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Criterion
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Design sheets and interface cards connect to jointly written pseudocode with highlighted unresolved questions.
Architecture
ARID (Active Reviews for Intermediate Designs)
Paper illustration showing three sorted card stacks and an open question about a possible group.
UX Research
Card Sorting
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.ARID examines how well developers can work with a technical design. It focuses on a part of the system that can still be revised, between the architecture overview and the detailed specification.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.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
HighMediumLowLow
Timedifferent
1-4 Wochen2–4 h review as a planning range; preparation and evaluation additional20-45 min1-5 Tage
Participantsdifferent
1-6Designers, developers as users, and facilitationBased on research questionNutzertraffic
Formatdifferent
AsyncWorkshop + asyncWorkshop + asyncAsync
Outputdifferent
Experiment results, Decision log, Learning summaryPrioritized development tasks, Jointly produced code or pseudocode, Observed difficulties and open design questions, Proposed design revisionsContent groups, Label set, IA hypothesesInterest Metrics, Conversion Signal, Learning Note
Tagsno overlap
ExperimentsGrowthAnalyticsValidation
ArchitectureEngineeringFeedbackValidationTasks
Information architectureNavigationStructure
ValidationExperimentsDemandGrowth
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