Tranforming Philanthropy Through Data

Analytics in FundraisingResults from the March 2010 Survey on the Current Perspectives and Applications of Analytics in the Nonprofit Fundraising Industry

In March 2010, DonorCast conducted an informal online survey of fundraising professionals engaged in discussions of analytics. Our goal was to better understand the current perspectives and applications of analytics in the nonprofit fundraising industry. The survey had over 60 respondents, representing a diverse group of institutions with at least a modest interest in data-mining and analytics.

0%

18% 18%

71%

0%

20%

40%

60%

80%

100%

<10 10 to 24 25 to 99 100 +

Percentage with Dedicated Staffby Organization Size

SoftwareIn addition to qualified staff, DonorCast looked at the software applications employed in analytics work. Microsoft Excel (75 percent) and SPSS Statistics (56 percent) are the two most widely-used tools overall for in-house analytics. Nearly 20 other software packages were used by at least one organization but none registered more than 10 percent overall. Additionally, 25 percent used data visualization software.

75%

56%

31%

12% 10% 8% 8%5%

2% 2% 0%0%

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StaffingWhile 85 percent of the respondents indicated they have a dedicated prospect researcher or prospect development staff, 28 percent of the organizations have a full-time, dedicated analytics or data-mining staff. As seen below, those organizations with large resources are generally able to hire these analytics specialists.

ApplicationsDonorCast also reviewed the types of analytics conducted along with the application of this work. Descriptive analysis (67 percent), predictive modeling (67 percent), and point-based rankings (53 percent) were the most common types of analytics produced. Others, such as clustering and forecasting, were used minimally.

Tangent to the types of analytics produced, DonorCast notes that prospect identification (88 percent overall) is the leading application of these analyses across most organizations. This may not be surprising since the prospect research profession has been an early adopter of analytics; however, it is important to note that other important applications exist and are used.

67% 67%

53%

25%

12%8%

2%

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88%

62%58%

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As mentioned earlier, 28 percent of the respondents have dedicated analytics staff. Of this total, 69 percent of those with a dedicated staff raised over $100M compared to only 28 percent raising that figure overall (see below). Hiring a dedicated mining staff does not necessarily lead to $100M raised annually, but this group, which is composed primarily of higher education institutions, could represent thought-leaders and innovators in the non-profit analytics industry.

Looking ForwardThe majority of respondents (75 percent) indicated that using analytics positively affects the organization while the remainder commonly noted they simply did not know how to measure its value. With this in mind, investing the resources—both staff and technology—necessary to adequately undertake a comprehensive analytics approach is challenging for several organizations. One part of this is lack of resources. Another part is the lack of a standardized, easy-to-understand and measure process for organizations of all sizes that non-profit leaders can more easily implement. As these holes get filled, the growth of analytics in the industry could grow exponentially.

18%

9%

39%

20%14%

0%6%

0%6%

0%

69%

19%15%

7%

30%

15%

28%

5%

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<$5 million $25-49 Million $5-$24 Million $50-99 Million $100 Million or more

NA

Overall

Research University, 38%

Private College, 15%

Master’s Level University, 8%

Specialty Healthcare, 7%

Children's Hospital, 5%

Academic Medical Center, 3%

Healthcare, 2%

Arts, 2%

Social or Community Services, 2% Other, 18%

Survey Participant Breakdown

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