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The Paths table shows you exactly how people moved through your tree for each task – it tells you the steps they took – whether direct or indirect – to get to their final choice – whether that was correct or incorrect.
By using Paths you’ll get a better understanding of where participants may have gotten confused and, as you are able to view each path in an aggregated format, you will have a more concise picture of the distribution of paths in the tree.
Example of a high-scoring task
This task had two correct paths and destinations. We can see that 77% of participants had direct success (with 67% of those people navigating down the Open and apply > Bank accounts > Joint account, and only 10% going down the other path).
19% of participants got to the correct destination, but through an indirect path, meaning they backtracked part way through their path to go down another path. And we can see that one participant failed to find the correct destination.
Even though this task is fairly high-scoring, it’s worth exploring the indirect paths and failure in more depth. We can see that in both indirect success paths, the participants went back and forth a bit, which perhaps infers that they were confused about where to go to open a joint account. So, which label made them think they were or weren’t on the right track?
Looking at the two direct success paths, it’s clear that more people thought they’d find what they were looking for down the second path. It pays to think about this – is it worthwhile getting rid of the low scoring path? Or is it better to keep both paths, but make the labeling for the low scoring one more explicit?
Example of a low-scoring task
In the task below, we can see that only 48% of participants had direct success navigating down the right path to the correct destination. Then there’s a mixture of indirect success (they landed on the correct destination, but after backtracking), direct failure (they went directly down one path to an incorrect destination), and indirect failure (they backtracked but still ended up on an incorrect destination).
Looking closely at all of the results, apart from direct success, we can see that many of the participants were likely confused. The results for indirect success and indirect failure show us the labels that people clicked and then backtracked from.
Why do we think people may have backtracked from those labels and paths? For those who ended up with indirect failure, why did people choose those final destinations as correct? Now’s a good time to go back and iterate on these labels – and maybe the paths – then retest.