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| Criterion |  Growth A/B Testing |  Business Strategy Value Chain Analysis |  Product Discovery Experiment Canvas |  Product Discovery Hypothesis Prioritization Canvas |
|---|---|---|---|---|
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 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. | 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. |
Complexitydifferent | High | High | Low | Medium |
Timedifferent | 1-4 Wochen | Half day | 30-60 min | 60-90 min |
Participantsdifferent | 1-6 | 3-8 | 1-5 | 3-8 |
Formatdifferent | Async | Workshop | Workshop + async | Workshop |
Outputdifferent | Experiment results, Decision log, Learning summary | Value Chain Map, Lever List | Completed Experiment Canvas, Success Metric | Prioritization Canvas, Hypothesis Backlog |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | StrategyBusiness modelDiagnosisAnalysis | ExperimentsValidationDiscoveryHypothesis | ExperimentsPrioritizationDiscoveryHypothesis |