THE DATA OF FUNDRAISING
Episode aired Jan. 6, 2021: The Data of Fundraising
- data points you should be looking for to raise more and increase retention rates
- what your nonprofit is missing by not incorporating data into your operations
- how predictive modelling helps your fundraising and
- questions you need to consider when reviewing the data you’re collecting.
Below you can listen, watch or read this podcast episode.
Matthew: Hi Ephraim. Good, thank you. How are you?
Ephraim: I’m doing great. Let’s introduce you to our listeners, watchers and readers.
After coming out of a graduate degree in experimental psychology, Matthew Dubins stumbled into the nonprofit sector looking for a job that related to analytics primarily. At the time he didn’t realize that the nonprofit world would become the cornerstone to his entire professional focus. It was at his first nonprofit job that he started to hone his skills in applying analytics to understanding and predicting the behavior of peer-to-peer fundraisers and also of donors. Over the years Matthew gained experience working at agencies like KCI and Blakely where he realized that the consultant’s life was the one for him. Eventually he saw the need to take what he knew about donor analytics and predictive modeling and use it to start his own business. He’s been fortunate and privileged to work with such clients as Giving Tuesday, The Mustard Seed, Analytical Ones, K2D Strategies and Georgetown Hospital Foundation. While his favorite things to do are to create major gift prospect models and dashboards, he’s also happy to help with much smaller projects like wealth screening and surveys.
Fear Of Data
In today’s episode we’re going to discuss the data of fundraising. Let’s dive right in. Matthew, there are nonprofiteers who have a fear of data. Maybe they hate numbers, maybe the data is too overwhelming. How can they overcome that fear?
Matthew: Well Ephraim, that’s a really charged question that cuts to an issue that I believe I’ve come up against numerous times since I started my business. If we’re speaking hypothetically, I think that someone at a nonprofit who has a fear of data really needs to sit down with someone they trust, perhaps more than a few times and have it explained to them.
The key here is they must be shown the business value. What are they missing by not incorporating data into their nonprofit operations? How much better could their communications be by being mindful of donor behavior segments? What donor insights are they missing out on that could give birth to new and better communication strategies? How much time and money could they be saving by eliminating large swaths of donors from consideration in their annual appeals or their mid-level or major gift appeals? I’ve tried to communicate this with potential clients in the past but the reality is in those situations, I’m just not a trusted colleague and my message does have a tendency of getting lost in that regard.
Data Points Fundraisers Need To Use
Ephraim: Got it. Today’s actionable item: Could you please tell us three to five data points or markers fundraisers should be looking at carefully and constantly to help them raise more money and raise retention rates?
Matthew: Absolutely. So I’ve got four items to share with you. Number one, years of giving to the nonprofit. If you want to raise more high-level gifts, first you need to start looking at… we’re looking for donors who can and want to make such a gift. A great start to finding such donors is by looking at your pool of donors who’ve given to your nonprofit for many years, perhaps five or more years out of the last ten. Ask yourself, why do they keep coming back? It’s probably not because of the food. It’s because you built a good relationship with them. In the context of a good relationship, they’re much more likely to want to give at a high level, especially if you ask them the right way. You’ll increase the number of high-level donors over what might have happened organically.
Item number two, first gift amount. Another reliable indicator of people who are more likely to give at a higher level is the amount of money they donated as part of the first gift to your organization. Even someone who gave you know $50 or even like $100 is much more likely to go on to give at a relatively, a really high level compared to those who start who started at a lower gift amount. The key here is that after you notice someone coming in a higher than average first gift is that you must communicate with them accordingly, thanking them for their generosity and making them feel special. Subsequently pay close attention to them as this is another pool of donors where you’re more likely to find high level donors.
Item number three is appeal or appeal type preferences. There are some donors who are at a much higher risk of lapsing compared to others. They’re the ones who gave because there’s some specific pressing needs, such as a food drive or an emergency appeal. I get the motivation because I’ve been that type of donor in the past. So what do you do sending them every single one of your appeals and hoping for the best just isn’t going to work out so well in the grand scheme of things. What I like to suggest is that if you’re going to have any luck retaining these donors, hold off on contacting them until the next such appeal as what they had preferred over their lifetime on file. That way you’re not contacting unresponsive donors multiple times a year but rather only contacting them when they’re most likely to respond.
Finally item number four is letting the donor segments guide your communication strategy. Do you have a group of lapsed or inactive donors or p2p fundraisers? Of course you do. Everyone does. I want everyone listening to this to ask themselves whether it really makes sense to talk to these donors with the kind of language that says, Matthew you’re a legend! All in all you’ve raised 442 dollars when it’s been like five years since you last had anything to do with the organization. That’s a real story by the way of an email campaign that I got just this past weekend. Or more generally wording like, thanks for your continued support. Now wording like that tells the person on the other end of your appeal that you’ve turned a completely blind eye to what your donor hasn’t been doing in the past so many years. All you need to do is look at your gift history data and you can very easily separate out your lapsed and active donors from your current donors. You quite simply need to talk with them differently. Talking with them differently is an act of caring. It’s only logical to try to let them know that you notice it’s been awhile since their last donation, inform them about the good work your nonprofit’s done since then, continues to do. If you’re good at communicating, I promise you’ll get better results reactivating those donors. Those are my action items.
Ephraim: Fantastic answer and that email notwithstanding, Matthew you are a legend! Predictive modeling. What is that and how can it help fundraisers make decisions about where to get the most bang for the buck?
Matthew: Okay. Predictive modeling, for those who know me, know that it’s a topic that’s near and dear to my heart. At its most basic level in fundraising is the practice of teaching a computer how to distinguish between donors who engage in a charitable behavior of interest versus those who don’t. After this process of teaching the computer, you wind up with a list of characteristics which best predict who will do the thing that you want them to do, as well as a set of numerical scores that help you to sort your donors based on their likelihood to do it. I was purposely broad in my definition of predictive models and fundraising. Modeling really is a tool you can use on a very many… on a very large number of problems and in fundraising you could choose to use it to predict major gift likelihood, mid-level gifts likelihood, monthly donor conversion likelihood and churn likelihoods, just to give you a few examples. One of the best things that I like about creating predictive models is examining the essential data, insights that are generated along the way, things like creating maps that show how donors who live further away from the nonprofit are less likely to donate at a high level. Or possibly donors with a lifetime preference for annual campaigns or lower value or even how external giving to similar nonprofits helps predict high-level giving to one of my clients organizations. When I show clients these sorts of donor data insights, it allows them… it gives them ideas on how to change their donor comms strategies in the future.
Let’s Learn More About Matthew
Ephraim: Love that. Perfect. Let’s move on to the lightning round and learn more about you. If there’s one thing you could shake up in the nonprofit world, what would it be?
Matthew: I’ve been trying my darndest to shake up the nonprofit world since day one of oversight consulting and I’ve been trying to do it by bringing an implacable focus on high quality data, analytics, dashboarding, data insight and predictive modeling. Predictive modeling and external data all for very reasonable fees. Now it’s my fourth year of running this business and finally finally getting the response out of the nonprofit sector that I wanted.
Ephraim: Excellent. That’s good news. Algebra or calculus, which was easier for you?
Matthew: Algebra for sure.
Matthew: Yeah. I didn’t like either of them.
Ephraim: Three things or three reasons why you like living in Toronto?
Matthew: Number one is so many conveniences and necessities of life can be found not too far away from where I live. Number two, we have an enormous Jewish community here, as you yourself well know and number three, the food. So much food from so many diverse cultures. I love it.
Ephraim: I had never thought about the food aspect of why I personally love Toronto but fantastic. I love that answer. Thank you very much Matthew for appearing on the podcast today. You can connect with Matthew on LinkedIn and you can learn more about his work on his website, donorscience.ca Matthew, thanks very much!
Matthew: Alright, you’re welcome. Thanks for having me Ephraim.
Ephraim: A pleasure. Have a good day.
Matthew: Alright, bye.