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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 for PDCA Cycle.
Operations
PDCA Cycle
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
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.For an improvement that still has to prove itself in everyday work, the method runs it through small learning loops. It connects planning, checking, and standardization into a repeatable learning mode.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
MediumLowHigh
Timedifferent
1-2 Tage1 h bis mehrere Wochen1-4 Wochen
Participantsdifferent
Based on research question1-81-6
Formatdifferent
AsyncWorkshop + asyncAsync
Outputdifferent
Findability Metrics, Path Analysis, Revised IAPDCA Log, Experiment Plan, Learning Outcome, Standard ChangeExperiment results, Decision log, Learning summary
Tagsno overlap
Information architectureNavigationFindability
Continuous improvementLeanExperiments
ExperimentsGrowthAnalyticsValidation
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Methods with strong topical overlap with the current selection, not yet in the comparison.

First-click Testing method illustration showing its working structure
UX Research
First-click Testing
Paper illustration for Smoke Test.
Product Discovery
Smoke Test
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 showing three sorted card stacks and an open question about a possible group.
UX Research
Card Sorting