Demonstrated Interest Goes Digital
Congratulations to the 1,088 students accepted to Barnard College's Class of 2022. You are part of the most selective class in Barnard's history. Barnard chose you from 7,897 applicants for an effective acceptance rate of 13.7%.
Barnard’s acceptance rate has dropped precipitously over the past four years. Twenty-four percent of applicants were admitted to the class of 2018, 20 percent to the class of 2019, 16 percent to the class of 2020, 15.4 percent to the class of 2021, and now 13.7 percent to the class of 2022. Let's explore how Barnard was able to achieve this impressive level of selectivity in such a short period of time.
Barnard managed to not only increase the number of applications received in each of these class years but was able to fill each incoming class even though Barnard accepted 213 fewer students to the Class of 2022 than it did to the Class of 2019.
Filling the incoming class is a key metric for all colleges as empty seats pay no tuition. Barnard enrolled 603 of 1,190 students accepted to the Class of 2021 delivering an enrollment yield of 50.6%. Assuming Barnard is seeking to enroll the same number of students to the Class of 2022, Barnard's enrollment yield will jump to 55.4%. An acceptance rate of 13.7% coupled with an enrollment yield of 55.4% places Barnard in elite college territory.
More Applications. Less Acceptances.
Barnard's performance is representative of the admissions metrics attained by many other colleges over the past 5 years. Student enrollment is the heart of the economic engine that drives universities and universities have become sophisticated users of predictive analytics to achieve their performance goals. By tracking prospective pupils’ digital footprints, schools can make calculated decisions about their admissions outreach and acceptance decisions. Enter the age of big data.
More colleges are deploying software that provides them with data-driven predictive algorithms for enrollment. "It’s smart business, certainly. But the practice risks turning schools from educational institutions into just that—businesses" says Robert Massa, senior vice president for enrollment and institutional planning at Drew University.
College admissions offices have begun to use algorithms that work on an individual-student basis to profile and predict their behavior. They use social media data, as well as the data supplied by the applications, to compute the likelihood a given student will enroll if accepted, the extent of financial aid needed by the student—or needed to recruit a relatively well-off student—and the chances that student will graduate.
For years, colleges have made predictive analytics a key element of their enrollment management plans. Schools use this information to help forecast the size of incoming and returning classes. They also use it to narrow their recruitment and marketing efforts to target those students most likely to apply, enroll, and succeed at the institution. Predictive analytics has also helped colleges anticipate the financial need of incoming and returning classes, and determine whether or not a student will accept the financial aid award offered.
A digitally-engaged audience offers colleges more touch points to educate, engage, and influence prospects. More importantly, digital channels provide more data to flow into algortihms allowing colleges to track, analyze, and understand prospect’s behaviors and motivations.