Equity and Efficiency: Navigating the New Frontier of AI-Powered Analytics in Philanthropy

By Mark M. Parker CFRE, Director of Consulting Partnerships, DonorSearch; Associate Consultant, Rose City Philanthropy

I have had a front-row seat in recent years to witness a marked change in how the not-for-profit space thinks about prospect development. A long overdue assessment of what works and what doesn’t work with conventional prospect analytics is well underway. The summer of 2020 was an inflection point. In the midst of the national conversations concerning race and social justice emanating from the murder of George Floyd, not-for-profits and consulting firms were increasingly challenging prospect analytics vendors to help expand, if not redefine, the established notion of what constituted “good” donor prospects.

In my thirty years in this space, identifying “good prospects” generally meant following a “go-where-the-money-is” strategy, and prospect analytics evolved accordingly. The available tools got better, cheaper, and more granular in unearthing and scoring prospects based on markers of wealth: real estate ownership augmented with SEC filings, philanthropic contributions, business ownership data and the like. And we all went about our business of weighting gift officer portfolios with those who rose to the top in our wealth-driven scoring rubrics. We were data-driven, and at the very least we were diving into the most promising of haystacks in search of the needles that would lead to our financial goals.

Meanwhile, the 80-20 Rule (80% of dollars coming from just 20% of the donor population) morphed into the 90-10 Rule as mega-gifts got more and more mega and the overall number of donors turned persistently downward year over year.

There were always flies in this ointment: the Venn diagram of wealth and generosity is anything but a circle, as every gift officer soon learns. But, if we are being honest, the limitations of “wealth screening” must be spelled out in more blunt terms: it is fundamentally biased in the direction of where wealth is concentrated in our country: aging white males, my own demographic cohort.

Kristel Enter, a prospect researcher at Massachusetts General Hospital, sums up the status quo precisely: Writing for the February 2022 APRA Journal, Enter makes the case that prospect researchers “devalue prospects and donors from historically excluded groups, which perpetuates a homogenous donor base.”

Enter rightly notes that the “people we are researching are multidimensional and cannot be summarized in assets, wealth indicators, and capacity ratings.” Yes, people are complex and defy simple categorizations; and yet some form of categorization or segmentation is vital for making any actionable sense out of large populations of prospects.

We plainly need smarter tools to inform more equitable and more productive prospecting processes.

Fortunately, here in 2024, we have incredibly powerful and subtle technologies at hand to fundamentally alter prospect research for the better—the technology that kindly informed me this morning that I am consistently meeting my sleep goals and that my morning commute would be 8 minutes in light traffic.

Yes, Artificial Intelligence.

AI is already at work, or soon will be, in your organization’s CRM. And AI applications are increasingly at work in the data and tools provided by your analytics vendor. To me, these advancements represent the most dramatic and promising breakthrough for non-profits since, well, the introduction of wealth intelligence in the 1990s or even the advent of the internet as a tool for “knowing” someone without having to even talk to them.

Only the promise of today’s technology is so much greater. AI represents a breakthrough in our ability to measure affinity—and in real time; a breakthrough in eliminating the human biases in conventional predictive modeling, a breakthrough in portfolio management, priority setting, and resource allocation. These are huge advantages as we work at once to reverse the decline in America’s donor pool and to realize the full potential of philanthropy in general.

Think of a pool of people where AI has identified those who really do want to talk with a gift officer or be invited to an event. Or any of the following scenarios:

The 1,500 out of 100,000 medical patients who are grateful and motivated by the exceptional care they or loved ones experienced.
The 2,500 out of 100,000 alumni of a university, who based upon their interactions over many decades with AI, are known to look fondly on their educational experience.
The 5,000 out of 500,000 people who visit a museum each year and, who, thanks to AI insights, should receive a follow-up letter or email about making a year-end gift because they love the museum and/or had a terrific time on their visit.

That kind of analysis will get us to the heart of the matter. While AI-driven analytics will, I believe, prove unprecedented in its ability to accurately point us in the direction of philanthropic potential in communities of color, and help us discover new avenues for support, the final mile remains very much what it has always been in fundraising: the actions and choices of gift officers and their leadership.

Our behaviors will have to be equal to the promise of the technology. Fundraising success, as always, will be achieved by teams driven by curiosity, an affinity for people and for positive change, and the drive and skill to build new relationships and new spheres of engagement. As my fundraising mentor never tired of reminding me, “we (fundraisers) are brokers of peoples’ philanthropic needs.”

Let’s hew to that wisdom and not just embrace but pursue new relationships grounded in genuine affinity and connection, wherever they may be found.

Learn more about Mark Parker here.

Marts&Lundy partners with DonorSearch Ai to ensure our clients have the most advanced machine learning solution.