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| Criterion |  Operations Change Analysis |  Growth Hooked Model |  Product Discovery Fake Door Test |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | For a deviation after a change, the method isolates the influence of the altered condition. It narrows down which differences are relevant and which are just accompanying noise. | 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. | When demand is still unclear, it measures interest in a feature before it is built. It separates real behavior from polite agreement and deliberately keeps build effort small. | 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 | Medium | Medium | High |
Timedifferent | 45-120 min | Multiple workshops over several weeks | 1-5 Tage | 1-4 Wochen |
Participantsdifferent | 2-6 | 2-8 | Nutzertraffic | 1-6 |
Formatdifferent | Workshop + async | Workshop + async | Async | Async |
Outputdifferent | Change Matrix, Cause Hypotheses, Validation Questions, Action List | Hooked loop, Trigger map, Reward design, Ethics check | Click Data, Interest Signal, Learning Decision | Experiment results, Decision log, Learning summary |
Tagsno overlap | ChangeRoot causeTroubleshootingComparison | GrowthBehaviorRetention | ValidationExperimentsDemandDiscovery | ExperimentsGrowthAnalyticsValidation |