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| Criterion |  Growth A/B Testing |  Growth North Star Metric |  Growth Pirate Metrics AARRR |  Product Discovery Smoke Test |
|---|---|---|---|---|
Purposedifferent | When two variants compete, discussions quickly decide by taste rather than effect. A/B Testing checks behavior under controlled conditions and separates real improvement from chance or expectation effects. | When product teams track many metrics, the view of the actual customer outcome easily gets lost. A North Star Metric bundles growth, usage, and value contribution into one signal that makes the system's direction visible. | For products with complex usage paths, overall growth alone is too coarse to reveal bottlenecks. Pirate Metrics breaks the relationship with the product into consecutive stages and shows where the funnel actually leaks. | When demand only needs to be roughly verified, it tests interest with minimal effort. It measures whether people would take a next step at all. |
Complexitydifferent | High | Medium | Medium | Low |
Timedifferent | 1-4 Wochen | 1-2 h | 1-2 h Setup, laufend | 1-5 Tage |
Participantsdifferent | 1-6 | 3-8 | 2-8 | Nutzertraffic |
Formatdifferent | Async | Workshop + async | Workshop + async | Async |
Outputdifferent | Experiment results, Decision log, Learning summary | North Star metric, Input metric tree, Measurement cadence | AARRR funnel, Metric baseline, Experiment backlog | Interest Metrics, Conversion Signal, Learning Note |
Tags1 shared | ExperimentsGrowthAnalyticsValidation | GrowthMetricsAlignmentRetention | GrowthMetricsExperiments | ValidationExperimentsDemandGrowth |