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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
Paper illustration of shared options, independently placed voting dots, and a highlighted shortlist.
Facilitation
Dot Voting
Paper illustration for Smoke Test.
Product Discovery
Smoke Test
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 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 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
MediumHighLowLow
Timedifferent
1-3 h1-4 Wochen5-15 min1-5 Tage
Participantsdifferent
1-51-63-20Nutzertraffic
Formatdifferent
AsyncAsyncWorkshopAsync
Outputdifferent
Funnel report, Drop-off analysis, Optimization hypothesesExperiment results, Decision log, Learning summaryRanked list, Consensus signal, ShortlistInterest Metrics, Conversion Signal, Learning Note
Tagsno overlap
AnalyticsConversionGrowth
ExperimentsGrowthAnalyticsValidation
FacilitationVotingConsensusPrioritization
ValidationExperimentsDemandGrowth
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