Today, we collect and store mountains of information on our prospects – the work they do, gifts they make, events they attend, groups they belong to, and opinions they share. All too often, though, our big data sits in our big databases and leaves us at a big loss for to how to use it.
How can we make our databases smaller?
Predictive modeling (the use of statistics to predict an outcome) can help. It’s the same tool used by meteorologists to forecast the weather and by banks to evaluate someone’s likelihood to repay a loan. It can also be used by fundraisers to segment a prospect pool, to decide how to allocate limited resources, and to make our vast databases feel smaller. Modeling can help to:
- Rate an individual’s likelihood to make a gift
- Determine the optimal solicitation channel for a prospect
- Set appropriate ask amounts
According to AGN’s annual survey, 1 out of 3 annual giving program leaders considers predictive modeling to be an important part of their strategy. Moreover, this group also reported higher response rates for their direct appeals when compared with programs that did not consider it to be important. Perhaps predictive modeling isn’t as popular as it is effective, though it should be.
Want to learn more? CLICK HERE for AGN’s Webinar on Predictive Modeling for Annual Giving.