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| Criterion |  Growth Hooked Model |  Growth A/B Testing |  Operations ALPEN Method |  Product Discovery Fake Door Test |
|---|---|---|---|---|
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 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. | With an overloaded day full of too many tasks, a realistic picture of the day emerges. The method connects estimating, deciding, and buffer thinking so planning fits available energy and time. | 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. |
Complexitydifferent | Medium | High | Low | Medium |
Timedifferent | Multiple workshops over several weeks | 1-4 Wochen | 10-20 min daily | 1-5 Tage |
Participantsdifferent | 2-8 | 1-6 | 1 | Nutzertraffic |
Formatdifferent | Workshop + async | Async | Async | Async |
Outputdifferent | Hooked loop, Trigger map, Reward design, Ethics check | Experiment results, Decision log, Learning summary | Daily Plan, Time Estimates, Review Notes | Click Data, Interest Signal, Learning Decision |
Tagsno overlap | GrowthBehaviorRetention | ExperimentsGrowthAnalyticsValidation | PlanningTime managementProductivityOperations | ValidationExperimentsDemandDiscovery |