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| Criterion |  Growth A/B Testing |  Growth Growth Experiment |  Business Strategy Value Chain Analysis |  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. | 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. | 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 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 | Medium | High | Low |
Timedifferent | 1-4 Wochen | 1-2 Wochen | Half day | 1-5 Tage |
Participantsdifferent | 1-6 | 1-6 | 3-8 | Nutzertraffic |
Formatdifferent | Async | Workshop + async | Workshop | Async |
Outputdifferent | Experiment results, Decision log, Learning summary | Experiment card, Result summary, Next bet | Value Chain Map, Lever List | Interest Metrics, Conversion Signal, Learning Note |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | MarketingGrowthExperimentsLearning | StrategyBusiness modelDiagnosisAnalysis | ValidationExperimentsDemandGrowth |