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| Criterion |  Growth Hooked Model |  Decision Making Force Field Analysis |  Product Discovery Assumption Mapping |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | The Hooked Model helps clarify engagement loops, user behavior, and experiments. It makes repeat behavior measurable and captures the result as a hooked loop, trigger map, and reward design. | 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 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 | Medium | Low | Medium | High |
Timedifferent | Multiple workshops over several weeks | 45-90 min | 45-60 min | 1-4 Wochen |
Participantsdifferent | 2-8 | 3-12 | 2-8 | 1-6 |
Formatdifferent | Workshop + async | Workshop | Workshop + async | Async |
Outputdifferent | Hooked loop, Trigger map, Reward design, Ethics check | Force Field Map, Change Levers, Risk Notes | Assumption map, Test backlog, Risk ranking | Experiment results, Decision log, Learning summary |
Tagsno overlap | GrowthBehaviorRetention | ChangeDecisionStrategy | AssumptionsRiskExperimentsValidation | ExperimentsGrowthAnalyticsValidation |