View methods side by side.
Choose up to four methods. Add them using the search and share the comparison by copying its link.
| Criterion |  Facilitation Dot Voting |  Growth Hooked Model |  Growth A/B Testing |  Product Discovery Smoke Test |
|---|---|---|---|---|
Purposedifferent | 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. | 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 | Low | Medium | High | Low |
Timedifferent | 5-15 min | Multiple workshops over several weeks | 1-4 Wochen | 1-5 Tage |
Participantsdifferent | 3-20 | 2-8 | 1-6 | Nutzertraffic |
Formatdifferent | Workshop | Workshop + async | Async | Async |
Outputdifferent | Ranked list, Consensus signal, Shortlist | Hooked loop, Trigger map, Reward design, Ethics check | Experiment results, Decision log, Learning summary | Interest Metrics, Conversion Signal, Learning Note |
Tagsno overlap | FacilitationVotingConsensusPrioritization | GrowthBehaviorRetention | ExperimentsGrowthAnalyticsValidation | ValidationExperimentsDemandGrowth |