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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
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration for Smoke Test.
Product Discovery
Smoke Test
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 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.
Complexitydifferent
MediumMediumHighLow
Timedifferent
3-14 Tage1-3 h1-4 Wochen1-5 Tage
Participantsdifferent
50+1-51-6Nutzertraffic
Formatsame
AsyncAsyncAsyncAsync
Outputdifferent
Survey Results, Charts, Segment InsightsFunnel report, Drop-off analysis, Optimization hypothesesExperiment results, Decision log, Learning summaryInterest Metrics, Conversion Signal, Learning Note
Tagsno overlap
QuantitativeResearchValidation
AnalyticsConversionGrowth
ExperimentsGrowthAnalyticsValidation
ValidationExperimentsDemandGrowth
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