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| Criterion |  Growth A/B Testing |  Decision Making Force Field Analysis |  Systems Thinking Leverage Points |  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. | In change initiatives, supporting and restraining forces sit at the table at the same time. Force Field Analysis makes these tensions explicit and shows where change can be pushed forward by strengthening or relieving. | Leverage Points show exactly where interventions in a system produce a disproportionate effect. It draws relationships, patterns, and feedback loops. The result is captured as a leverage map and action strategy. | 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 | Low | High | Low |
Timedifferent | 1-4 Wochen | 45-90 min | Half day | 1-5 Tage |
Participantsdifferent | 1-6 | 3-12 | 3-12 | Nutzertraffic |
Formatdifferent | Async | Workshop | Workshop | Async |
Outputdifferent | Experiment results, Decision log, Learning summary | Force Field Map, Change Levers, Risk Notes | Leverage Map, Action Strategy | Interest Metrics, Conversion Signal, Learning Note |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | ChangeDecisionStrategy | Systems thinkingChangeStrategy | ValidationExperimentsDemandGrowth |