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How Surefoot turned a paused custom build into a five-day Bike Finder MVP that powered a two-year testing program.
The brand
The Pro's Closet is an online marketplace for certified pre-owned bikes, built around a multi-point inspection process and a buyback program that gives cyclists a clear, trustworthy way to upgrade or sell their gear.
When Surefoot came on, the brief looked simple: build a guided shopping quiz to help high-consideration buyers find the right bike. The first plan was a fully custom build, but a mid-project platform change led us to pivot to a lean Typeform version that launched in five days. That quiz went on to collect six figures of first-party data and became the foundation for the two years of testing that followed.
The impact
When a platform change forced us to pause a custom build, the team pivoted and shipped a Typeform MVP in five days, and that quiz ran for the rest of the engagement. That's the kind of testing partnership we want to be: fast where it matters, patient where it has to be.
The challenge
Sizing, condition, returns, shipping, assembly: every unanswered question on a $1,000+ purchase is a reason to exit, and a buyer who leaves to research doesn't always come back.
Traffic was healthy, but most of it was anonymous: people researching for months, comparing models, and disappearing before they ever bought. There was no first-party data engine to keep the conversation going.
Partway into a custom Bike Finder build, the site's search platform was set to change, and the facets we'd designed the quiz around would have changed with it. We needed an approach that didn't depend on any single tool.
Because every bike was pre-owned, each listing was effectively one of a kind, and the bike a visitor liked might sell before they returned. Standard 'personalize the catalog' plays didn't apply when no two items were the same.
The approach
A 44-person cyclist survey told us what the quiz needed to ask, how long it could run, and what people expected from the results. When the platform change paused our custom build, we shipped a Typeform MVP in five days and began collecting data right away.
Rather than a standalone popup, email submission was connected to things the visitor wanted: quiz results, bike-drop alerts, and saved searches. People shared an address because doing so gave them something useful in return.
Once the quiz was at 100%, the next question was how many people actually left an email. A follow-up test made email required to view results, with a significant lift in captures and no impact on purchase metrics.
The same friction points the survey surfaced shaped the rest of the testing roadmap: bike drop alerts, pedal add-ons, account modals, and an expanded nav.
What we learned
The Typeform MVP launched in five days and ran for months. Watching real shoppers use it taught us more about buying intent than continuing to refine a custom build would have.
The quiz collected more emails than a standalone popup would have, because it gave visitors something useful in return: tailored results, bike-drop alerts, and saved searches.
The friction points the survey surfaced, including sizing, trust, and finding new inventory, set the direction for two years of testing across discovery, PDP, cart, and account flows.
The results
By month nine, the Bike Finder quiz had collected more than 100,000 emails. A follow-up test that required an email to view results lifted unique captures another 49%, with no impact on purchases. Each iteration of the quiz also fed the broader testing roadmap: bike-drop alerts, pedal upsells, account modals, and an expanded nav, all shaped by what the quiz taught us about how cyclists shop.
The takeaway
A custom build that stalled mid-design became a five-day MVP that ran for the rest of the engagement, turning anonymous research traffic into a first-party data engine.
Frequently asked
They needed to turn high-intent but anonymous research traffic into a known audience they could nurture. The site already had healthy traffic. What they were missing was a first-party data engine.
Conversion rate optimization, A/B testing, and user research, anchored by a guided shopping quiz (the Bike Finder) and a continuous experimentation roadmap across discovery, PDP, cart, and account flows.
High-consideration ecommerce brands with long buying cycles tend to see compounding gains when they pair a useful, value-exchange capture mechanism with a sustained testing program.
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