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| Criterion |  Agile Ideal Days |  Growth Flywheel |  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. | Growth often breaks down where a reinforcing mechanism builds up too much friction. A Flywheel shows the cycle of value, repetition, and reinforcement meant to sustain growth. | 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 | High |
Timedifferent | 15-60 min | 60-120 min | 1-4 Wochen |
Participantsdifferent | 2-9 | 3-8 | 1-6 |
Formatdifferent | Workshop + async | Workshop | Async |
Outputdifferent | Ideal Day Estimates, Assumption Notes, Capacity Caveats | Flywheel Map, Friction Points, Growth Levers, Experiment Backlog | Experiment results, Decision log, Learning summary |
Tagsno overlap | EstimationEffortAgile | GrowthRetentionConversion | ExperimentsGrowthAnalyticsValidation |
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