WEBINAR

Predictive AI: How You Should Implement Propensity Modeling to Maximize ROI 

Thursday, July 17th, at 1:00 PM ET / 10:00 AM PT

What is predictive AI? And how can you avoid its pitfalls?

Predictive AI has the power to transform your fundraising strategy by helping you cut through the noise and identify the constituents most likely to give—even before they make their first gift. It allows you to be proactive instead of reactive, focusing your time and resources where they’ll have the greatest impact.

But the promise of Predictive AI doesn’t come from simply building a model or scoring a list. To truly drive results, you need to implement those insights effectively—and that’s where many organizations get stuck. From poorly integrated systems to unclear activation strategies, the most common mistakes can dilute or even derail your efforts.

That’s why Windfall is bringing together two of our top experts—CEO Arup Banerjee and Head of Solutions Engineering Matt Donahue—to guide you through the practical side of Predictive AI implementation. This session will focus not only on what Predictive AI is, but also on how to use it to increase donor conversion, retention, and lifetime value.

In this webinar, we will explore:

  • Best practices for activating propensity scores within your CRM so your team can use them in daily workflows
  • How to prioritize and segment prospects using score cutoffs, decile groupings, or tiered ratings
  • Real-world examples of how to engage prospects based on where they fall on the propensity spectrum
  • Ways to measure and track the ROI of your Predictive AI efforts to demonstrate value to internal stakeholders
  • BONUS: A look at how Windfall’s Nonprofit SaaS and AI application simplifies activation and delivers scalable, data-driven results

Please fill out the form to save your seat. We hope you and your team will join us!

Presenters

Arup Banerjee

Arup Banerjee

Co-Founder & CEO, Windfall

Matt Donahue

Matt Donahue

Head of Solutions Engineering, Windfall

Sign Up Today