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Criterion
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Surveys method illustration showing its working structure
UX Research
Surveys
Paper illustration of a decision table with criteria rows, weighted ratings, and a narrowly leading alternative.
Decision Making
Decision Matrix
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 a topic needs to be validated broadly and many people can answer the same question, surveys gather structured feedback in a scalable form. Answers become comparable and segmentable instead of remaining merely anecdotal.When several options collide with several criteria, comparison quickly becomes subjective. A Decision Matrix makes the trade-off visible and brings weighting, criteria, and options into a shared logic.When assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first.
Complexitydifferent
HighMediumMediumMedium
Timedifferent
1-4 Wochen3-14 Tage45-90 min45-60 min
Participantsdifferent
1-650+2-82-8
Formatdifferent
AsyncAsyncWorkshop + asyncWorkshop + async
Outputdifferent
Experiment results, Decision log, Learning summarySurvey Results, Charts, Segment InsightsDecision Matrix, Scoring Rationale, Selected OptionAssumption map, Test backlog, Risk ranking
Tagsno overlap
ExperimentsGrowthAnalyticsValidation
QuantitativeResearchValidation
DecisionCriteriaScoringTradeoffs
AssumptionsRiskExperimentsValidation
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