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| Criterion |  Product Discovery Pretotyping |  Knowledge Modeling Event Modeling |  Product Discovery Assumption Mapping |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | Pretotyping clarifies whether a customer problem and solution idea create enough real demand. It separates problem, assumption, solution, and evidence, and captures the result as a pretotyping sketch, test setup, and conversion data. | Event Modeling connects business workflows with commands, events, and views into one coherent mental model. It helps design behavior, UI, and technical slices from the same underlying logic. | When assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first. | 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 | Stunden bis wenige Tage | 2-6 h | 45-60 min | 1-4 Wochen |
Participantsdifferent | 1-4 | 2-8 | 2-8 | 1-6 |
Formatdifferent | Workshop + async | Workshop + async | Workshop + async | Async |
Outputdifferent | Pretotyping sketch, Test setup, Conversion data, Go or no-go decision | Event Model, UI Flow, Commands, Read Models | Assumption map, Test backlog, Risk ranking | Experiment results, Decision log, Learning summary |
Tagsno overlap | ValidationDemandMVP | EventsBlueprintDomain-Driven DesignBehavior | AssumptionsRiskExperimentsValidation | ExperimentsGrowthAnalyticsValidation |