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| Criterion |  Decision Making Constraint Analysis |  Growth Hooked Model |  Product Discovery Smoke Test |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | When an initiative stalls, the limit often lies not in the idea but in hard or soft boundary conditions. Constraint Analysis separates these limits and shows which of them can actually be shaped. | 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 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 | Low | Medium | Low | High |
Timedifferent | 30-90 min | Multiple workshops over several weeks | 1-5 Tage | 1-4 Wochen |
Participantsdifferent | 2-8 | 2-8 | Nutzertraffic | 1-6 |
Formatdifferent | Workshop + async | Workshop + async | Async | Async |
Outputdifferent | Constraint List, Hard/Soft Classification, Option Impact Notes, Decision Boundaries | Hooked loop, Trigger map, Reward design, Ethics check | Interest Metrics, Conversion Signal, Learning Note | Experiment results, Decision log, Learning summary |
Tagsno overlap | ConstraintsDecisionPlanningOptions | GrowthBehaviorRetention | ValidationExperimentsDemandGrowth | ExperimentsGrowthAnalyticsValidation |