Case Study: Johns Hopkins University reduces churn with Cliently

Predicting Customer Churn for John’s Hopkins University & Medicine well in advance and making recommendations to reduce it

Johns Hopkins University & Medicine, a leading academic and medical institution, faced a significant challenge with a 23% annual churn rate among its donors in key programs like Annual Giving and Gift Planning. This high churn threatened a major portion of their revenue, as retaining existing donors is far more cost-effective than acquiring new ones. They engaged Cliently to predict this donor churn well in advance and understand the underlying factors causing it.

Cliently implemented its AI-driven revenue intelligence platform to unify data from nine disparate CRMs, clean it, and build predictive models. Using machine learning and survival analysis, they provided each donor with a churn probability and an estimated churn date, enabling proactive engagement. The solution also calculated Customer Future Value to prioritize outreach, identifying 2,000 lapsed donors with an $8 million future value potential. Cliently's work provided a data-driven roadmap that is projected to reduce churn by 13%, saving 10,000 donors from churning in the following year and potentially saving $100 million in churn over five years.

Johns Hopkins University

Carlos A Rodriguez

Director of Business Intelligence and Analytics