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