Challenge:Increasing number of organizations are realizing the value of predictive analytics and what it can do for them. A non-profit museum needs to generate a highly targeted prospect list for their upcoming fundraising campaign. Since it’s difficult for a small size organization to employ full-time statisticians and data scientists, Kavi Global stepped in to help them build predictive models in SAS Enterprise Miner and to meet their business goals.
Solution: Rapid Predictive Modeler, an Enterprise Miner add-on, helps business managers and subject-matter experts with limited statistical expertise quickly generate their own predictive models. Kavi Global trained the museum managers and analysts by demonstrating the development of the predictive models for their upcoming campaign. To increase the overall campaign yield and target better, the following two models were built – a) predicting the likelihood of donations for every prospect, b) predicting the likelihood of prospects capable of donating major gifts, i.e. above a certain monetary value. With the right partner and the right tools, the development of these model took less than a week, leaving the museum enough time to roll out a top quality campaign.
Outcome: The ensemble model developed in SAS helped museum maximize their ROI, i.e., top 20% of the prospects had an 85% likelihood to donate to the museum.
