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| Criterion |  Growth A/B Testing |  Product Discovery Assumption Mapping |  Growth North Star Metric |  Product Discovery Smoke Test |
|---|---|---|---|---|
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 assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first. | When product teams track many metrics, the view of the actual customer outcome easily gets lost. A North Star Metric bundles growth, usage, and value contribution into one signal that makes the system's direction visible. | 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. |
Complexitydifferent | High | Medium | Medium | Low |
Timedifferent | 1-4 Wochen | 45-60 min | 1-2 h | 1-5 Tage |
Participantsdifferent | 1-6 | 2-8 | 3-8 | Nutzertraffic |
Formatdifferent | Async | Workshop + async | Workshop + async | Async |
Outputdifferent | Experiment results, Decision log, Learning summary | Assumption map, Test backlog, Risk ranking | North Star metric, Input metric tree, Measurement cadence | Interest Metrics, Conversion Signal, Learning Note |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | AssumptionsRiskExperimentsValidation | GrowthMetricsAlignmentRetention | ValidationExperimentsDemandGrowth |