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| Criterion |  Product Strategy Counter Metrics |  Domain Modeling Bounded Context Canvas |  Product Discovery Assumption Mapping |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | When a headline metric could mask side effects, it adds guardrail signals against unwanted outcomes. It connects customer value, product logic, and decision priorities. The result is captured as a counter-metric list and guardrail definitions. | When a business context is still loosely outlined, it shapes language, responsibility, and integration space. It clarifies what belongs together and where a boundary needs to hold. | 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 | 30-60 min | 1-3 h | 45-60 min | 1-4 Wochen |
Participantsdifferent | 2-6 | 3-8 | 2-8 | 1-6 |
Formatdifferent | Workshop + async | Workshop + async | Workshop + async | Async |
Outputdifferent | Counter Metric List, Guardrail Definitions | Context Canvas, Glossary, Integration Notes | Assumption map, Test backlog, Risk ranking | Experiment results, Decision log, Learning summary |
Tagsno overlap | MetricsMeasurementStrategyExperiments | Domain-Driven DesignBoundariesModeling | AssumptionsRiskExperimentsValidation | ExperimentsGrowthAnalyticsValidation |