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| Criterion |  Growth Funnel Analysis |  Decision Making Constraint Analysis |  Delivery Cost of Delay |  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 an initiative stalls, the limit often lies not in the idea but in hard or soft boundary conditions. Constraint Analysis separates these limits and shows which of them can actually be shaped. | 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 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 | Low | High | High |
Timedifferent | 1-3 h | 30-90 min | 90-180 min | 1-4 Wochen |
Participantsdifferent | 1-5 | 2-8 | 3-8 | 1-6 |
Formatdifferent | Async | Workshop + async | Workshop | Async |
Outputdifferent | Funnel report, Drop-off analysis, Optimization hypotheses | Constraint List, Hard/Soft Classification, Option Impact Notes, Decision Boundaries | CoD Table, Prioritization Sequence | Experiment results, Decision log, Learning summary |
Tagsno overlap | AnalyticsConversionGrowth | ConstraintsDecisionPlanningOptions | PrioritizationDeliveryEconomicsDecision | ExperimentsGrowthAnalyticsValidation |