For many Jewish nonprofits, fundraising often can seem like an art — a process of educated guesswork based largely on intuition, word of mouth and experience.
So when David Gad-Harf, the chief development officer of the Jewish Federation of Northern New Jersey, saw a way to introduce more science into the process, he went for it.
With the help of the Washington consulting firm Measuring Success, the federation earlier this year combined information from its own database with survey results and data purchased elsewhere to rank 1,900 donors in order of the likelihood that they would become major donors (giving more than $10,000) down the road. The rankings were based on a list of 12 attributes that the data showed reliably predict which small donors will become major ones in the future.
Those who made a major gift to an organization in Israel or a major university, or already devoted a significant portion of their charitable donations to federation, were far more likely to become major supporters, Measuring Success determined. Meanwhile, the attributes that federations often believe make people big givers — a big life change, Jewish involvement in childhood, becoming an honoree at a gala event — didn’t turn out to reliably predict future giving, the data showed.
“We now have a much clearer sense of who are the people we should be engaging,” Gad-Harf told JTA. “This information is useful, but it’s only useful up to a certain point. You still need to reach out to them, open doors, cultivate them, engage them in the organization. But at least we have a road map.”
With nonprofits across the Jewish world struggling to maintain fundraising levels in a still shaky economic climate, organizations are looking to the promise of rigorous, data-driven analysis to increase efficiency and improve their operations.
“I think it’s finally clicking for a lot of lay leadership in many communities, many of whom have experience in evidence-based disciplines like finance or science,” said Sacha Litman, the founder of Measuring Success. “The idea is to analyze through data, identify trends and then leverage that to make effective decisions.”
Many of the methods being employed fall broadly under the rubric of what some have begun to call “big data” — the vast trove of information generated by everything from sensors in industrial equipment to millions of clicks on a webpage. Powerful computing algorithms can sift through the material, teasing out patterns and generating insights that otherwise would be impossible to identify.
Internet companies such as Google and Facebook and major retailers like Target and Walmart have been doing this for years.
Among the programs Litman has helped to create in the Jewish world is a soon-to-be-released mobile app called Grapevine that provides recommendations for Jewish events based on a user’s location and interests. Over time, the app learns the user’s individual preferences and habits to make more intelligent recommendations — much in the way that Netflix recommends movies based on past choices and user feedback.
Even more valuable for sponsoring groups, the app can collect precious, continually updated information about individual users: where they live, how old they are, who their friends are, what sorts of things tickle their fancy.
“All that data that we’re going to be gathering is going to give us a much better sense of what’s working in Jewish engagement and what kinds of things appeal to what kinds of people,” said Hindy Poupko, executive director of the Council of Young Jewish Presidents, which has sponsored the Grapevine project in New York. “This is data that our community has never had before because it’s been very hard to track.”
It’s precisely this sort of activity that has generated broad concern about privacy in an age when so much personal data is already tracked and recorded, from web surfing habits to where consumers swipe their credit cards for lunch. UJA-Federation of New York, which claims to be the first federation to hire a full-time data analyst, says it has “huge amounts of data” at its disposal and has made a strategic choice to exploit that information to maximize donations.
At the Scheck Hillel Community School in North Miami Beach, Fla., an analysis of standardized testing data revealed that Latino students were outperforming native English speakers across the board, including in English — the very opposite of what administrators had assumed. The insight led the Jewish school to conclude that more resources were needed in remediation programs for native speakers, not more ESL classes.
A similarly counterintuitive finding became apparent when the Gann Academy in Massachusetts undertook a survey of its parents, a project that Measuring Success helped the school to execute.
The academy’s head of school, Marc Baker, told JTA he had assumed that families whose children were receiving additional help would rank the school highest on the question of how well it supported individual learning. In fact, the opposite was the case — a finding that matters a lot given how much day schools rely on parental recommendations to drive enrollment.
Not every use of a data analysis requires cutting-edge tools, and many of the insights gleaned merely confirm what organizations already know anecdotally to be true. But the ability to demonstrate that knowledge numerically still has its uses.
At B’nai Jeshurun, a New York City synagogue that routinely draws hundreds to its Friday-night services, a 2011 membership survey showed that many participants felt unwelcome in such a large crowd and not truly part of a community. This was hardly a surprise. But the fact that there were numbers to back up the assumption helped the staff marshal resources to start a welcoming initiative.
“It wasn’t until we had the hard numbers that we were able to be proactive about making changes,” said Belinda Lasky, the synagogue’s executive director.
One of the data’s most powerful effects may be more political than analytic.
“In a community with so much access to leaders, I do think there can be a tendency for loud voices to have influence,” Baker said. “Data can help mitigate the phenomenon where one very loud stakeholder railroads through a priority.”
