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| Criterion |  Growth Funnel Analysis |  Delivery Cost of Delay |  Decision Making Delphi Method |  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. | Helps clarify scope, order, and delivery flow in concrete terms. It makes work, constraints, and sequence manageable. The result is captured as a Cost of Delay table and prioritization sequence. | 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. |
Complexitydifferent | Medium | High | High | High |
Timedifferent | 1-3 h | 90-180 min | 1-4 Wochen | 1-4 Wochen |
Participantsdifferent | 1-5 | 3-8 | 6-30 Experten | 1-6 |
Formatdifferent | Async | Workshop | Async | Async |
Outputdifferent | Funnel report, Drop-off analysis, Optimization hypotheses | CoD Table, Prioritization Sequence | Expert Forecast, Consensus Range, Assumption Notes | Experiment results, Decision log, Learning summary |
Tagsno overlap | AnalyticsConversionGrowth | PrioritizationDeliveryEconomicsDecision | ForecastingExpertsDecisionStrategy | ExperimentsGrowthAnalyticsValidation |