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| Criterion |  Product Discovery Fake Door Test |  Knowledge Modeling Ontology Design Patterns |  Product Discovery Experiment Canvas |  Product Discovery Hypothesis Prioritization Canvas |
|---|---|---|---|---|
Purposedifferent | 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. | 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 experiments become unreadable after the fact, it arranges hypothesis, signal, and learning goal on a single canvas. It separates problem, assumption, solution, and evidence. The result is captured as a Completed Experiment Canvas and a Success Metric. | When many hypotheses compete for attention, it brings order to their learning sequence and importance. It separates problem, assumption, solution, and evidence. The result is captured as a prioritization canvas and a hypothesis backlog. |
Complexitydifferent | Medium | Medium | Low | Medium |
Timedifferent | 1-5 Tage | 1-3 h pro Pattern | 30-60 min | 60-90 min |
Participantsdifferent | Nutzertraffic | 1-6 | 1-5 | 3-8 |
Formatdifferent | Async | Workshop + async | Workshop + async | Workshop |
Outputdifferent | Click Data, Interest Signal, Learning Decision | Selected Patterns, Adapted Schema Fragments, Pattern Documentation | Completed Experiment Canvas, Success Metric | Prioritization Canvas, Hypothesis Backlog |
Tagsno overlap | ValidationExperimentsDemandDiscovery | OntologyPatternsReuseSemanticModeling | ExperimentsValidationDiscoveryHypothesis | ExperimentsPrioritizationDiscoveryHypothesis |