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Criterion
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration showing three sorted card stacks and an open question about a possible group.
UX Research
Card Sorting
A paper-based illustration representing Design Sprint with its core stages and visible working result.
Innovation
Design Sprint
Paper illustration of a calm four-quadrant Assumption Map with hypothesis cards and emphasis on important assumptions with little evidence.
Product Discovery
Assumption Mapping
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 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 the product question is unclear and time pressure is high, the method takes a team from an open idea to a testable solution. It connects problem understanding, decision, and learning in one compact format, lowering the risk of spending a lot of energy on a mere guess.When assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first.
Complexitydifferent
HighLowHighMedium
Timedifferent
1-4 Wochen20-45 min4-5 Tage45-60 min
Participantsdifferent
1-6Based on research question5-82-8
Formatdifferent
AsyncWorkshop + asyncWorkshopWorkshop + async
Outputdifferent
Experiment results, Decision log, Learning summaryContent groups, Label set, IA hypothesesPrototype, Test Findings, Decision RationaleAssumption map, Test backlog, Risk ranking
Tagsno overlap
ExperimentsGrowthAnalyticsValidation
Information architectureNavigationStructure
Design sprintPrototypeValidationInnovation
AssumptionsRiskExperimentsValidation
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