Use What You Know!
You already know a lot about your audience. You deal with them every day – face-to-face, with emails and phone calls. You might even know more if you’ve done focus groups or surveys. It’s important to use all of that information to better understand what your audience wants and how to give it to them.
At the start of each web project, we ask you to build a picture of what your audience wants and how they currently get it through:
- Website feedback
- Previous interviews, focus groups, surveys, etc.
- Website analytics
Use that data to set a baseline to measure how your website performs in the future. And to understand who visits your site, what they want, and how you can build your site to help them get it.
You can use analytics to figure out what your visitors do on your website. Many UO websites already have Google analytics set up to monitor web traffic. So, use them.
Look at your analytics at the start of a project to figure out your users are doing right now, like what pages they visit and how they get there.
Web analytics have their own language. Here are some basics to help you understand your analytics.
What is Bounce Rate?
Bounce rate is the percentage of users who enter your website – entrances in Google analytics – and visit that one page on your site and then leave your website entirely – a bounce.
Bounce Rate = Bounces ÷ Entrances
Example: 50% bounce rate = 5,000 entrances ÷ 2,500 bounces
Great = 25% – 55%
Good = 56% – 70%
Needs investigation = Over 70%
When is a high Bounce Rate a concern?
A high bounce rate is bad when you want that page to keep people on your website. When it guides visitors to more in-depth content on your site.
When is a high Bounce Rate ok?
A high bounce rate is good if that page has everything your visitor needs or links to other external websites.
What is Exit Rate?
Exit rate is the percentage of people who leave your site through a particular page.
When is a high Exit Rate a concern?
Needs investigation = Over 75%
A high exit rate is bad if the page isn’t the end of a process and you want people to keep looking through your site. So, if people look at a list of majors on a page and then leave your site without clicking on any of the majors, you need to find out why.
But, a high exit rate is good if that page gives visitors the final information they need and they have no need to continue on your site. So, it’s good if people click on a major on one page, read about that major on the next page, then go to a departmental site to find out more. That’s what you want them to do.
When is a low Exit Rate a concern?
Needs investigation = Below 30%
A low exit rate is bad if the page gives visitors what you think they need so they should exit the site, but they don’t leave. Look into why users keep looking through your site.
Using analytics for set a baseline for improvement
Once you understand how your visitors interact with your site, you can use this information to set a baseline for meaningful improvement.
Key Performance Indicators
The first step is to identify the key performance indicators (KPIs) that will indicate whether or not your project is a success. What you choose as KPIs depends upon how your department measures success. Whatever you decide, make sure your KPIs are actionable and measurable.
Here are a few things to consider when deciding your KPIs:
- What web actions are you encouraging end-users to take?
- On the flip side, what user interactions would you like to see reduced (e.g. increased number of pages visited per session, reducted bounce and exit rates where appropriate, increased use of calls to action like apply, visit, etc.).
- Are you using social media or email communications? If so, are you using UTM codes to track their success? What outcomes will prove that this is a good use of your time?
Brainstorm with your stakeholders to come up with a list. We will then help you decide how you can measure these after site launch.
Once you know your KPIs, we can help you establish baselines of current performance around these metrics. This can be done by looking at your analytics data over the previous academic year.