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Criterion
Paper illustration of Hooked Model with its method-specific working model.
Growth
Hooked Model
Paper illustration of Cost of Delay with its method-specific working model.
Delivery
Cost of Delay
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.Helps clarify scope, order, and delivery flow in concrete terms. It makes work, constraints, and sequence manageable. The result is captured as a Cost of Delay table and prioritization sequence.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
MediumHighLowHigh
Timedifferent
Multiple workshops over several weeks90-180 min30-60 min1-4 Wochen
Participantsdifferent
2-83-81-51-6
Formatdifferent
Workshop + asyncWorkshopWorkshop + asyncAsync
Outputdifferent
Hooked loop, Trigger map, Reward design, Ethics checkCoD Table, Prioritization SequenceCompleted Experiment Canvas, Success MetricExperiment results, Decision log, Learning summary
Tagsno overlap
GrowthBehaviorRetention
PrioritizationDeliveryEconomicsDecision
ExperimentsValidationDiscoveryHypothesis
ExperimentsGrowthAnalyticsValidation
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