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| Criterion |  Growth A/B Testing |  Product Strategy KPI Tree |  Decision Making Delphi Method |  Product Strategy Counter Metrics |
|---|---|---|---|---|
Purposedifferent | 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 metrics across the organization drift apart, it arranges drivers and effects under one shared logic. It connects customer value, product logic, and decision priorities. The result is captured as a KPI tree and owner list. | 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. |
Complexitydifferent | High | Medium | High | Low |
Timedifferent | 1-4 Wochen | 90-180 min initial, dann laufend | 1-4 Wochen | 30-60 min |
Participantsdifferent | 1-6 | 3-8 | 6-30 Experten | 2-6 |
Formatdifferent | Async | Workshop + async | Async | Workshop + async |
Outputdifferent | Experiment results, Decision log, Learning summary | KPI Tree, Owner List | Expert Forecast, Consensus Range, Assumption Notes | Counter Metric List, Guardrail Definitions |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | MetricsStrategyAlignmentMeasurement | ForecastingExpertsDecisionStrategy | MetricsMeasurementStrategyExperiments |