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Criterion
Growth Experiment workspace showing the question, observations, and next decision.
Growth
Growth Experiment
Paper illustration for Flywheel.
Growth
Flywheel
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
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 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
1-2 Wochen60-120 min30-60 min1-4 Wochen
Participantsdifferent
1-63-81-51-6
Formatdifferent
Workshop + asyncWorkshopWorkshop + asyncAsync
Outputdifferent
Experiment card, Result summary, Next betFlywheel Map, Friction Points, Growth Levers, Experiment BacklogCompleted Experiment Canvas, Success MetricExperiment results, Decision log, Learning summary
Tagsno overlap
MarketingGrowthExperimentsLearning
GrowthRetentionConversion
ExperimentsValidationDiscoveryHypothesis
ExperimentsGrowthAnalyticsValidation
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