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| Criterion |  Product Strategy ICE Scoring |  Growth Hooked Model |  Product Discovery Smoke Test |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | When ideas need sorting quickly, it condenses impact, confidence, and effort into one compact score. It connects customer value, product logic, and decision priorities. The result is captured as an ICE table and top-ideas list. | 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 | 30-60 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 | ICE Table, Top Idea List | Hooked loop, Trigger map, Reward design, Ethics check | Interest Metrics, Conversion Signal, Learning Note | Experiment results, Decision log, Learning summary |
Tags1 shared | PrioritizationScoringGrowthDecision | GrowthBehaviorRetention | ValidationExperimentsDemandGrowth | ExperimentsGrowthAnalyticsValidation |