|
|
|||
|
|
|
|
|
|
||||
|
Spectra library collections analysis |
Simple Sample Analysis of Fundraising Data Introduction: We begin building your Affinity Insight Model by analyzing and exploring a comprehensive data pull from your institution's donor database. Once potential predictor variables have been identified, an appropriate statistical modeling technique will be used to produce scores. For each record, a score will rank the prospective donor on his or her affinity to your institution and likelihood of making a gift to you. You will then import the scores into your donor database so that they can be used for targeting of major and planned gift candidates and for generating optimal lists for annual fund mail and phone campaigns. The charts here are from a sample analysis of actual donor/ prospective donor data for a North American university. For all clients we perform a thorough analysis that looks at dozens of potential predictor variables and possibly several outcome variables. 
Chart 1. The Lifetime Giving bar chart shows that more than half of the alumni for this institution have given nothing and that fewer than a quarter of the alumni have given less than $115.
Chart 2. This chart shows that those alumni who have a home phone number listed in the donor database are more than twice as likely to have donated to the institution (27% vs. 56%) than those alumni who do not have a home phone number listed. The chart also shows that the home phone numbers were not necessarily collected when a gift was received; 43 % of those with home phone numbers have given nothing.
Chart 3. This chart shows that the presence of a business phone number is also a good predictor of giving. Almost 70% of those alumni with a business phone listed have given something to this institution, with more than 40% of these alumni giving $115 or more. As you can see, alumni without a business phone listing are less likely to be givers.
Chart 4. This institution records the sorority/fraternity affiliation of each alum. This chart shows that those alums that were affiliated with a Greek organization have given considerably more money than those alums who were not part of a Greek organization. And, like those with a business phone listing, many of the Greek-affiliated alums have given $115 or more in lifetime gifts to this institution.
Chart 5. The marital status chart also shows a pretty interesting story: 75% of those alums with no listed marital status have given nothing to this institution, while only 33% of those alums a listed marital status have given nothing. Clearly, the presence of a marital status code is related to giving.
Chart 6. The chart for graduation year is also informative. We see that giving is clearly higher for those alums who graduated in 1971 or earlier.
 Creating a Score. We can use the insight gained from the charts here to create a simple score for predicting an alum's likelihood for giving. Each of the variables to the right of the equal sign are 0/1 indicator variables. If a certain state exists for an alum a 1 is added to the score, if not a 0 is added. The 3 is a constant to keep the scores above 0.  For example, an alum with a home phone, marital status, and Greek affiliation listed in the database who graduated in 1980 would have a score of 5.
Charts 7 and 8. These charts show the results of our scoring. We see that both the number of gifts and the average lifetime dollars given to this institution are much larger for the higher scores compared to giving associated with the lower scores. Clearly, this simple predictive model helps identify those alumns most likely to give, allowing this institution to increase the dollars raised while decreasing the investment needed to raise those dollars. |
Health Care |
|||
|
|||||
|
|
|||||
