Knowledge area
Metrics and analytics
Build a measurement system that supports decisions instead of decorating reports.
Dashboards and the rhythm of management
How to build product dashboards and review rhythm metrics: audiences, levels of detail, alerts and data decisions.
Read articleExperiments: A/A, A/B, power
A/A and A/B tests for the product: hypothesis, power, sample size, duration, metrics and typical analysis errors.
Read articleFannel, cohorts, retention
Funnel, cohort and retention practice: event definitions, segments, periods, retention curves, and diagnosis.
Read articleMisinterpretation of data
Typical errors in product analytics are sample bias, correlation and causality confusion, average values, and multiple checks.
Read articleNorth Star + input metrics
How to choose North Star Metric and Input Metrics: Good Score Criteria, Decomposition and Protection from Local Optimization
Read articleProduct metric system
How to build a system of product metrics: outcome, North Star, input metrics, guardrails, cause tree and owners.
Read articleSQL for the product (minimum)
Minimum SQL for the product manager: SELECT, JOIN, aggregations, terms, dates, window functions and check the result of the query.
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