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Criterion
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration of Pretotyping with its method-specific working model.
Product Discovery
Pretotyping
Paper illustration for Fake Door Test
Product Discovery
Fake Door Test
Paper illustration for Smoke Test.
Product Discovery
Smoke Test
Purposedifferent
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.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 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.When demand only needs to be roughly verified, it tests interest with minimal effort. It measures whether people would take a next step at all.
Complexitydifferent
HighLowMediumLow
Timedifferent
1-4 WochenStunden bis wenige Tage1-5 Tage1-5 Tage
Participantsdifferent
1-61-4NutzertrafficNutzertraffic
Formatdifferent
AsyncWorkshop + asyncAsyncAsync
Outputdifferent
Experiment results, Decision log, Learning summaryPretotyping sketch, Test setup, Conversion data, Go or no-go decisionClick Data, Interest Signal, Learning DecisionInterest Metrics, Conversion Signal, Learning Note
Tags1 shared
ExperimentsGrowthAnalyticsValidation
ValidationDemandMVP
ValidationExperimentsDemandDiscovery
ValidationExperimentsDemandGrowth
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