Data Mining a Non-Profit File for High Value Donors and Planned Givers


Data Mining a Non-Profit File for High Value Donors and Planned Givers


Presented by Perry D. Drake and Rhonda Knehans Drake at the SAS 2004 Data Mining Technology Conference, Las Vegas, Nevada

A non-profit organization needed to identify best donors in order to focus planned giving activities against the donors most likely to develop into “Planned Givers” and other “High Value Donors.”

The challenges regarding the objectives were:

  • highly seasonal donor campaigns
  • an acquisition strategy that favored the use of premiums
  • a retention donor strategy that leveraged RFM principles rather than treating all donors equally for a period of time
  • mixed use of premiums in the retention strategy
  • a declining acquisition and retention response due to name trading arrangements with other non profits

The successful development of identifying “Planned Givers” and “High Value Donors” began with the creation of cohort groups with appeal and donation activity frozen in time relative to a donors first gift.

Once the cohort groups were defined, data was then explored through factor analysis followed by segmentation and regression modeling to understand the importance of various appeal strategies and their correlation to “Planned Giver” activity. In particular, we examine how premiums with appeals, holiday appeals and a club approach to appeals impacts the likelihood of a donor to becoming a “Planned Giver.”

Using this combined segmentation and model strategy the increased likelihood of identifying planned givers rose from 1.1 percent to over 7.0 percent. This represents a gain of over 600 in the ability to identify this highly desirable group.


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