How does iDBQuery help a product manager?
A product manager can use iDBQuery to answer usage, adoption and retention questions in plain language directly from the product database, with every figure cited to its source. It reads your product tables as one live model, so feature decisions rest on real numbers instead of a queued analytics request.
A product manager constantly needs numbers to make decisions, but getting them usually means writing SQL or waiting on the data team. iDBQuery reads your product database, and event and CRM data, as one live model and answers in plain language, citing every result to the source.
Questions a product manager asks iDBQuery: - How many users adopted the new feature in its first month, and how does their retention compare to non-users? - Which features correlate with accounts that renew versus churn? - What is weekly active usage trending by plan tier?
Every answer cites the exact rows, so you can put a real number in a spec or roadmap review instead of a guess. Follow-up questions keep context, letting you move from an adoption headline into the specific cohorts behind it. iDBQuery shows the SQL it wrote if you want to check it, and lets the Analyst agent investigate open questions like which behaviours predict churn. It works alongside your existing analytics tools — giving PMs self-serve, cited answers so decisions move at the speed of the questions, not the reporting backlog.
Updated 2026-06-22