Three Web Analytics in Higher Education You Can’t Ignore in 2023

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Track These Outcomes in Google Analytics to Understand Your Prospective Students Better

Making landing page and user experience decisions based on Web Analytics for higher education is absolutely critical going forward. Competition for new students is fierce in 2023, with many colleges and universities experiencing declines in enrollment for both undergraduate and graduate programs.

Improved web analytics in higher education can help you compete better for students
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Reductions in applications are fed, in turn, by fewer adults wanting to enroll and therefore searching for college-related information in search engines. The end result is more colleges competing to appear in fewer degree searches, chasing a shrinking pie.

Conversion Rate Optimization (CRO) is Critical in 2023

Therefore, it is more and more important to convert as high a percentage of website visitors as possible. And to do that, you need to understand what your users are doing across their journey. The three web analytics in higher education elements we discuss below can help you optimize your landing page and website experience to increase conversion rates.

Web Analytics Item 1: Bounce Rate (But Not That Bounce Rate)

Yes, the first thing on our list is bounce rate. But not the much-maligned generic bounce rate you see in a standard Google Analytics installation. No, the “bounce rate” in 2023 needs to work more like an interaction rate instead of a simple record of single-page website visits.

When your site wide and page specific tracking elements are set up well, what bounce rate will then tell you is what percentage of your website visitors did not meet your minimum threshold of page interaction. In other words, your bounce rate should work in tandem with your (customized!) higher ed web analytics to tell you things like:

  • Did my visitor spend X amount of time reading my content?
  • Did they view enough of the page to see the information and actions I wanted them to?
  • Did the visitor use any interactive elements on the page, like accordions, calculators, videos and the like?
  • Did the visitor click any call-to-action buttons?

… And many more user experience elements across the site. If your bounce rate is working correctly in 2023, you’ll know right away the visits that did or did not take any of your desired actions or visit outcomes.

Web Analytics in Higher Education Item 2: “Micro” Web Conversions

Even small interactions are meaningful for higher ed web analytics
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Once your website has deep user interaction tracking set up, a more accurate bounce rate is just the start. Each user journey from landing page to program page to additional pages will have many chances to measure what I like to call micro conversions. These are website events or interactions that can provide a rough measurement of how engaged the website user was and how effectively you are guiding them along on their website journey.

One example scenario of how this works for higher ed web analytics:

  1. Website visitor lands on the university’s home page
  2. They find the Academics page quickly (resulting in a short time on page for the Home page itself)
  3. On the Academics page, they are able to locate the degree program they are interested in (again, a short time on page here means the experience was a good one)
  4. When the visitor goes to the primary degree program page, they spend several minutes reading the content, and view almost all of the page.
  5. Instead of converting on a request for information (RFI) form, as we would love them to, they go on to additional pages for student life, housing, and financial aid.
  6. On the financial aid page, they use a “net price calculator” tool to look at their college costs. Their website visit ends here.

Of the above, I would consider several actions to be “micro” conversions:

  • Going from the Academics page to the degree program page
  • Time spent and page content viewed on the degree program page
  • Additional enrollment-specific pages viewed after the degree program page
  • Use of the Net Price Calculator

Even without gathering contact information, there are several ways to split out the user for a remarketing / retargeting ad campaign, for example. These website analytics in higher education have already told us a lot about the visitor.

When the user has visited a degree page and then gone on to use the Net Price Calculator, an obvious use of this data would be to add them to an ad campaign with information on paying for college, for example. And each step along the way is similar if the website journey had ended earlier.

Web Analytics Item 3: Return Visits to Program and Admissions Pages

Whether through a remarketing campaign or from a direct or organic search visit, getting the user who did not convert on their first visit back to the website is key to increasing your success rate.

Here, instead of looking at initial website visits, a successful outcome would be a visitor who returns back to the program page (usually counted as a direct website visit), and then goes on to admissions pages again or converts on the RFI form on the page.

These types of visits are a big win for the university website, so splitting out the conversion rate for new visitors versus return visitors by channel is vital to understand the prospective student.

Need Help With Your College Website Analytics?

If you need assistance with setting up deep user tracking, large scale SEO projects, or evaluating user journeys, I would be happy to serve as your web analytics consultant. Contact me to set up a free consultation.

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