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Criterion
Paper illustration of a branching category tree with a highlighted search path and possible dead ends.
UX Research
Tree Testing
Paper illustration showing three sorted card stacks and an open question about a possible group.
UX Research
Card Sorting
Paper illustration of an assumption matrix with prioritized test cards
Decision Making
Assumption Surfacing
Purposedifferent
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 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.Plans often contain assumptions that were never openly stated and remain dangerous precisely because of that. Assumption Surfacing makes these silent premises visible and prioritizes which of them carry the initiative or could sink it.
Complexitydifferent
MediumLowLow
Timedifferent
1-2 Tage20-45 min45-90 min
Participantsdifferent
Based on research questionBased on research question2-8
Formatdifferent
AsyncWorkshop + asyncWorkshop + async
Outputdifferent
Findability Metrics, Path Analysis, Revised IAContent groups, Label set, IA hypothesesAssumption List, Critical Assumptions, Learning Plan
Tagsno overlap
Information architectureNavigationFindability
Information architectureNavigationStructure
AssumptionsRiskDecisionDiscovery
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Often compared together

Methods with strong topical overlap with the current selection, not yet in the comparison.

Paper illustration of a calm four-quadrant Assumption Map with hypothesis cards and emphasis on important assumptions with little evidence.
Product Discovery
Assumption Mapping
Paper illustration of DIBB with its method-specific working model.
Product Strategy
DIBB
First-click Testing method illustration showing its working structure
UX Research
First-click Testing
A hypothetical failure makes concrete risks, signals, and fitting mitigations visible.
Decision Making
Pre-Mortem