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Criterion
Funnel Analysis workspace showing the question, observations, and next decision.
Growth
Funnel Analysis
Paper illustration for Dot Estimation.
Facilitation
Dot Estimation
Paper illustration for Fake Door Test
Product Discovery
Fake Door Test
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
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 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 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 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.
Complexitydifferent
MediumLowMediumHigh
Timedifferent
1-3 h5-20 min1-5 Tage1-4 Wochen
Participantsdifferent
1-53-20Nutzertraffic1-6
Formatdifferent
AsyncWorkshopAsyncAsync
Outputdifferent
Funnel report, Drop-off analysis, Optimization hypothesesEffort Heatmap, Risk Signals, Discussion TargetsClick Data, Interest Signal, Learning DecisionExperiment results, Decision log, Learning summary
Tagsno overlap
AnalyticsConversionGrowth
EstimationEffortRisk
ValidationExperimentsDemandDiscovery
ExperimentsGrowthAnalyticsValidation
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