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| Criterion |  Growth Flywheel |  Operations PDCA Cycle |  Growth Growth Experiment |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | 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. | For an improvement that still has to prove itself in everyday work, the method runs it through small learning loops. It connects planning, checking, and standardization into a repeatable learning mode. | When growth ideas surface quickly, the temptation to build immediately instead of learning is high. A Growth Experiment frames an assumption so target group, lever, and measurement are clear before the first deployment. | 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 | 60-120 min | 1 h bis mehrere Wochen | 1-2 Wochen | 1-4 Wochen |
Participantsdifferent | 3-8 | 1-8 | 1-6 | 1-6 |
Formatdifferent | Workshop | Workshop + async | Workshop + async | Async |
Outputdifferent | Flywheel Map, Friction Points, Growth Levers, Experiment Backlog | PDCA Log, Experiment Plan, Learning Outcome, Standard Change | Experiment card, Result summary, Next bet | Experiment results, Decision log, Learning summary |
Tagsno overlap | GrowthRetentionConversion | Continuous improvementLeanExperiments | MarketingGrowthExperimentsLearning | ExperimentsGrowthAnalyticsValidation |