The Behavioral Science of Fundraising Metrics
You’ve heard us talk about applying behavioral science to help nudge donors in the right direction with topics like:
- Symmetrically structuring your symbolic gifts
- The desire to complete sets and goals
- What happens in your brain as you donate
- Using the fresh start effect
- Creating exceptions to mental accounting
- How to frame your matching gift
But, did you know that the same behavioral science techniques work as a way of framing your metrics to your best advantage? Here are a few:
Loss aversion. Anyone familiar with The Undoing Project or the works of Kahneman and Tversky can skip down to where “retention rate” is written in bold. Scientists asked people to imagine preparing for the outbreak a disease expected to kill 600 people. If Program A is adopted, 200 people will be saved. If Program B is adopted, there is a 1/3 probability that 600 people will be saved, and a 2/3 probability that no people will be saved. Seventy-two percent of people opted for program A.
They also asked people about two other programs. If Program C is adopted 400 people will die. If Program D is adopted there is a 1/3 probability that nobody will die, and a 2/3 probability that all 600 people will die. Seventy-eight percent of people opted for program D.
The thing is that programs A and C are the same and programs B and D are the same.
The study is here. All that changes is the framing device. People hate the option of program C — that 400 people will die. And they hate the option of program B, where they can’t lock in gains.
The authors conclude that people faced with choices involving gains are often risk averse. However, we will take risks to avoid losses.
With that in mind, why do we talk about retention rate? Somehow in the mists of time, we’ve become numb to a 21% first-time donor retention rate.
What if we frame this with loss aversion: we are burning 79% of our newly acquired donors each year? And once we get them to second gift, we’re going to burn 40% more of them every year.
It sounds – it feels – more painful, no? And losing donors should hurt. If I make Thanksgiving dinner for 12, I shouldn’t celebrate the three people who didn’t have to go to the hospital; I should worry about the nine who did. (Bad example. But, I’m a terrible cook.)
We know that you, dear Agitator reader, are not standing in the way of making substantial changes to your program to increase retention. It’s someone else in your organization.
So perhaps framing retention in terms of a loss will shake them out of their complacency and get them to invest in that retention idea you’ve wanted to implement for eons.
Word choice. The words we use matter. Note my use of “burning” donors above. There’s a great study where they showed participants a car crash and asked how fast the cars were going when they crashed. Except instead of crashed, the authors tendered a few different verbs; here are the results:
- Smashed: 40.5 MPH
- Collided: 39.3 MPH
- Bumped: 38.1 MPH
- Hit: 34.0 MPH
- Contacted: 31.8 MPH
I wish I knew about this study back in high school when my parent’s car contacted a metal pole while I was driving.
So we aren’t “buying” donors; we’re “investing” in our donor file. We aren’t “bouncing” donors with our near-unusable landing page; we are “repulsing” them. And we aren’t “adding” a 13th mailing to our membership series; we are “rethinking” whatever life decisions got us to the idea that a 13th membership mailing is a good idea.
Like good copy, you can imbue your metrics with power through naming.
Identifiable victim effect. Since Ethel first donated to your organization in 1992, she’s given over 100 gifts. Nothing exorbitant – she’s now giving $30 every three or four months – but she also has volunteered, come to three walks, signed up for emails, and taken almost every advocacy action you offer.
On the other hand, you acquired Dorothy from an outside list in 2012. She gave $25, but nothing since then. You don’t have her email or phone number, but a last chance lapsed package piqued her interest four months ago and she gave another $25.
What do these two have in common? They look the same on a traditional RFM analysis: they are both 4-6 month $25-49.99 multis.
The behavioral science literature virtually screams that attaching a name and a person to a larger issue increases donations. I’ve also found it helps lay audiences understand that the metrics we have represent individual people and that the decisions we make to increase donor lifetime value mean that we’re going to focus in on Ethel and leave Dorothy aside.
Pictures. The human brain retains images better than anything else. There’s a semi-famous experiment where they gave noted oenologists (French for “wine snobs”) white wine with red food coloring. The experts used all the words that one uses to describe red wine, without ever noting that it was actually a white wine. When confronted with this, the so-called wine experts all resigned their posts and took up the study of nonprofit direct marketing to do something useful with their lives.
OK, I’m lying about that last part.
My point is that we privilege our sight over all other senses – in essence, we are all visual learners. When we see words on a slide, our brain, which is still trying to figure out why it isn’t hunting mastodons, sees the letters and must pause to think “what’s with all of those defective pictures?”
So graphs – especially those that have simple concepts like “this line is going up and up is good” – are your helpmates in relaying complex information.
Other thoughts on techniques to give your metrics extra power?
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