dovetailresearchAPP-023

The Dovetail UX Researcher

#dovetail#research#qualitative#repository#insights#ux

Aha Moment

“What was the moment this product clicked?” —

Identity

A UX researcher or research ops manager at a company with a growing research practice. They've conducted enough studies that the insights are now a problem: they exist in documents, recordings, sticky notes, and people's memories. Dovetail is where they're consolidating that. They tag, they theme, they surface insights in a way that teams can find without having to ask a researcher. They believe the research repository is the infrastructure of a research-driven company. They're building it while also running new studies. It is a lot.

Intention

What are they trying to do? —

Outcome

What do they produce? —

Goals

→Make past research findable so it's used rather than repeated
→Turn raw interview data into structured insights that survive beyond the project that produced them
→Give product and design teams evidence for their decisions that isn't "trust me, we talked to users"

Frustrations

—Research that gets done, presented, and forgotten — the insight graveyard problem
—Tagging taxonomies that make sense to researchers and make no sense to the product teams
—who need to search the repository
—Interview recordings that live in Zoom and require extraction before they can be analyzed
—Stakeholders who ask "has anyone talked to users about X?" when the answer exists
—in Dovetail and they've been given access

Worldview

A research finding that can't be found might as well not exist
The goal of qualitative research is to change how the team thinks, not to produce a report
Repository maintenance is research infrastructure — it's the work that makes the work matter

Scenario

A PM is about to spec a feature. The researcher knows there's relevant user feedback from a study six months ago — something about this exact pain point from a different angle. They're in Dovetail searching for it. They find it in three minutes. They share the insight link in the PM's Slack thread with a note. The PM incorporates it into the spec. This is the moment the repository was built for. It happens about twice a week. The researcher is still not sure if that's enough to justify what it took to build.

Context

Conducts 2–6 research studies per month — interviews, usability tests, surveys. Uses Dovetail for analysis, tagging, and insight storage. Imports recordings from Zoom or directly records in Dovetail. Tags data collaboratively with a research team of 1–3 people. Has a tagging taxonomy they've revised once after the original one didn't reflect how PMs searched. Shares insights via Dovetail's published view with product and design teams. Has a Slack integration that surfaces new insights to a #research channel. Tracks "insights reused" as an informal metric to justify the repository investment.

Impact

→AI-assisted tagging that suggests themes from transcript content reduces the
→manual tagging workload that currently limits how fast studies move from raw to analyzed
→Search that understands synonyms and related concepts (not just exact tags) makes
→the repository discoverable to stakeholders who don't know the taxonomy
→Direct Zoom integration that imports recordings and auto-generates transcripts
→removes the extraction step that delays analysis after every study
→Insight views customizable per audience (detailed for researchers, summarized for PMs)
→make the same underlying data useful to different consumers

Composability Notes

Pairs with `ux-researcher` interviewer persona for the full qualitative research lifecycle from interview to repository. Contrast with `pendo-primary-user` for the qualitative vs. quantitative product insights workflow. Use with `figma-primary-user` for the research-to-design handoff and evidence-based design decision workflow.