Prospect Research, Big Data, and Poetry

For those of us in Wisconsin, the NCAA championship didn’t go quite the way we hoped—despite the Badgers’ stunning victory in Dan Klamm’s March Madness Social Media Faceoff. But a shining light broke through my despondency when I learned that April is National Poetry Month!

It wasn’t long before I noticed that “prospect research” contains every letter in the word “poetry” except one: Y. So I will try to answer that now.

As Keith Hannon pointed out earlier this month, higher ed’s tightening budgets and fears about spending on overhead have advancement offices looking at every FTE position. Keith describes a new role at Cornell that has introduced efficiency: digital gift officers who leverage social media to reach, engage, and cultivate larger constituencies at a lower price point than traveling major gift staff.

Prospect research also introduces efficiencies to fundraising and, like an investment in social, an investment in research will initially increase administrative costs and overhead. Yet, when research is at its most effective, advancement offices will see their fundraisers asking the right people for the right gift, at the right time, and for the right program, which means fewer costly (and often embarrassing) mistakes. Just as poets are forever searching for the right words to tell their stories, so prospect researchers are looking for the right donors who, together with their nonprofit, will tell a great story. As Keith argues so passionately for an investment in social, I would argue for an investment in prospect research.

Two things that have the nonprofit world buzzing at conferences, in blogs, and on Twitter, are big data and overhead. These two concepts often come together in the world of prospect research, where tools—like data modeling, analytics, wealth screenings, and EverTrue’s GivingTree—streamline our work. Big data tools reduce the time it takes to identify top prospects by surfacing their public assets, known philanthropy, and recognized interests. And reducing time can reduce costs.

Several years ago, big data helped me quickly find and qualify the wealthiest nursing alumni in a major metropolitan area where the dean of our College of Nursing was visiting. Efficiency and overhead drove this small project. There wasn’t a gift officer assigned to this area, and the dean was already traveling, so she could visit and engage these newly identified alumni without incurring any extra travel expenses. Clearly, vetting only the wealthiest alumni in that large metro area took a lot less time and money than looking at all of them.

Additionally, by going to the right source and asking the right questions, big data helped me find the alumna who had built a million-dollar McMansion in a neighborhood of bungalows. When our analyst queried our screening data for wealth indicators at the individual level, I was able to find that outlier with the big house even though she did not bubble up in a wealthy ZIP code search and she may not have emerged in a Census tract query (such as I described a few months ago on this blog).

However, a recent story in the New York Times, which has spurred a lot of discussion in the prospect research world, points out some of the pitfalls of big data as it gets deployed in more and more industries. Now that it is being used to guide decisions where the stakes are high—in medicine, finance, and civil rights—some have called for retaining an element of human intervention. Meanwhile, others argue that doing so only “introduces human bias”—the very thing algorithms and data science are meant to remove.

I may end up on the wrong side of history, but I would still argue for the human touch—for verifying that big data has found the right Betty Smith and has correctly connected her to assets and interests. I believe that, like poetry, prospect research requires a human touch that big data can’t provide alone.

Finally, because it’s National Poetry Month, and prospect research is something I am passionate about, you are going to get a sonnet.

Some would say your work can by a machine
Be done. My love, I choose to disagree.
How to verify, save to intervene,
Data gathered automatically?
With shrinking budgets, and attention paid
To overhead, wherefore prospect research?
Efficiency! Decisions must be made!
Does she own property? Give to her church?
Are they philanthropic, even a bit?
Is he on LinkedIn? How much can he give?
Which of our programs will be the right fit?
Can a machine connect those dots, make them live?
With your human touch, the data, it sings!
Transformational gifts, your research brings!

Read Sarah’s “‘House of Cards’ Guide to Prospect Research” to learn more about storytelling through prospect research!   

 

Sarah Bernstein is an independent consultant in Milwaukee, WI, supporting nonprofit organizations with prospect research and database analysis. She earlier worked in both the social service and higher education sectors. Sarah is an active member of APRA International and past president of the APRA Wisconsin Chapter. She blogs at The Fundraising Back-Office and can also be found on LinkedIn and Twitter.