The Critical Step in Allocating Resources Across Alumni Relations and Annual Giving
Most alumni relations and annual giving operations have limited intelligence about who will be a strong reunion volunteer, annual giver, or alumni travel prospect—if the person has not previously participated in any of those activities. But rather than pulling a random database query and then reaching out at random to the contents of the entire resulting list, applying predictive analytics can help provide a more targeted allocation of your resources and more targeted messaging. Why Predictive Modeling is Critical Many organizations seeking to improve operating performance are turning to predictive analytics and predictive modeling to either increase revenues, decrease costs, or both. The size of our alumni population and database at Penn make focusing resources critical to fundraising success. The objectives of our early pilot projects in predictive modeling have been to reduce fundraising-related marketing costs and/or increase the dollars raised, or improve business performance in some other way. Here are examples of how our recent analytics efforts at Penn have informed critical resourcing decisions: The Steps for Effective Predictive Modeling The steps in the predictive modeling process are: Identification of the business need and a proper problem definition are critical for a successful project. In most data warehouse systems, […]