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Criterion
Surveys method illustration showing its working structure
UX Research
Surveys
Paper illustration of shared options, independently placed voting dots, and a highlighted shortlist.
Facilitation
Dot Voting
Paper illustration of ICE Scoring with its method-specific working model.
Product Strategy
ICE Scoring
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 a workshop has produced too many options and the group needs to condense quickly, dot voting makes preferences visible in a short time. It bundles individual votes into a solid signal for the next selection.When ideas need sorting quickly, it condenses impact, confidence, and effort into one compact score. It connects customer value, product logic, and decision priorities. The result is captured as an ICE table and top-ideas list.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
MediumLowLowHigh
Timedifferent
3-14 Tage5-15 min30-60 min1-4 Wochen
Participantsdifferent
50+3-202-81-6
Formatdifferent
AsyncWorkshopWorkshop + asyncAsync
Outputdifferent
Survey Results, Charts, Segment InsightsRanked list, Consensus signal, ShortlistICE Table, Top Idea ListExperiment results, Decision log, Learning summary
Tagsno overlap
QuantitativeResearchValidation
FacilitationVotingConsensusPrioritization
PrioritizationScoringGrowthDecision
ExperimentsGrowthAnalyticsValidation
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