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Criterion
Paper illustration of DIBB with its method-specific working model.
Product Strategy
DIBB
Paper illustration for Flywheel.
Growth
Flywheel
Funnel Analysis workspace showing the question, observations, and next decision.
Growth
Funnel Analysis
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
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.Growth often breaks down where a reinforcing mechanism builds up too much friction. A Flywheel shows the cycle of value, repetition, and reinforcement meant to sustain growth.When many visitors or users drop off along the way, the reason behind the number often stays hidden. Funnel Analysis exposes these transitions and makes visible exactly where the path collapses.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
LowMediumMediumHigh
Timedifferent
1-2 h60-120 min1-3 h1-4 Wochen
Participantsdifferent
2-83-81-51-6
Formatdifferent
Workshop + asyncWorkshopAsyncAsync
Outputdifferent
DIBB document, Belief list, Bet list, Learning reportFlywheel Map, Friction Points, Growth Levers, Experiment BacklogFunnel report, Drop-off analysis, Optimization hypothesesExperiment results, Decision log, Learning summary
Tagsno overlap
StrategyDecisionAssumptionsHypothesis
GrowthRetentionConversion
AnalyticsConversionGrowth
ExperimentsGrowthAnalyticsValidation
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