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Criterion
Paper illustration of shared options, independently placed voting dots, and a highlighted shortlist.
Facilitation
Dot Voting
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration for Fake Door Test
Product Discovery
Fake Door Test
Paper illustration of Hypothesis Prioritization Canvas with a method-specific labelled workspace.
Product Discovery
Hypothesis Prioritization Canvas
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 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 is still unclear, it measures interest in a feature before it is built. It separates real behavior from polite agreement and deliberately keeps build effort small.When many hypotheses compete for attention, it brings order to their learning sequence and importance. It separates problem, assumption, solution, and evidence. The result is captured as a prioritization canvas and a hypothesis backlog.
Complexitydifferent
LowHighMediumMedium
Timedifferent
5-15 min1-4 Wochen1-5 Tage60-90 min
Participantsdifferent
3-201-6Nutzertraffic3-8
Formatdifferent
WorkshopAsyncAsyncWorkshop
Outputdifferent
Ranked list, Consensus signal, ShortlistExperiment results, Decision log, Learning summaryClick Data, Interest Signal, Learning DecisionPrioritization Canvas, Hypothesis Backlog
Tagsno overlap
FacilitationVotingConsensusPrioritization
ExperimentsGrowthAnalyticsValidation
ValidationExperimentsDemandDiscovery
ExperimentsPrioritizationDiscoveryHypothesis
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