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Criterion
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
Surveys method illustration showing its working structure
UX Research
Surveys
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 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 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 assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first.
Complexitydifferent
MediumHighMediumMedium
Timedifferent
1-3 h1-4 Wochen3-14 Tage45-60 min
Participantsdifferent
1-51-650+2-8
Formatdifferent
AsyncAsyncAsyncWorkshop + async
Outputdifferent
Funnel report, Drop-off analysis, Optimization hypothesesExperiment results, Decision log, Learning summarySurvey Results, Charts, Segment InsightsAssumption map, Test backlog, Risk ranking
Tagsno overlap
AnalyticsConversionGrowth
ExperimentsGrowthAnalyticsValidation
QuantitativeResearchValidation
AssumptionsRiskExperimentsValidation
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