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| Criterion |  Decision Making Delphi Method |  Growth A/B Testing |  Engineering Goal Question Metric |  Growth North Star Metric |
|---|---|---|---|---|
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. | Helps clarify technical problems, hypotheses, and next steps in concrete terms. It breaks a technical problem into testable parts. The result is captured as a GQM table and metric briefs. | When product teams track many metrics, the view of the actual customer outcome easily gets lost. A North Star Metric bundles growth, usage, and value contribution into one signal that makes the system's direction visible. |
Complexitydifferent | High | High | Medium | Medium |
Timedifferent | 1-4 Wochen | 1-4 Wochen | 90-180 min | 1-2 h |
Participantsdifferent | 6-30 Experten | 1-6 | 3-6 | 3-8 |
Formatdifferent | Async | Async | Workshop | Workshop + async |
Outputdifferent | Expert Forecast, Consensus Range, Assumption Notes | Experiment results, Decision log, Learning summary | GQM Table, Metric Profiles | North Star metric, Input metric tree, Measurement cadence |
Tagsno overlap | ForecastingExpertsDecisionStrategy | ExperimentsGrowthAnalyticsValidation | MetricsMeasurementEngineeringAlignment | GrowthMetricsAlignmentRetention |