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Criterion
Paper illustration of Pretotyping with its method-specific working model.
Product Discovery
Pretotyping
Growth Experiment workspace showing the question, observations, and next decision.
Growth
Growth Experiment
Paper illustration for Fake Door Test
Product Discovery
Fake Door Test
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.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.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 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
LowMediumMediumHigh
Timedifferent
Stunden bis wenige Tage1-2 Wochen1-5 Tage1-4 Wochen
Participantsdifferent
1-41-6Nutzertraffic1-6
Formatdifferent
Workshop + asyncWorkshop + asyncAsyncAsync
Outputdifferent
Pretotyping sketch, Test setup, Conversion data, Go or no-go decisionExperiment card, Result summary, Next betClick Data, Interest Signal, Learning DecisionExperiment results, Decision log, Learning summary
Tagsno overlap
ValidationDemandMVP
MarketingGrowthExperimentsLearning
ValidationExperimentsDemandDiscovery
ExperimentsGrowthAnalyticsValidation
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