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| Criterion |  Growth A/B Testing |  Product Strategy Counter Metrics |  Decision Making Delphi Method |  Growth Pirate Metrics AARRR |
|---|---|---|---|---|
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 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 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. | For products with complex usage paths, overall growth alone is too coarse to reveal bottlenecks. Pirate Metrics breaks the relationship with the product into consecutive stages and shows where the funnel actually leaks. |
Complexitydifferent | High | Low | High | Medium |
Timedifferent | 1-4 Wochen | 30-60 min | 1-4 Wochen | 1-2 h Setup, laufend |
Participantsdifferent | 1-6 | 2-6 | 6-30 Experten | 2-8 |
Formatdifferent | Async | Workshop + async | Async | Workshop + async |
Outputdifferent | Experiment results, Decision log, Learning summary | Counter Metric List, Guardrail Definitions | Expert Forecast, Consensus Range, Assumption Notes | AARRR funnel, Metric baseline, Experiment backlog |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | MetricsMeasurementStrategyExperiments | ForecastingExpertsDecisionStrategy | GrowthMetricsExperiments |