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| Criterion |  Growth Growth Experiment |  Growth Flywheel |  Growth Hooked Model |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | 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. | 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. | 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 | Medium | Medium | Medium | High |
Timedifferent | 1-2 Wochen | 60-120 min | Multiple workshops over several weeks | 1-4 Wochen |
Participantsdifferent | 1-6 | 3-8 | 2-8 | 1-6 |
Formatdifferent | Workshop + async | Workshop | Workshop + async | Async |
Outputdifferent | Experiment card, Result summary, Next bet | Flywheel Map, Friction Points, Growth Levers, Experiment Backlog | Hooked loop, Trigger map, Reward design, Ethics check | Experiment results, Decision log, Learning summary |
Tags1 shared | MarketingGrowthExperimentsLearning | GrowthRetentionConversion | GrowthBehaviorRetention | ExperimentsGrowthAnalyticsValidation |