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| Criterion |  Decision Making Delphi Method |  Growth Growth Experiment |  Product Strategy Counter Metrics |  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 a headline metric could mask side effects, it adds guardrail signals against unwanted outcomes. It connects customer value, product logic, and decision priorities. The result is captured as a counter-metric list and guardrail definitions. | 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 | Low | High |
Timedifferent | 1-4 Wochen | 1-2 Wochen | 30-60 min | 1-4 Wochen |
Participantsdifferent | 6-30 Experten | 1-6 | 2-6 | 1-6 |
Formatdifferent | Async | Workshop + async | Workshop + async | Async |
Outputdifferent | Expert Forecast, Consensus Range, Assumption Notes | Experiment card, Result summary, Next bet | Counter Metric List, Guardrail Definitions | Experiment results, Decision log, Learning summary |
Tagsno overlap | ForecastingExpertsDecisionStrategy | MarketingGrowthExperimentsLearning | MetricsMeasurementStrategyExperiments | ExperimentsGrowthAnalyticsValidation |