Advanced web analytics for higher ed
Numbers drive action in higher education. Whether they represent SAT scores, marketing leads, submitted applications, admitted students, tuition dollars, GPA, fundraising targets or graduating class size, numbers are used throughout your institution to make decisions and assess success.
When you measure what you do, you end up doing what you measure more than anything else.
That’s why fitness tracking apps have worked so well in changing our daily behaviors. That’s also why it’s important to measure what matters most to reach the strategic digital goals of your institution.
While it’s not always easy to measure the impact of digital initiatives in higher education, some institutions are making big strides in the right direction.
When there isn’t a strong call to action to register, sign up or donate directly through your web content, how can you show its financial impact or justify its budget? You can use the notion of economic value and remember how media relations efforts were measured in the pre-web era.
At Penn State, Todd Gregory did it for the main story on the website home page. Gregory, a digital analyst, calculated this economic value by first researching the cost of similar exposure for his institution on the web.
Next, looking at the price of digital advertising on the Chronicle of Higher Education website, he came up with a fair CPM (cost per thousand page views) rate for the feature story on Penn State’s home page. By factoring in the total number of page views in a given year, it was easy to calculate the annual economic value for this highly visible component of the homepage.
While a fair CPM rate will vary depending on your situation and your reference frame, you can adapt and apply this approach to much of your web content developed for branding purposes.
Quantifying value in every step
Although it’s possible to put a real dollar value on a web conversion (an application, a request for information, etc.), it’s still rarely done in higher education. It requires tracking your web visitors from their first visit on your website to their first tuition payment.
At British Columbia Institute of Technology, Alan Etkin, senior systems analyst, managed to connect the tracking dots with Google Analytics from the website to the school’s Banner system.
It was a long and collaborative project involving many units at the school, but Etkin can now put a dollar value on every digital step in the admissions process. When you can calculate how much an online registration for a campus visit or an open house costs your school, everything becomes easier.
With this strategic information, you can request a bigger budget to support the next iteration of your digital campaign to drive these registrations.
Correlation is not causation, and there’s no exception to this rule in digital marketing. Digital analytics reports often show strong correlation between what was done and what happened.
Yet it’s possible to prove causation—after the fact—with the help of predictive analytics. Predictive techniques are generally used to forecast probable outcomes, but they can also help you predict a probable future with a certain level of certainty, much like election polls do.
Moreover, you can use the same techniques to calculate what would likely have happened without a digital marketing campaign. This is what Joshua Dodson, now director of SEO at Southern New Hampshire University, did when he worked at Eastern Kentucky University.
When EKU ended its relationship with an outside vendor and brought marketing and lead generation efforts for a given academic program in-house, the web traffic data was religiously tracked.
Soon, it was possible to show the impact of this decision by plotting the actual traffic data against the predicted data had the school kept working with the outside vendor. The positive difference helped officials confirm they had made the right choice.