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| Criterion |  Product Discovery Kano Model |  Growth A/B Testing |  Product Strategy ICE Scoring |  Product Discovery Smoke Test |
|---|---|---|---|---|
Purposedifferent | When features need to be distinguished by their effect on satisfaction, it makes expectations and surprises comparable. It separates basic needs, performance contribution, and delight. | 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 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 | Medium | High | Low | Low |
Timedifferent | 1-2 Tage | 1-4 Wochen | 30-60 min | 1-5 Tage |
Participantsdifferent | 10-50 | 1-6 | 2-8 | Nutzertraffic |
Formatdifferent | Workshop + async | Async | Workshop + async | Async |
Outputdifferent | Kano Matrix, Feature Classes, Priority Themes | Experiment results, Decision log, Learning summary | ICE Table, Top Idea List | Interest Metrics, Conversion Signal, Learning Note |
Tagsno overlap | SatisfactionPrioritizationCustomer | ExperimentsGrowthAnalyticsValidation | PrioritizationScoringGrowthDecision | ValidationExperimentsDemandGrowth |