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| Criterion |  Product Discovery Opportunity Solution Tree |  Product Discovery Fake Door Test |  Agile Affinity Estimation |  Product Discovery MVP Test Matrix |
|---|---|---|---|---|
Purposedifferent | 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. | When many tasks need to be classified quickly, it sorts them by perceived effort and similarity. It reduces the effort of fine-grained estimation for large volumes. | When several minimal variants compete to answer the same question, it makes comparing and choosing between them cleaner. It separates problem, assumption, solution, and evidence. The result is captured as a Test Matrix and a Test Plan. |
Complexitysame | Medium | Medium | Medium | Medium |
Timedifferent | 1-2 h Setup, laufend | 1-5 Tage | 30-90 min | 45-75 min |
Participantsdifferent | 2-6 | Nutzertraffic | 3-12 | 2-8 |
Formatdifferent | Workshop + async | Async | Workshop | Workshop |
Outputdifferent | Opportunity Solution Tree, Experiment Backlog, Learning Log | Click Data, Interest Signal, Learning Decision | Affinity Size Map, Grouped Estimates, Unclear Items | Test Matrix, Test Plan |
Tagsno overlap | DiscoveryOutcomesExperimentsOpportunity | ValidationExperimentsDemandDiscovery | EstimationBacklogRelative sizing | ExperimentsValidationDiscoveryOptions |