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| Criterion |  UX Research User Interviews |  Product Strategy ICE Scoring |  Product Discovery Hypothesis Prioritization Canvas |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | When teams derive needs only from assumptions and real motives are missing, user interviews give direct access to behavior and meaning. Conversations from the target group's everyday life make patterns, tensions, and open questions solidly visible. | 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 many hypotheses compete for attention, it brings order to their learning sequence and importance. It separates problem, assumption, solution, and evidence. The result is captured as a prioritization canvas and a hypothesis backlog. | 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 | Low | Medium | High |
Timedifferent | 30–60 min per interview | 30-60 min | 60-90 min | 1-4 Wochen |
Participantsdifferent | 1 participant per interview | 2-8 | 3-8 | 1-6 |
Formatdifferent | Workshop + async | Workshop + async | Workshop | Async |
Outputdifferent | Interview Notes, Themes, Insight Summary | ICE Table, Top Idea List | Prioritization Canvas, Hypothesis Backlog | Experiment results, Decision log, Learning summary |
Tagsno overlap | QualitativeResearchCustomerDiscovery | PrioritizationScoringGrowthDecision | ExperimentsPrioritizationDiscoveryHypothesis | ExperimentsGrowthAnalyticsValidation |