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Criterion
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
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration for Smoke Test.
Product Discovery
Smoke Test
Paper illustration of Experiment Canvas with a method-specific labelled workspace.
Product Discovery
Experiment Canvas
Purposedifferent
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 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 demand only needs to be roughly verified, it tests interest with minimal effort. It measures whether people would take a next step at all.When experiments become unreadable after the fact, it arranges hypothesis, signal, and learning goal on a single canvas. It separates problem, assumption, solution, and evidence. The result is captured as a Completed Experiment Canvas and a Success Metric.
Complexitydifferent
HighHighLowLow
Timedifferent
1 Tag bis mehrere Wochen1-4 Wochen1-5 Tage30-60 min
Participantsdifferent
4-101-6Nutzertraffic1-5
Formatdifferent
WorkshopAsyncAsyncWorkshop + async
Outputdifferent
Problem Statement, Prototype, Test LearningsExperiment results, Decision log, Learning summaryInterest Metrics, Conversion Signal, Learning NoteCompleted Experiment Canvas, Success Metric
Tagsno overlap
InnovationPrototypeResearch
ExperimentsGrowthAnalyticsValidation
ValidationExperimentsDemandGrowth
ExperimentsValidationDiscoveryHypothesis
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