The higher education website you manage is generating revenue, but how much? If you manage websites or digital campaigns for higher education enrollment you can gain additional clarity into your audience and degree page performance by mapping requests for information or admission application.
Take a moment and suspend your belief of what an e-commerce website is and let’s explore the commonalities between your enrollment-focused website and a traditional e-commerce website. Any website equipped with e-commerce functionality is an e-commerce website. For example, the product listing page (list of degrees) and product detail pages (individual degree program detail pages) are both, by nature, e-commerce; their functionality allows customers to purchase a good or service and in this case an educational service. However, because higher education websites are rarely looked at as e-commerce, many critical steps are overlooked. For instance, the product listing page and product detail pages must lead to one of two primary conversion points: a request for information web form or an admission application submission form. By leading your viewers to conversion points you can begin tracking conversions as Google Analytics e-commerce transactions. This allows you to capture the rich metadata from the form, giving you a greater granularity into website and degree level data. Program name, internal program code, college, degree level, campus type (modality), and net revenue values can be captured through this process, making an analysis of paid advertising return on investment easy within the GA reporting interface.
Now that I have hopefully convinced you that your website is indeed an e-commerce site, let’s look at some requirements, strategies, and outcomes of setting up conversion points and tracking them with Google Analytics.
Cost Per Acquisition (CPA) can be defined as an enrollment marketing budget divided by the total number of leads or applicants for a given time period minus operating cost (net revenue). Ideally, at least one year’s worth of data to accommodate for differing acquisition cycles across audiences.
In order to find the target CPA for application submission, I’ve previously used a 3 year average of net revenue by program divided by the total number of submitted admission applications by program for the given time period. This will give you a ballpark figure to better understand the revenue your website is generating and evaluating paid marketing campaign return on investment. Request for information CPA can be calculated in a similar manner but may require additional analysis work to match historical submitted RFIs to the matriculated student.
Target CPA is needed in order to assign a monetary value to the e-commerce transaction in Google Analytics which fires on form submits.
Identifying your target CPA also allows your marketing team to optimize all paid digital media toward that CPA. The process becomes simple for analyzing Google Ad performance. Go to Acquisition > Google Ads > Campaigns and compare the Cost column with the Revenue column. If your cost is higher than revenue, adjust your campaign to improve performance. Move to spend from lower-performing ads to advertisements with a higher conversion rate, lower bounce rate, etc. The same method can be used for non-Google ads but you’ll need to import your 3rd party ad’s cost data into Google Analytics. See Data Import developer documentation for this approach.
Once e-commerce transactions are in place, Google Analytics will calculate total revenue by the program, now stored as products, within Google Analytics. Google Analytics will also automatically calculate the page value dimensions for pages converting users visited, which can be used to optimize web pages to improve conversions, return on investment from paid campaigns, and revenue per session can be calculated.
Request information forms should (ideally) be hosted on the primary domain that’s being tracked under your Google Analytics account to reduce implementation complexity. This process can be achieved on 3rd party websites or subdomains but you need the ability to add JavaScript and a web developer that can implement fairly straightforward Google Analytics JavaScript code.
Tracking admission application submissions can be more challenging to implement. This is primarily due to 3rd party admission application’s ability to support 3rd party JavaScript tracking.
You must have the ability to add JavaScript code to the 3rd party website. This is not possible with The Common Application currently but can be achieved with the Slate or Salesforce CRM systems with support from Slate/Salesforce developers. If you manage your own internal application and have the ability to add JavaScript, you should be able to implement this technique without much challenge, however there are details not included in this post such as cross-domain tracking, which may need to be addressed. Google’s e-commerce documentation is accurate and easy to follow.
Researching and understanding your target cost per acquisition for prospective student request for information submissions and admission application submissions will help you to identify an estimated target value for CPA. Even a lowball estimate in revenue per session will demonstrate incredible value of your website, helping organizations to allocate appropriate resources for their primary marketing channel.
If your website’s forms collect personal information from visitors, for example, request for information submissions, newsletter sign-ups, and admission applications, you can treat these leads as a revenue-generating conversion point. Visitors who provide their personal information, assuming it’s valid info, are highly engaged visitors and can be targeted with specific messaging to drive action further down the funnel.
The trend, since roughly 2010 for higher education prospect focused websites is a shift towards a pseudo-e-commerce model; clear primary navigation links that leads the prospective student audience to the appropriate section of the website for them to learn about program offerings and apply for a degree program. Typically visitors will find degree listing pages which lead to individual program detail pages. You can think of degree detail pages as “product” pages to better help to conceptualize the e-commerce model.
In this example, we’ll be exploring the prospective student website journey in an effort to align the user’s experience and Google Analytics reporting data to better understand, segment, and target the prospective student audience.
When prospective students arrive to a dot Edu website, best practice suggests they typically find themselves exploring degree program detail pages. These pages, which I referenced above as “product” pages, analogous to an e-commerce site, will typically be organized by academic level (undergraduate and graduate), and filtering options such as field of study or subject area. The primary calls-to-action are typically request information and apply.
Prospective student websites are, in the simplest of terms, lead generation websites. There is value in the prospective student’s personal information that is submitted via request for information web forms.
Submission of prospective student information forms is a critical step in the enrollment funnel because it exposes your highest intent audience, which can then segment in Google Analytics. Segments allow analysis by visitor cohort and allow you to easily create remarketing audiences to be deployed to the Google Ads platform. From there you can use display advertising email drip campaigns and text messaging to nurture the prospective student down the enrollment funnel.
From here on, let’s focus on tracking admission application submissions.
Once a target cost per acquisition is established for the given conversion point you can follow this template to assign values of your Google Analytics e-commerce transactions.
<br />ga("e-commerce:addItem", {<br />id: "1234", // Transaction ID. Required. Same ID as transaction ID above<br />name: "MS Data Science", // Product name. Required. - Degree Program Name<br />sku: "1234", // SKU/code. - Internal program code<br />category: "Graduate", // Category or variation. Degree level<br />price: "$XX.XX", // Unit price. Target CPA<br />quantity: "1" // Quantity. Always set to 1.<br />});<br />This method doesn’t support interest in multiple programs however E-Nor can help if that is your use case.
Now that you’ve gone through the effort of estimating your cost per acquisition for a given conversion point, setup your Google Analytics e-commerce code and having validated your data, you’re ready to enjoy the additional benefits unfolded in the Google Analytics reporting interface.
E-commerce transactions provide additional dimensions and metrics that were not available out of the box with a standard Google Analytics implementation. Adding e-commerce transactions is where Google Analytics starts to sing with additional reporting capabilities.
Days to conversion, sessions to conversion, highest revenue-generating degree program pages, lowest revenue-generating degree program pages can all be uncovered once using monetized e-commerce transactions in Google Analytics for inquiries or enrollment application submissions.
In the screenshot below we see a report for our fictitious higher education website used to demonstrate a proof of concept.
What cool stuff can we see in this report? We can see the top 10 converting programs, we can also see an estimation of revenue by program and in aggregate.
PageValue: Once you have data collected for all of your product (degree) pages, you can use the pageValue dimension to compare the performance of pages with the same HTML template. For example, if you find one degree program detail page has a higher pageValue than another you can open both pages side by side in a browser and compare the differences, perhaps the hero image could be improved or one of the pages lacks content that’s assisting in conversions such as career outcomes, or a prospective student-focused video. My favorite technique using pageValue, suggested to me originally by Brian Clifton, is to take the top performing 10% of a group of similarly designed pages and the bottom 10% of your least performing pages and look for opportunities to optimize your content strategy by comparing top performers to bottom performers.
Let’s use the PageValue dimension to improve the performance of degree detail pages. We’ll start with the example provided below. Since both degree detail pages below are using the same HTML templates we can look at the PageValue metric to examine differences across like pages. In the example below we can see that the BS Microbiology Degree detail (A) page uses as classroom photo modeling what an in class experience might be like. The BS Computer Science (B) page uses a stock photo of computer programming code. Perhaps the degree detail page with human subjects is more compelling to prospective students? Let’s first look at the pages respective pageValue metrics in Google Analytics (C).
Once you start pushing monetized goals or e-commerce transactions, Google Analytics will automatically calculate pageValue metric for pages visitors passed through during their session to conversion. This is an incredibly useful metric as it shows the pages that are actually generating revenue off your website.
The pageValue metric is a simple calculation. Total revenue of monetized e-commerce transactions (or goal conversions) divided by the total number of pages visited in that session. Let’s say for the sake of simplicity your goal or transaction value is $100. If a visitor visits 10 pages and then completes the transaction valued at $100, Google Analytics divides the total value ($100) by the number of pageViews, 100/10. Each page would receive $10 value in this example.
e-commerce Revenue + Total Goal Value
Number of Unique Pageviews for Given Page
In the example below (C), we can see that both the BS in Molecular Biology degree detail page and the BS Computer Science degree detail page have roughly the same amount of pageViews for the given time period however the BS Molecular Biology page has a higher pageValue. We’ve collected enough data at this point to more closely scrutinize the two pages and make a hypothesis as to why MS Molecular Biology has a higher pageValue. Perhaps our original hypothesis on the difference in human subjects in the hero photo is improving conversions? Good news! This hypothesis can easily be tested using Google Optimize to determine the most engaging content for the audience. Google Optimize is a free product which allows website administrators to perform A/B or multivariate tests to examine changes to the user experience and measure those changes against conversion rate or other KPIs to improve outcomes.
We’ve discussed a lot here; primarily, the value of monetizing prospective student conversion points on higher education enrollment marketing websites, estimating target cost per acquisition for degree related conversions to better inform our digital marketing efforts and to understand our website’s revenue potential, optimizing two like degree detail pages using the PageValue dimension and changing the way we think about revenue generating lead generation websites. I hope you enjoyed this overview. Please feel free to reach out with any questions. E-Nor is here to help!
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