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Criterion
Paper illustration showing three sorted card stacks and an open question about a possible group.
UX Research
Card Sorting
Paper illustration of a branching category tree with a highlighted search path and possible dead ends.
UX Research
Tree Testing
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 content only makes sense internally and users can't find the structure again, card sorting exposes their mental order. Terms, groups, and naming are then aligned with the target group's expectations.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.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
20-45 min1-2 Tage1-4 Wochen1-2 h
Participantsdifferent
Based on research questionBased on research question6-30 Experten2-8
Formatdifferent
Workshop + asyncAsyncAsyncWorkshop + async
Outputdifferent
Content groups, Label set, IA hypothesesFindability Metrics, Path Analysis, Revised IAExpert Forecast, Consensus Range, Assumption NotesDIBB document, Belief list, Bet list, Learning report
Tagsno overlap
Information architectureNavigationStructure
Information architectureNavigationFindability
ForecastingExpertsDecisionStrategy
StrategyDecisionAssumptionsHypothesis
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