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Splitting your our analysis by user group or other criteria (such as region) is a common need, especially for larger websites.

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If you we have more than one user group visiting your our site (and most of us do), analyzing a tree test is a lot easier if you we analyze each user group separately.

If you we run a separate tree test for each user group (as we discussed in Different tasks for different user groups in Chapter 7), then you’re we’re going to have a separate set of results for each test, so that’s already taken care of.

If, however, you we run a single tree test across all of your our user groups, we recommend that you do doing a separate analysis for each group. That way, you we can see the differences in their performance, instead of having their respective highs and lows mushed together into middling scores.

Suppose, for example, that we were looking at the results for a single tree test of the Shimano website. In Which part of the tree? in Chapter 6, we saw that Shimano has 3 major types of users – cyclists, anglers, and rowers. And suppose that the cyclists and anglers had no problem with tasks that covered the Corporate section of the site, but rowers failed miserably at those. If you we looked at the results of all users together, the high scores of the cyclists and anglers would get mixed in with the low scores of the rowers, and you we would just see a middling composite score, with no easy way to find out what caused it.

If, however, you we could separate the groups and do the same analysis for each group, you we could see that it was the rowers who had problems – the other two groups were just fine.

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