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