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| Criterion |  Product Discovery Smoke Test |  Business Strategy Value Chain Analysis |  Product Discovery Experiment Canvas |  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. | 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 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 | High | Low | High |
Timedifferent | 1-5 Tage | Half day | 30-60 min | 1-4 Wochen |
Participantsdifferent | Nutzertraffic | 3-8 | 1-5 | 1-6 |
Formatdifferent | Async | Workshop | Workshop + async | Async |
Outputdifferent | Interest Metrics, Conversion Signal, Learning Note | Value Chain Map, Lever List | Completed Experiment Canvas, Success Metric | Experiment results, Decision log, Learning summary |
Tagsno overlap | ValidationExperimentsDemandGrowth | StrategyBusiness modelDiagnosisAnalysis | ExperimentsValidationDiscoveryHypothesis | ExperimentsGrowthAnalyticsValidation |