Product metrics and experiments

Metrics and experimentation give product teams an evidence system for learning quickly, reducing risk, and improving retention, activation, and monetization over time.

What you will learn

How to pick north-star, input, and guardrail metrics that matter.
How to design low-risk experiments with clear success criteria.
How to instrument product analytics for actionable insights.
How to interpret results without overreacting to noisy data.

Common mistakes

Tracking too many vanity metrics that do not inform decisions.
Running experiments without a clear hypothesis or stop rule.
Interpreting short-term wins as sustainable behavior change.

Start here path

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Course and module links

Glossary links

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