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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
EventStorming on a long working surface: colored event cards form a business flow, friction points are marked, and a boundary separates different areas of responsibility.
Domain Modeling
EventStorming
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 a domain consists of many events, rules, and states, it creates a shared modeling space for the team. It bundles language, flows, and boundaries before domain knowledge fragments into siloed views.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 Wochen2-8 h1-5 Tage
Participantsdifferent
1-41-65-12Nutzertraffic
Formatdifferent
Workshop + asyncAsyncWorkshopAsync
Outputdifferent
Pretotyping sketch, Test setup, Conversion data, Go or no-go decisionExperiment results, Decision log, Learning summaryEvent Timeline, Ubiquitous Language, Boundaries, Open QuestionsClick Data, Interest Signal, Learning Decision
Tagsno overlap
ValidationDemandMVP
ExperimentsGrowthAnalyticsValidation
Domain-Driven DesignEventsDiscoveryWorkshop
ValidationExperimentsDemandDiscovery
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