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| Criterion |  Decision Making Decision Tree |  Product Discovery Opportunity Interview |  Product Discovery Experiment Canvas |  Product Discovery MVP Test Matrix |
|---|---|---|---|---|
Purposedifferent | For decisions with follow-on paths and dependencies, a linear comparison is often not enough. A Decision Tree shows how options branch under conditions and which consequences hang on each branch. | 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 experiments become unreadable after the fact, it arranges hypothesis, signal, and learning goal on a single canvas. It separates problem, assumption, solution, and evidence. The result is captured as a Completed Experiment Canvas and a Success Metric. | 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. |
Complexitydifferent | Medium | Medium | Low | Medium |
Timedifferent | 30-90 min | 30-60 min je Interview | 30-60 min | 45-75 min |
Participantsdifferent | 1-6 | 5-12 Interviews | 1-5 | 2-8 |
Formatdifferent | Workshop + async | Workshop + async | Workshop + async | Workshop |
Outputdifferent | Decision Tree, Option Map, Assumption List | Interview Notes, Opportunity Themes, Customer Quotes | Completed Experiment Canvas, Success Metric | Test Matrix, Test Plan |
Tagsno overlap | DecisionTreeOptions | DiscoveryInterviewsOpportunityCustomer | ExperimentsValidationDiscoveryHypothesis | ExperimentsValidationDiscoveryOptions |