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| Criterion | ![]() Growth Hooked Model | ![]() Growth A/B Testing | ![]() Product Discovery Fake Door Test | ![]() Product Discovery MVP Test Matrix |
|---|---|---|---|---|
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. | 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 several minimal variants compete to answer the same question, it makes comparing and choosing between them cleaner. It separates problem, assumption, solution, and evidence. The result is captured as a Test Matrix and a Test Plan. |
Complexitydifferent | Medium | High | Medium | Medium |
Timedifferent | Multiple workshops over several weeks | 1-4 Wochen | 1-5 Tage | 45-75 min |
Participantsdifferent | 2-8 | 1-6 | Nutzertraffic | 2-8 |
Formatdifferent | Workshop + async | Async | Async | Workshop |
Outputdifferent | Hooked loop, Trigger map, Reward design, Ethics check | Experiment results, Decision log, Learning summary | Click Data, Interest Signal, Learning Decision | Test Matrix, Test Plan |
Tagsno overlap | GrowthBehaviorRetention | ExperimentsGrowthAnalyticsValidation | ValidationExperimentsDemandDiscovery | ExperimentsValidationDiscoveryOptions |



