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Criterion
Paper illustration of shared options, independently placed voting dots, and a highlighted shortlist.
Facilitation
Dot Voting
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 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 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
LowMediumHighLow
Timedifferent
5-15 min1-3 h1-4 Wochen1-5 Tage
Participantsdifferent
3-201-51-6Nutzertraffic
Formatdifferent
WorkshopAsyncAsyncAsync
Outputdifferent
Ranked list, Consensus signal, ShortlistFunnel report, Drop-off analysis, Optimization hypothesesExperiment results, Decision log, Learning summaryInterest Metrics, Conversion Signal, Learning Note
Tagsno overlap
FacilitationVotingConsensusPrioritization
AnalyticsConversionGrowth
ExperimentsGrowthAnalyticsValidation
ValidationExperimentsDemandGrowth
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