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| Criterion |  Product Discovery Outcome-Driven Innovation |  Product Discovery Opportunity Solution Tree |  Innovation Design Thinking |  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. | For complex user problems with an uncertain cause, the method connects observation, interpretation, and experiment into a learning cycle. It keeps the focus on real needs and avoids premature solution language. This produces robust decisions for product and service. | 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 | High | Medium |
Timedifferent | Mehrere Wochen | 1-2 h Setup, laufend | 1 Tag bis mehrere Wochen | 1-5 Tage |
Participantsdifferent | 2-6 researchers plus sample | 2-6 | 4-10 | Nutzertraffic |
Formatdifferent | Workshop + async | Workshop + async | Workshop | Async |
Outputdifferent | Desired outcome statements, Opportunity landscape, Segmentation by underserved needs, Innovation hypotheses | Opportunity Solution Tree, Experiment Backlog, Learning Log | Problem Statement, Prototype, Test Learnings | Click Data, Interest Signal, Learning Decision |
Tagsno overlap | OutcomesInnovationResearchQuantitative | DiscoveryOutcomesExperimentsOpportunity | InnovationPrototypeResearch | ValidationExperimentsDemandDiscovery |