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| Criterion |  Growth A/B Testing |  Growth Flywheel |  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. | Growth often breaks down where a reinforcing mechanism builds up too much friction. A Flywheel shows the cycle of value, repetition, and reinforcement meant to sustain growth. | 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 | 60-120 min | 1-2 h Setup, laufend | 1-5 Tage |
Participantsdifferent | 1-6 | 3-8 | 2-8 | Nutzertraffic |
Formatdifferent | Async | Workshop | Workshop + async | Async |
Outputdifferent | Experiment results, Decision log, Learning summary | Flywheel Map, Friction Points, Growth Levers, Experiment Backlog | AARRR funnel, Metric baseline, Experiment backlog | Interest Metrics, Conversion Signal, Learning Note |
Tags1 shared | ExperimentsGrowthAnalyticsValidation | GrowthRetentionConversion | GrowthMetricsExperiments | ValidationExperimentsDemandGrowth |