Samantha Whitehorne is deputy editor of Associations Now in Washington, DC.
The Children's Cancer Research Fund uses big data and predictive analytics to uncover insights into donors' behaviors. Even better: Positive results have led to increased knowledge and greater revenue.
If you work for a foundation or nonprofit that relies on donations, you're always looking for ways to increase donors and contributions, lower direct marketing costs, and spark innovation and creativity among staff. Groups are turning to big data and predictive analytics to help achieve those goals.
Recently John Hallberg, CEO of Children's Cancer Research Fund (CCRF), had a realization. "Data is our biggest asset, in addition to our people and mission," he says. "We were not learning as much or gathering the insights that I knew were in our data."
Hallberg suspected that if CCRF dug into its data, it would likely
reveal valuable intelligence, such as which of its previous donors were most likely to lapse. Lacking the internal staff capacity to take on such a project, the nonprofit worked with JCA Analytics to mine CCRF's data and uncover insights into donors' behavior.
The outcome of the project has been overwhelmingly positive. "[W]e've seen dramatic improvements in our recapture rates," he says. "The analytics project JCA is doing to study our 'one-and-done' donors makes us smarter, better, more efficient."
For a recent acquisition campaign, which included new and lapsed donors, CCRF projected a direct marketing acquisition cost of $1.77 per donor. "We ended up at $1.24—a 30 percent reduction," Hallberg says. "We mailed to fewer people and acquired more donors." CCRF is in the beginning stages of another initiative with JCA that will identify midlevel donors and their communication preferences.
Hallberg says that mining good data does more than help the organization garner repeat or new donations. For example, when staff was talking to a potential sponsor about an event, CCRF was able to provide a specific reason to sign on: 70 percent of the 800 people who would attend fell in the company's target market.
For Hallberg, the success of the project has come in the form of increased knowledge and revenue. "For our direct marketing, it's pretty straightforward—lower our cost to raise a dollar," he says. "For the mid and major giving programs, it's more nuanced. The analytics gives us deeper dimensions to help us understand it."
He admits there's a learning curve to get staff to understand and use the data. "For example, if we can effectively identify our top prospects, we can help a gift officer spend their time more efficiently and our metrics around major giving performance improve," he says. "But we have to be committed to that work and to improving their skills in these areas. We need to empower our entire team to put the data to work."
[This article was originally published in the Associations Now print edition, titled "Donor Data."]