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Criterion
Anonymous individual judgments pass through feedback loops to form a distribution.
Decision Making
Delphi Method
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration for Concierge MVP
Product Discovery
Concierge MVP
Paper illustration of MVP Test Matrix with a method-specific labelled workspace.
Product Discovery
MVP Test Matrix
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 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.When an idea can first fail or grow through genuine hands-on support, it relies on manual work instead of automation. It shows whether user value holds up even under manual execution.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.
Complexitydifferent
HighHighMediumMedium
Timedifferent
1-4 Wochen1-4 Wochen1-4 Wochen45-75 min
Participantsdifferent
6-30 Experten1-63-10 Kunden2-8
Formatdifferent
AsyncAsyncWorkshop + asyncWorkshop
Outputdifferent
Expert Forecast, Consensus Range, Assumption NotesExperiment results, Decision log, Learning summaryConcierge Learnings, Service Blueprint, MVP RisksTest Matrix, Test Plan
Tagsno overlap
ForecastingExpertsDecisionStrategy
ExperimentsGrowthAnalyticsValidation
MVPValidationServiceDiscovery
ExperimentsValidationDiscoveryOptions
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