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Criterion
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration of a participant using a prototype while an observer takes notes beside a highlighted usability issue.
UX Research
Usability 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
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 product is built but people get stuck on tasks, usability testing shows the friction at concrete points. Observed use instead of self-report makes visible where orientation, understanding, or interaction breaks down.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
HighMediumHighLow
Timedifferent
1-4 Wochen1-2 h je Session1 Tag bis mehrere Wochen1-5 Tage
Participantsdifferent
1-6Based on research question4-10Nutzertraffic
Formatdifferent
AsyncWorkshop + asyncWorkshopAsync
Outputdifferent
Experiment results, Decision log, Learning summaryUsability Issues, Severity List, RecommendationsProblem Statement, Prototype, Test LearningsInterest Metrics, Conversion Signal, Learning Note
Tagsno overlap
ExperimentsGrowthAnalyticsValidation
ValidationUXPrototype
InnovationPrototypeResearch
ValidationExperimentsDemandGrowth
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