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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 of an assumption matrix with prioritized test cards
Decision Making
Assumption Surfacing
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.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.Plans often contain assumptions that were never openly stated and remain dangerous precisely because of that. Assumption Surfacing makes these silent premises visible and prioritizes which of them carry the initiative or could sink it.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
HighMediumLowMedium
Timedifferent
1-4 Wochen1-2 h Setup, laufend45-90 min1-5 Tage
Participantsdifferent
1-62-82-8Nutzertraffic
Formatdifferent
AsyncWorkshop + asyncWorkshop + asyncAsync
Outputdifferent
Experiment results, Decision log, Learning summaryAARRR funnel, Metric baseline, Experiment backlogAssumption List, Critical Assumptions, Learning PlanClick Data, Interest Signal, Learning Decision
Tagsno overlap
ExperimentsGrowthAnalyticsValidation
GrowthMetricsExperiments
AssumptionsRiskDecisionDiscovery
ValidationExperimentsDemandDiscovery
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