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| Criterion |  Growth Funnel Analysis |  Decision Making Delphi Method |  Growth Pirate Metrics AARRR |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | When many visitors or users drop off along the way, the reason behind the number often stays hidden. Funnel Analysis exposes these transitions and makes visible exactly where the path collapses. | 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. | 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 | Medium | High | Medium | High |
Timedifferent | 1-3 h | 1-4 Wochen | 1-2 h Setup, laufend | 1-4 Wochen |
Participantsdifferent | 1-5 | 6-30 Experten | 2-8 | 1-6 |
Formatdifferent | Async | Async | Workshop + async | Async |
Outputdifferent | Funnel report, Drop-off analysis, Optimization hypotheses | Expert Forecast, Consensus Range, Assumption Notes | AARRR funnel, Metric baseline, Experiment backlog | Experiment results, Decision log, Learning summary |
Tagsno overlap | AnalyticsConversionGrowth | ForecastingExpertsDecisionStrategy | GrowthMetricsExperiments | ExperimentsGrowthAnalyticsValidation |