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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
Design Thinking as a learning loop: an observation notebook, a focused problem statement, different idea sketches, a cardboard prototype and user-test notes. Feedback leads to new understanding.
Innovation
Design Thinking
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.For complex user problems with an uncertain cause, the method connects observation, interpretation, and experiment into a learning cycle. It keeps the focus on real needs and avoids premature solution language. This produces robust decisions for product and service.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
LowHighHighLow
Timedifferent
Stunden bis wenige Tage1-4 Wochen1 Tag bis mehrere Wochen1-5 Tage
Participantsdifferent
1-41-64-10Nutzertraffic
Formatdifferent
Workshop + asyncAsyncWorkshopAsync
Outputdifferent
Pretotyping sketch, Test setup, Conversion data, Go or no-go decisionExperiment results, Decision log, Learning summaryProblem Statement, Prototype, Test LearningsInterest Metrics, Conversion Signal, Learning Note
Tagsno overlap
ValidationDemandMVP
ExperimentsGrowthAnalyticsValidation
InnovationPrototypeResearch
ValidationExperimentsDemandGrowth
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