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| Criterion |  Decision Making Force Field Analysis |  Growth Funnel Analysis |  Product Strategy DIBB |  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. | DIBB helps clarify target groups, value, goals, and priorities by making the logic behind a decision explicit. It captures results as a DIBB document, belief list, bet list, and learning report. | 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 | Low | High |
Timedifferent | 45-90 min | 1-3 h | 1-2 h | 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 | DIBB document, Belief list, Bet list, Learning report | Experiment results, Decision log, Learning summary |
Tagsno overlap | ChangeDecisionStrategy | AnalyticsConversionGrowth | StrategyDecisionAssumptionsHypothesis | ExperimentsGrowthAnalyticsValidation |