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| Criterion |  Agile Ideal Days |  Growth Funnel Analysis |  Growth Hooked Model |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | When effort needs to be thought of as real working time, it offers a simple common denominator for comparison. It sorts work by value, risk, and delivery ability. The result is captured as Ideal Day Estimates, Assumption Notes, and Capacity Caveats. | 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. | The Hooked Model helps clarify engagement loops, user behavior, and experiments. It makes repeat behavior measurable and captures the result as a hooked loop, trigger map, and reward design. | 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 | Low | Medium | Medium | High |
Timedifferent | 15-60 min | 1-3 h | Multiple workshops over several weeks | 1-4 Wochen |
Participantsdifferent | 2-9 | 1-5 | 2-8 | 1-6 |
Formatdifferent | Workshop + async | Async | Workshop + async | Async |
Outputdifferent | Ideal Day Estimates, Assumption Notes, Capacity Caveats | Funnel report, Drop-off analysis, Optimization hypotheses | Hooked loop, Trigger map, Reward design, Ethics check | Experiment results, Decision log, Learning summary |
Tagsno overlap | EstimationEffortAgile | AnalyticsConversionGrowth | GrowthBehaviorRetention | ExperimentsGrowthAnalyticsValidation |