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| Criterion |  Growth Hooked Model |  Product Discovery Fake Door Test |  Decision Making Assumption Surfacing |  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. | 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. | Plans often contain assumptions that were never openly stated and remain dangerous precisely because of that. Assumption Surfacing makes these silent premises visible and prioritizes which of them carry the initiative or could sink it. | 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 | Low | High |
Timedifferent | Multiple workshops over several weeks | 1-5 Tage | 45-90 min | 1-4 Wochen |
Participantsdifferent | 2-8 | Nutzertraffic | 2-8 | 1-6 |
Formatdifferent | Workshop + async | Async | Workshop + async | Async |
Outputdifferent | Hooked loop, Trigger map, Reward design, Ethics check | Click Data, Interest Signal, Learning Decision | Assumption List, Critical Assumptions, Learning Plan | Experiment results, Decision log, Learning summary |
Tagsno overlap | GrowthBehaviorRetention | ValidationExperimentsDemandDiscovery | AssumptionsRiskDecisionDiscovery | ExperimentsGrowthAnalyticsValidation |