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| Criterion |  Product Strategy ICE Scoring |  Domain Modeling Bounded Context Canvas |  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. | When a business context is still loosely outlined, it shapes language, responsibility, and integration space. It clarifies what belongs together and where a boundary needs to hold. | 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 | 1-3 h | 1-5 Tage | 1-4 Wochen |
Participantsdifferent | 2-8 | 3-8 | Nutzertraffic | 1-6 |
Formatdifferent | Workshop + async | Workshop + async | Async | Async |
Outputdifferent | ICE Table, Top Idea List | Context Canvas, Glossary, Integration Notes | Interest Metrics, Conversion Signal, Learning Note | Experiment results, Decision log, Learning summary |
Tagsno overlap | PrioritizationScoringGrowthDecision | Domain-Driven DesignBoundariesModeling | ValidationExperimentsDemandGrowth | ExperimentsGrowthAnalyticsValidation |