Both an art and a science, enrollment projections have become a major component to effective college and university fiscal planning. With stagnant or declining state budget support for public higher education along with an increasing emphasis on revenue generation, never before has predicting the size of an entering class become more imperative. Too few students and budgets are sure to suffer; too many students and residence halls will be overflowing. This article presents several approaches to manage enrollment data for an entering class and predict enrollment yield. By examining past yield behavior coupled with trend and conversion data, a college or university will be better positioned to provide exceptionally accurate enrollment forecasts to senior administration. The authors provide pragmatic examples to empirically engage and data mine applicant pools for both first year and transfer populations in order to predict yield conversion with a greater level of confidence. Special attention will be placed on describing different statistical and mathematical techniques to predict enrollment.
Ever since the beginning of the Great Recession, higher education has braced for the impending age of austerity and changing demographics. Now a reality, these conditions threaten the ability of institutions of higher education to remain competitive in an ever growing global marketplace. This article presents several core SEM strategies that can be implemented for four‐year public colleges and universities in weathering these times of economic uncertainty and greater accountability. The authors weave in strategic recommendations for enrollment management leaders designed to more effectively expand the admissions funnel and engage in effective financial aid leveraging. Special attention is placed on how econometrics and elasticity of demand play in crafting an effective SEM response to fiscal exigency at their institutions of higher education.
The field of strategic enrollment management has become increasingly invested in data‐informed practices. In 2015, The College at Brockport, State University of New York implemented a recruitment strategy that incorporated both predictive analytics and customer relationship management (CRM) technology. This effort both reduced budget expenditures and yielded the largest incoming first‐year cohort in over 30 years. A step‐by‐step pragmatic approach is introduced to allow key enrollment management leaders the ability to understand how to seamlessly integrate statistical modeling with constituent relationship marketing platforms. By providing key components related to design, development procedures for statistical model development, and outcomes, SEM managers can utilize the knowledge gained from this primer in their SEM efforts.
Competition for students can be very fierce. With students shopping for the best deals, families will frequently scour the web for colleges and universities that offer the best value for their investment. Often a variance of as little as $100–$500 in net costs can make the difference on whether a student will attend your college or look elsewhere. For public colleges that have seen their state funding evaporate over the years, this situation can be fiscally devastating. And for private colleges and universities that are largely tuition‐dependent, these circumstances can be similarly harmful.
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