Building Healthy Expectations with Fundraising Data (Part One)

Like most industries, the collection and use of data has been a hot topic in fundraising over the past decade. Fundraising has benefited greatly from data, and many in the field continue to pioneer new uses and applications that benefit both fundraisers as well as the donors they interact with.

But with all the data hype, many fundraisers and boards unfairly expect data to be perfect—a cure to all challenges. Although much of today’s data is very accurate and getting better, it will never meet that standard. Too often, one experience with inaccurate data damages trust of the information and supersedes all the instances where additional data was helpful.  For example, an organization pulled a profile from one of the big data services for a well-known donor in Des Moines which mistakenly listed the donor’s daughter's name under "Spouse". Luckily this faux pas didn’t damage the relationship with the donor, serving only as a reminder of the importance of validation (more on validation in part two).

Assuming data is perfect will inevitably lead to disappointment. The point of data is that it provides information that makes a prediction more accurate than simply guessing. For example, if I asked you how many points you think Los Angeles Lakers guard Kyle Kouzma will score in his next game, you would likely be pulling a guess from thin air (unless of course you’re a Lakers fan). But if I provided the additional data that he’s averaging 18.8 points per game this season, your guess would be a lot more accurate. Adding data points about Kouzma’s average in home versus road games, as well as the defensive ability of the team he’s playing would help refine your guess even further.

In a fundraising context, think of the benefit of more accurate information to inform ask amounts. Suppose you visit a donor who is passionate about your cause but lives in a very modest home. Because of their passion and gift history, you plan to ask for a $10,000 gift. But like the Kouzma example, adding an additional data point indicating the donor has a high net worth would likely revise your ask amount upwards. Now let’s say, based on this additional net worth information, you decide to ask this donor for $50,000. If they decline that amount but say they will donate $30,000, it might seem like a disappointment based on the ask amount. But even though the ask amount wasn’t perfect, the additional information still resulted in receiving three times the amount you would have without the data.

In part two, we will explore the importance of data and validation and building personal relationships with donors.