Academic Partnerships provides outsourced enrollment services across four verticals, where they support marketing, application, and enrollment activities for 60+ partner universities. They needed a roadmap to identify and prioritize ways to leverage AI and machine learning to improve the student journey and increase operational efficiency.
Atrium helped develop a roadmap prioritizing AI use cases to improve the student journey and increase operational efficiency in the student life cycle. A lead-to-application propensity model was created using marketing data sourced from opportunities and phone/email/SMS contacts (InContact, Silverpop, and Marketing Cloud). We identified driving factors steering application propensity including: re-inquiry, campaign sources, contact cadence, and early successful contact. From there, a differentiated contact strategy for leads based on source, lead age, and presence of a re-inquiry was suggested.
By project completion, Academic Partnerships realized more effective management of their funnel to nurture students to complete the application process. Atrium helped form a targeted contact and content strategy based on insights and propensity to apply, reducing the contact attempts to get to re-inquiry faster. Additional data integration sources were identified, which will yield further insights into their lead-to-apply process. As a result of these enhancements, AP expects a 10-20% improvement in lead-to-application completion rate, and a ~25% decrease in new enrollment melt rate (abandoned enrollment).