How to Use and Interpret Analytics Data

Graphic visualizing website analytics

Website Analytics

You may already know a lot about your audience through everyday interactions. If you’ve done focus groups or surveys, you know even more. 

Website analytics data gives you another window into what your audience needs and whether your website meets those needs.

Here are some basics to help you understand your analytics.

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

When is a high Bounce Rate a concern?

A high bounce rate suggests an issue if the goal is for site visitors to engage with links to access more detailed content, yet they exit the page without interacting. A bounce rate over 70% needs investigation.

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.

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?

A high exit rate is concerning if the page is not intended as the final step and you want visitors to continue exploring your site. For example, there may be a problem if the primary purpose of a page is to get users to click on a major to learn more about it, yet most site visitors are leaving without clicking any links. An exit rate over 75% on this type of page should be investigated.

When is a high Exit Rate ok?

A high exit rate can indicate success if the page provides visitors with all the information they need and you would not expect them them to navigate further on your site. For example, people may 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, then exit the site.

When is a low Exit Rate a concern?

A low exit rate can be concerning if you expect the page to be a final stop, but users continue to search the site for information on that topic. In this case, an exit rate below 30% may require investigation.

Using analytics to 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.

Identify 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? (e.g. increased use of calls to action like apply, visit, etc.)
  • What user interactions would you like to see reduced? (e.g. reduced bounce and exit rates where appropriate)
  • 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.

Establish Baselines

Once you know your KPIs, you can establish baselines of current performance around these metrics. This can be done by looking at your analytics data over the previous academic year.