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Criterion
Paper illustration of two people facing each other, speech bubbles and an open interview notebook.
UX Research
User Interviews
Decision Tree method illustration showing its working structure
Decision Making
Decision Tree
Anonymous individual judgments pass through feedback loops to form a distribution.
Decision Making
Delphi Method
Paper illustration of DIBB with its method-specific working model.
Product Strategy
DIBB
Purposedifferent
When teams derive needs only from assumptions and real motives are missing, user interviews give direct access to behavior and meaning. Conversations from the target group's everyday life make patterns, tensions, and open questions solidly visible.For decisions with follow-on paths and dependencies, a linear comparison is often not enough. A Decision Tree shows how options branch under conditions and which consequences hang on each branch.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.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.
Complexitydifferent
LowMediumHighLow
Timedifferent
30–60 min per interview30-90 min1-4 Wochen1-2 h
Participantsdifferent
1 participant per interview1-66-30 Experten2-8
Formatdifferent
Workshop + asyncWorkshop + asyncAsyncWorkshop + async
Outputdifferent
Interview Notes, Themes, Insight SummaryDecision Tree, Option Map, Assumption ListExpert Forecast, Consensus Range, Assumption NotesDIBB document, Belief list, Bet list, Learning report
Tagsno overlap
QualitativeResearchCustomerDiscovery
DecisionTreeOptions
ForecastingExpertsDecisionStrategy
StrategyDecisionAssumptionsHypothesis
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