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| Criterion |  Growth A/B Testing |  Product Discovery Pretotyping |  Product Discovery Smoke Test |  Growth Funnel Analysis |
|---|---|---|---|---|
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. | Pretotyping clarifies whether a customer problem and solution idea create enough real demand. It separates problem, assumption, solution, and evidence, and captures the result as a pretotyping sketch, test setup, and conversion data. | 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 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 | High | Low | Low | Medium |
Timedifferent | 1-4 Wochen | Stunden bis wenige Tage | 1-5 Tage | 1-3 h |
Participantsdifferent | 1-6 | 1-4 | Nutzertraffic | 1-5 |
Formatdifferent | Async | Workshop + async | Async | Async |
Outputdifferent | Experiment results, Decision log, Learning summary | Pretotyping sketch, Test setup, Conversion data, Go or no-go decision | Interest Metrics, Conversion Signal, Learning Note | Funnel report, Drop-off analysis, Optimization hypotheses |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | ValidationDemandMVP | ValidationExperimentsDemandGrowth | AnalyticsConversionGrowth |