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| Criterion |  Product Discovery Context Canvas |  Growth A/B Testing |  Knowledge Modeling Shape-First Modeling |  Knowledge Modeling Competency Questions |
|---|---|---|---|---|
Purposedifferent | When an environment of users, systems, and constraints is hard to grasp, it puts the context compactly on the table. It creates a clear reading of influence, boundary, and dependency. | 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. | 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. | Competency Questions translate a domain model into concrete questions that it must be able to answer. The method keeps the model's scope clean and prevents pretty but useless structures. |
Complexitydifferent | Low | High | Medium | Medium |
Timedifferent | 45-90 min | 1-4 Wochen | Halber Tag pro Domain Slice | 2-4 h |
Participantsdifferent | 3-10 | 1-6 | 1-4 | 2-8 |
Formatdifferent | Workshop | Async | Workshop + async | Workshop + async |
Outputdifferent | Context canvas, Open questions, Shared context notes | Experiment results, Decision log, Learning summary | SHACL or ShEx Shapes, Validation Reports, Data Contracts, Shape Documentation | Competency Question Set, Required Concepts, Test Queries, Coverage Matrix |
Tagsno overlap | ContextFramingRequirementsCanvas | ExperimentsGrowthAnalyticsValidation | Knowledge graphValidationSemantic | OntologyKnowledge graphScopeRequirementsSemantic |