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| Criterion |  Product Discovery Smoke Test |  Growth A/B Testing |  Growth Flywheel |  Growth Funnel Analysis |
|---|---|---|---|---|
Purposedifferent | 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. | 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. |
Complexitydifferent | Low | High | Medium | Medium |
Timedifferent | 1-5 Tage | 1-4 Wochen | 60-120 min | 1-3 h |
Participantsdifferent | Nutzertraffic | 1-6 | 3-8 | 1-5 |
Formatdifferent | Async | Async | Workshop | Async |
Outputdifferent | Interest Metrics, Conversion Signal, Learning Note | Experiment results, Decision log, Learning summary | Flywheel Map, Friction Points, Growth Levers, Experiment Backlog | Funnel report, Drop-off analysis, Optimization hypotheses |
Tags1 shared | ValidationExperimentsDemandGrowth | ExperimentsGrowthAnalyticsValidation | GrowthRetentionConversion | AnalyticsConversionGrowth |