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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 Riskiest Assumption Test with a method-specific labelled workspace.
Product Discovery
Riskiest Assumption Test
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 an idea hinges on one critical unknown, it prioritizes testing that exact piece of uncertainty first. It separates problem, assumption, solution, and evidence. The result is captured as a prioritized list of assumptions, a test plan, and a result report.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
LowHighMediumMedium
Timedifferent
Stunden bis wenige Tage1-4 Wochen1-2 Wochen pro Iteration1-5 Tage
Participantsdifferent
1-41-62-6Nutzertraffic
Formatdifferent
Workshop + asyncAsyncWorkshop + asyncAsync
Outputdifferent
Pretotyping sketch, Test setup, Conversion data, Go or no-go decisionExperiment results, Decision log, Learning summaryPrioritized Assumption List, Test Plan, Results ReportClick Data, Interest Signal, Learning Decision
Tags1 shared
ValidationDemandMVP
ExperimentsGrowthAnalyticsValidation
ExperimentsValidationDiscoveryAssumptions
ValidationExperimentsDemandDiscovery
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