Enrollment Analytics
Let us show you how you can quickly identify who is most likely to enroll and how you can change the outcome.
Let us show you how you can quickly identify who is most likely to enroll and how you can change the outcome.
Othot’s predictive modeling software transforms your data into helpful insights that you can use to drive your enrollment strategy. Predictions for every prospect are delivered in real-time and updated throughout the entire lifecycle, so you will know which students to target and how best to reach them.
A higher education institution used likelihood scores from the Othot platform to evaluate and analyze the quality of every lead from its list purchase. Othot’s analysis showed that ~6% of purchased names resulted in applications, but only ~1% were predicted to enroll. With this insight, the institution changed the way it approached list buys, relying less on names from purchased lists and focusing on higher quality sources of names.
Othot’s platform was created to take the cost and complexity out of predictive analytics. Our models are built from scratch for each customer to identify which students are most likely to enroll and how to influence that likelihood. We build and deliver our models quickly, so you’re up and running in weeks, not years.
Typically, we onboard customers in 30 to 45 days after data has been provided. We work with our customers to create a timeline that fits their needs.
Othot’s platform is cloud-based. You can access it 24/7 from anywhere on any device that has an internet connection and web browser.
No, our models are customized for each institution. The first step in our process is to identify the “High Impact Questions” (HIQs) that matter most for your school, such as, “What is the likelihood that a student will enroll?” Then our team creates a machine learning model built around answering that question. Othot’s predictive engines also combine a school’s historical data with external data and can be customized to create predictions for a school’s unique “What-If” scenarios, such as specific campus visit types or scholarships.
This proprietary approach produces predictive intelligence that offers a more comprehensive solution than other analytic programs.