June 17, 2020

Predictive Analytics Helps Boost Enrollment at Taylor University

Terri White

Topic:   Industry Focus

Taylor University, a non-denominational Christian liberal arts college, uses ibi business intelligence (BI) and analytics platform as its enterprise standard to help foster a culture of “data-informed decision-making.” Faculty, staff, and students throughout the institution visualize information through easy-to-use, self-service applications that let non-technical users easily explore data through charts, graphs, reports, and other interactive content.

Located in Upland, Indiana, Taylor University is reliant on student tuition for its institutional budget. Like most small private colleges, institutional funds are leveraged to encourage enrollment to meet annual budget goals. This process, known as discounting, lowers the cost for students to attend college. As discount rates rise across the industry, operational efficiency is needed to meet bottom-line revenue goals. Taylor University does more than just analyze historical data to identify academic,
financial, or administrative trends; it also uses advanced analytics to do predictive modeling, machine learning, and data mining in preparation for the future. For example, in the admissions department, a team of five full-time recruiters processes an inquiry pool of 50,000 prospective students to fill about 500 enrollment spots. With limited spots for admission, Taylor needs to select students who will not only attend the institution, but also earn degrees there. ibi predictive analytics helps recruiters determine the best prospective students. In the future, it will also indicate which ones are most likely to enroll.

Working in collaboration with Taylor University’s Enterprise Data Systems team, the admissions department built predictive models with ibi tools that monitor the progression of students through the sales funnel, computing the relative probabilities that help the sales and marketing groups target their efforts. The system compares current prospective students to past students to discover patterns in financial aid data, customer relationship management (CRM) data, and census data, such as median household income, academic interests, and a variety of demographic data points.

“We identified approximately 60 variables, with the goal of trying to predict who is likely to enroll, and why,” notes Ben Roller, a data analyst on the Enterprise Data Systems team. “The sales cycle has multiple stages, and we want to help the admissions department optimally allocate resources at each stage, from initial inquiry to final enrollment.”

Thanks to these ratings, Taylor University has better intelligence about its tactical sales activities as well as more specific insights to set up and stage its marketing campaigns. “The measurable output of our engagements is higher than ever,” says Baker. “Thanks to ibi, we have current stats on the number of phone calls, number of text messages, number of mailings, all tied to the number of applications that we’ve received. Our efforts are much more targeted and measurable than ever been before.”

The admissions application is just one example of how ibi analytics platform has transformed Taylor University’s use of information. Another new Academic Information Portal presents trend analysis metrics to the provost, deans, and academic chairs regarding enrollment, graduation rates, student success, relative growth of popular majors, persistence, and other important information.

“More requests are flowing into our office as people see the potential for BI, data visualization, mapping, and all types of analytics,” he concludes. “The goal of self-service analytics is for our Institutional Research and Academic Reporting personnel to field fewer calls and respond to less email because the user community can run reports for themselves.”