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Criterion
Anonymous individual judgments pass through feedback loops to form a distribution.
Decision Making
Delphi Method
Growth Experiment workspace showing the question, observations, and next decision.
Growth
Growth Experiment
Paper illustration of a Test Card with four fields for hypothesis, test, metric, and success threshold.
Product Discovery
Test Card
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 growth ideas surface quickly, the temptation to build immediately instead of learning is high. A Growth Experiment frames an assumption so target group, lever, and measurement are clear before the first deployment.The Test Card turns a critical assumption into a testable claim and specifies in advance which result counts as success.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 Wochen20-35 min1-4 Wochen
Participantsdifferent
6-30 Experten1-61-51-6
Formatdifferent
AsyncWorkshop + asyncWorkshop + asyncAsync
Outputdifferent
Expert Forecast, Consensus Range, Assumption NotesExperiment card, Result summary, Next betTest Card with a pre-set thresholdExperiment results, Decision log, Learning summary
Tagsno overlap
ForecastingExpertsDecisionStrategy
MarketingGrowthExperimentsLearning
ExperimentsValidationDiscoveryHypothesis
ExperimentsGrowthAnalyticsValidation
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