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| Criterion |  Growth A/B Testing |  Growth Flywheel |  Growth Funnel Analysis |  Product Discovery Fake Door 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. | When many visitors or users drop off along the way, the reason behind the number often stays hidden. Funnel Analysis exposes these transitions and makes visible exactly where the path collapses. | 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. |
Complexitydifferent | High | Medium | Medium | Medium |
Timedifferent | 1-4 Wochen | 60-120 min | 1-3 h | 1-5 Tage |
Participantsdifferent | 1-6 | 3-8 | 1-5 | Nutzertraffic |
Formatdifferent | Async | Workshop | Async | Async |
Outputdifferent | Experiment results, Decision log, Learning summary | Flywheel Map, Friction Points, Growth Levers, Experiment Backlog | Funnel report, Drop-off analysis, Optimization hypotheses | Click Data, Interest Signal, Learning Decision |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | GrowthRetentionConversion | AnalyticsConversionGrowth | ValidationExperimentsDemandDiscovery |