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Criterion
Paper illustration of Pretotyping with its method-specific working model.
Product Discovery
Pretotyping
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
Pretotyping clarifies whether a customer problem and solution idea create enough real demand. It separates problem, assumption, solution, and evidence, and captures the result as a pretotyping sketch, test setup, and conversion data.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
LowMediumLowHigh
Timedifferent
Stunden bis wenige Tage60-120 min30-60 min1-4 Wochen
Participantsdifferent
1-43-81-51-6
Formatdifferent
Workshop + asyncWorkshopWorkshop + asyncAsync
Outputdifferent
Pretotyping sketch, Test setup, Conversion data, Go or no-go decisionFlywheel Map, Friction Points, Growth Levers, Experiment BacklogCompleted Experiment Canvas, Success MetricExperiment results, Decision log, Learning summary
Tagsno overlap
ValidationDemandMVP
GrowthRetentionConversion
ExperimentsValidationDiscoveryHypothesis
ExperimentsGrowthAnalyticsValidation
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