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| Criterion |  Growth Hooked Model |  Product Discovery Fake Door Test |  Product Strategy ICE Scoring |  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. | When ideas need sorting quickly, it condenses impact, confidence, and effort into one compact score. It connects customer value, product logic, and decision priorities. The result is captured as an ICE table and top-ideas list. | 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 | 30-60 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 | ICE Table, Top Idea List | Experiment results, Decision log, Learning summary |
Tagsno overlap | GrowthBehaviorRetention | ValidationExperimentsDemandDiscovery | PrioritizationScoringGrowthDecision | ExperimentsGrowthAnalyticsValidation |