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Criterion
Paper illustration of Hooked Model with its method-specific working model.
Growth
Hooked Model
Growth Experiment workspace showing the question, observations, and next decision.
Growth
Growth Experiment
Paper illustration for Flywheel.
Growth
Flywheel
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Purposedifferent
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 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.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
MediumMediumMediumHigh
Timedifferent
Multiple workshops over several weeks1-2 Wochen60-120 min1-4 Wochen
Participantsdifferent
2-81-63-81-6
Formatdifferent
Workshop + asyncWorkshop + asyncWorkshopAsync
Outputdifferent
Hooked loop, Trigger map, Reward design, Ethics checkExperiment card, Result summary, Next betFlywheel Map, Friction Points, Growth Levers, Experiment BacklogExperiment results, Decision log, Learning summary
Tags1 shared
GrowthBehaviorRetention
MarketingGrowthExperimentsLearning
GrowthRetentionConversion
ExperimentsGrowthAnalyticsValidation
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