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| Criterion |  Growth Hooked Model |  Growth A/B Testing |  Facilitation Dot Voting |
|---|---|---|---|
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 a workshop has produced too many options and the group needs to condense quickly, dot voting makes preferences visible in a short time. It bundles individual votes into a solid signal for the next selection. |
Complexitydifferent | Medium | High | Low |
Timedifferent | Multiple workshops over several weeks | 1-4 Wochen | 5-15 min |
Participantsdifferent | 2-8 | 1-6 | 3-20 |
Formatdifferent | Workshop + async | Async | Workshop |
Outputdifferent | Hooked loop, Trigger map, Reward design, Ethics check | Experiment results, Decision log, Learning summary | Ranked list, Consensus signal, Shortlist |
Tagsno overlap | GrowthBehaviorRetention | ExperimentsGrowthAnalyticsValidation | FacilitationVotingConsensusPrioritization |
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