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Criterion
Paper illustration of Pretotyping with its method-specific working model.
Product Discovery
Pretotyping
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration of Experiment Canvas with a method-specific labelled workspace.
Product Discovery
Experiment Canvas
Paper illustration for Fake Door Test
Product Discovery
Fake Door Test
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.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.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 demand is still unclear, it measures interest in a feature before it is built. It separates real behavior from polite agreement and deliberately keeps build effort small.
Complexitydifferent
LowHighLowMedium
Timedifferent
Stunden bis wenige Tage1-4 Wochen30-60 min1-5 Tage
Participantsdifferent
1-41-61-5Nutzertraffic
Formatdifferent
Workshop + asyncAsyncWorkshop + asyncAsync
Outputdifferent
Pretotyping sketch, Test setup, Conversion data, Go or no-go decisionExperiment results, Decision log, Learning summaryCompleted Experiment Canvas, Success MetricClick Data, Interest Signal, Learning Decision
Tags1 shared
ValidationDemandMVP
ExperimentsGrowthAnalyticsValidation
ExperimentsValidationDiscoveryHypothesis
ValidationExperimentsDemandDiscovery
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