cited and double-checked the sources. Ultimately, human reflection was an invaluable tool for critical thought when looking at analytic trends.
The study surfaced so much volume of information that it continues to have a long-tail impact across the organization. Affirm’s research team continues to drip shareouts to different departments, tailored for different teams like product, business intelligence, and sales. Their insights are being used in roadmap conversations months later, and they have opportunities to continue going through data to surface specific insights that are needed.
Ultimately, Dscout’s team helped Affirm’s research arm achieve what they thought was a nearly impossible feat—a study with 75 different cohorts and 1,500 different participants, all on a tight timeline.
The study brought the types of invaluable insights that the C-suite needed to make critical product, sales, and marketing decisions. With AI as an analysis partner, Affirm also had the ability to surface patterns faster, all while keeping human analysis and storytelling at the forefront.