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| Criterion |  Growth Hooked Model |  Decision Making Constraint Analysis |  Product Discovery Fake Door Test |  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 an initiative stalls, the limit often lies not in the idea but in hard or soft boundary conditions. Constraint Analysis separates these limits and shows which of them can actually be shaped. | 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 | Low | Medium | High |
Timedifferent | Multiple workshops over several weeks | 30-90 min | 1-5 Tage | 1-4 Wochen |
Participantsdifferent | 2-8 | 2-8 | Nutzertraffic | 1-6 |
Formatdifferent | Workshop + async | Workshop + async | Async | Async |
Outputdifferent | Hooked loop, Trigger map, Reward design, Ethics check | Constraint List, Hard/Soft Classification, Option Impact Notes, Decision Boundaries | Click Data, Interest Signal, Learning Decision | Experiment results, Decision log, Learning summary |
Tagsno overlap | GrowthBehaviorRetention | ConstraintsDecisionPlanningOptions | ValidationExperimentsDemandDiscovery | ExperimentsGrowthAnalyticsValidation |