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| Criterion |  Decision Making Delphi Method |  Growth A/B Testing |  Product Discovery Concierge MVP |  Product Discovery Experiment 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 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 an idea can first fail or grow through genuine hands-on support, it relies on manual work instead of automation. It shows whether user value holds up even under manual execution. | 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 | Medium | Low |
Timedifferent | 1-4 Wochen | 1-4 Wochen | 1-4 Wochen | 30-60 min |
Participantsdifferent | 6-30 Experten | 1-6 | 3-10 Kunden | 1-5 |
Formatdifferent | Async | Async | Workshop + async | Workshop + async |
Outputdifferent | Expert Forecast, Consensus Range, Assumption Notes | Experiment results, Decision log, Learning summary | Concierge Learnings, Service Blueprint, MVP Risks | Completed Experiment Canvas, Success Metric |
Tagsno overlap | ForecastingExpertsDecisionStrategy | ExperimentsGrowthAnalyticsValidation | MVPValidationServiceDiscovery | ExperimentsValidationDiscoveryHypothesis |