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Executive Summary

Rahul Bhosale In collaboration with Elif Koekcechen

Introduction

Fundraising is a vital part for non-profit organizations across the world. To serve their Constituents, organizations greatly depend on the generosity of the public to continue1. Successful planned donation program building is a challenge, and worth the effort. So what’s an organization to do? Avoid the common mistakes organizations make, when attempting to secure planned gifts:2

♦Targeting the wrong prospects2 ♦Sending the wrong appeal2 ♦Asking too late2 ♦Soliciting planned gift prospects for major gifts2

Many times, these common pitfalls lead to poor responses and ultimately deter organizations from future attempts at developing a planned giving program. Too many organizations give up, inadvertently allowing them to miss a major opportunity to strengthen the long-term viability of their organizations2.

Objective

Use data mining to improve the number of donors from 5% out of 13 million records. Also to improve the donation appeal program in order to reduce expenses of the program and increase the donation from average $13.

Results

The use of data mining helps to define new strategy for the organizations’ Fundraising Effectiveness Project3. Looking at the top 5 records, sorted by Predicted value ascending, we can say that the person who has high income and wealth as well, have relatively higher possibility of being donor with significantly high amount. But the person having either income or wealth or both low will have less possibility of donation.

Table 1: Future fundraising prediction result, Top 5 records sorted by predicted value ascending. INCOME GENDER WEALTH AVGGIFT Predicted Class Prob. for 1 (success) Predicted Value

6 0 6 15.00 1 0.26 124.49 2 0 9 10.00 0 0.18 123.24 1 0 1 11.15 0 0.22 101.12 5 1 9 4.43 1 0.41 88.09

Table 2: Statistical comparison of previous year and predicted performance of fundraising

Fundraising F13 Future fund raising predictions Total Records : 2,099 Males : 827 Females : 1,272

% Males : 39.4 %Females : 60.6

Total Records : 2,000 Males : 809 Females : 1,191

% Males : 40.5 %Females : 59.5

Total Donors : 539 Males : 198 Females : 341

% Males : 36.7 %Females : 63.3

Total Donors : 1,222 Males : 431 Females : 791

% Males : 35.3 %Females : 64.7

Total Amount :$7,195 Avg amount :$13.35

Total Amount :$18,940 Avg amount :$15.5

%hike (Amt) : 263% %hike (Avg) : 116%

1 Jablonski L. 2 blackbaud 3 Drezner N.

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From the statistics of the results, it can be seen that out of 2,000 records 1,222 are found to be possible

donors. About 64.73% females are predicted to be donor, higher than total female count of 59.6%. The total predicted donation is $18,940 with average of $15.5

The statistics clarifies that females are more generous than male and have high probability of contributing to organizations. In both, previous year records and future predictions, the percent of female donors are approximately equal, 63.3% and 64.7% respectively, and noticeably higher than males.

Recommendations

Using data mining, organization can decide who to approach and mail. The selective persuasion strategy results in low, including but not limited to direct mailing expenses, thereby high net donation amount. Also the organization can solicit people based on other particular attributes about which they are most likely to donate. For example,

• When donors typically give? Do they respond to end-of-the-fiscal-year? [Behaviour] • Do they prefer to give at the end of the tax year? [Date and Time] • Do they respond to ‘crisis' solicitations? What are their solicitation preferences? [Preferences] • Do they prefer direct mail, e-solicitations, or telephone calls? [Method] • How do they give? Do they give online, by check, or by credit card? [Mode]

With this knowledge you can segment your mass solicitations by time of year and solicitation method that will be more successful and cost-effective to your budget based on the given donor4. Also understanding how to ask for a donation is critical. After identifying best prospects, for effective solicitations consider following tips:

• Simple message – ask should be clear, concise, and focused5. • Solicitations on anniversary dates5 • Adopt a segmented solicitation strategy – send the best type of solicitation for each prospect5. • Cultivate relationships with annual donors – build ongoing relationships with annual donors5. • Integrate staff activities – encourage annual fund staff members to work with planned givers2.

Caution

The data is powerful. However, it can also provide wrong directions. While trying to reach the goals of efficiency (minimizing fundraising costs) and effectiveness (maximizing growth in giving) some might interpret the data in a way that might lead them not to continue to approach certain segment of the database. We have to take a step back sometimes and see if there is something more, than what our data is showing 4.

There is a growing body of literature that looks at philanthropic giving within communities of color and how it differs in motivation and practice from the white majority (e.g.; Smith, Shue, Vest, & Villarreal, 1999; Gow Petty, 2002; Gasman & Anderson-Thompkins, 2003). Understanding these differences and the fact that the first principle of fundraising is that ‘people give because they are asked,' before we ‘write them off' we should look to our strategies and see if we can engage these populations in a more culturally sensitive way 4.

Conclusion

Using data in the creation and implementation of the fundraising strategy is the centrepiece of the Fundraising Effectiveness Project (FEP). By understanding the power of data, collecting it, and analyzing it, one can reach the both of these Efficiency and Effectiveness. The use of data within fundraising allows "our strategy [to be] grounded in facts, not assumptions"6. Using data to implement strategy will never obsolete the traditional development officer and their personal understanding and experiences, rather, the statistician’s analytics will always be needed to be interpreted by the development officers. Birkholz (2008, p. 210) reminds us that "it is easier for fundraisers to be successful when they are armed with the knowledge of context and implementation than it is for statisticians armed only with technology. [However,] when knowledge and technology come together, the potential is limitless" (p. 210). In the end, using data does not take the "art" of advancement away, it just adds the science. 4 Drezner N. 5 blackbaud 6 Birkholz, 2008, p. 3

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