If you’re using an online testing tool, you’ll probably need to do some data clean-up before analyzing your results. |
Overall scores (based on factors such as success rate, directness, and speed) give you a quick idea of your tree’s effectiveness and how it compares to other trees. |
Task scores will show you where your tree is performing well or poorly. |
Low task success rates show you where your participants got confused, disagreed about where the answer would be found, or were lured down the wrong path by a promising (but wrong) intermediate heading. |
First clicks are especially important to analyze, because they greatly affect success rates. |
Finding where people backtracked helps you find evil attractors and dead ends. |
Spotting areas of your tree that slowed participants shows you where subheadings need to be clarified. |
Look for patterns of behavior across several related tasks. |
Look for patterns of success or failure across different sections of the tree. |
You can compare the results of different user groups (or other criteria) if you run separate tests for each, or if you run a single test and filter results by a corresponding survey question. |
Next: Chapter 13 - Communicating results