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| Criterion |  Product Discovery Fake Door Test |  Growth Funnel Analysis |  Product Discovery Smoke Test |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | 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 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 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. |
Complexitydifferent | Medium | Medium | Low | High |
Timedifferent | 1-5 Tage | 1-3 h | 1-5 Tage | 1-4 Wochen |
Participantsdifferent | Nutzertraffic | 1-5 | Nutzertraffic | 1-6 |
Formatsame | Async | Async | Async | Async |
Outputdifferent | Click Data, Interest Signal, Learning Decision | Funnel report, Drop-off analysis, Optimization hypotheses | Interest Metrics, Conversion Signal, Learning Note | Experiment results, Decision log, Learning summary |
Tagsno overlap | ValidationExperimentsDemandDiscovery | AnalyticsConversionGrowth | ValidationExperimentsDemandGrowth | ExperimentsGrowthAnalyticsValidation |