Screening, Analytics and Predictive Modeling

Using data to make decisions is an integral part of successful fundraising endeavors. Data analytics can be utilized to achieve many goals including determination of fundraising capacity/potential at department or project specific levels, ranking and scoring of top donor prospects, development of gift pyramids, evaluation of donor pipeline, review and optimization of prospect pool and project specific prospect segmentation. Since our approach to data analytics is customized to client needs, we also offer specialized models based on your needs.

Utilizing constituent wealth screening data and building custom predictive models, we can rank prospects according to likelihood to give a major gift, planned gift or annual gift. Since our approach to data analytics is customized, predictive models will be adapted to determine donors likely to give to capital or program specific projects and resulting gift pyramids will be developed. For example, a customized predictive model can be built to identify and rank prospects with the highest likelihood to give a major gift to an athletics capital project or a planned gift to the specific academic program. Once these prospects are identified, we use constituency capacity analysis to develop comprehensive gift pyramids focusing on the size and number of gifts needed to reach specific project fundraising goals. Additionally, we can develop yearly fundraising goals and utilize historical trends to forecast progress and target completion dates.

Additional analysis, such as field officer analysis to measure productivity, is often beneficial to determine if additional staff is necessary to reach fundraising goals. Utilizing field staff historical trends, we can measure productivity at both an aggregate level and an individual level. This analysis will allow us to determine when campaign goals are likely to be reached or if additional staff are necessary to achieve the goal.