Yeah sure Dovetail offers a "repository" but our researchers felt it was suffocating. They had very little confidence they could get their stakeholders in there and leveraging their insights. So I built them something custom.
Coda doc architect and handy-man.
1 month to go from 0-1
Our UX research team needed a way to let non-researchers browse through their growing collection of key findings and recommendations.
Until our repo, this information was only accessible in static presentation decks and the minds of our research team. Researchers have better things to do then respond to dozens of Slack requests saying "can you send me the link to the studies that have key findings about [topic]?" And the volume of such messages increased drastically during quarterly OKR planning season. During that time, researchers would spend a significant amount of their time helping gather findings. And it was all up to their individual memories... "oh, I think we have a study on that but I didn't lead it, so-and-so did, let me message them..."
This was inefficient, and unreliable. And the research team knew this. They felt the time-suck, and were burdened knowing this time could be spent running studies for new insights, or doing meta analysis on existing findings. But they had to keep keeping on, the business was dependent on their trapped knowledge.
A perfect opportunity for me, the operations gal, to help with a new solution.
We needed a proper research repository. But not the one baked into our qualitative analysis tool, Dovetail—it was too opinionated in how we organize insights. The team wanted the flexibility to organize their fidnings in a way that suited both them and product managers, designers, and engineers. Dovetail's solution wasn't up to scratch.
Enter Coda. At its core, our Research Repo Doc was run by just 3 data tables:
These would be interlinked with lookups. And through the magic of structured data, we could associate a finding to a certain page of the product, component, or user flow. Here's a walkthrough of me using the Coda research repo with dummy data:
Not only did this meet our self-serve solution, we could also show the business the rate at which research was producing insights, meeting with users, and time spent steeped in raw data.
Every study we ran was tracked as row in our "Studies" table.
Mix in "months", "quarters", and "years" and we can begin to measure UXR output over time. And contextualize it! For instance, maybe Q2 saw a 50% decrease in studies ran compared to Q1, but that was because the research team was conducting the annual benchmark study (a big effort with a massive payoff).
With this information, the team could tell a richer story of their contributions to the business.
It only took a couple extra columns to start helping researchers understand each other's expertise. Up until the repo, folks would just hear in passing or absorb through exposure things like, "so-and-so is really knowledgeable when it comes to tree tests." Now we had a way to track it!
With this the team had a way to understand who was expert in what, and easily get guidance and support from them as they had their go using a new method. This is a massive asset for new hires who don't yet know each teammate and their bodies of work. It's also beneficial for designers who want to get practice leading research initiatives. This allows them to find an appropriate partner.
