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Criterion
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration for Flywheel.
Growth
Flywheel
Paper illustration for Fake Door Test
Product Discovery
Fake Door Test
Purposedifferent
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.Growth often breaks down where a reinforcing mechanism builds up too much friction. A Flywheel shows the cycle of value, repetition, and reinforcement meant to sustain growth.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
HighMediumMedium
Timedifferent
1-4 Wochen60-120 min1-5 Tage
Participantsdifferent
1-63-8Nutzertraffic
Formatdifferent
AsyncWorkshopAsync
Outputdifferent
Experiment results, Decision log, Learning summaryFlywheel Map, Friction Points, Growth Levers, Experiment BacklogClick Data, Interest Signal, Learning Decision
Tagsno overlap
ExperimentsGrowthAnalyticsValidation
GrowthRetentionConversion
ValidationExperimentsDemandDiscovery
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Methods with strong topical overlap with the current selection, not yet in the comparison.

Paper illustration for Smoke Test.
Product Discovery
Smoke Test
Paper illustration of Experiment Canvas with a method-specific labelled workspace.
Product Discovery
Experiment Canvas
Funnel Analysis workspace showing the question, observations, and next decision.
Growth
Funnel Analysis
Paper illustration of a Learning Card with four fields for hypothesis, observation, insight, and action.
Product Discovery
Learning Card