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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
Paper illustration of a branching category tree with a highlighted search path and possible dead ends.
UX Research
Tree 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.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 a navigation exists but search paths still fail, tree testing checks findability without visual distraction. The method shows whether labels, levels, and paths really lead to the intended destination.
Complexitydifferent
LowHighMedium
Timedifferent
1-2 h1-4 Wochen1-2 Tage
Participantsdifferent
2-86-30 ExpertenBased on research question
Formatdifferent
Workshop + asyncAsyncAsync
Outputdifferent
DIBB document, Belief list, Bet list, Learning reportExpert Forecast, Consensus Range, Assumption NotesFindability Metrics, Path Analysis, Revised IA
Tagsno overlap
StrategyDecisionAssumptionsHypothesis
ForecastingExpertsDecisionStrategy
Information architectureNavigationFindability
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Paper illustration of an assumption matrix with prioritized test cards
Decision Making
Assumption Surfacing
Paper illustration showing three sorted card stacks and an open question about a possible group.
UX Research
Card Sorting
First-click Testing method illustration showing its working structure
UX Research
First-click Testing
Paper illustration of the Force Field Analysis working structure.
Decision Making
Force Field Analysis