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| Criterion |  Decision Making Force Field Analysis |  Growth Funnel Analysis |  Product Discovery Assumption Mapping |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | 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. | When many visitors or users drop off along the way, the reason behind the number often stays hidden. Funnel Analysis exposes these transitions and makes visible exactly where the path collapses. | When assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first. | 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 | Medium | Medium | High |
Timedifferent | 45-90 min | 1-3 h | 45-60 min | 1-4 Wochen |
Participantsdifferent | 3-12 | 1-5 | 2-8 | 1-6 |
Formatdifferent | Workshop | Async | Workshop + async | Async |
Outputdifferent | Force Field Map, Change Levers, Risk Notes | Funnel report, Drop-off analysis, Optimization hypotheses | Assumption map, Test backlog, Risk ranking | Experiment results, Decision log, Learning summary |
Tagsno overlap | ChangeDecisionStrategy | AnalyticsConversionGrowth | AssumptionsRiskExperimentsValidation | ExperimentsGrowthAnalyticsValidation |