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| Criterion |  Decision Making Delphi Method |  Product Discovery Experiment Canvas |  Growth A/B Testing |  Product Discovery Hypothesis Prioritization Canvas |
|---|---|---|---|---|
Purposedifferent | When knowledge is distributed and direct dominance should be avoided, groups quickly fall under the sway of their opinion leaders. The Delphi Method gathers assessments iteratively and gradually brings expert judgments closer together. | 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 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 many hypotheses compete for attention, it brings order to their learning sequence and importance. It separates problem, assumption, solution, and evidence. The result is captured as a prioritization canvas and a hypothesis backlog. |
Complexitydifferent | High | Low | High | Medium |
Timedifferent | 1-4 Wochen | 30-60 min | 1-4 Wochen | 60-90 min |
Participantsdifferent | 6-30 Experten | 1-5 | 1-6 | 3-8 |
Formatdifferent | Async | Workshop + async | Async | Workshop |
Outputdifferent | Expert Forecast, Consensus Range, Assumption Notes | Completed Experiment Canvas, Success Metric | Experiment results, Decision log, Learning summary | Prioritization Canvas, Hypothesis Backlog |
Tagsno overlap | ForecastingExpertsDecisionStrategy | ExperimentsValidationDiscoveryHypothesis | ExperimentsGrowthAnalyticsValidation | ExperimentsPrioritizationDiscoveryHypothesis |