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| Criterion |  Growth A/B Testing |  Product Discovery Assumption Mapping |  Knowledge Modeling Shape-First Modeling |  Product Discovery Riskiest Assumption 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. | When assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first. | Shape-First Modeling defines data quality through shapes before implementation or integration frays at the edges. The approach fits when validation and data contracts should be part of the design from the start. | When an idea hinges on one critical unknown, it prioritizes testing that exact piece of uncertainty first. It separates problem, assumption, solution, and evidence. The result is captured as a prioritized list of assumptions, a test plan, and a result report. |
Complexitydifferent | High | Medium | Medium | Medium |
Timedifferent | 1-4 Wochen | 45-60 min | Halber Tag pro Domain Slice | 1-2 Wochen pro Iteration |
Participantsdifferent | 1-6 | 2-8 | 1-4 | 2-6 |
Formatdifferent | Async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Experiment results, Decision log, Learning summary | Assumption map, Test backlog, Risk ranking | SHACL or ShEx Shapes, Validation Reports, Data Contracts, Shape Documentation | Prioritized Assumption List, Test Plan, Results Report |
Tags1 shared | ExperimentsGrowthAnalyticsValidation | AssumptionsRiskExperimentsValidation | Knowledge graphValidationSemantic | ExperimentsValidationDiscoveryAssumptions |