How Data Can Help Nonprofits Bring in More Donations

The data was all there. It was simple, really. All Joe Stabb had to do was analyze it. Stabb, a professor who also consults on fundraising projects, saw it when he was helping a college figure out who its best prospects were.

The Multiplier Effect

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After spending about four hours analyzing six months’ worth of email data, he found the 20 people who had most often opened email communications and clicked on links inside. Yet no fundraisers had ever visited them or asked them for a gift in person. Stabb added a final layer of analysis: He ran the names through a wealth-screening tool.

“We found out that there were five people out of the 20 that, based on their capacity, could give a major gift to the university — which for them would be a gift of $25,000 or more annually,” he says. “So within the first year of gift officers talking to these five people, we had one major gift come in — just from that one data set.”

That is the power of an organization using its data, Stabb says. By taking information that an organization already has, nonprofits can home in on their most promising prospects and better connect with all donors.

There was a time when many fundraising leaders were skeptical about whether data and analysis could really translate into more gifts or better, richer relationships with donors. The first step for data-minded fundraisers was winning over wary bosses. No more.

University of Tennessee

Still, nonprofits face plenty of roadblocks to incorporate data analysis into their fundraising programs. And the challenges aren’t all ones and zeros.

Building a strong fundraising analytics program requires deft people management as much as sophisticated technology. While development leaders are largely on board with data in fundraising, winning over the frontline folks who talk to donors can be tough. Fundraising teams also need to change how they operate. Database managers and analysts can’t be successful working in isolation. They need to be part of fundraising decision making.

“It’s really about trying to have people speak the language of analytics so that there can be a culture of analytics,” says Steve Grimes, associate director of data insight at Helen Brown Group, a prospect-research consulting firm.

The stakes are high. If nonprofits don’t integrate data into their practices, they probably won’t survive, says Nathan Chappell, senior vice president at DonorSearch.

“There’s no future where you compete effectively in a world where you’re not using big data and technology,” he says. “Every nonprofit that wants to be here tomorrow needs to be able to leverage data to some extent.”

Inside a Donor’s Head

Jon Thompson had a fundraising epiphany while watching TV with his daughter.

Thompson is the associate vice president of philanthropic strategy and technology at the Children’s Hospital of Philadelphia. And the show that inspired his epiphany was DuckTales, an animated series involving the ultra-rich Scrooge McDuck and his three nephews. During the episode, Scrooge ends up in the hospital, and Thompson briefly thought Scrooge might be moved to donate after getting excellent care. But that was wrong, and the light bulb went on for Thompson.
“Scrooge McDuck was both wealthy and now attached and yet still a jerk,” he says. “He wasn’t going to donate.”

It’s a truth that many fundraisers often miss in their piles of data: Wealth is not the most critical factor in seeking donations. Instead, it’s crucial to use data to find people who both give to causes and are connected to your organization.

“Wealth does not equal philanthropy,” says Chappell at DonorSearch. “We do not include wealth data in any of our algorithms. We actually take all wealth data out because wealth does not determine whether someone gives.”

Chris O’Brien, Children’s Hospital of Philadelphia

After Thompson realized that, he doubled down on using data to figure out how interested potential donors are in the hospital, whether they want to give, and even how they think. In addition to the data it routinely collects, the hospital also purchases data to layer on top of that — such as information from advertisers about which products people buy online and which other charities they support.

Thompson pairs that data with technology to build psychographic profiles of donors — an approach used in marketing to look at people’s attitudes, interests, hobbies, emotional triggers, and lifestyle. For Thompson, these profiles provide fundraisers the chance to craft tailored approaches to each person they interact with.

“It might say, John Doe is actually a little bit pessimistic, and by and large he’s investing in causes because he doesn’t think the world is headed in the right place,” Thompson says. “He’s investing not because he thinks it’s the right thing to do but because nobody else is doing it and he needs to solve this problem. We are able to give that information to the gift officers so they know what tone and syntax to lead with when reaching out to John Doe.”

In the past, the information fundraisers saw before meeting a new prospect was pretty bare bones, says Freddie Marianacci, executive director of development at the Cancer Center and Neuroscience Center for the Children’s Hospital of Philadelphia. They might have been told a donor had given $100,000 to other charities, lived in a $2 million house, and attended one gala.

Having the more holistic picture of the prospect lets fundraisers think more deeply about how to start a relationship, says Marianacci. “We don’t want the connections that we make at CHOP to be transactional,” he says. “We want them to be meaningful and long-lasting.”

The way the data is presented now helps gift officers find better starting places for their conversations with donors. “What’s most helpful for our frontline gift officers is not necessarily seeing all of those 800 data points that we have available to us,” Marianacci says. “We trust our research team and our data folks to provide the overall view, and we don’t have to lift up the hood to see everything.”

In addition to helping fundraisers understand how to approach a donor, the hospital uses machine learning to help identify who the best prospects are by analyzing people who have made big donations in the past to see what they have in common. Then it looks for potential donors to see who resembles those previous donors. One pattern the organization has found: People who give to international causes are more likely to donate to hospitals. While Thompson doesn’t entirely understand the correlation, he thinks it’s important to know.

So far the technique has been a success: Potential donors identified by the algorithm moved from their first connection with a fundraiser to making a contribution 17 percent faster than typical prospects. What’s more, their gifts were 22 percent higher, on average, than other donors’ contributions.

“If somebody moves through 17 percent faster, it really means that you can take on more leads than you could have [before],” Thompson says. “A gift officer who is typically working with 25 people now can start working with 35 because they’ve got extra bandwidth.”

Rise of the Database Manager

At the John F. Kennedy Center for the Performing Arts, fundraisers are using machine learning to paint a picture of who their donors are and how they’re connected to the organization — and then they use that information to identify their most engaged patrons.

The arts center received a $100,000 grant from Amazon Web Services for the project. It will allow the fundraising staff to combine information on donors, ticket purchasers, members, and other patrons into a single database. Then a machine-learning program will comb through past donor behavior to try to predict what current patrons will do next. The goal is to figure out what kind of performances they’re most interested in — just because people attended a ballet doesn’t mean they want to see an opera or a play — and identify who is most likely to give.

Yassine El Mansouri, The Kennedy Center for the Performing Arts

“We’re not just looking at the financial capacity of our database,” says Sarah Wilber, vice president of capital campaigns and strategic planning. “Instead, we’re really trying to say, What are the things that we can leverage within our database to tell us how people are engaged today, how they might become engaged in the future, and how can we use that — whether it’s for fundraising or even earned revenue opportunities moving forward.”

It’s a strategy that depends on a partnership between frontline fundraisers and the data-analytics team.

The data-analytics team relies on fundraisers to add the information they glean from one-on-one calls and meetings into the database for analysis. To make that happen, managers had to overcome fundraisers’ skepticism about the value of databases. In the past, the arts organization used a system that fundraisers didn’t find helpful, so they stopped entering essential donor information. Fundraisers were tracking stats in a spreadsheet they kept outside the database.

Once Wilber showed fundraisers the kind of reports she could generate if they just entered the information, it was transformational.

“When we put that in front of them and said, ‘We’re going to add in a couple of other tools that can help you increase your impact,’ it was deeply motivating,” Wilber says.

Persuading fundraisers to adopt the data-analytics process so they could spend the bulk of their time with donors was crucial, she says. “Their time is my most precious resource, and I can only spend it once.”

At its core, fundraising with data boils down to two activities: weaving data together to paint a holistic picture of the donor, and using that story to connect with donors in ways that draw in donations. That means it’s crucial for data managers and fundraisers to work collaboratively.

Yet experts say that’s not happening at many organizations. Fundraisers and the people who manage donor databases often work separately. What’s more, database teams are routinely excluded from discussions of fundraising strategy and decision making.

Jamie Shover is director of data and analytics at the Kennedy Center. She says an important part of her job is developing user-friendly ways for fundraisers to organize the data they need the most. For example, key details like dietary restrictions or special interests can get left behind in the notes field of the database or else are jotted down in a fundraiser’s personal notes on their donor portfolio but are absent from the database.

That’s understandable, Shover says. “It’s hard to capture in a data field the one piece of the conversation that really lit up someone’s face when they talked about it.”

Fundraisers might list the topics that interest a donor in the database, but it’s more challenging to convey how the tone of the conversation changed when a certain topic came up. Shover says that’s where a strong working relationship between fundraisers and their data team is key. “Sometimes maybe even a small adjustment to how something is captured can mean a world of difference in pulling the data out later.”

Frontline fundraisers are prized for their abilities to forge strong ties with donors, holding deep discussions about their passions and the legacies they hope to leave. Database managers are expert at using technology to get to the bottom of who donors are and what motivates them to give. It’s a skill that can deepen the work that frontline fundraisers are already doing.

Sam Laprade, a consultant at Gryphon Fundraising, says she hit her stride as a fundraiser when she stopped just asking her database manager to pull reports for her and asked what she as a frontline fundraiser could do to help the database manager. Their subsequent conversations led to innovative solutions, like assigning barcodes to each donor to simplify gift processing.

It’s important to include database managers in day-to-day fundraising strategy, rather than only calling on them when fundraisers have data queries, says Jay Kahn, senior assistant vice president for advancement and campaigns at the University of Oklahoma Foundation. He makes sure data analysts and prospect researchers are active participants in fundraising meetings and don’t just work at the beck and call of fundraisers.

“They’re not in meetings as support staff; they’re in meetings as partners, and they have a say in how the work’s going to get done,” Kahn says. “Fundraisers are encouraged to treat them like their partner, not like a service.”

Frontline fundraisers don’t win gifts on their own. Kahn says people like database managers and prospect researchers enable gift officers to identify potential donors faster and build stronger relationships with them quicker. “As a frontline fundraiser, you are not effective if everybody else is ineffective.”