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| Criterion | ![]() Growth Hooked Model | ![]() Facilitation Nominal Group Technique | ![]() Growth A/B Testing | ![]() Product Discovery Smoke 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 loud voices could dominate a round, Nominal Group Technique protects individual thinking time from group effects. It collects ideas separately first and only then enables shared weighting. | 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 only needs to be roughly verified, it tests interest with minimal effort. It measures whether people would take a next step at all. |
Complexitydifferent | Medium | Medium | High | Low |
Timedifferent | Multiple workshops over several weeks | 60-120 min | 1-4 Wochen | 1-5 Tage |
Participantsdifferent | 2-8 | 5-12 | 1-6 | Nutzertraffic |
Formatdifferent | Workshop + async | Workshop | Async | Async |
Outputdifferent | Hooked loop, Trigger map, Reward design, Ethics check | Ranked Ideas, Clarified Options, Group Priority | Experiment results, Decision log, Learning summary | Interest Metrics, Conversion Signal, Learning Note |
Tagsno overlap | GrowthBehaviorRetention | FacilitationPrioritizationVotingInclusion | ExperimentsGrowthAnalyticsValidation | ValidationExperimentsDemandGrowth |



