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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 of Experiment Canvas with a method-specific labelled workspace.
Product Discovery
Experiment Canvas
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 experiments become unreadable after the fact, it arranges hypothesis, signal, and learning goal on a single canvas. It separates problem, assumption, solution, and evidence. The result is captured as a Completed Experiment Canvas and a Success Metric.
Complexitydifferent
LowHighMediumLow
Timedifferent
5-20 min1-4 Wochen60-90 min30-60 min
Participantsdifferent
3-201-63-81-5
Formatdifferent
WorkshopAsyncWorkshopWorkshop + async
Outputdifferent
Effort Heatmap, Risk Signals, Discussion TargetsExperiment results, Decision log, Learning summaryPrioritization Canvas, Hypothesis BacklogCompleted Experiment Canvas, Success Metric
Tagsno overlap
EstimationEffortRisk
ExperimentsGrowthAnalyticsValidation
ExperimentsPrioritizationDiscoveryHypothesis
ExperimentsValidationDiscoveryHypothesis
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