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| Criterion |  Growth A/B Testing |  Delivery Cost of Delay |  Decision Making Assumption Surfacing |  Product Discovery Experiment Canvas |
|---|---|---|---|---|
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. | Helps clarify scope, order, and delivery flow in concrete terms. It makes work, constraints, and sequence manageable. The result is captured as a Cost of Delay table and prioritization sequence. | Plans often contain assumptions that were never openly stated and remain dangerous precisely because of that. Assumption Surfacing makes these silent premises visible and prioritizes which of them carry the initiative or could sink it. | 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. |
Complexitydifferent | High | High | Low | Low |
Timedifferent | 1-4 Wochen | 90-180 min | 45-90 min | 30-60 min |
Participantsdifferent | 1-6 | 3-8 | 2-8 | 1-5 |
Formatdifferent | Async | Workshop | Workshop + async | Workshop + async |
Outputdifferent | Experiment results, Decision log, Learning summary | CoD Table, Prioritization Sequence | Assumption List, Critical Assumptions, Learning Plan | Completed Experiment Canvas, Success Metric |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | PrioritizationDeliveryEconomicsDecision | AssumptionsRiskDecisionDiscovery | ExperimentsValidationDiscoveryHypothesis |