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| Criterion |  Growth Funnel Analysis |  Facilitation Dot Voting |  Growth Hooked Model |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | When many visitors or users drop off along the way, the reason behind the number often stays hidden. Funnel Analysis exposes these transitions and makes visible exactly where the path collapses. | 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. | 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. |
Complexitydifferent | Medium | Low | Medium | High |
Timedifferent | 1-3 h | 5-15 min | Multiple workshops over several weeks | 1-4 Wochen |
Participantsdifferent | 1-5 | 3-20 | 2-8 | 1-6 |
Formatdifferent | Async | Workshop | Workshop + async | Async |
Outputdifferent | Funnel report, Drop-off analysis, Optimization hypotheses | Ranked list, Consensus signal, Shortlist | Hooked loop, Trigger map, Reward design, Ethics check | Experiment results, Decision log, Learning summary |
Tagsno overlap | AnalyticsConversionGrowth | FacilitationVotingConsensusPrioritization | GrowthBehaviorRetention | ExperimentsGrowthAnalyticsValidation |