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Criterion
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
A paper-based illustration representing Pirate Metrics (AARRR) with its core stages and visible working result.
Growth
Pirate Metrics AARRR
Paper illustration for Fake Door Test
Product Discovery
Fake Door Test
Paper illustration for Smoke Test.
Product Discovery
Smoke 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.For products with complex usage paths, overall growth alone is too coarse to reveal bottlenecks. Pirate Metrics breaks the relationship with the product into consecutive stages and shows where the funnel actually leaks.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 demand only needs to be roughly verified, it tests interest with minimal effort. It measures whether people would take a next step at all.
Complexitydifferent
HighMediumMediumLow
Timedifferent
1-4 Wochen1-2 h Setup, laufend1-5 Tage1-5 Tage
Participantsdifferent
1-62-8NutzertrafficNutzertraffic
Formatdifferent
AsyncWorkshop + asyncAsyncAsync
Outputdifferent
Experiment results, Decision log, Learning summaryAARRR funnel, Metric baseline, Experiment backlogClick Data, Interest Signal, Learning DecisionInterest Metrics, Conversion Signal, Learning Note
Tags1 shared
ExperimentsGrowthAnalyticsValidation
GrowthMetricsExperiments
ValidationExperimentsDemandDiscovery
ValidationExperimentsDemandGrowth
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