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Manage Yield, Avoid Melt

Reveal the status of your class with plenty of time and insight to manage yield and avoid melt by confidently focusing efforts on admitted students who have a high-predicted probability of depositing and enrolling. ENROLL, coupled with a solid yield strategy, allows you to achieve your enrollment goals year after year. Admitted students in the top decile of the ENROLL predictive model enroll at 5 times the rate of lower-predicted applicants.

main enroll dashboard
WHy Enroll matters

Next-level Enrollment Models

ENROLL allows you to gauge the status of your class ahead of time, and convert students from admits to deposits, and deposits to enrollments while optimizing your yield campaigns and melt control efforts.

Convert Students

Focus on admits who have not deposited but have a high likelihood of doing so.

Gauge Your Class

Know the status of your class with plenty of time to take effective action.

Save Resources

Save on your yield efforts by directing resources to students likely to enroll.

Augment Your Staff

Benefit from the insight and expertise of Capture’s data science team.

Enroll Machine Learning screen shot
Yield Maximization, Melt Minimization

Secure your Class with Confidence

ENROLL creates a robust enrollment prediction model that uses an extensive and diverse set of data including behavioral data, academic profiles, geographic data and more. Using ENROLL’s predictions, you can focus your yield strategy and outreach efforts, control melt, and shape your class with confidence.


Compare Deposits with Prior Admission Performances

ENROLL allows you to compare predicted enrollment with admissions performances from the same period in prior years. The model helps you allocate resources to students who are a better fit for your school. Also, you can model the number of students to admit. Running different groups of students you’re considering for admission through the model will show you predictions on what your class and financial aid picture will look like if you admit that specific cohort of students. 

data and chart screenshots from ENROLL dashboard
real time charts in ENROLL

Visibility Into the Details of Your Class

The ENROLL dashboard provides group predictions that offer insight into where your class will land and the characteristic composition of the class including gender split, diversity information, academic profile, and more. Knowing the enrollment prediction information early in the cycle (including shortages or surpluses) lets you appropriately alter yield communications and marketing efforts.


A Winning Late-Cycle Strategy

ENROLL comes with a team of experts to support adoption and application into your institution’s late-cycle process. You will receive 15 model iterations and the option (if necessary) to rebuild the model two times during the cycle, in consultation with your Capture data science team. Iterations are based on your enrollment cycle, representing your timing intervals.  

Virtue of Iteration
Best Practices screenshot

Best Practices for Using the Data

Predictive insights are most useful when paired with behavioral and actual human intelligence. ENROLL provides valuable insight into your incoming class through data and machine learning. In addition, Capture’s data scientists and account executives provide best practices for using this data across your institution on an ongoing basis. 

ENroll Outcomes

Increasing Yield

In a time of decreasing yield, the average Capture client with an ENROLL model saw a 1.5 percentage point yield increase (the percent of admitted students who enrolled) in their first year using the model.

The Proof Is In The Pudding

ENROLL’s Success Stories

Predicting Success – University of South Carolina

The University of South Carolina wanted a better idea of what their class would look like, so they turned to ENROLL, one of three predictive modelling products within Capture’s Behavioral Intelligence Platform.

Inspiring Women To Be Leaders –
Sweet Briar

Sweet Briar’s first-year enrollment increases by over 40%. Students, faculty and alumnae rallied to save their college and the decision to close was reversed.

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