By Joey Mechelle Farqué, Head of Content
Last week, a colleague shared an interesting article from The New York Times. It was about mice.
Specifically, the mice at the Kennedy Center, and the story the staff tell about them. These aren’t ordinary American gray field mice. They’re about half the size, with oversized ears and tan, almost golden fur. And according to decades of institutional lore, they aren’t American at all. When Italy donated thousands of tons of Carrara marble for the building’s facade in the late 1960s, the slabs crossed the Atlantic in straw-cushioned crates. Somewhere in that straw, the story goes, were a few Italian alpine field mice. Their descendants have been running the halls ever since.
It’s a wonderful story that stagehands pass to new hires, and it has been told for roughly fifty years.
Yet nobody ever checked it because it was such a great story, and they all wanted to believe it.
When a New York Times reporter finally did this summer, it took one email. A rodent specialist at the U.S. Fish and Wildlife Service replied within the hour: the photo was too blurry to tell an exotic Italian Apodemus from an ordinary local white-footed mouse. To know, they’d need to see a skull, specifically, the teeth. A Smithsonian curator was blunter about why the legend endures. People always want to believe their situation is special.
Maybe, as the reporter put it, the story was “too good to check.”
You’ve heard versions of these:
Each of these began as real observations, backed by data and reported by a credible source.
Some have remarkable staying power. Several years ago, Avalon, our lead agency, built an entire conference session around dispelling myths through file analysis. One myth read, “We need to target millennials.”
“The myth never dies; it just changes its target demographic,” says Jackie Biancolli Libby, SVP & Director of Client Services, Avalon. “It’s the same slide today with Gen Z in the headline.”
That session’s research found younger donors underperformed and were too costly to acquire. Whether it holds in a 2026 file is worth asking about and testing again rather than inheriting it as its own myth.
The mice are a precise analogy and not just a cute one. If you need truth and accuracy, a blurry photo can’t answer that question, no matter how long you stare at it.
Reporting is the right place to start. Channel averages, segment response rates, and year-over-year roll-ups tell you what happened and where to look next. But they’re also the blurry photo: pitched at a level where competing explanations of donor behavior look the same.
Individual-level modeling is the skull and teeth. Here’s one from VeraData’s files: A client believed their acquisition program couldn’t bring in gifts of $100 or more. Their average acquisition gift was $35.
That $35 was accurate. It was also the blurry photo. We built a high-dollar model, layered it with an acquisition response model, and reversed the ask string to lead with the highest gift. The average gift in the high-dollar segment ranged from $107 to $409.
The model found who could give more. Then we asked, and they gave.
Take the belief that major donors should be shielded from direct mail. It sounds like donor care. When one organization tested it, prospects left in the mail stream gave at 84 percent, against 60 percent for those “protected” in exchange for personal solicitation.
“Even strong major gift teams can’t always reach every donor in a portfolio consistently, especially as more donors engage asynchronously,” says Lindsay Marino Long, VP Donor Engagement & Retention, Avalon. “Working in close partnership with our clients, we layer direct mail in as air cover between MG touchpoints. It complements the personal relationship, keeping donors engaged and connected between those one-to-one moments. In one case, major gift revenue grew 19.8% over four years, with mail introduced in year three. Nearly 90% of that four-year growth came after mail was added to the strategy.”
How about the assumption that a donor who ignored your first drop won’t respond to a second? That’s testable at the record level. VeraData’s ReMail Model predicts the likelihood that a donor will respond after an initial communication, so the follow-up drop goes to the people most likely to respond rather than to whoever an assumed touch limit allows.
Verifying the Kennedy Center mice was easy and inexpensive. The specialist responded within an hour, and the test was available the entire time. Nobody checked because nobody wanted to. Asked whether she’d like to know the truth, one staff member said plainly that she’d rather not.
Same diagnosis for most untested assumptions in a donor file. Nobody wants to find out they were wrong. Testing a long-held belief means accepting that hard-won expertise might have picked up some folklore along the way.
The untested version costs more. Suppressed donors who would have given, spend aimed at the wrong audience. None of it appears on a report, so it can run for years.
An outside read helps. VeraData’s Strategic Audits and Descriptive Analytics Summary compare your file health, retention, and migration trends against benchmarks for your vertical. The audit tells you which assumptions to test; a model like ReMail is how you test one.
So, what do you believe about your donors that nobody has ever tested?
Make the list. Then pick one and check it.