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| Criterion |  Growth A/B Testing |  Product Discovery Fake Door Test |  Growth Funnel Analysis |  Product Discovery MVP Test Matrix |
|---|---|---|---|---|
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. | 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 several minimal variants compete to answer the same question, it makes comparing and choosing between them cleaner. It separates problem, assumption, solution, and evidence. The result is captured as a Test Matrix and a Test Plan. |
Complexitydifferent | High | Medium | Medium | Medium |
Timedifferent | 1-4 Wochen | 1-5 Tage | 1-3 h | 45-75 min |
Participantsdifferent | 1-6 | Nutzertraffic | 1-5 | 2-8 |
Formatdifferent | Async | Async | Async | Workshop |
Outputdifferent | Experiment results, Decision log, Learning summary | Click Data, Interest Signal, Learning Decision | Funnel report, Drop-off analysis, Optimization hypotheses | Test Matrix, Test Plan |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | ValidationExperimentsDemandDiscovery | AnalyticsConversionGrowth | ExperimentsValidationDiscoveryOptions |