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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 of Experiment Canvas with a method-specific labelled workspace.
Product Discovery
Experiment Canvas
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.When experiments become unreadable after the fact, it arranges hypothesis, signal, and learning goal on a single canvas. It separates problem, assumption, solution, and evidence. The result is captured as a Completed Experiment Canvas and a Success Metric.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
MediumMediumLowHigh
Timedifferent
Multiple workshops over several weeks1-2 Wochen30-60 min1-4 Wochen
Participantsdifferent
2-81-61-51-6
Formatdifferent
Workshop + asyncWorkshop + asyncWorkshop + asyncAsync
Outputdifferent
Hooked loop, Trigger map, Reward design, Ethics checkExperiment card, Result summary, Next betCompleted Experiment Canvas, Success MetricExperiment results, Decision log, Learning summary
Tagsno overlap
GrowthBehaviorRetention
MarketingGrowthExperimentsLearning
ExperimentsValidationDiscoveryHypothesis
ExperimentsGrowthAnalyticsValidation
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