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Over the past two decades, technology has revolutionized the way people give to organizations they care about. In the late 1990s, donations were still about checks in the mail and credit card numbers over the phone. Today, websites, online banking, sites like Paypal and devices like Square have changed everything. People can even give a small pre-determined amount, often $10, by texting a specific number.

One thing that hasn’t really changed, however, is the way nonprofits find donors. Schools reach out to their graduates. Theaters target people who’ve purchased single tickets to a show. Animal welfare organizations mail out calendars and collect emails and phone numbers at adoption events. However, technology is finally starting to disrupt the way advancement departments evaluate and qualify potential donors.

One of the best examples of this is seen at the University of California at San Francisco. Instead of spending money on mailers and phone calls to all alumni, the University has found a way to target the donors who are most likely to give. They use an algorithm that qualifies potential givers based on a number of factors. Algorithms can be built that incorporate publicly-available data about income and wealth, and cross-reference it with information from donor profiles.

Anyone in fundraising knows that a personal touch can be important. These algorithms won’t replace personal interactions. They’re really creating an improved CRM system. People working in advancement and giving departments will still want to reach out to new donors to find out why they gave, thank them personally and find out why they feel connected to the organization. Where algorithms excel is in cutting through numbers that are unmanageable for humans.

Consider large non-profits, public universities and popular arts organizations have hundreds of thousands to millions of names in their databases. Algorithms allow these organizations to drop the names of low-income people who gave a small amount once. They allow them to target donors who have been consistent over a number of years, who have money to give, and who feel a true connection to the organization. The algorithms also divide the names in the middle into tiers. Those names can be also be targeted, but at the appropriate level at which they’re likely to give.