Retain, reactivate or acquire: Can nonprofits reliably use community profiles as an alternative to past donation data?

Abstract

Nonprofits face the challenge of low response rates to solicitations, leading to unachieved fundraising goals. They face difficulty in retaining active donors, reactivating lapsed donors, and acquiring prospective donors. The challenge often stems from the need for more reliable data for predicting the expected behavior of different groups of donors. Although nonprofits have reliable data relating to past donations from active donors, the data on lapsed donors is limited, and data on prospective donors is nonexistent. We propose that nonprofits can use community-clustered donor profiles to predict the expected donations. Our results validate that predictions based on “actual donation data” and “community donor profiles” are equivalent in accuracy. Drawing insights from the nonprofit marketing and social psychology literature, we suggest that nonprofits can reliably devise targeting strategies for active, lapsed, and prospective donors using community-clustered profiles. We test these predictions using a donation incidence model and conduct several robustness checks.