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Criterion
Paper illustration for Flywheel.
Growth
Flywheel
Paper illustration of Hooked Model with its method-specific working model.
Growth
Hooked Model
Paper illustration of Hypothesis Prioritization Canvas with a method-specific labelled workspace.
Product Discovery
Hypothesis Prioritization Canvas
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Purposedifferent
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 many hypotheses compete for attention, it brings order to their learning sequence and importance. It separates problem, assumption, solution, and evidence. The result is captured as a prioritization canvas and a hypothesis backlog.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
60-120 minMultiple workshops over several weeks60-90 min1-4 Wochen
Participantsdifferent
3-82-83-81-6
Formatdifferent
WorkshopWorkshop + asyncWorkshopAsync
Outputdifferent
Flywheel Map, Friction Points, Growth Levers, Experiment BacklogHooked loop, Trigger map, Reward design, Ethics checkPrioritization Canvas, Hypothesis BacklogExperiment results, Decision log, Learning summary
Tagsno overlap
GrowthRetentionConversion
GrowthBehaviorRetention
ExperimentsPrioritizationDiscoveryHypothesis
ExperimentsGrowthAnalyticsValidation
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