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| Criterion |  Knowledge Modeling Domain Storytelling |  Product Discovery MVP Test Matrix |  Product Discovery Smoke Test |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | Domain Storytelling translates domain knowledge into a shared narrative of actors, objects, and workflows. It is especially useful when language, rules, and process understanding must be tightly connected. | 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. | 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. | 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 | Low | High |
Timedifferent | 1-2 h | 45-75 min | 1-5 Tage | 1-4 Wochen |
Participantsdifferent | 2-8 | 2-8 | Nutzertraffic | 1-6 |
Formatdifferent | Workshop | Workshop | Async | Async |
Outputdifferent | Domain Story, Glossary Notes, Process Narrative | Test Matrix, Test Plan | Interest Metrics, Conversion Signal, Learning Note | Experiment results, Decision log, Learning summary |
Tagsno overlap | KnowledgeDomain-Driven DesignProcess | ExperimentsValidationDiscoveryOptions | ValidationExperimentsDemandGrowth | ExperimentsGrowthAnalyticsValidation |