methodatlas
Compare

View methods side by side.

Choose up to four methods. Add them using the search and share the comparison by copying its link.

Criterion
Paper illustration of DIBB with its method-specific working model.
Product Strategy
DIBB
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 Smoke Test.
Product Discovery
Smoke Test
Purposedifferent
DIBB helps clarify target groups, value, goals, and priorities by making the logic behind a decision explicit. It captures results as a DIBB document, belief list, bet list, and learning report.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 demand only needs to be roughly verified, it tests interest with minimal effort. It measures whether people would take a next step at all.
Complexitydifferent
LowHighHighLow
Timedifferent
1-2 h1-4 Wochen1-4 Wochen1-5 Tage
Participantsdifferent
2-86-30 Experten1-6Nutzertraffic
Formatdifferent
Workshop + asyncAsyncAsyncAsync
Outputdifferent
DIBB document, Belief list, Bet list, Learning reportExpert Forecast, Consensus Range, Assumption NotesExperiment results, Decision log, Learning summaryInterest Metrics, Conversion Signal, Learning Note
Tagsno overlap
StrategyDecisionAssumptionsHypothesis
ForecastingExpertsDecisionStrategy
ExperimentsGrowthAnalyticsValidation
ValidationExperimentsDemandGrowth
Add more methods