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| Criterion |  Product Discovery Outcome-Driven Innovation |  Product Discovery Opportunity Solution Tree |  Product Discovery Product Kata |  Product Discovery Fake Door Test |
|---|---|---|---|---|
Purposedifferent | 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. | Product Kata helps clarify customer problems, solution ideas, and evidence through a repeatable improvement routine. It captures direction, current metric, target metric, experiment notes, and learning. | 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 | High | Medium | Medium | Medium |
Timedifferent | Mehrere Wochen | 1-2 h Setup, laufend | 1-2 Wochen je Loop | 1-5 Tage |
Participantsdifferent | 2-6 researchers plus sample | 2-6 | 3-10 | Nutzertraffic |
Formatdifferent | Workshop + async | Workshop + async | Workshop + async | Async |
Outputdifferent | Desired outcome statements, Opportunity landscape, Segmentation by underserved needs, Innovation hypotheses | Opportunity Solution Tree, Experiment Backlog, Learning Log | Direction, Current metric, Target metric, Experiment note, Learning report | Click Data, Interest Signal, Learning Decision |
Tagsno overlap | OutcomesInnovationResearchQuantitative | DiscoveryOutcomesExperimentsOpportunity | OutcomesDiscoveryLearningIterationCoaching | ValidationExperimentsDemandDiscovery |