The Difference Between Descriptive and Diagnostic Data Analytics
Before discussing specific enrollment strategies, members of the panel explained it was important to understand that data analytics is divided into two tiers. There’s descriptive analytics, which describes the incident, and there’s diagnostic analytics, which clarifies why it happened.
Descriptive analytics, for example, can be used to describe the demographics of students who recently visited campus, while diagnostic analytics could track whether those students visited in response to a particular event.
Using Predictive vs. Prescriptive Data Analytics for Enrollment
In the next step up, there is predictive and prescriptive analytics. Predictive analytics helps colleges and universities predict the likelihood of a certain outcome. It uses descriptive and diagnostic analytics to further the probability of that desired outcome.
For example, if your student analytics indicates a visiting high school graduate is 30 percent likely to enroll, you’d use prescriptive analytics to maximize that possibility. Your plans could involve financial aid, an innovative marketing program, direct mail or a personal phone call.
It can help institutions achieve a desired outcome and track its success.
RELATED: Learn how data analytics helped Millersville University reopen campus.
Why Predictive Analytics is Important to Enrollment
Blake Bedsole, vice president for enrollment management at Arkansas Tech, described how his university used predictive analytics to decide how to target their marketing — “whether that’s completing an application or coming to campus to take a visit.”
The university sought to capture the attention and interest of a qualified set rather than “scatter the spaghetti on the wall and see what sticks.”