Higher Education: Deploying Predictive ROI-based Analytics within Student and Constituent Lifecycles
Presented by Chris Engstrom, Director, Data Science
Colleges have a problem: fewer applicants every year and rising costs. Universities are competing for any edge they can get including offering more financial aid and others are building state of the art facilities. Most colleges and universities are facing increased competition for new students while at the same time struggling to identify and retain their current students.
Lost revenue due to student attrition can be alarming and can contribute to a pernicious cycle that puts additional pressure on costs, tuition, and the institution’s reputation. Applying predictive analytics within defined student and constituent lifecycle frameworks allows administrations to improve admissions processes, increase student retention, and better engage alumni and donors.