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| Criterion |  Product Discovery Opportunity Interview |  Product Discovery Fake Door Test |  Product Discovery Concierge MVP |  Product Discovery Opportunity Solution Tree |
|---|---|---|---|---|
Purposedifferent | When opportunities are still hidden behind signals of need, it structures conversations around needs and obstacles. It looks for patterns that lead to new product opportunities. | 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. | When an idea can first fail or grow through genuine hands-on support, it relies on manual work instead of automation. It shows whether user value holds up even under manual execution. | 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. |
Complexitysame | Medium | Medium | Medium | Medium |
Timedifferent | 30-60 min je Interview | 1-5 Tage | 1-4 Wochen | 1-2 h Setup, laufend |
Participantsdifferent | 5-12 Interviews | Nutzertraffic | 3-10 Kunden | 2-6 |
Formatdifferent | Workshop + async | Async | Workshop + async | Workshop + async |
Outputdifferent | Interview Notes, Opportunity Themes, Customer Quotes | Click Data, Interest Signal, Learning Decision | Concierge Learnings, Service Blueprint, MVP Risks | Opportunity Solution Tree, Experiment Backlog, Learning Log |
Tags1 shared | DiscoveryInterviewsOpportunityCustomer | ValidationExperimentsDemandDiscovery | MVPValidationServiceDiscovery | DiscoveryOutcomesExperimentsOpportunity |