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Interpreting the pietree
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The pietree gives you an interactive, holistic view of your participants’ journeys for each task. There’s a lot that pietrees can tell us.
The first thing to do is to review the overall size of the pietree. Is it big and scattered with small circles and lots of lines? Is it small with large circles and not so many lines? Does it look like a many-legged spider or does it look like a stick insect!? Or is it somewhere in between? The overall size of the pietree can provide insight into how long and complex your participants’ pathways to their nominated correct destination were.
Let’s take a look at the pietree below, from our banking website tree test.
The task was: The bank lent you some money a year ago to help you buy a new car. You just got a bonus from work and want to put it towards this debt. Where would you go to do this?
The pietree is fairly small with big circular nodes – these are the parent and child nodes added to the tree when you set your study up. There’s also a thick green line leading from the home page node to the correct destination node. This tells us that participants followed a direct pathway to the correct destination (the one that you set as correct).
You want your participants to be able to reach their goal quickly and directly without navigating down other paths. Using this pietree as an example, we know that most of our participants had no issues navigating to the correct destination, via the correct path. Therefore, we can be confident that our IA for this particular task is clear.
You’ll notice there are some thinner lines branching out to smaller nodes, we’ll talk about that in the example below.
Now let’s look at another pietree.The task was: You’re about to go on holiday and want to make sure you’re covered financially if anything bad happens. How would you start the process of doing this?
This pietree is bigger with paths and nodes scattered off in all directions. It shows us that participants took a lot of indirect or winding paths to end up on both correct and incorrect destinations, as well as starting down a certain path then immediately backtracking.
This can indicate that people felt lost or confused when trying to complete the task. It’s shown with red (an incorrect path), blue (the participant has backtracked) on the nodes of the tree, and gray lines leading to smaller yellow nodes (what they’ve nominated as the correct destination).
We can see that, from the offset, participants were confused about where to go and there were a few false starts. The image below shows us that 59.5% of participants started down the wrong path and either continued down that path and nominated an incorrect destination, or they backtracked to go down the right path.
This tells us that perhaps we need to do a bit of work on our top level labeling to ensure participants can confidently navigate to where they’re meant to go.
Example of a high-scoring task and Pietree
In this example, we can see that 95% of participants selected the correct destination and 75% of them navigated down the correct path to get there. That means most of the participants understood the IA correctly.
However, even when the success score is high, it’s still worth delving into the directness score and looking at the 20% of participants who clicked back through the tree before landing on the correct destination (indirect success). Seeing which paths they started down in the pietree can give you insight into whether or not your node labels are completely clear and understandable.
The green circles (nodes) and lines tell us instantly that most people went directly to the right destinations. In this example, there are two green lines leading to two yellow circles – this is because the task had two correct destinations on the tree.
You can see that the path Home > Open and apply > Bank accounts > Open a joint account was far more popular than the other path. While both destinations are correct, participants obviously felt more confident they’d find the answer to their question down one path more than the other.
There’s also a couple of nodes that aren’t completely green. Take ‘Everyday banking’, this shows us that 4 of the 6 participants that landed on this node clicked back, meaning that they didn’t think they’d be able to open a joint bank account if they kept down that path.
You can see in ‘Bank accounts’ that there’s some red. This means 2 out of 20 participants went down an incorrect path (in this case, ‘Open a checking account’), with one nominating it as the correct destination and one clicking back to ‘Bank accounts’ to right themselves.
This is a good opportunity to delve into why these participants thought they’d be able to open a joint account here and re-look at your labeling or paths.
Example of a low-scoring task and Pietree
We can see that while the success score was 70%, the directness was only 55%, giving an overall score of 5/10. On top of this, it took participants an average of 18.45 seconds to finish the task, which is a long time given the speed with which we generally navigate through a website.
We need to delve into:
- Why 30% of participants failed to select the correct destination
- Why 25% of the participants who successfully selected the correct destination did so indirectly.
To understand this, we need to look at the paths they took (their first clicks, when they went back up the tree, and so on) and their destinations (the answers they incorrectly nominated as correct). We can find out more about these things on the pietree, as well as the Paths, First click, and Destinations tabs.
The pietree tells us instantly that people nominated multiple different destinations as correct. The branches going out in every direction tell us that people were clicking all over the tree. The gray in the nodes tell us that people got partway down a path before backtracking to go down another path. The small yellow nodes tell us that a number of participants thought they’d find what they were looking for here.
There are two things to look at here. First, is it possible that the task was unclear? The task was meant to encourage them to apply for travel insurance, but looking at some of the nominated correct destinations (‘Manage your cards’ and ‘Report card lost or stolen’), we can infer that some people perhaps thought the task was more along the lines of losing your card or money on holiday.
Second, despite the potential confusion of the task, there’s still a number of potential starting points for improving this IA. Keep it simple and start with the big numbers. Looking at the red in the ‘Home’ node, we can see that 58.3% of people started down the wrong path.
This indicates that, for this task, people were confused by our second-level labels. If we look back at our tree (and the options that caused so much confusion for people), we can see the exact labels that need work.
Take what you’ve learnt from this task result and pietree and use it to iterate on your second-level labels before testing again.