Cultivating Disaster Donors Using Data Analytics

Ilya O. Ryzhov, Bin Han, Jelena Bradić (2016) Cultivating Disaster Donors Using Data Analytics. Management Science 62(3):849-866

Posted: 21 Feb 2013 Last revised: 7 Apr 2016

See all articles by Ilya Ryzhov

Ilya Ryzhov

University of Maryland - Robert H. Smith School of Business

Bin Han

University of Maryland

Jelena Bradic

University of California San Diego

Date Written: January 24, 2013

Abstract

Nonprofit organizations use direct-mail marketing to cultivate one-time donors and convert them into recurring contributors. Cultivated donors generate much more revenue than new donors, but also lapse with time, making it important to steadily draw in new cultivations. The direct-mail budget is limited, but better-designed mailings can improve success rates without increasing costs. We propose an empirical model to analyze the effectiveness of several design approaches used in practice, based on a massive data set covering 8.6 million direct-mail communications with donors to the American Red Cross during 2009-2011. We find evidence that mailed appeals are more effective when they emphasize disaster preparedness and training efforts over post-disaster cleanup. Including small cards that affirm donors’ identity as Red Cross supporters is an effective strategy, whereas including gift items such as address labels is not. Finally, very recent acquisitions are more likely to respond to appeals that ask them to contribute an amount similar to their most recent donation, but this approach has an adverse effect on donors with a longer history. We show via simulation that a simple design strategy based on these insights has potential to improve success rates from 5.4% to 8.1%.

Keywords: business analytics; nonprofit operations; donor cultivation; charitable donations

Suggested Citation

Ryzhov, Ilya and Han, Bin and Bradic, Jelena, Cultivating Disaster Donors Using Data Analytics (January 24, 2013). Ilya O. Ryzhov, Bin Han, Jelena Bradić (2016) Cultivating Disaster Donors Using Data Analytics. Management Science 62(3):849-866, Available at SSRN: https://ssrn.com/abstract=2220915

Ilya Ryzhov (Contact Author)

University of Maryland - Robert H. Smith School of Business ( email )

College Park, MD 20742-1815
United States

Bin Han

University of Maryland ( email )

College Park
College Park, MD 20742
United States

Jelena Bradic

University of California San Diego ( email )

9500 Gilman Drive
Mail Code 0502
La Jolla, CA 92093-0112
United States

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