Enrollment management refers to both the recruiting of new students and the retention of currently enrolled students. As the start of a new academic year nears, it can seem like an enormous undertaking to determine what your class size is going to be, and how many returning students you will have.
In this on-demand video, Senior Data Analyst Jon MacMillan discusses how you can use historical data to predict which students are most likely to enroll while simultaneously predicting their likelihood of retention.
This presentation focuses on the data preparation required to create these predictive models, as well as a walkthrough of the actual model building process for both an enrollment and an early retention model. These specific models can be used to predict your incoming class size, as well as identify students who may be at risk of attrition before they even step on campus. You will learn about:
- Common data points for enrollment management models
- Different methods for predicting both enrollment and retention
- How to utilize model results
This presentation includes an in-depth product demonstration of the Veera platform, an analytics platform for data preparation, analysis, and access.