WebAdMIT Predictive delivers a likelihood-to-enroll score powered by machine learning—right inside WebAdMIT. With actionable insights at a glance, you can prioritize outreach, strengthen yield, and make smarter decisions without adding complexity.
WebAdMIT Predictive uses advanced machine learning models to analyze historical application and enrollment data, uncovering patterns that indicate likelihood to enroll. These predictions appear directly inside WebAdMIT, with additional interpretation fields for added context. Institutions can export predictive scores and related data to SIS systems or reporting environments for effortless integration with established workflows.
Gain deeper insights by adding Othot platform access. Access to the platform provides you with tools for impact analysis, cohort dashboards, segmentation, trend monitoring, and scenario modeling gives you the foresight to plan yield and enrollment initiatives with confidence.
WebAdMIT Predictive gives you more than a score, it delivers foresight. By leveraging machine learning, you’ll identify enrollment likelihood, prioritize outreach, and optimize yield strategies with confidence. Make smarter decisions that shape the future of your class without guesswork or complexity.
