View methods side by side.
Choose up to four methods. Add them using the search and share the comparison by copying its link.
| Criterion |  Product Discovery Outcome-Driven Innovation |  Product Discovery Problem Interview |  Product Discovery Opportunity Solution Tree |  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 the picture of the problem still needs to become solid, it asks about real situations and consequences. It separates genuine suffering from mere interest in a solution. | 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 | High | Medium | Medium | Medium |
Timedifferent | Mehrere Wochen | 30-60 min je Interview | 1-2 h Setup, laufend | 1-5 Tage |
Participantsdifferent | 2-6 researchers plus sample | 5-12 Interviews | 2-6 | Nutzertraffic |
Formatdifferent | Workshop + async | Workshop + async | Workshop + async | Async |
Outputdifferent | Desired outcome statements, Opportunity landscape, Segmentation by underserved needs, Innovation hypotheses | Problem Evidence, Risk Notes, Customer Segments | Opportunity Solution Tree, Experiment Backlog, Learning Log | Click Data, Interest Signal, Learning Decision |
Tagsno overlap | OutcomesInnovationResearchQuantitative | DiscoveryInterviewsValidation | DiscoveryOutcomesExperimentsOpportunity | ValidationExperimentsDemandDiscovery |