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Criterion
Anonymous individual judgments pass through feedback loops to form a distribution.
Decision Making
Delphi Method
Paper illustration for Smoke Test.
Product Discovery
Smoke Test
Paper illustration of MVP Test Matrix with a method-specific labelled workspace.
Product Discovery
MVP Test Matrix
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.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 several minimal variants compete to answer the same question, it makes comparing and choosing between them cleaner. It separates problem, assumption, solution, and evidence. The result is captured as a Test Matrix and a Test Plan.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
HighLowMediumHigh
Timedifferent
1-4 Wochen1-5 Tage45-75 min1-4 Wochen
Participantsdifferent
6-30 ExpertenNutzertraffic2-81-6
Formatdifferent
AsyncAsyncWorkshopAsync
Outputdifferent
Expert Forecast, Consensus Range, Assumption NotesInterest Metrics, Conversion Signal, Learning NoteTest Matrix, Test PlanExperiment results, Decision log, Learning summary
Tagsno overlap
ForecastingExpertsDecisionStrategy
ValidationExperimentsDemandGrowth
ExperimentsValidationDiscoveryOptions
ExperimentsGrowthAnalyticsValidation
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