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| Criterion |  Growth A/B Testing |  Business Strategy Value Chain Analysis |  Product Discovery Hypothesis Prioritization Canvas |  Product Discovery Fake Door 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. | Value Chain Analysis shows where value is created, costs accrue, and differentiation becomes possible along the process. It compares strengths, risks, market logic, and courses of action. The result is captured as a value-chain map and lever list. | When many hypotheses compete for attention, it brings order to their learning sequence and importance. It separates problem, assumption, solution, and evidence. The result is captured as a prioritization canvas and a hypothesis backlog. | 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. |
Complexitydifferent | High | High | Medium | Medium |
Timedifferent | 1-4 Wochen | Half day | 60-90 min | 1-5 Tage |
Participantsdifferent | 1-6 | 3-8 | 3-8 | Nutzertraffic |
Formatdifferent | Async | Workshop | Workshop | Async |
Outputdifferent | Experiment results, Decision log, Learning summary | Value Chain Map, Lever List | Prioritization Canvas, Hypothesis Backlog | Click Data, Interest Signal, Learning Decision |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | StrategyBusiness modelDiagnosisAnalysis | ExperimentsPrioritizationDiscoveryHypothesis | ValidationExperimentsDemandDiscovery |