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| Criterion |  Decision Making Delphi Method |  Growth Growth Experiment |  Product Discovery MVP Test Matrix |  Growth A/B Testing |
|---|---|---|---|---|
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 growth ideas surface quickly, the temptation to build immediately instead of learning is high. A Growth Experiment frames an assumption so target group, lever, and measurement are clear before the first deployment. | When several minimal variants compete to answer the same question, it makes comparing and choosing between them cleaner. It separates problem, assumption, solution, and evidence. The result is captured as a Test Matrix and a Test Plan. | 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 | High | Medium | Medium | High |
Timedifferent | 1-4 Wochen | 1-2 Wochen | 45-75 min | 1-4 Wochen |
Participantsdifferent | 6-30 Experten | 1-6 | 2-8 | 1-6 |
Formatdifferent | Async | Workshop + async | Workshop | Async |
Outputdifferent | Expert Forecast, Consensus Range, Assumption Notes | Experiment card, Result summary, Next bet | Test Matrix, Test Plan | Experiment results, Decision log, Learning summary |
Tagsno overlap | ForecastingExpertsDecisionStrategy | MarketingGrowthExperimentsLearning | ExperimentsValidationDiscoveryOptions | ExperimentsGrowthAnalyticsValidation |