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| Criterion |  Growth A/B Testing |  Knowledge Modeling Ontology Design Patterns |  Product Discovery Assumption Mapping |  Product Discovery Smoke Test |
|---|---|---|---|---|
Purposedifferent | 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. | Ontology Design Patterns provide reusable building blocks for recurring modeling problems. The method brings structure to the search for clean concepts, relationships, and roles. | When assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first. | 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 | High | Medium | Medium | Low |
Timedifferent | 1-4 Wochen | 1-3 h pro Pattern | 45-60 min | 1-5 Tage |
Participantsdifferent | 1-6 | 1-6 | 2-8 | Nutzertraffic |
Formatdifferent | Async | Workshop + async | Workshop + async | Async |
Outputdifferent | Experiment results, Decision log, Learning summary | Selected Patterns, Adapted Schema Fragments, Pattern Documentation | Assumption map, Test backlog, Risk ranking | Interest Metrics, Conversion Signal, Learning Note |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | OntologyPatternsReuseSemanticModeling | AssumptionsRiskExperimentsValidation | ValidationExperimentsDemandGrowth |