Optimizing Constituent Engagement with Salesforce Einstein Prediction Builder

Predict what your supporters will do next. In this case study, discover how the National Kidney Foundation (NKF) partnered with Equals 11 to leverage Salesforce Einstein Prediction Builder. From identifying major donors to preventing churn, this project used AI to drive smarter decisions and more meaningful constituent relationships.

Print Length: 1 PDF - 4 pages
⏱ Estimated Reading Time: 5 minutes

What You’ll Learn:

• How National Kidney Foundation used predictive models to identify engagement levels, renewal risks, and donor behavior

• The “Equalizer Way” implementation process, from workshops to deployment

• Which constituent signals, like donation history or email engagement were turned into actionable forecasts

• The real-world impact: improved retention, donation lift, and strategic resource allocation