This is part two in a three-part series on the role of Big Data in the college-search process. You can read part one on colleges’ year-long pursuit of students here. Check back for part three on data in an era of demographic change.
A decade ago, Saint Louis University found itself in a precarious situation. About half of the university’s 8,600 undergraduates were from Missouri and Illinois, and the demographic forecast for the Midwest looked bleak: the number of high-school graduates from the region was projected to drop by nearly a third by 2028.
So the university started to dig deeper for prospects in its backyard, purchasing more names of prospective high-school students from the College Board and ACT and targeting those teenagers with marketing materials. At one point, admissions officials at Saint Louis University were buying upwards of 250,000 names annually.
“We approached searching for students the way most schools did at the time,” said Jay Goff, the university’s vice president for enrollment and retention management. “We would take the demographics of the previous year’s freshman class and try to purchase more names that matched them the following year.”
Given demographic trends, university leaders knew that such a strategy was unsustainable. Like many of its peers, Saint Louis University also wanted to recruit from new geographic regions and improve the racial and economic diversity of its student body, as well as its retention and graduation rates. Those goals called for a new way of searching for potential students, and in doing so, created a new data-driven approach to admissions adopted by hundreds of other colleges and universities over the past several years.