User interviews: the insight is in the hesitation
Users are polite. They say your product is “pretty intuitive” while describing a four-step workaround they invented to avoid your main flow. Research value lives in exactly the material that summaries flatten: hedges, contradictions, the pause before “sure, I’d pay for that.” Donna records the session, transcribes it faithfully with Whisper large-v3, and reads it like a senior researcher — while participant recordings, which are personal data, stay on your own server instead of a transcription vendor’s cloud.
What goes wrong without a real record
- Notetaking while moderating splits your attention exactly when the user goes off-script — where the insight is.
- Highlight reels get built from what confirmed the roadmap; the disconfirming mumble doesn’t make the deck.
- Participant consent forms rarely contemplate “and a third-party AI vendor will store this indefinitely.”
What Donna catches here
“I’d definitely use this” at minute 4 became “maybe for bigger projects” at minute 22. The shift — and what demo moment caused it — is the finding.
You asked about pricing twice; the user answered a different question twice. Donna logs the dodge, which is more honest than any survey response.
Verbatim, timestamped quotes ready to drop into research reports — no more re-scrubbing recordings for the sentence you half-remember.
The moment the user pushed back on your framing — the exchange most likely to invalidate an assumption, preserved instead of smoothed over.
All eight sections of the report, explained: meeting intelligence vs meeting notes.
Questions, answered straight
Does self-hosting matter for research recordings?
Yes — participant recordings are personal data under GDPR-class regimes, and your consent form governs where they go. “Stored on our own server, processed with our own API keys” is a consent line participants and review boards accept far more readily than a list of SaaS subprocessors.
Can Donna analyze interviews I already recorded?
Yes. Donna’s upload pipeline takes existing audio or video recordings, transcribes them with Whisper large-v3, and runs the same two-pass analysis — useful for working through a backlog of past sessions.
Does Donna replace a research repository?
No — she feeds one. Each session yields a timestamped transcript and a structured report in your PostgreSQL database; your synthesis and tagging workflow sits on top of clean, quotable raw material.
Put Donna in your next meeting
Donna deploys onto your own VPS in an afternoon: nginx, pm2, PostgreSQL, your API keys. Early access is open — tell us about your team and we’ll get her a seat at your table.
Request early access