I use Dovetail both at my full-time job as a UX researcher in a big product company and for smaller freelance projects, and it’s been a game changer in both settings.
The automatic transcription is probably my favorite feature — I don’t have to waste time typing things out, and I can jump straight into tagging and organizing insights. I really like how easy it is to set up tags, group them into folders, and gradually build an analysis as I go through interviews. Pulling highlights into reels and then exporting them is another feature I lean on a lot. Stakeholders love seeing direct clips, and it makes the research feel more tangible.
Lately, I’ve been using the built-in AI more and more. It’s great that I can ask it questions at different levels — within one user, a project, or even a whole folder — and get quick summaries or answers to research questions. It definitely speeds up the process of turning raw conversations into insights.
And honestly, I appreciate that the most important features — transcription, tagging, highlights — are included in the lower-cost plan. That’s what makes it realistic for me to use Dovetail as a freelancer as well, not just in a corporate setting.
Overall, it’s become one of those tools I can’t really imagine doing research without anymore. Review collected by and hosted on G2.com.
One area where Dovetail still falls short for me is reporting. I find it much easier to build research reports in Miro — creating documents or boards directly in Dovetail feels clunky. For example, I can’t freely resize images, and the formatting options are pretty limited, which makes it harder to design something visually clear and engaging.
Another challenge is integrating quantitative research. I don’t expect Dovetail to analyze survey data for me, but I haven’t yet found a smooth way to bring quant data into the same repository alongside qual studies. Right now we still keep these two streams of research separate. Review collected by and hosted on G2.com.
