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| Criterion |  Product Discovery Solution Interview |  Decision Making Decision Tree |  Innovation Design Thinking |  Product Discovery MVP Test Matrix |
|---|---|---|---|---|
Purposedifferent | When a solution idea is already on the table, it checks how it is understood and evaluated. It looks for resonance, objections, and missing fit early in the conversation. | 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. | 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 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 | High | Medium |
Timedifferent | 30-60 min je Interview | 30-90 min | 1 Tag bis mehrere Wochen | 45-75 min |
Participantsdifferent | 5-10 Interviews | 1-6 | 4-10 | 2-8 |
Formatdifferent | Workshop + async | Workshop + async | Workshop | Workshop |
Outputdifferent | Solution Feedback, Objection List, Validation Notes | Decision Tree, Option Map, Assumption List | Problem Statement, Prototype, Test Learnings | Test Matrix, Test Plan |
Tagsno overlap | ValidationInterviewsPrototype | DecisionTreeOptions | InnovationPrototypeResearch | ExperimentsValidationDiscoveryOptions |