In Production
Redesigning sign-up for expert participants
A participant-facing project at Prolific. Redesigned the expert sign-up flow, cutting a 7-page form to 2 and adding a fast-track path around the waitlist. Shipped and A/B tested — with meaningful lifts on password creation, onboarding, and first response.
Product
Web app
Timeline
2026 · 4 months
Role
Lead product designer
Team
1 PM, 1 Data Scientist, 4 Engineers
Overview
A redesign that cut friction for high-value participants
At Prolific, expert participants — participants with specific professional backgrounds — are among the platform's most valuable supply. Yet the path to becoming one took, on average, 6 days from first click to first response.
I led the redesign end-to-end, cutting the form from 7 pages to 2, adding a fast-track path around the waitlist, and moving verification from a pre-access gate to an in-product step. Shipped and validated via A/B test.
The problem
A 6-day path was losing us the participants we needed most
Expert participants aren't a general audience. They're recruited for research studies that require specific expertise — clinical, legal, technical — and researchers pay a premium to reach them. Every one we lose in sign-up is one a researcher can't find.
Two structural issues, from data and interviews:
A 7-page sign-up form front-loaded every question researchers might one day want to filter on — leading to high drop-off before submission.
A waitlist gated entry to the product. Applicants qualified during sign-up had to wait days for a manual review, and many never returned.
The previous sign up flow
HMW statement
How might we reduce time-to-first-response for expert participants, without dropping the trust bar the platform depends on?
Understanding users
Understanding the current flow
I started by mapping the existing journey — every screen, every field, every wait state — and layering behavioural data on top: where drop-off spiked, where sessions timed out, where re-engagement failed.
Understanding competitors
Competitor analysis
I audited how comparable platforms handle specialist onboarding.
Three patterns emerged:
Trim the front, skip the wait. Fewer questions upfront, no verification gate — applicants enter the product immediately.
Minimum entry, expand later. A handful of steps at sign-up; deeper questions once inside.
Pre-fill from existing sources. CV upload or LinkedIn connect to auto-populate — less perceived effort, same data collected.
Some examples of competitor analysis
Ideation workshop
One workshop, whole problem space
I ran a single cross-functional workshop covering problem framing and ideation together — with PM, engineering, data, marketing and other stakeholders. Framing the problem and the solution space in one session kept everyone aligned on the trade-offs from the start.
Some ideas from the session
Ideation
Three directions from the workshop
The workshop produced three main directions for cutting time-to-first-response:
Shorten the flow. Cut every non-essential question from the sign-up form itself.
Remove the waitlist entirely. Let anyone who submitted sign-up straight into the product, and handle qualification through in-product signals.
LinkedIn integration. Let applicants connect their LinkedIn to auto-populate professional fields — reducing perceived effort while collecting more, not less.
Mapping ideal user journey
I started with flow diagrams — mapping each direction end-to-end to see how they'd interact — then moved into design, iterating with engineering and PM feedback at each stage. The goal wasn't a "final" design early on; it was to make the trade-offs visible enough for the team to make good calls about what to build.
User and prolific flow
What we chose, and what we didn't
We shipped the shortened flow and a fast-track path: applicants who met defined criteria at sign-up now bypass the waitlist and enter the product immediately. Verification still happens — but for qualified applicants, it moves in-product, after they're already engaged.
Removing the waitlist entirely was tempting but risky: not every applicant met the trust bar researchers depended on. A conditional fast-track let us protect quality where it mattered, while removing friction for the applicants we most wanted to reach.
LinkedIn integration was the strongest idea on paper, but the build cost — OAuth, field mapping, edge cases — would have pushed launch by weeks.
Testing with users
Usability testing with experts
I built a clickable prototype in Figma Make — an AI-assisted build that let me test a higher-fidelity flow than a traditional prototype allows. I ran moderated tests with 6-8 expert participants recruited via Maze, all matching the target profile.
One finding shaped the final design:
The first-week Home risked feeling like a checklist. Too many prompts at once turned the Home into a to-do list. I sequenced them to reveal one at a time — turning obligation into progress.
The solution
From 7 pages to 2
I cut the sign-up form to two pages: just enough to identify who someone is and confirm they're eligible in principle. Everything else — the granular expertise fields, work history, availability — moved into the product itself, as progressive profile-building rather than a pre-access wall.
Adding fast track path around the waitlist, verification moved in-product
Applicants who met the eligibility criteria now enter the product immediately. Identity and expertise verification happens inside the product, after sign-up — meaning users complete these steps while already engaged, seeing the studies they'd unlock. This flipped verification from a friction point (something between the user and the product) to a progression cue (something they do because they can already see the reward).
Social proof designed for expert eyes
Expert participants know their own value. I built a layer of social proof into the new flow, aimed specifically at that question:
Institutions using Prolific — surfacing recognisable names in academia and industry
Published research — real papers with participants recruited through the platform
Total paid to participants — a running counter, updated live
High-value study feed — an animated stream of recent, well-paid studies in expert-relevant categories
A new Home for the first-week experience
Moving verification in-product only works if the product itself pulls new users forward. I designed a dedicated Home for newly signed-up expert participants — a landing that made the next best action obvious at every stage.
Results
Business impacts
We ran the new flow against the old with a subset of expert applicants. Three headline metrics:
Created password: participants in the new flow were ~3.45x more likely to create a password (=account) than in the old flow.
Completed onboarding: ~2.1x more likely — though with a wider confidence interval, meaning the true effect is more uncertain and warrants continued measurement.
Completed first response: ~3.15x more likely — again with a wide confidence interval.
3.45x
Create an account
2.1x
Complete onboarding
3.15x
Complete the first study
What this means
The changes moved the metrics we cared about, in the direction we cared about. Time-to-first-response wasn't measured directly this cycle, but every stage in that funnel improved. We shipped the new flow to 100% of expert applicants; verification-in-product is still rolling out in phases.
Reflection
What I'd change: run more tests before shipping the full change
The decision to change two structural things at once — form length and waitlist removal — was pragmatic (we were confident in both, and shipping separately would have doubled the timeline) but it made attribution messier. The wider confidence intervals on onboarding and first response probably reflect that. Next time, if the timeline allows, I'd stage the changes and measure each independently. Speed came at the cost of clarity.
What I've carried forward: sequence matters as much as content
The biggest unlock in this project wasn't shortening the form — it was moving verification after first exposure to the product. Same information collected, different order, wildly different outcome. And the same logic applied downstream: the new Home wasn't a set of features, it was a sequence of prompts. When each step motivates the next, the whole flow feels lighter than the sum of its parts.
Other projects
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Redesigned how data collectors set participant pay — tested, iterated, and shipped to 100%. Drove 12.2% revenue uplift.
Redesigning the participant profile
A participant-facing project at Prolific. Redesigned the about you page to drive higher completion — shipped to 100%. Increased completion rate by 25% to 68%.
© 2026 Go Ogata - Product Designer