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Criterion
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 showing three sorted card stacks and an open question about a possible group.
UX Research
Card Sorting
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 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 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.
Complexitydifferent
HighLowLow
Timedifferent
1-4 Wochen1-5 Tage20-45 min
Participantsdifferent
1-6NutzertrafficBased on research question
Formatdifferent
AsyncAsyncWorkshop + async
Outputdifferent
Experiment results, Decision log, Learning summaryInterest Metrics, Conversion Signal, Learning NoteContent groups, Label set, IA hypotheses
Tagsno overlap
ExperimentsGrowthAnalyticsValidation
ValidationExperimentsDemandGrowth
Information architectureNavigationStructure
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Often compared together

Methods with strong topical overlap with the current selection, not yet in the comparison.

Paper illustration for Fake Door Test
Product Discovery
Fake Door Test
Paper illustration of a calm four-quadrant Assumption Map with hypothesis cards and emphasis on important assumptions with little evidence.
Product Discovery
Assumption Mapping
Paper illustration of Experiment Canvas with a method-specific labelled workspace.
Product Discovery
Experiment Canvas
First-click Testing method illustration showing its working structure
UX Research
First-click Testing