Dynamic predictive modeling scores are updated in real-time
To meet enrollment targets, Texas Tech University will turn to Othot for it’s dynamic predictive modeling. With a real-time dashboard that updates throughout the enrollment period, the “What-if” simulations will help the staff know who to target and how to reach them.
- THE NEED
- Predictive modeling ‘at the back end’ to drive enrollment strategy and shape the freshman class with best-fit students
- THE CHALLENGE
- Finding a predictive modeling solution so TTU can respond strategically and proactively to a student’s current likelihood to enroll
- THE RESULTS
- When probability scores are updated dynamically throughout the enrollment period, admissions teams can make the best use of their time and see what actions will have the biggest impact on likelihoods to enroll
Associate Vice President for Enrollment Management
I think this is the forefront of where the market needs to be. Since I’ve been involved in enrollment management, we’ve used predictive models at the front end, or what I call static predictive modeling. What makes Othot different is that it’s dynamic, not static: we get a realtime dashboard that shows us the current scenario 24/7.