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| Criterion |  Growth Funnel Analysis |  Product Discovery Fake Door Test |  Product Discovery Assumption Mapping |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | 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. | When assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first. | 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 | 1-3 h | 1-5 Tage | 45-60 min | 1-4 Wochen |
Participantsdifferent | 1-5 | Nutzertraffic | 2-8 | 1-6 |
Formatdifferent | Async | Async | Workshop + async | Async |
Outputdifferent | Funnel report, Drop-off analysis, Optimization hypotheses | Click Data, Interest Signal, Learning Decision | Assumption map, Test backlog, Risk ranking | Experiment results, Decision log, Learning summary |
Tagsno overlap | AnalyticsConversionGrowth | ValidationExperimentsDemandDiscovery | AssumptionsRiskExperimentsValidation | ExperimentsGrowthAnalyticsValidation |