Tree Testing: Your Guide to Improve Navigation and UX

In the previous chapter, we talked about how you can conduct a card sorting session to solve issues related to your information architecture (IA). Card sorting is typically complemented by tree testing to validate the identified categories. In this chapter, we delve into this research method to learn how it can help you create a better user experience.

Tree testing is a UX research method used to evaluate the navigability of your site or app and the findability of topics on it. It consists of presenting your site architecture in plain text labels or category labels organized hierarchically. Put simply, users are asked to find something on your site—maybe a certain feature or product—using a deconstructed outline of your site or app. It’s an important step in understanding if users can find what they need on your product.

Sometimes tree testing is also described as ‘reverse card sorting’ because, while tree testing is used to assess the findability of items in a given structure, card sorting is used to understand how users would naturally categorize information. Both methods give you actionable insights to improve the UX or assess the navigation of your product.

From redesigns to site migrations, tree testing can be used to challenge your assumptions before developing a product or making any significant changes.

Some of the questions tree testing can answer include:

Whether you're launching a new product or managing a content-heavy platform, tree testing can help inform design decisions. Some key moments to use tree testing are:

Before we get into how to conduct your own tree test, let’s take a look at some examples of how you can use tree testing:

Tree testing is an excellent method to evaluate the effectiveness of your website or app’s navigation hierarchy early on in the design process. The data collected from a tree test helps you understand how users navigate your site so you can better organize your content. Let’s break down all the benefits in detail:

As you’ll see from the examples above, you can use tree testing to identify navigation problems such as confusing labels, redundant pages, or dead-end paths that prevent users from finding what they need, signing up, or activating. This involves assessing whether your navigation successfully supports the overall goals of your website or product. If users take a long time to locate these items, your navigation may not effectively support your site's goals.

The labels you use for your categories, menus, and other navigation elements help users traverse your site or app. Tree testing allows you to test your labels in a stripped-down context, devoid of visual design, without actual content (like the text on a page or items in a list), and interactive elements (like buttons or links) that might otherwise influence users' interpretations. It’s an honest and bare-bones assessment of whether your labeling works.

A mental model refers to a user's internal understanding and expectation of how something works based on their past experiences and assumptions. These heavily influence how users approach and interact with a product—what they expect to find, where they expect to find it, and how they expect it to behave. So, the more you understand users’ mental models, the more intuitive and user-friendly you can make your product.

By analyzing how users interact with your 'tree', you can identify specific areas of your structure that are causing confusion or difficulty—categories that users frequently misunderstand, labels that are unclear, or items that are hard to locate.

But not all issues are equally impactful. While some issues cause significant difficulty for many users, others might be minor nuisances that only affect a handful of people. Tree testing measures the severity of different issues through usability metrics like task completion rates, time taken to complete tasks, or users' subjective feedback.

As with any UX research method, the first step to running a tree test is to create a research plan and align with stakeholders on the objectives of the research. Plus, defining the research questions and communicating the timeline to the team are also key.

To conduct a tree test, start by getting your site structure ready, create tasks for your participants, and define the key metrics you’ll record to analyze the data gathered.

Keep in mind that during the tree testing session, only the text version of the site is given to your participants, who are asked to complete tasks to locate particular items on the site. It’s recommended that you keep these sessions short ranging from 15 to 20 minutes and ask participants to complete no more than 10 tasks.

Begin by outlining the tree structure with the categories, subcategories, and pages in your site or app. Being specific about your subcategories is important because it will prompt realistic user behavior. For instance, a category in the navigation could be called Resources. Respectively, the menu structure for subcategories can be Blog, Help Center, Guides.

Even if you want to test a particular area in your product, make sure your target audience understands how that area relates to the product as a whole. This will enable you to get actionable information you can act on when reviewing your results.

Next, create tasks for participants to find a page or location in a tree using a top-down approach. Just like in usability testing, writing good tasks is key when doing a tree test study.

For example, if you want to test the discoverability of the upgrade page in your product, you can create a task that asks participants to find the best way to upgrade the product. Here’s an example of a tree test task:

“You’ve signed up to a 7-day free trial for a budgeting app. You’ve enjoyed using the app and want to upgrade your account. Find how to do that.”

NNgroup recommends that for each task you write, you should also define the right answers that correspond to where the information is located within the tree, so you can automatically calculate success rates for each task.

Other best practices for writing great tasks include making tasks actionable, setting a scenario, and avoiding giving precise instructions to avoid bias.

Typically, tree testing shouldn’t take longer than 20 minutes and it should include up to 10 tasks. For example, Melanie from Shopify shares that for the product she works on, her team had to test the taxonomy structure of a list of services so they wanted to understand what path people would take when navigating different categories of services.

Here’s the task they created:

“Imagine you wanted to hire someone to help set up your business on Shopify; please find which service you’d have to hire for.”

When you’re preparing a tree test, an important element to take into consideration is the participants you will work with. The number of participants depends on a variety of factors like the type of testing you are conducting, your product’s target group, the confidence level you need, and the goal of your project.

Melanie Buset, Senior UX Researcher at Shopify, recommends using at least 50 users when running a tree test so you can identify user behavior trends and clear patterns.

And if you’re using a platform like Maze to run remote testing, you can easily recruit participants based on various filters like industry, language, device, age, gender, and country. This way, you’ll uncover a broader range of user preferences, and gather a more comprehensive understanding of your target audience.

The key thing for selecting the right participants is to spend time understanding your target audience and identifying who will be the most impacted if you were to make changes to your design.

Mario Tedde, Senior UX Researcher at FedEx Express, explains: “Let’s assume that you want to design a website that is going to be used by different types of personas such as psychiatrists, tutors, parents, and young adults that need mental care. If you decide to make one website that will fit all their needs, you need to consider performing tree testing with participants that represent all these personas.”

Tree testing can be run in-person or remotely using UX research tools like Maze. With in-person, moderated testing, the advantage is that you can ask participants why they made certain choices—or any other relevant questions that occur to you in the moment.

However, remote testing is advantageous because of its ease of use and speed. You will only need a web browser for testers to participate, and they can do so anywhere and at any time without you being present. Plus, if you’re using Maze, you can use templates to quickly create your tree structure by adding or removing blocks and organizing them according to your product structure.

An important step in the process is organizing a pilot test before your official tree test session to see if the test makes sense and works as expected.

Atlassian recommends doing this by opening up the study to a small portion of participants from your panel. This approach will help you mitigate the risk of missing important details, adjust your instructions, and get more valuable insights for future sessions.

Pilot runs are useful as they bring new perspectives to the study. You will be able to find out what’s missing or what’s confusing and be prepared for the actual session.

This step is fairly straightforward. If you choose to conduct tree testing as a remote, unmoderated study, the testing tool will give you a link to the test that you can send to participants.

You can also follow-up the tree test with survey questions that participants will answer after or before they complete the tasks. The questions can help supplement the user research data you need to know about the participants, such as demographic information or their familiarity with the product.

Once all the participants have completed the test, you can start analyzing the results and making informed design decisions. If you want to test different versions of a tree—say a new version of a tree with the existing one, you can run split testing and compare the results of the new tree to the old version.

After participants complete a tree test, the results will be recorded in the tool you are using, allowing you to start analyzing them (see how to analyze results in Maze). Typically, the metrics you can analyze for a tree test include success rate, directness, average time to complete a task, and the path taken by users.

These results often tie back to questions like:

By analyzing the accumulated data, you can validate or invalidate your hypotheses and design a navigation that makes sense to users.

Tree testing has several specific use cases, which makes it ideal for certain research objectives—like assessing the findability, labeling, and information architecture of a website or app. Combined with other usability testing methods, you can unlock user insights with additional context and deeper understanding.

There are three types of card sorting: open (users create and name their own groups), closed (users sort cards into predefined groups), and hybrid (users can create/name their own groups, and sort into predefined groups).

In a card sort, users are given a set of cards (digital or physical) representing a piece of content or functionality they must categorize in a way that makes sense to them.

The result is a user-centered view of how content should be organized and labeled, which can form the basis of your initial IA design. Once you’ve drafted the IA, you can then use tree testing to identify any issues with your structure or labels, and make necessary refinements. By using these methods in tandem, you ensure your site's IA is both informed by user expectations (through card sorting) and validated by user behavior (through tree testing).

To optimize the usability of your website, you need to first start with tree testing. While users are performing tasks, pay special attention to their first click—which category or option do they choose first when trying to find an item or complete a task? This is the 'first click.'

Generally, users that make a correct first click are more likely to complete their task successfully. If users make incorrect first clicks, something about your structure or labels may be misleading. Use this insight to refine your structure and make it more intuitive. Once you’ve adjusted your website, you can run another round of tree testing to check if users' first clicks (and overall success rates) have improved.

Combining A/B testing with tree tests can help evaluate the effectiveness of the different versions of your website’s IA. These versions can have variations in category labels, item organization, depth of the navigation tree, or any aspect of the IA you want to assess and optimize. Run a tree test by dividing your participants into groups and assigning them a series of tasks, then compare the data to identify the better-performing IA.

After you’ve implemented the results into your live environment, you can run an A/B test to confirm the results. Show some users the old version of your IA (as a control) and others the new version. You can then compare user behavior and key performance indicators (KPIs) across the two versions to validate the effectiveness of the new IA.

Tree testing is typically conducted in the early stages of product development after you've designed a draft version of your IA, but before you've created any detailed designs or prototypes. This is where you identify and resolve any problems with your structure or labels early on, before you invest time and resources into detailed design work.

But, tree testing is just one part of the larger usability testing process. Once you've refined your IA based on tree testing, the next step is to create a prototype. Prototype testing helps you validate design decisions, and gain a deeper understanding of how users navigate and engage with your product. It provides a realistic and interactive environment for evaluating the user experience, enabling you to make iterations based on user feedback.

Just as with all UX research methods, tree testing has ideal use cases and situations where an alternative method may be more suited. One of the benefits of tree testing is its tight focus on evaluating IA and navigation, but this can also be a disadvantage, depending on your objectives.

Tree testing tests the top-down organization of a site and the labeling of features, but this means you won’t get any feedback on other areas of navigation or the overall usability of the site, as you may with other research methods.

However, this can be easily mitigated by supplementing tree testing with additional types of research, such as card sorting or basic usability testing, to build a wider picture of any issues with your site’s design and structure.

The other main downfall of tree testing is that it often works best as a remote, unmoderated study. This does, however, mean that you miss out on qualitative data such as comments users may make while conducting the test or wider context for how users approach the task at hand.

In the next chapter, we go over the five-second testing research method, which you can use to measure how well a design communicates a message.