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Criterion
Paper illustration for Dot Estimation.
Facilitation
Dot Estimation
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration of Hypothesis Prioritization Canvas with a method-specific labelled workspace.
Product Discovery
Hypothesis Prioritization Canvas
Paper illustration for Fake Door Test
Product Discovery
Fake Door Test
Purposedifferent
When size or effort can only be estimated roughly, Dot Estimation condenses the group's experience into a quick range. It turns individual contributions into a visible selection. The result is captured as an Effort Heatmap, Risk Signals, and Discussion Targets.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 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.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.
Complexitydifferent
LowHighMediumMedium
Timedifferent
5-20 min1-4 Wochen60-90 min1-5 Tage
Participantsdifferent
3-201-63-8Nutzertraffic
Formatdifferent
WorkshopAsyncWorkshopAsync
Outputdifferent
Effort Heatmap, Risk Signals, Discussion TargetsExperiment results, Decision log, Learning summaryPrioritization Canvas, Hypothesis BacklogClick Data, Interest Signal, Learning Decision
Tagsno overlap
EstimationEffortRisk
ExperimentsGrowthAnalyticsValidation
ExperimentsPrioritizationDiscoveryHypothesis
ValidationExperimentsDemandDiscovery
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