This is part one in a three-part series on the role of Big Data in the college-search process. Check back for future installments on sophisticated student-targeting formulas and data in an era of demographic change.
April is decision month for high-school seniors who still haven’t made up their minds about where they’re attending college next fall. With students applying to more schools than ever before—more than one-third now apply to at least seven schools—many seniors are likely weighing multiple offers as well as competing financial-aid packages.
As a result, colleges put on a full-court press in these final weeks before the traditional May 1 decision day, hoping a personalized email, a phone call, or a visit to campus with other admitted students will be enough to assure a deposit for the freshman class. But securing that commitment is becoming more difficult by the year for admissions offices nationwide. Yield rates—the number of admitted students who actually attend—have been in a free fall at all but the most elite institutions in recent years.
Compounding the low yield rates are stagnant retention rates among first-year students and colleges’ over reliance on tuition dollars as a main source of revenue. In a move to fill seats with students who will stay through graduation and are able to pay a significant slice of the tuition bill, colleges are increasingly turning to Big Data to better pinpoint prospects as early as their sophomore year of high school. The new approach builds on colleges’ efforts of the past two decades in which they aggressively adopted the playbook of consumer marketers by purchasing student names from the big testing companies—the ACT and the College Board.