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Criterion
Surveys method illustration showing its working structure
UX Research
Surveys
Funnel Analysis workspace showing the question, observations, and next decision.
Growth
Funnel Analysis
Paper illustration of a calm four-quadrant Assumption Map with hypothesis cards and emphasis on important assumptions with little evidence.
Product Discovery
Assumption Mapping
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Purposedifferent
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 many visitors or users drop off along the way, the reason behind the number often stays hidden. Funnel Analysis exposes these transitions and makes visible exactly where the path collapses.When assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first.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.
Complexitydifferent
MediumMediumMediumHigh
Timedifferent
3-14 Tage1-3 h45-60 min1-4 Wochen
Participantsdifferent
50+1-52-81-6
Formatdifferent
AsyncAsyncWorkshop + asyncAsync
Outputdifferent
Survey Results, Charts, Segment InsightsFunnel report, Drop-off analysis, Optimization hypothesesAssumption map, Test backlog, Risk rankingExperiment results, Decision log, Learning summary
Tagsno overlap
QuantitativeResearchValidation
AnalyticsConversionGrowth
AssumptionsRiskExperimentsValidation
ExperimentsGrowthAnalyticsValidation
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