How does iDBQuery help a product analyst?
A product analyst can use iDBQuery to run funnel, cohort and behavioural analysis in plain language across product, event and revenue data, then verify the SQL it wrote. It joins those sources into one live model and cites every figure, cutting the data-prep that eats most of an analyst's day.
A product analyst's hardest work is often just assembling the data before the real analysis begins. iDBQuery joins your product database, event stream and revenue data into one live model and answers in plain language, always showing the SQL it generated so you stay in control.
Questions a product analyst asks iDBQuery: - Build the activation funnel from signup to first key action and show drop-off at each step. - Compare 30-, 60- and 90-day retention across the last six monthly cohorts. - Which events in a user's first week predict conversion to paid?
Every answer cites the exact source rows, so a stakeholder can trust the readout, and you can drill from a summary into the underlying events with a follow-up. iDBQuery handles wide tables and many-table schemas, uses a semantic layer to make sense of cryptic column names, and exports clean results to Excel or a shareable report. Rather than replacing you, it strips out the tedious extraction and joining so you can spend your time on the harder questions — the analysis, the interpretation, and the story behind the metric.
Updated 2026-06-22