Business analytics and experiments

SQL, section-by-section explanations, assumptions and validation queries.

A dashboard outline, chart rationale, filtering rules and data checks.

Retention definitions, calculation drafts, cohort tables and interpretation limits.

An analysis procedure, results table, assumption checks and decision rationale.

A forecasting plan, backtest design, model comparison and usage limits.

A theme codebook, segmented summaries, anonymous quotes and action list.

Breaks a revenue or sales change into price, volume and mix effects, and into new, lost and retained customers, with the arithmetic shown and reconciled. Use to explain why revenue moved.

Finds which behaviours and attributes predict churn in customer data, simple comparisons first and a model only if justified, with an action and a test per driver. Use at subscription businesses.

Writes SQL for activation rate and ordered conversion funnels from an event table, with conversion windows, strict step order, time zones, internal users, bots and late-arriving events handled.

Reviews someone else's forecast or projection by surfacing its hidden assumptions, testing them against base rates and capacity limits, and finding the few that drive the result.