In the End, Students Are Customers
When Klotz started at SLU four years ago, the school did not have a student analytics office. The practice of data sharing simply did not exist. Instead, information in departmental silos formed the basis of simple reporting. This consisted of straightforward student surveys that captured data at a single point in time.
But these static solutions are no longer good enough for the rapidly changing dynamics between students and schools.
Klotz recommends that IT practices at post-secondary schools should start to resemble those of financial firms. “Students are now clients,” he says. “Schools are slowly catching up with other industries.”
In fact, the Journal of Retailing and Consumer Services published a study in 2018 that reached the same conclusion: In order for a university to be financially successful, “students must be considered customers in the development of marketing strategy,” the study notes.
For higher education, this means connecting disparate data sources to discover key trends. Without this crucial information, schools cannot incorporate best practices for customer-focused enrollment initiatives.
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How to Overcome Data Silos and Drive Enrollment
As Inside Higher Ed notes, some schools have already hit their enrollment goals for next semester, while others are struggling to keep up. Why are certain institutions doing better than others?
One major disadvantage that is holding many schools back is siloed data.
SLU is an institution that once relied on data silos and reporting. And according to Klotz, this underpins the present problem. “Schools are meticulous collectors of data, but don’t use it,” he says. “They need the right person and the right tools.”
For example, SLU saw marked success after Klotz and his team began combining multiple data sets to uncover “transaction signals.” These signals covered everything from affinity scores during campus visits to email conversations and on-campus connections.
The results speak for themselves. In 2019, the school recruited its largest freshman class in history. This was largely made possible due to “strategic decision-making that enhanced traditional methods,” says Klotz.
Along with on-demand affinity analysis, Klotz says SLU also uses data analysis tools to “identify look-alike markets.” This helps the university determine where to allocate resources for student investments and targeted marketing. By linking disparate data sets to find crucial demographic trends, SLU can determine where counselors would have the most impact across the nation. This allows SLU to strategically target recruits with higher than average potential for enrollment.
Furthermore, post-secondary schools also face the challenge of recruiting mobile-first clients who prefer digital interactions. To address this issue, Klotz recommends a departure from “glossy copy and mass mailers.” Colleges and universities should instead prioritize creating an engaging and interactive online presence.
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The Future of Data Analytics in Higher Ed
As higher education institutions tackle the ever-evolving challenges of COVID-19, it is no surprise that 86 percent of college presidents list fall and summer enrollment numbers as their most pressing pandemic issue. It does not help that post-secondary students are pushing back against full tuition fees for both current and future online classes.
To complicate matters further, several of the measurements that schools typically use to make admissions decisions — such as SAT and GMAT scores — are missing this year. After all, many of these standardized tests were temporarily canceled in light of the pandemic.
So, how can higher education address these urgent concerns? Klotz believes the answer lies in data-driven student analytics. “Now is the time to get in this game,” he says. While there is no single analytics solution that can predict the future of post-pandemic education, many universities and colleges will need a shift in fundamental frameworks.
This will require an incremental, in situ approach that starts with IT infrastructure. Without cloud-based computing and storage, schools would have a difficult time combining siloed data. What’s more, colleges and universities need advanced analytics tools that can drill through large demographic data sets to unearth dynamic trends.
Finally, post-secondary schools must deploy IT teams with a clear mandate: You should ask big questions to discover key enrollment trends and take action to capture those critical markets.
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To Increase Enrollment, Go Big or Go Home
At the end of the day, enrollment is an uphill battle. Even for the most popular post-secondary schools, increased competition—and new educational delivery methods—have made it challenging to fill freshman classes.
To create future-proof enrollment frameworks, higher education institutions must have complete data capture and prioritize affinity and client-focused marketing. This is the only way forward.
