Consider this: Your site visitors depend on your information architecture (IA) — the organization of information on your website — to navigate and achieve their goals on your platform. But does your IA truly align with their expectations?
Missed steps or misaligned structures can create barriers, driving users away and making you lose potential business opportunities. Ensuring a seamless, intuitive path is crucial. That's where tree testing comes into play.
In this comprehensive guide, we cover everything you need to know about tree testing to get started, from benefits, limitations, and best practices, to the top tree testing tools you can use.
Tree testing — also known as reverse card sorting — is a UX research method used to evaluate the findability, and intuitiveness of a website's or app's information architecture (IA). After isolating the navigation structure, or tree, from visual elements and content, participants are asked to navigate through the tree to find items or complete tasks. This usability technique sheds light on whether users can find information through the intended navigational paths without the influence of design or other interactive elements.
The primary purpose of tree testing is to identify potential problem areas within the IA, such as misplaced, mislabeled, or confusing categories.
The navigation choices, success rates, and time taken provide valuable insights into potential pain points or ambiguities in your IA, allowing for data-driven improvements that reduce friction in your website or app’s user experience.
Today, tree testing is widely embraced by designers and researchers for assessing how easily users can locate content on websites or other systems with nested menu options.
Tree testing often involves participants undertaking specific tasks that test the clarity and effectiveness of the site's or app's information architecture. Here are some common tasks typically included in tree testing:
Let's look at more reasons why tree testing is worth your time and effort when building digital product experiences:
One of the primary advantages of tree testing in UX research is its ability to assess the usability and effectiveness of your website or app's navigational layout. By simulating a user's journey through the barebones structure of your platform, you can pinpoint areas where users may face confusion, hesitancy, or complete roadblocks.
These insights provide a clear roadmap for refining and optimizing the hierarchical structure, ensuring that users can intuitively and quickly access the content they're seeking.
Through tree testing, you have the opportunity to examine your website’s labels in their purest form, free from the distractions of visuals, content specifics, or interactive components. The technique exposes any ambiguities, jargon, or misaligned phrasing that might complicate the user experience. It gives you a chance to see your platform through the users' eyes, ensuring that every label, menu option, and instruction resonates with clarity.
Tree testing in UX research provides you with a unique window into the mental models of your users. As they navigate through a simplified tree of your site or app, you gain insight into how they categorize and relate information, revealing their inherent expectations and associations. This knowledge helps you tailor your platform's structure to mirror the intuitive pathways your users naturally follow.
Tree testing lets you zoom in on problematic zones within your site or app's structure. Whether it's misinterpreted categories, ambiguous labels, or elusive items, you gain a precise understanding of where users are stumbling. However, the brilliance of tree testing lies in its ability to rank these problems, as not every identified issue will hold the same weight.
Some glitches may significantly affect numerous users, while others may be minor obstacles affecting only a select few. Through metrics provided by tree testing, such as task completion rates, the duration required for tasks, and direct user feedback, you're equipped to prioritize these problems based on their impact. This enables you to strategically allocate resources and attention to areas that most warrant improvement.
Like any research method, tree tests do have limitations to consider, such as:
Tree testing evaluates the information architecture in isolation, without visual design or interactive elements. While this ensures a pure assessment of the IA, it doesn't account for how visual cues, imagery, or interface design might influence user navigation in the wild.
Tree testing focuses on a user's ability to locate items within a structure. However, it doesn't capture other essential aspects of user behavior, such as how they would interact with content, their scrolling behavior, or their reactions to animations and transitions.
In a real-world scenario, users have various motivations that drive their behavior. Tree testing assumes a user's motivation by assigning tasks, which might not capture the entire spectrum of genuine user intent.
Tree testing is a powerful tool when you need to assess the clarity and effectiveness of the labels and organizational structure within your website, intranet, or app. This method offers insights throughout your design journey, whether you're conceptualizing an entirely new platform or refining an existing one.
Here are the specific instances where tree testing proves most beneficial:
At this foundational stage, tree testing provides a platform to gauge the efficiency of your current information architecture. It spotlights areas of ambiguity and potential pitfalls that need revision. While qualitative usability tests offer insights into visual design, layout, and interaction, tree testing distinctively zeroes in on the IA, setting a benchmark for more valuable enhancements.
Card sorting often yields results that, while insightful, lack definitive direction. Card sorts do not provide users a clear-cut IA structure, which makes tree testing an ideal follow-up exercise in order to validate your findings. Tree testing helps you corroborate and refine the emergent hierarchies from a card sorting exercise.
At this stage, tree testing allows you to evaluate various IA propositions without the need for intricate designs, coding, or content generation. By validating the hierarchy and labels in this early phase, your design team can ensure a solid foundation for subsequent development. Consequently, this preemptive measure minimizes potential revisions, saving both time and resources as the project unfolds.
After any significant updates or the introduction of new features, it's essential to ensure they integrate seamlessly within the existing IA. Tree testing can be key here, allowing you to assess whether users can naturally locate and engage with the new content or functionalities, and ensuring the updates enhance rather than obstruct the user experience.
To better illustrate tree testing's practical applications, let’s explore some common use cases, including real-world examples.
Whenever a new IA is proposed, it's important to test its feasibility and user-friendliness before rolling it out. For example, an e-commerce website revamping its product categories can run a tree test to determine if users can easily locate products within the new structure.
When multiple IA designs are on the table, tree testing is a great way to objectively evaluate which one resonates best with users. For instance, a news portal considering various ways to categorize articles can tree-test each option to determine which allows readers to find stories most intuitively.
If there's a suspicion that certain labels or terms are unclear to users, tree testing can validate or disprove these assumptions. For example, a health portal can test if labels like 'cardiovascular' or 'hematology' are clear to users or if simpler terms might be more effective.
When adding new sections or features, it's essential to ensure they are discoverable and fit well within the existing IA. An example is a social media platform introducing a new 'marketplace' feature. They can use tree testing to see if users can naturally locate and use this new section.
You can approach tree testing from a qualitative or quantitative angle. Each approach offers distinct insights and caters to different facets of user experience and information architecture evaluation. Let’s take a closer look at each.
On the one hand, qualitative tree testing delves deep into the "why" behind user decisions. It focuses on understanding users' thought processes, emotions, and motivations as they navigate through a given structure. For instance, when a user hesitates between two categories or backtracks to a previous option, qualitative testing seeks to unpack the reasoning behind such actions by asking follow-up questions.
Employing techniques like think-aloud protocols helps you gain a more profound understanding of potential ambiguities, misinterpretations, or complexities within the IA. This insight helps in crafting a more intuitive, user-friendly navigation by shedding light on the nuances of user behavior and interpretation.
On the other hand, quantitative tree testing is rooted in metrics, numbers, and broader user patterns. It captures data on a larger scale, analyzing the performance of a significant number of participants to derive more generalized conclusions. Through this approach, you can track metrics such as task completion rates, time taken for specific actions, and the frequency of specific navigation paths.
Tree testing, card sorting, and first-click testing are all important usability techniques, each of which addresses different facets of the user experience. While they share common goals of enhancing the user interface and information architecture, their applications and methodologies are distinct.
As discussed earlier, tree testing focuses on improving the usability of a website or app's information architecture (IA). The goal is to evaluate findability — how effectively users can navigate and locate specific items.
Card sorting serves as a foundational method to create or refine a platform's IA. Participants categorize and label groups of content or features into what they deem as logical groupings. This exercise helps you discern users' mental models, providing insights into how they expect information to be organized, which then informs the design or revision of an IA.
First-click testing evaluates the immediate choices users make when trying to complete a task on a website or app. When you analyze where users click first, you can determine if the most crucial navigational cues are effectively capturing user attention. It's particularly useful for assessing the clarity of landing pages or determining if call-to-action elements are optimally placed.
While each of these methodologies focuses on different aspects of the user experience, their combined use can offer a comprehensive understanding of a platform's strengths and weaknesses.
Before starting any test, it's important to outline what you want to achieve. Whether it's to validate a new information architecture, pinpoint navigational challenges, or compare two potential structures, clear objectives should guide your entire testing process.
Based on your existing or proposed IA, create a hierarchical tree structure. This should be a text-only version, stripped of all visual design elements. Use labels and categories that you wish to test.
The participants should represent your target user base. Generally, a sample size of 50 participants can provide a good balance between resource expenditure and the reliability of the results.
Create realistic tasks that you'd like participants to perform using the tree. These tasks should reflect common user goals and be written clearly. For example, "Find where you could get information about pricing for enterprise teams."
Using a tree testing tool or platform, invite participants to navigate the tree, and complete the tasks. Ensure you have a system to capture where participants click, how long they take, and any backtracking they do.
Beyond just observing participants' choices, gather qualitative feedback. Ask them about any difficulties they faced, any labels they found confusing, or any suggestions they might have.
Look at metrics like task completion rates, time taken for tasks, and the paths participants took. Identify areas where users struggled or where they made incorrect choices.
When recruiting participants for your tree test, you should ensure they align with your target demographics for more genuine, actionable feedback. So how do you identify and recruit the right participants?
If you're revamping an internal product or wish to gather feedback from loyal customers, it’s best to tap into your existing user base or employees. A personalized email invitation with a compelling research incentive as a reward can drive participation.
You can invite people to participate in your tree testing exercise through your brand's social media platforms or launch call-to-action banners on your website to drive participation. A crucial aspect to note is that if you're not offering incentives, you should anticipate the need to reach out to a broader audience than you'd initially planned.
To ensure the participants meet your desired criteria, it’s a good idea to use a screener survey. This step filters out unqualified or unsuitable candidates, ensuring that your final list of participants is both relevant and engaged.
If you're seeking a streamlined recruitment process where you can also manage your incentives (and more), Great Question has you covered. Start a free account to see for yourself.
Once your participants have finished the tree test, the results are typically stored in your chosen tree testing software, ready for in-depth analysis. A range of metrics can help you better understand how users navigate your site or app's structure.
Beyond the quantitative metrics, don't forget to consider qualitative feedback. Participants might share insights about what they found confusing or which labels they didn't understand.
To run an effective tree test that yields insights, follow these best practices:
Ensure you recruit participants who closely match your target audience demographics. A representative sample will lead to more accurate and actionable insights.
Simulate real-world tasks that typical users would undertake on your site or app. This makes the tree test more authentic and offers insights into actual user navigation behavior.
Ensure that tasks and questions are unbiased and don't inadvertently guide participants toward specific answers.
Overburdening participants can lead to fatigue and inauthentic responses. It's generally recommended to have no more than 10-15 tasks per session.
Before rolling out to your entire participant pool, conduct a pilot test. This helps in identifying any issues or ambiguities in the tasks or the tree itself.
While tree testing provides valuable insights, it's beneficial to combine it with other UX research methods, like card sorting or first-click testing, for a holistic understanding.
Tree testing tools streamline the process, offer rich data analysis features, and facilitate actionable insights. Here are five of the best tree testing software options at your disposal today:
UXtweak is a comprehensive tree-testing platform with robust analytics capabilities. It allows you to effortlessly import trees via CSV files, make adjustments, or even construct a tree from the ground up using its intuitive editor. UXtweak provides detailed insights, including analysis of users' first clicks and the paths they take, ensuring you understand user navigation patterns.
Optimal Workshop's Treejack facilitates the quick creation and launching of tree tests to validate site navigation using authentic user data. The platform offers a user-friendly experience for participants, enabling unmoderated tree tests without the necessity for constant guidance. Treejack provides automatic result analysis with various visualization techniques, simplifying data interpretation and sharing.
PlaybookUX offers an all-in-one solution to recruit, execute, and analyze tree tests. After each task, the platform provides the capability to pose various follow-up questions, including multiple choice, rating scales, and open-ended responses. Its analytical features, like the task success chart and the option to predefine correct paths, streamline the evaluation process, highlighting content accessibility and users' navigation efficiency.
Useberry enables you to set up tree tests by adding task titles and providing context for each task to the testers. The platform facilitates creating a customized tree structure to fit your needs. Additionally, it offers a flexible recruiting system by generating a shareable link, which can be distributed through email, social media, or even embedded directly on your website.
UXArmy provides a versatile platform where you can upload your menu tree via Excel or CSV files or craft one manually. The tool is designed to assess the ease of locating products within the menu hierarchy, automatically detecting task success as users navigate.
Each task and tester's journey is well documented, with highlights on backtracking, direct finds, and points of struggle. The comprehensive metrics, including time taken, user confidence, and directness weightage, are presented in tabulated results, guiding you toward data-driven decision-making.
In the dynamic world of UX design, understanding and optimizing your website's information architecture is paramount. Tree testing is an essential usability technique that provides valuable insights about the ease and efficiency with which users navigate your content.
From selecting the right software tools to embracing best practices, your journey to mastering tree testing starts here. Remember, a tree well-tested is an elevated user experience. Dive deep into these insights, refine your navigation, and watch your users sail smoothly through your product or site.
Jack is the Senior Content Lead at Great Question, the end-to-end research platform for customer-centric teams. Previously, he led content marketing and strategy as the first hire at two insurtech startups, Breeze and LeverageRx. He lives in Omaha, Nebraska.