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| Criterion |  Product Discovery Smoke Test |  Growth Funnel Analysis |  Product Discovery Riskiest Assumption Test |  Growth A/B Testing |
|---|---|---|---|---|
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 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 an idea hinges on one critical unknown, it prioritizes testing that exact piece of uncertainty first. It separates problem, assumption, solution, and evidence. The result is captured as a prioritized list of assumptions, a test plan, and a result report. | 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 | Low | Medium | Medium | High |
Timedifferent | 1-5 Tage | 1-3 h | 1-2 Wochen pro Iteration | 1-4 Wochen |
Participantsdifferent | Nutzertraffic | 1-5 | 2-6 | 1-6 |
Formatdifferent | Async | Async | Workshop + async | Async |
Outputdifferent | Interest Metrics, Conversion Signal, Learning Note | Funnel report, Drop-off analysis, Optimization hypotheses | Prioritized Assumption List, Test Plan, Results Report | Experiment results, Decision log, Learning summary |
Tagsno overlap | ValidationExperimentsDemandGrowth | AnalyticsConversionGrowth | ExperimentsValidationDiscoveryAssumptions | ExperimentsGrowthAnalyticsValidation |