A university website has a difficult job. It needs to support prospective students exploring their options, current students navigating university life, researchers looking for opportunities, and staff accessing essential information. Each audience arrives with different goals and levels of familiarity with the institution.
These websites can become complex – over time, new pages, departments, and services are added, often without reconsidering how everything fits together. Navigation grows, content becomes fragmented, and information that makes perfect sense internally can be difficult for users to find.
A website redesign offers an opportunity to address these problems. But changing the appearance or reorganising content without understanding how people actually use the website risks carrying the same issues into a new design.
This is where user experience (UX) research becomes essential
By gathering evidence before making design decisions, universities can better understand what their audiences need, where their existing website falls short, and which improvements will have the greatest impact.
Here are five UX research methods worth considering before embarking on a university website redesign.
1. User interviews: understanding what people really need
Before looking at navigation structures, page layouts or visual design, it’s important to understand the people using the website.
User interviews provide an opportunity to explore users’ motivations, expectations and challenges in their own words. Unlike surveys, which typically capture responses to predefined questions, interviews allow researchers to follow up on unexpected findings and explore the reasons behind particular behaviours. For universities, this is especially valuable because different audiences can have very different relationships with the same website.
A prospective undergraduate might want to compare courses, understand entry requirements and get a sense of student life. An international applicant might be more concerned with tuition fees, visa requirements and accommodation. Meanwhile, a current student may visit primarily to access support services or academic information.
These differences aren’t always obvious from website analytics alone…so what can interviews uncover?
- What information users prioritise when researching a university
- Which questions they struggle to answer online
- How they compare institutions and make decisions
- What terminology or content they find confusing
- Which external sources they use alongside the university website
For example, interviews might reveal that prospective students care strongly about graduate career opportunities but struggle to find meaningful information about them. This could prompt a university to reconsider where employability content appears and how it’s presented.
When to use this method: At the beginning of a redesign, particularly when the university needs to understand its audiences, their priorities and the wider context surrounding their website use.
It’s also worth speaking to a range of users rather than relying on one audience to represent everyone. The needs of undergraduate applicants, postgraduate researchers and international students may overlap, but they shouldn’t automatically be treated as interchangeable.
2. Website analytics: identifying where users encounter difficulties
While interviews help explain people’s needs and motivations, website analytics offer a broader view of how users interact with the existing digital experience. Analytics can reveal which pages attract the most traffic, how visitors move between sections, where they leave the website, and which journeys appear to generate the most engagement.
For universities managing thousands of pages, this information can be particularly useful for identifying areas that deserve closer investigation. Rather than focusing exclusively on headline metrics, such as page views or visitor numbers, universities should examine patterns that might indicate usability challenges.
For example:
- Popular entry pages: Which pages do users arrive on first, and do they provide clear routes to relevant information?
- Navigation pathways: How do users move between course information, entry requirements, fees and applications?
- Internal search behaviour: What are visitors searching for, and does the website make that information easy to locate?
- Potential drop-off points: Are there stages in important journeys where users frequently leave?
- Device differences: Are mobile users experiencing different patterns of engagement compared with desktop visitors?
Imagine that a university’s scholarship pages receive substantial traffic from internal search, but relatively little traffic through the main navigation.
This could suggest that users know the information exists but cannot easily find it through the website’s structure.
However, analytics alone cannot confirm why this is happening. Users might be struggling with navigation labels, overlooking relevant links or simply preferring to search.
That’s why analytics are most useful when combined with qualitative research.
When to use this method: During the initial discovery phase, to establish how the current website performs, identify areas for investigation and create a baseline against which future improvements can be assessed.
Importantly, analytics should guide questions rather than provide all the answers. A high exit rate, for example, doesn’t necessarily indicate a problem. A user might leave because they’ve successfully found what they needed.
3. Card sorting: organising content around users' expectations
One of the biggest challenges facing university websites is information architecture (IA): how information is grouped, labelled and organised.
Universities are often structured around faculties, schools, departments and administrative teams. While these divisions are meaningful internally, they don’t always reflect how external audiences think about information.
A prospective student looking for scholarships might not know whether to explore admissions, student services, finance or a particular academic department.
Card sorting helps address this disconnect.
In a card sorting exercise, participants are presented with a selection of content topics and asked to group them in ways that make sense to them.
Depending on the approach, participants may create their own categories (open card sorting) or place content into predefined groups (closed card sorting).
Card sorting can help researchers understand:
- Which topics users naturally associate with one another.
- Where existing categories feel unclear or unintuitive.
- How different audiences interpret content groupings.
- Which labels users might expect to see in the navigation.
- Where an existing information architecture may conflict with users’ mental models.
For example, a university might currently place campus maps, transport options and accessibility information in separate areas of its website.
Card sorting could reveal that prospective students expect to find these topics together under a broader category such as “Visiting us” or “Campuses and locations”.
This insight could inform a more intuitive navigation structure.
It’s important, however, not to treat card sorting results as an automatic blueprint for the website. Participants may disagree, and the most common groupings aren’t necessarily appropriate for every audience or task.
Researchers need to interpret the results alongside the university’s content requirements and findings from other methods.
When to use this method: When reviewing or redesigning the website’s information architecture, particularly before committing to new navigation categories and content groupings.
Card sorting is especially useful when universities suspect their current structure reflects internal organisational priorities more than user expectations.
4. Tree testing: checking whether users can find information
Once a proposed navigation structure has been developed, how can a university know whether it actually works? Tree testing evaluates how easily users can locate information within a website’s information architecture, without the influence of visual design.
Participants are shown a simplified, text-based version of the website’s navigation and asked to complete specific tasks.
For example, a prospective student might be asked:
You want to find out whether financial support is available for your chosen postgraduate course. Where would you look?
The participant then navigates through the structure to select where they believe the information should be located.
What does tree testing reveal?
Tree testing can help universities identify:
- Whether users can find important information successfully.
- Which navigation paths cause confusion.
- Where users make incorrect selections.
- Whether labels communicate their intended meaning.
- How directly users reach the right destination.
For instance, if participants repeatedly look for postgraduate funding under “Fees and funding” but the information sits within a category labelled “Research opportunities”, this may indicate a mismatch between user expectations and the proposed structure.
Because tree testing removes visual distractions, it provides a clearer picture of whether the underlying organisation of information makes sense.
It’s also particularly valuable for comparing an existing navigation structure with a proposed alternative.
Universities can test both versions using equivalent tasks to understand whether the redesigned structure improves findability.
When to use this method: After developing a proposed information architecture but before investing significant time in detailed page designs or development.
One important distinction is that card sorting explores how users group information, while tree testing assesses whether they can find it within a defined structure.
Used together, the two methods provide valuable evidence for making navigation decisions.
5. Usability testing: observing users completing real tasks
Even with a well-researched information architecture, a website can still be difficult to use.
Pages might contain too much information, important calls to action may be overlooked, or interactions might behave differently from what users expect.
Usability testing helps uncover these problems by observing participants as they attempt realistic tasks using an existing website or prototype.
Rather than asking users whether they like a design, researchers examine whether they can accomplish what they came to do.
For a university website, participants could be asked to:
- Find the entry requirements for a particular course.
- Compare tuition fees for different study options.
- Locate accommodation information.
- Find out how to book an open day.
- Identify the next step in the application process.
As participants work through these tasks, researchers can observe where they hesitate, what they overlook and which interactions create confusion.
Consider a student attempting to find course entry requirements.
They might successfully reach the correct course page but struggle to distinguish between standard qualifications, international equivalents and contextual offers.
This suggests the problem isn’t necessarily navigation. Instead, it may relate to content hierarchy, terminology or how information is displayed.
Without usability testing, those issues could easily go unnoticed until after launch.
Test early, not just before launch
A common misconception is that usability testing should happen once the website has been designed.
In reality, testing can begin much earlier.
Low-fidelity wireframes and interactive prototypes can be tested before visual designs are finalised, allowing teams to identify usability problems when changes are relatively inexpensive to make.
Testing should also continue as the design develops, particularly for high-priority journeys such as course discovery, applications and student support.
When to use this method: Throughout the design process, from early prototypes through to more developed experiences, and again after launch to evaluate real-world performance.
Bringing the methods together
Each of these five methods answers a different question, and their value becomes even greater when they’re used together. User interviews help universities understand what people need and why. Analytics provide evidence of how the existing website is being used. Card sorting explores how information should be grouped, while tree testing evaluates whether people can find it. Finally, usability testing assesses whether the resulting experience supports users in completing their goals.
They don’t necessarily need to happen in a rigid sequence, and not every project requires the same level of research. The right approach depends on the university’s objectives, available resources, existing evidence and the problems the redesign is intended to solve.
What’s important is that research informs decisions throughout the process, rather than being treated as a one-off exercise at the beginning.
Designing university websites around evidence rather than assumptions
A successful redesign should help people find relevant information, understand their options and complete important tasks with confidence. By investing in UX research before making major design decisions, universities can challenge internal assumptions, uncover problems that might otherwise remain hidden and create digital experiences grounded in real user behaviour.
At Make it Clear, we believe effective digital experiences start with understanding the people who use them. Through UX research, information architecture and user-centred design, we help organisations turn complex digital challenges into clearer, more intuitive experiences.
