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| Criterion |  Product Discovery Context Canvas |  Knowledge Modeling Shape-First Modeling |  Product Discovery Smoke Test |  Product Discovery Assumption Mapping |
|---|---|---|---|---|
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. | 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 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 assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first. |
Complexitydifferent | Low | Medium | Low | Medium |
Timedifferent | 45-90 min | Halber Tag pro Domain Slice | 1-5 Tage | 45-60 min |
Participantsdifferent | 3-10 | 1-4 | Nutzertraffic | 2-8 |
Formatdifferent | Workshop | Workshop + async | Async | Workshop + async |
Outputdifferent | Context canvas, Open questions, Shared context notes | SHACL or ShEx Shapes, Validation Reports, Data Contracts, Shape Documentation | Interest Metrics, Conversion Signal, Learning Note | Assumption map, Test backlog, Risk ranking |
Tagsno overlap | ContextFramingRequirementsCanvas | Knowledge graphValidationSemantic | ValidationExperimentsDemandGrowth | AssumptionsRiskExperimentsValidation |