Goals

For each test, we aimed to recruit at least five students, five faculty, and five staff members. We emailed various groups and invited them to take the test online. To ensure that we were getting genuine results, we only invited participants to complete a single test. If a participant was contacted during Round 1, for example, we did not contact that person again for subsequent rounds.

For each test, we determined all the clearest paths a person could take to get to the information they were searching for. When a participant follows one of these clear paths, it’s considered a success. We aimed for an 80% success rate for each task and test overall. If a success rate for a task was below 80%, that told us where we needed to improve for the next round of testing. If a task’s success rate was above 80%, that told us where things are working. With each round of testing, we hoped to improve success rates across the board.

Round 1

For the first round of tree testing, we wanted to establish a performance and participation baseline for all future exercises. To do this, we designed Tree Test A: a menu system with the exact same options, wording, and organization as our website’s current navigation menus. Commonly referred to as the “Mega Menu,” this navigation system contains a total of 116 links divided into seven categories:

1. Admissions
2. ĚÇĐÄVlog´«Ă˝
3. Students
4. Community
5. Research
6. About
7. Quick Links

Round 2

After we analyzed the results from Round 1 and looked for areas of improvement, we designed two hypothetical navigation menus for the second round of testing: Tree Test B and Tree Test C. Each test took a different approach to solve the issues we identified from Round 1.

The menu for Tree Test B contained 81 links divided into three categories:

1. New Students
2. Current Students
3. Our University

In Tree Test C, the menu contained 67 links divided into three slightly different categories:

1. Students
2. Faculty & Staff
3. Our University

Round 3

For the next round, we analyzed the strengths and weaknesses of the tests from Round 2 and designed Tree Test D. This was the simplest menu we tested, with 58 links divided into three categories:

1. Students
2. Faculty & Staff
3. Our University

We planned to conclude all tree testing before beginning Phase 2 of the redesign project, so we were pleased to have finished six weeks ahead of schedule.

Results

Just as we expected, many participants in Tree Test A felt overwhelmed by the amount of options and had a hard time finding what they were looking for. This was consistent with the feedback we received during stakeholder interviews in the past: the current mega menu is too complicated to be helpful.

When we began exploring simpler menus in Round 2, people were more likely to find what they were looking for. We gave participants the option to leave feedback, and many people left positive comments about how much easier the menus were to use. Tree Test C ended up being the menu with the highest overall success rate and the first test to meet our goal of an 80% success rate. It had room for improvement, however, so we moved forward with creating Tree Test D.

Although Tree Test D had a slightly lower overall success rate than Test C, it resulted in the highest success rates by audience. Students, faculty, and staff each had the easiest time finding information with this version of the test. The feedback was also overwhelmingly positive.

Next Steps

Since we met our success rate goals with Tree Test D, we’ve concluded tree testing. We’ll use the results to help inform our decisions as we build a menu system for the redesigned site. We now know that having fewer options that are organized in a familiar way is most helpful to people.

Next, we’re going to begin preference tests to determine what words and phrases make the most sense to our audiences.

This post was written by Ashi Loftus, UI/UX Designer.

The post Tree Testing Results appeared first on University Website Redesign.

What is “Tree Testing?”

Also known as reverse card sorting, tree testing is a type of usability technique for measuring how easy or difficult it is to find information in a menu. Although we call it a “test,” there are no right or wrong answers.

Each test included a hypothetical website menu that worked like a simple decision tree. Participants were given five different tasks and asked where they would expect to find certain pieces of information within the menu. If they couldn’t find what they were looking for, they could skip the question and move on. There was no time limit, but most participants completed the exercise in less than five minutes.

By conducting tree tests with students, faculty, and staff, we’re able to gain a better understanding of how different people search for common topics. Not only will this help us build a better menu, but we’ll be able to improve the overall organization of the website.

Planning the Tests

We wanted to create tasks that were relevant to our actual audience, so we looked at the current demographics of our campus community, created user personas, and then came up with five topics that those personas would be interested in:

1. Majors and programs
2. Tuition and fees
3. Registration deadlines
4. A professor’s phone number
5. Career planning and job placement

Next, we researched different options for conducting the tests virtually. There are many ways to set up a tree test, but we found that participants were the most comfortable when they could take the test on their own devices without someone actively watching them. We chose to use a tool called because it’s easy to use and gathers helpful information like user flows and time on task.

Finally, we started recruiting anonymous participants from three different audiences: students, faculty, and staff. For each test, we aimed to recruit at least five individuals from each audience.

Our Goals

Although there are no right or wrong answers in a tree test, we did want to figure out which menus were the most intuitive. For each test, we determined all the clearest paths a person could take to get to the information they were searching for. When a participant follows one of these clear paths, it’s considered a success.

For example, Task 1 asked them to find information about our majors and programs. If a person went to the ĚÇĐÄVlog´«Ă˝ homepage, they would immediately find information about majors and programs, which would successfully complete the task. If a person went to the Research homepage, however, they would need to click through several other pages before reaching a list of majors and programs. This would be considered a failure.

As a goal, we wanted to have an 80% success rate for each task and for the test overall. If a success rate for a task was below 80%, that tells us where we need to improve. If it’s above 80%, that tells us where things are working. With each round of testing, we hoped to improve success rates across the board.

Next Steps

In the next blog post, I’ll be sharing the results from our first three rounds of tree testing and what we learned from them.

This post was written by Ashi Loftus, UI/UX Designer.

The post Reorganizing Menus with Tree Testing appeared first on University Website Redesign.