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| Criterion |  Business Strategy Value Chain Analysis |  Growth A/B Testing |  Product Discovery Fake Door Test |  Product Discovery Experiment Canvas |
|---|---|---|---|---|
Purposedifferent | 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 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 experiments become unreadable after the fact, it arranges hypothesis, signal, and learning goal on a single canvas. It separates problem, assumption, solution, and evidence. The result is captured as a Completed Experiment Canvas and a Success Metric. |
Complexitydifferent | High | High | Medium | Low |
Timedifferent | Half day | 1-4 Wochen | 1-5 Tage | 30-60 min |
Participantsdifferent | 3-8 | 1-6 | Nutzertraffic | 1-5 |
Formatdifferent | Workshop | Async | Async | Workshop + async |
Outputdifferent | Value Chain Map, Lever List | Experiment results, Decision log, Learning summary | Click Data, Interest Signal, Learning Decision | Completed Experiment Canvas, Success Metric |
Tagsno overlap | StrategyBusiness modelDiagnosisAnalysis | ExperimentsGrowthAnalyticsValidation | ValidationExperimentsDemandDiscovery | ExperimentsValidationDiscoveryHypothesis |