Missy Garner, Former Director of Prospect Research
Rick Loveday, Prospect Research Analyst

Part 4: Using the Model

This post is the fourth in a four-part series that will outline how Clemson University’s Prospect Research Team developed a philanthropic model score.

Over the past few months we have looked at how to develop the concept of the project, in this case the model score (Part 1). Next we looked at how to build the model (Part 2). Nothing is ever perfect out of the box, so we then detailed how our team refined and tweaked the model (Part 3). Now that the easy parts were over, the hardest challenge loomed in front of us. We had to figure out how to introduce the score to our Development Officers.

Our Development Officers live in a world of hard assets. They are accustomed to focusing on wealth data like property values, salary, stock ownership, and in some cases personal property such as planes and boats. This model score asks our Development Officers to abandon most of that line of thinking. A full break from asset-based wealth would have been an impossible sell. That was part of our reason for keeping property ownership of $2 million or more in the model. It kept something that was familiar to the Development Officers, while still introducing some new logic.

One of the perks we discovered while doing research in preparation for the project was the analysis that DonorSearch had done on their own philanthropic database. They found some key levels of real estate ownership and how those levels tied into philanthropy.

• An individual that owns $750K – 1 million worth of real estate is 2 times more likely to give philanthropically than the average person.
• An individual that owns $1-2 million worth of real estate is 4 times more likely to give philanthropically than the average person.
• An individual that owns $2+ million worth of real estate is 17 times more likely to give philanthropically than the average person.

*https://www.donorsearch.net/how-to-identify-a-high-quality-fundraising-prospect

Using this information, we were able to show our Development Officers how real estate ownership is more than a wealth marker. It is also a philanthropic marker.

We rolled out the concept at the group, or team, level. We started with the Principal Gift Committee. This served the dual purpose of introducing it to a team and to our Vice President and Associate Vice Presidents, since they were all on the Committee. Simply showing up with a list of prospects would not be enough. We had to explain what they were looking at and why they should care. We included key points such as the real estate ownership stats (listed above) and the political giving stats (from Part 2).

We also created two cheat sheets to help make the score easily understandable. The first was a color-coding system that prioritized what we felt were the important groups. We added the minimum values for each of the scores to give a dollar range minimum for each color.

The second cheat sheet explained the dollar value associated with each of the decimal places.

While the Principal Gift team digested the cheat sheets, we saved the best example for last. In the course of building the model, we identified the perfect prospect to highlight the validity of using philanthropic data over asset-based data. This prospect had a history of over $700,000 in political giving. When we looked the prospect up in our database, we found the estimated wealth rating of just over $500,000. That rating labeled the prospect as a fringe Major Gift Level prospect who would likely never make it on a Development Officer’s radar. We saw shocked looks on the faces around the table as we relayed that information.

We also developed a report that tracked the potential principal gift prospects. It showed the attempted appointments and meetings for each prospect. At the request of the Principal Gift Committee, we agreed to review this report at the future monthly meetings.

As with any good project, our effort is never officially completed. It can always be tweaked or updated. With the success of the initial test batch screening of 5,000, we made plans to screen and apply the model to a larger group of our constituents. We recently screened an additional 25,000 people.

If you have any questions about this project or you want to know more details about building the model, feel free to email me at rloveda@clemson.edu.

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