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| Criterion |  Decision Making Delphi Method |  Product Strategy Counter Metrics |  Product Discovery Smoke Test |  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 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 demand only needs to be roughly verified, it tests interest with minimal effort. It measures whether people would take a next step at all. | 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 | Low | Low | High |
Timedifferent | 1-4 Wochen | 30-60 min | 1-5 Tage | 1-4 Wochen |
Participantsdifferent | 6-30 Experten | 2-6 | Nutzertraffic | 1-6 |
Formatdifferent | Async | Workshop + async | Async | Async |
Outputdifferent | Expert Forecast, Consensus Range, Assumption Notes | Counter Metric List, Guardrail Definitions | Interest Metrics, Conversion Signal, Learning Note | Experiment results, Decision log, Learning summary |
Tagsno overlap | ForecastingExpertsDecisionStrategy | MetricsMeasurementStrategyExperiments | ValidationExperimentsDemandGrowth | ExperimentsGrowthAnalyticsValidation |