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| Criterion |  Growth Funnel Analysis |  Operations ALPEN Method |  Decision Making Decision Tree |  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. | With an overloaded day full of too many tasks, a realistic picture of the day emerges. The method connects estimating, deciding, and buffer thinking so planning fits available energy and time. | For decisions with follow-on paths and dependencies, a linear comparison is often not enough. A Decision Tree shows how options branch under conditions and which consequences hang on each branch. | 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 | Medium | High |
Timedifferent | 1-3 h | 10-20 min daily | 30-90 min | 1-4 Wochen |
Participantsdifferent | 1-5 | 1 | 1-6 | 1-6 |
Formatdifferent | Async | Async | Workshop + async | Async |
Outputdifferent | Funnel report, Drop-off analysis, Optimization hypotheses | Daily Plan, Time Estimates, Review Notes | Decision Tree, Option Map, Assumption List | Experiment results, Decision log, Learning summary |
Tagsno overlap | AnalyticsConversionGrowth | PlanningTime managementProductivityOperations | DecisionTreeOptions | ExperimentsGrowthAnalyticsValidation |