Internal Research Ops Tool
Helping Nearmap’s UX researchers manage and work from a growing research participant pool.
Overview
Nearmap had launched an in-product recruitment initiative inside MapBrowser, allowing users to opt into future research. This created a valuable participant pool, but the UX researchers were still managing it through a bloated spreadsheet. I designed and built a tailored internal tool to help them manage participants more effectively, reduce admin, and save time.
Role
Product Designer/ Builder
Scope
End to end product design, product development
Status
Launched and in use
Why this mattered
The team had participant data, but no reliable way to work with it.
The research team already had a growing pool of research participants, but important information was buried in a spreadsheet, key fields were incomplete, and there was no tailored workflow for tracking outreach, ownership, or participant value. The opportunity was not just to organise data, but to give the researchers a faster and more usable way to manage their panel.
How I approached it
I validated the need quickly and worked in tight feedback loops using Claude Code as my main design tool
Once I saw the opportunity, I quickly mocked up an early concept and showed it to the researchers to test whether a tool like this would actually be useful. The response was very positive, which led to a workshop where we mapped out the pain points in their current panel-management workflow and defined what they needed from a better tool.
From there, I worked in very fast feedback loops. I made changes directly in a live Claude Code prototype, the researchers tested it, gave feedback, and I iterated. I worked almost entirely in Claude Code, occasionally jumping into Figma to refine specific visual details before bringing those decisions back into the build.
The solution
I turned raw participant data into a tailored research workflow.
The core experience was a shared participant table with a detailed side panel. Researchers could quickly scan, filter, and search the pool, then open a participant to update role, status, notes, ownership, and linked research records. I used the existing data to surface more useful signals like usage tiers and recency, helping the team identify stronger participants more easily.
I later expanded the tool by bringing in Itel usage data as well, turning it from a single-product participant list into a richer cross-product profile.
Prototype Walk Through
Particpant Panel: See product usage, assign research actions, add tags and notes
Add participants manually, edit participant profiles, add/ remove columns, filter content
Dark mode
Outcome
I built the tool myself, and it was adopted straight into the team’s workflow.
I built the tool myself using Claude Code and Supabase. The project was uploaded to GitHub and I received guidance from Nearmap’s Developer Operations team. Because the prototype was being tested continuously as I worked, the final tool already reflected the researchers’ real needs by the time it was ready.
It was adopted immediately and introduced into their workflow, replacing a slower spreadsheet-based process with a more tailored and efficient experience. The project saved the team time and showed me how much AI-enabled tooling has changed what a designer can independently take on.
1cianobrien@gmail.com
Made in Framer, with custom code components built with help from Claude.