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| Criterion |  Growth A/B Testing |  Agile Acceptance Criteria Workshop |  Product Discovery Experiment Canvas |  Agile Example Mapping |
|---|---|---|---|---|
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 a story needs clear checkpoints before implementation, it sharpens expectation and scope together. It sorts work by value, risk, and delivery ability. The result is captured as Acceptance Criteria and a Story Update. | When experiments become unreadable after the fact, it arranges hypothesis, signal, and learning goal on a single canvas. It separates problem, assumption, solution, and evidence. The result is captured as a Completed Experiment Canvas and a Success Metric. | When a story carries business rules and exceptions, it brings clarity before implementation. It makes examples, open questions, and boundaries visible enough that the logic becomes jointly sound. |
Complexitydifferent | High | Low | Low | Low |
Timedifferent | 1-4 Wochen | 20-40 min pro Story | 30-60 min | 30-60 min |
Participantsdifferent | 1-6 | 3-6 | 1-5 | 3-7 |
Formatdifferent | Async | Workshop | Workshop + async | Workshop |
Outputdifferent | Experiment results, Decision log, Learning summary | Acceptance Criteria, Story Update | Completed Experiment Canvas, Success Metric | Example Map, Acceptance Criteria, Open Questions |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | AgileRequirementsRefinementBehavior-Driven Development | ExperimentsValidationDiscoveryHypothesis | Behavior-Driven DevelopmentRequirementsExamplesRefinement |