Automated segmentation of prospects (by demographics, GPA and SAT, educational background, academic interests, extracurricular activities, etc.).

Tracking enrollment KPIs (e.g., acceptance rate, yield rate, diversity metrics, enrollment by program).

AI-powered analysis of prospect applications to streamline the admissions process and identify patterns in applicant data.

Analyzing historical enrollment data to identify enrollment drivers and bottlenecks.

Marketing analytics, including lead scoring and campaign ROI calculations.

Benchmarking enrollment results against peers.

Predictive analytics to forecast enrollment numbers, graduation and drop-out likelihood.