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| Criterion |  Product Discovery Smoke Test |  Knowledge Modeling Ontology Design Patterns |  Product Discovery Fake Door Test |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | 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. | 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 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. | 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. |
Complexitydifferent | Low | Medium | Medium | High |
Timedifferent | 1-5 Tage | 1-3 h pro Pattern | 1-5 Tage | 1-4 Wochen |
Participantsdifferent | Nutzertraffic | 1-6 | Nutzertraffic | 1-6 |
Formatdifferent | Async | Workshop + async | Async | Async |
Outputdifferent | Interest Metrics, Conversion Signal, Learning Note | Selected Patterns, Adapted Schema Fragments, Pattern Documentation | Click Data, Interest Signal, Learning Decision | Experiment results, Decision log, Learning summary |
Tagsno overlap | ValidationExperimentsDemandGrowth | OntologyPatternsReuseSemanticModeling | ValidationExperimentsDemandDiscovery | ExperimentsGrowthAnalyticsValidation |