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| Criterion |  Growth Pirate Metrics AARRR |  Product Discovery Fake Door Test |  Product Discovery Hypothesis Prioritization Canvas |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | 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 is still unclear, it measures interest in a feature before it is built. It separates real behavior from polite agreement and deliberately keeps build effort small. | When many hypotheses compete for attention, it brings order to their learning sequence and importance. It separates problem, assumption, solution, and evidence. The result is captured as a prioritization canvas and a hypothesis backlog. | 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. |
Complexitydifferent | Medium | Medium | Medium | High |
Timedifferent | 1-2 h Setup, laufend | 1-5 Tage | 60-90 min | 1-4 Wochen |
Participantsdifferent | 2-8 | Nutzertraffic | 3-8 | 1-6 |
Formatdifferent | Workshop + async | Async | Workshop | Async |
Outputdifferent | AARRR funnel, Metric baseline, Experiment backlog | Click Data, Interest Signal, Learning Decision | Prioritization Canvas, Hypothesis Backlog | Experiment results, Decision log, Learning summary |
Tags1 shared | GrowthMetricsExperiments | ValidationExperimentsDemandDiscovery | ExperimentsPrioritizationDiscoveryHypothesis | ExperimentsGrowthAnalyticsValidation |