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| Criterion |  UX Research User Interviews |  Product Discovery Outcome-Driven Innovation |  Product Discovery Opportunity Solution Tree |  Product Discovery Fake Door Test |
|---|---|---|---|---|
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. | Outcome-Driven Innovation clarifies customer problems, solution opportunities, and evidence. It separates jobs, desired outcomes, importance, satisfaction, and opportunity, and captures results as desired outcome statements, an opportunity landscape, and segments by underserved needs. | When discovery keeps swinging between goals, ideas, and learning loops, it creates clear steering logic. It connects the desired outcome, opportunities, and experiments into a legible structure. | When demand is still unclear, it measures interest in a feature before it is built. It separates real behavior from polite agreement and deliberately keeps build effort small. |
Complexitydifferent | Low | High | Medium | Medium |
Timedifferent | 30–60 min per interview | Mehrere Wochen | 1-2 h Setup, laufend | 1-5 Tage |
Participantsdifferent | 1 participant per interview | 2-6 researchers plus sample | 2-6 | Nutzertraffic |
Formatdifferent | Workshop + async | Workshop + async | Workshop + async | Async |
Outputdifferent | Interview Notes, Themes, Insight Summary | Desired outcome statements, Opportunity landscape, Segmentation by underserved needs, Innovation hypotheses | Opportunity Solution Tree, Experiment Backlog, Learning Log | Click Data, Interest Signal, Learning Decision |
Tagsno overlap | QualitativeResearchCustomerDiscovery | OutcomesInnovationResearchQuantitative | DiscoveryOutcomesExperimentsOpportunity | ValidationExperimentsDemandDiscovery |