Predictive Modeling 101 for Advancement Professionals

Last updated June 3, 2013

Predictive Modeling 101 for Advancement Professionals

Last updated June 3, 2013

Overview

Advancement shops are increasingly turning to predictive models to assess their donor pools and ensure that their most valuable donors are receiving the appropriate level of attention. Despite this trend, many front-line fundraisers are still unclear about what predictive modeling is, how it can be leveraged in their everyday work, and how to calculate a return on investment from the use of predictive models.

Join us online to learn the fundamentals of predictive modeling and how your shop can use this model to guide your fundraising strategy. You will hear case studies from institutions across the country that have successfully integrated predictive modeling into their operations.Included in your registration fee is a comprehensive glossary of terms commonly used when discussing predictive analytics.

Who should attend?

Advancement/development professionals, including: directors, executive directors, associate vice presidents, assistant vice presidents, and vice presidents will learn more about the basics of predictive modeling, the return on investment associated with developing predictive models, and the pros and cons associated with developing predictive models in-house. Please note: this session does not cover the specific details of developing predictive models.

Agenda

  • What is predictive modeling?
    • Overview of predictive modeling and analytics
    • Understanding how predictive modeling can help you do your job better
    • Using predictive modeling to determine strategy
    • Generating buy-in for investment in developing predictive modeling
  • Getting started with predictive modeling
    • Developing in-house models vs. using an external consultant
      • Data needed
      • Pros and cons of each option
      • Resources (staff and financial)
  • Case studies: using predictive models across the donor pipeline
    • Major gift example
    • Leadership gift example
    • Acquisition example
  • Assessing return on investment of predictive models