As we have mentioned in previous posts, we have spent a lot of time collecting user stories related to the public that used our website. This gave us a lot of information, but it doesn’t really tell us which activities are really important to users (main activities) and which activities are less important (tiny activities). This is where the next phase of our research comes into play.
We have identified three distinct primary audiences that our website needs to work for.
There are a number of other audiences that don’t fall into these categories, but they represent a smaller percentage of traffic. While we will keep them in mind during development and provide specific solutions for them in the future, the above audience is our initial focus.
Each of these audiences was asked to complete two tasks related to the distilled task list we collected as part of the research above.
- Select your top ten activities.
- Put all activities into groupings that make sense to them.
How did we get our attendees?
It’s worth mentioning because sometimes it’s the hardest part of what we do; find people representative of the target audience who are willing to spend time completing tasks.
For the prospective student’s homework we tried different methods. The most public of these was placing a banner on the ‘Study’ section of the website which we know is visited by a large number of prospective students every day. However, the response rate was relatively low (6-10 responses), despite us offering a £50 prize draw of Amazon vouchers.
The most effective method we’ve found so far is to use the relationships people have across the university to tap into networks that otherwise wouldn’t have been open to us. Throughout all of the research so far, we’ve been thrilled to have people volunteering to help us connect with these networks, so now was an ideal time to call on those offers. These networks included:
- High school students through the Expanded Access Program.
- Potential candidates through our global engagement team.
- Open day visitors who have signed up to receive marketing information.
To date, we’ve received 222 responses to the top ten tasks and 80 to the grouping task.
When we do this type of research, we’ve found that once you get past about 30 responses, you start getting diminishing returns. While each user is unique, they Have substantially similar requirements. So 30 responses gives us very broad results, and anything else just adds a little more clarity to the placement of the activity results. For all the tests we ran, we far exceeded the baseline dataset requirement.
Top ten tasks
Below are the top ten businesses rated by our prospective students.
|Position||Task||% of participants rank it in the top ten|
|1||Check the admission requirements for a course||64%|
|2||Look at the modules of a course and how they are taught and assessed||40%|
|3||Search for a course||35%|
|4||Check out the prices for university accommodation||34%|
|5||Check out the accommodation options in Dundee||33%|
|6||See the facilities available on campus||31%|
|7||Find out what happens after I apply||28%|
|8||Compare two or more courses||27%|
|9 =||Find out how to apply for university accommodation||26%|
|9 =||View a list of courses and filter them||26%|
|10 =||Find out the deadlines for enrollment in the courses||24%|
|10 =||See examples of student work for a specific course||24%|
The most interesting thing about these activities is that very few can be completely implemented by Web Services alone. We can provide the means by which to visualize the data, but we will need to use the skills and knowledge of the entire University to not only obtain the data, but also to ensure that it is up to date.
While the top ten activities give us an indication of the important elements people are looking for, the grouping activity is useful in helping us determine how people want information to be grouped on the site and which elements should be placed together. Remember, each task has been described by someone, so it has an element of importance that can still sometimes be fulfilled, even if it didn’t score high.
It seems really confusing at first, but it’s a very effective way to visualize information. It essentially shows how often two tasks are grouped together. The redder the box, the more it has been grouped together. For us designers and developers, it helps us determine what people in similar places will be looking for, so we can implement designs that satisfy that desire.
The study is not fully completed yet because we want to give as many people who want to respond, the opportunity to do so. However we are already starting to analyze what is coming and design some first concepts.
Over the next few weeks, we’ll be posting a few posts looking at these first concepts for parts of the site, based on this feedback, so you can see how we use data to give people what they want.