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Criterion
Paper illustration showing three sorted card stacks and an open question about a possible group.
UX Research
Card Sorting
Paper illustration for PDCA Cycle.
Operations
PDCA Cycle
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration for Smoke Test.
Product Discovery
Smoke Test
Purposedifferent
When content only makes sense internally and users can't find the structure again, card sorting exposes their mental order. Terms, groups, and naming are then aligned with the target group's expectations.For an improvement that still has to prove itself in everyday work, the method runs it through small learning loops. It connects planning, checking, and standardization into a repeatable learning mode.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.
Complexitydifferent
LowLowHighLow
Timedifferent
20-45 min1 h bis mehrere Wochen1-4 Wochen1-5 Tage
Participantsdifferent
Based on research question1-81-6Nutzertraffic
Formatdifferent
Workshop + asyncWorkshop + asyncAsyncAsync
Outputdifferent
Content groups, Label set, IA hypothesesPDCA Log, Experiment Plan, Learning Outcome, Standard ChangeExperiment results, Decision log, Learning summaryInterest Metrics, Conversion Signal, Learning Note
Tagsno overlap
Information architectureNavigationStructure
Continuous improvementLeanExperiments
ExperimentsGrowthAnalyticsValidation
ValidationExperimentsDemandGrowth
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