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| Criterion |  Knowledge Modeling Shape-First Modeling |  Decision Making Risk Matrix |  Growth A/B Testing |  Product Discovery Smoke 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 a project faces many possible disruptions, it quickly becomes unclear which risks deserve attention first. It separates options, evaluation criteria, and open risks. The result is captured as a Risk Matrix and a Top Risk List. | When two variants compete, discussions quickly decide by taste rather than effect. A/B Testing checks behavior under controlled conditions and separates real improvement from chance or expectation effects. | When demand only needs to be roughly verified, it tests interest with minimal effort. It measures whether people would take a next step at all. |
Complexitydifferent | Medium | Low | High | Low |
Timedifferent | Halber Tag pro Domain Slice | 30-60 min | 1-4 Wochen | 1-5 Tage |
Participantsdifferent | 1-4 | 3-10 | 1-6 | Nutzertraffic |
Formatdifferent | Workshop + async | Workshop + async | Async | Async |
Outputdifferent | SHACL or ShEx Shapes, Validation Reports, Data Contracts, Shape Documentation | Risk Matrix, Top Risk List | Experiment results, Decision log, Learning summary | Interest Metrics, Conversion Signal, Learning Note |
Tagsno overlap | Knowledge graphValidationSemantic | RiskDecisionPrioritizationAssessment | ExperimentsGrowthAnalyticsValidation | ValidationExperimentsDemandGrowth |