Built a voice response widget for Alchemer surveys after years of frustrated open-end data > honest feedback welcome
I run quantitative studies and the same thing keeps happening: I tack an open-end onto a closed question, "why did you give that score?", and I get back "good", "ok", "nothing to add." There's signal there. People just don't want to type it.
Tried longer prompts, tried rewording, tried making the question required. Marginal improvements at best.
What actually changed things: giving respondents a record button instead of a text box.
The depth difference is noticeable. I've been tracking it across matched questions and voice responses come in meaningfully longer than typed ones. Still pinning down the exact lift, but the qualitative difference is the part that matters anyway. People say things they wouldn't write: hesitations, "well, actually..." moments, emotional tone. The kind of context that turns "the product is fine" into something you can actually act on.
So I built a tool around it. It's called VoiceCapture, a widget that drops into Alchemer surveys (other platforms in progress) so you don't have to migrate your studies. Respondents click, speak, done. Audio is processed in-memory and discarded after transcription. The only retained copy is a fallback if transcription fails, and that's deletable. GDPR was a hard requirement.
One real limitation I've hit: desktop adoption is lower than mobile. On phones the mic permission flow is familiar (people grant it for voice notes all day), so they tap and talk. On desktop, more respondents skip the voice option and fall back to typing. Still figuring out if it's a copy problem, a UX problem, or just a behavioral baseline I can't move much.
I'm not here to pitch. I'd like to hear from this community.
What I'm curious about:
- Has anyone tried voice/audio in surveys before? What worked, what broke?
- The "respondents won't elaborate on open-ends" problem, solved it differently?
- Any concerns you'd raise about asking respondents to speak vs type (privacy, accessibility, demographic skew)?
A few comparisons I expect to come up:
- Addpipe: captures audio fine, but you DIY the transcription, analysis, and stitching back to response data. Fine with engineering capacity, friction without.
- Phonic.ai: building a full survey platform. I'm building a widget that lives inside the tools you already use, so you don't migrate your instrument.
Disclosure: yes, I built this. Posting because the problem is real and I want to know what this community's experience has been, not to spam. If anyone wants to try it on a real study, DM me and we'll sort it out.