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Competition for donor dollars increases towards the year's end, when charitable groups, political organizations and universities all increase their appeals in an effort to reach their annual giving targets. Learn how to cut through the noise and find the alumni most likely to respond to your institution's donation requests.
Advancement leaders are always hunting for cohorts of alumni who have the greatest likelihood to donate. But all too often, seemingly promising segmentation approaches don’t reveal actionable differences in giving rates. See the alumni segment at the College of Charleston that has nearly a 2x higher giving rate, even decades after graduating.
Most advancement teams aim to have at least 65% of their annual fund completed by the new year. Whether or not you fall above or below this percentage, one expert offers three tips to help your team reach, or even surpass, your annual giving target this year.
About the Webconference Both old and new, these annual giving best practices from Royall & Company will ensure that your annual fund not only finishes the calendar year strong, but also supports your greater Advancement goals by increasing engagement and sustaining philanthropic support for your institution. Thanks for your interest! To access this content, please […]
Alumni donors increasingly fail to give without an incentive for doing so, but some advancement leaders have good reasons to avoid offering physical objects as rewards for donating. Wake Forest boosted alumni engagement with a playful micro-campaign that raffles off naming rights for minor campus landmarks such as a flat speed bump and a skillet used by the dining hall chef.
Donors who visit the giving page often have trouble finding the causes they care most about. To help solve the problem, Colorado State University has built a fun alumni persona web quiz into their giving page. The quiz assigns one of six giving personas to alumni. The personas map to funds on campus that stretch across divisional siloes.
This webconference will explore use of the "R language" to build a predictive model for annual giving. It includes an explanation of the "R environment," statistical programming, and advanced analytic methods. It also explores the results of a predictive modeling case study demonstrating the influence of various factors (e.g., affinity, previous giving, age, marital status) on annual giving.