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| Criterion |  Growth A/B Testing |  Business Strategy Value Chain Analysis |  Growth Growth Experiment |  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. | 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 growth ideas surface quickly, the temptation to build immediately instead of learning is high. A Growth Experiment frames an assumption so target group, lever, and measurement are clear before the first deployment. | 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 | High | Medium | Low |
Timedifferent | 1-4 Wochen | Half day | 1-2 Wochen | 1-5 Tage |
Participantsdifferent | 1-6 | 3-8 | 1-6 | Nutzertraffic |
Formatdifferent | Async | Workshop | Workshop + async | Async |
Outputdifferent | Experiment results, Decision log, Learning summary | Value Chain Map, Lever List | Experiment card, Result summary, Next bet | Interest Metrics, Conversion Signal, Learning Note |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | StrategyBusiness modelDiagnosisAnalysis | MarketingGrowthExperimentsLearning | ValidationExperimentsDemandGrowth |