How does iDBQuery help a UX researcher?
A UX researcher can use iDBQuery to combine behavioural product data with survey and support data in plain language, getting cited answers that ground qualitative findings in numbers. It joins those sources into one live model, so you can size a usability issue or segment users without asking an analyst.
UX research is strongest when the qualitative story is backed by behavioural evidence — but that evidence lives in product tables, survey exports and support tickets. iDBQuery joins them into one live model and answers in plain language, citing every figure so your findings are defensible.
Questions a UX researcher asks iDBQuery: - How many users hit the error state in this flow last month, and on which step? - Do users who complete onboarding report higher satisfaction than those who don't? - Which segments abandon the checkout most often?
Survey and support exports load as CSV or through the API connector, and iDBQuery can even read a folder of PDF interview notes with OCR, making them searchable alongside the numbers. Every answer cites its source, so you can size the impact of a usability issue with confidence rather than anecdote. You don't need SQL — you ask in plain English and get a chart or table back, then follow up in the same thread. It lets researchers pair the "why" they uncover with a solid "how many," without waiting on the data team.
Updated 2026-06-22