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Criterion
Anonymous individual judgments pass through feedback loops to form a distribution.
Decision Making
Delphi Method
A paper-based illustration representing Pirate Metrics (AARRR) with its core stages and visible working result.
Growth
Pirate Metrics AARRR
Paper illustration for Smoke Test.
Product Discovery
Smoke Test
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Purposedifferent
When knowledge is distributed and direct dominance should be avoided, groups quickly fall under the sway of their opinion leaders. The Delphi Method gathers assessments iteratively and gradually brings expert judgments closer together.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 only needs to be roughly verified, it tests interest with minimal effort. It measures whether people would take a next step at all.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
HighMediumLowHigh
Timedifferent
1-4 Wochen1-2 h Setup, laufend1-5 Tage1-4 Wochen
Participantsdifferent
6-30 Experten2-8Nutzertraffic1-6
Formatdifferent
AsyncWorkshop + asyncAsyncAsync
Outputdifferent
Expert Forecast, Consensus Range, Assumption NotesAARRR funnel, Metric baseline, Experiment backlogInterest Metrics, Conversion Signal, Learning NoteExperiment results, Decision log, Learning summary
Tagsno overlap
ForecastingExpertsDecisionStrategy
GrowthMetricsExperiments
ValidationExperimentsDemandGrowth
ExperimentsGrowthAnalyticsValidation
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