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| Criterion |  Growth A/B Testing |  Agile Affinity Estimation |  Product Strategy ICE Scoring |  Product Discovery Smoke Test |
|---|---|---|---|---|
Purposedifferent | 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 many tasks need to be classified quickly, it sorts them by perceived effort and similarity. It reduces the effort of fine-grained estimation for large volumes. | 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 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 | High | Medium | Low | Low |
Timedifferent | 1-4 Wochen | 30-90 min | 30-60 min | 1-5 Tage |
Participantsdifferent | 1-6 | 3-12 | 2-8 | Nutzertraffic |
Formatdifferent | Async | Workshop | Workshop + async | Async |
Outputdifferent | Experiment results, Decision log, Learning summary | Affinity Size Map, Grouped Estimates, Unclear Items | ICE Table, Top Idea List | Interest Metrics, Conversion Signal, Learning Note |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | EstimationBacklogRelative sizing | PrioritizationScoringGrowthDecision | ValidationExperimentsDemandGrowth |