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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 Smoke Test.
Product Discovery
Smoke 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 only needs to be roughly verified, it tests interest with minimal effort. It measures whether people would take a next step at all.
Complexitydifferent
LowHighMediumLow
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 QuestionsInterest Metrics, Conversion Signal, Learning Note
Tagsno overlap
ValidationDemandMVP
ExperimentsGrowthAnalyticsValidation
Domain-Driven DesignEventsDiscoveryWorkshop
ValidationExperimentsDemandGrowth
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