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| Criterion |  Knowledge Modeling Shape-First Modeling |  Product Discovery MVP Test Matrix |  Product Discovery Learning Card |  Product Discovery Fake Door Test |
|---|---|---|---|---|
Purposedifferent | Shape-First Modeling defines data quality through shapes before implementation or integration frays at the edges. The approach fits when validation and data contracts should be part of the design from the start. | 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. | The Learning Card connects traceable test results to a reasoned next action while keeping the limits of the insight visible. | 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 | Medium | Medium | Low | Medium |
Timedifferent | Halber Tag pro Domain Slice | 45-75 min | 25-40 min | 1-5 Tage |
Participantsdifferent | 1-4 | 2-8 | 1-5 | Nutzertraffic |
Formatdifferent | Workshop + async | Workshop | Workshop + async | Async |
Outputdifferent | SHACL or ShEx Shapes, Validation Reports, Data Contracts, Shape Documentation | Test Matrix, Test Plan | Learning Card with evidence and next action | Click Data, Interest Signal, Learning Decision |
Tags1 shared | Knowledge graphValidationSemantic | ExperimentsValidationDiscoveryOptions | ExperimentsValidationDiscoveryLearning | ValidationExperimentsDemandDiscovery |