Tree Testing Part 2: Interpreting the Results

Summary: Analyze tree-testing results including success, first click, and directness to improve information architecture and navigation labels.

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This article is a follow-up to Tree Testing: Fast, Iterative Evaluation of Menu Labels and Categories . If you’re looking for details on how to set up and run a tree test, that article has you covered. This article will guide your data analysis and help you find insights.

Tree Testing

Tree testing evaluates the categories and labels in an information architecture . Unlike think-aloud usability testing,  tree tests are usually run as unmoderated studies and generate only quantitative data . This method allows you to collect data from a large number of users quickly but requires a different approach to extracting insights. You can’t just sit through a day of testing and jot down notes — instead, you need to perform a systematic analysis to identify data trends and evaluate their significance.

Tree-Testing Metrics

A variety of metrics capture how users understood (or misunderstood) your categories. Treejack and UserZoom (the two most common tree-testing tools) use slightly different styles for presenting these metrics, but both provide these quantitative measures for each task in your study:

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