Mathew Dubin founded Donor Science to help nonprofits tap into their own data to develop smarter, evidence based strategies to raise more funds. He joined us on the podcast to tell us more about Donor Science and how he has helped his clients discover unlock insights about their donors.
In this episode we talk about using your donor data to create better marketing strategies that will save your organization both time and money.
Sabrina: Hello and welcome to the Fundraising Superheroes podcast, a podcast celebrating nonprofit organizations and all the people that work to make the world a better place.
This podcast is brought to you by Donor Engine, a fully cloud based nonprofit management software platform that will transform your organization through its powerful, customizable, easy to use features. Visit donorengine.com today to learn how your organization can spend less time managing your nonprofit and more time focusing on your cause.
I’m your host Sabrina Sciscente and today we have the founder of Donor Science Mathew Dubin on the show with us. Donor Science uses your own data to help your organization become and stay competitive in today's crowded charity market. Their mission is to help charities increase donations and reduce campaign costs so they can be more effective. Thank you so much Mathew for being on the show!
Mathew: Oh you're welcome Sabrina I'm glad to be here!
Sabrina: So can you start us off by telling us how you got started working in the non-for-profit industry?
Mathew: Sure, well to tell you the truth it wasn't even on purpose. So after graduate school I sent out over a hundred resumes to companies across Toronto. Really I was trying to target companies who were offering job positions that had something to do with a data analysis. One of the companies that ended up giving me an interview was the Canadian Breast Cancer Foundation. So I ended up taking the job, the job title itself was the run data and research coordinator for their National Run for the Cure event.
I basically was doing a lot of regular an ad hoc analytical reporting work for the Run for the Cure and while I was there, I realized that doing data analytics work for the nonprofit world was something that provided a lot of meaning and positivity to my professional activities. What I would learn in the years after I worked there was that I was much better suited to analytics consulting work for multiple nonprofits. Rather than just being an in-house analytics person living under the same work life cycle from year after year.
Sabrina: Awesome, so you like that idea of working with more than one place to solve different types of problems and having variety in the data you collect?
Mathew: Oh my goodness, I crave it! I really crave it, you know? I need all sorts of challenges in order to stay interesting, and to be honest the challenges don't have to be overly complicated. It just has to be a different nonprofit or a different nonprofit facing organization and just a slightly different problem than what I was dealing with the last time. I like getting that variety and I just really like learning as much as I can about the industry through the analytical work that I do.
Sabrina: Yeah, cause I’m sure numbers can tell a lot about how a nonprofit is managing and can also give them a lot of insight on how to move forward.
Mathew: Ya, absolutely. The numbers definitely always have an interesting story to tell, but if I'm being honest that's really sort of half the stimulation for me, I mean the other half is the actual personalities who I work with. And the organizational structure and like how it gets things done and you know what impact the work that I do has on their organization, how much of a difficult time their organization has perhaps changed as a result of the work that I do. Maybe the work that I do, it just gets put on a shelf somewhere and then you know nothing happens.Or, on the flip side, maybe the work that I do actually ends up getting used and ends up having a really positive impact because the organization has a certain willingness to change.
Sabrina: So going into more about Donor Science, I know I gave a little bit of an intro at the beginning of the podcast- but can you tell us in your own words what the organization is all about, what your goal is, and the services you guys offer?
Mathew: Sure, well the basic idea is to take analytics and data science work and use it to help nonprofits save on the cost of soliciting their donors but also to help find them opportunities for net new donation dollars. So we do that through any number of services that are offered such as the web apps which we got into in a bit, the statistical donor model work that I do as well as online surveys that we are able to create and deploy.
And really throughout any of this, the basic idea is that the more that you know about your donors the more insight that you have and certainly the more you’re able to predict about your donors the better your fundraising performance is going to be. Because you're going to waste a lot less time and money in terms of soliciting your donors, whether it's through direct marketing or possibly major gift solicitation, whatever the case may be. And, also you're going to come across information that's gonna be of huge strategic value to the organization and when you come across this information often times what happens is the nonprofit realizes that "hey there is a a new strategic, what's the word I'm looking for, direction is the word I’m looking for on the basis of this analysis. Why don't we change the way that we're doing things so that we can really take advantage of the donor data insight.
And I'll give you an example of this a little bit later, but anyway in almost all cases the work that we do usually involves the nonprofit sharing some aspect of its anonymized date with Donor Science consulting, or possibly sharing it directly to our web apps. And then in return they get some kind of summary analysis or prediction which allows them to do better with their fundraising. And that’s a very high level description of the company and our services.
Sabrina: So you mentioned some of your webapps, so you have Donor Fam and you have Donor Focus. What do they do specifically, how are they different from each other?
Mathew: In both cases, you start with a gift history file but then what the apps do with that gift history file are quite different depending on the app. In terms of Donor Fam, what it does is it takes that file and it summarizes it in order to give the an attractive looking summary of the donation activity in their database. The levels get broken down into three overarching dimensions namely the recency of giving, frequency of giving and monetary level of giving. So it then shows how many donors all into any one of these categories or dimensions, like how much money was transacted from donors that fell into any one of these dimensions as well as the numbers gives, the average gift, median gifts and so forth. As well, it will then it will show other nonprofit has trended over in terms of these dimensions as well as some other info like number of new donors and second gift rates.
I feel like this need to like a little bit more explanation, and so just taking a little bit more concrete with what I mean, so when I say recency of giving I mean things like is this a new donor is this a renewed donor, is this a three-year consecutive donor. So you know, not only is this donor a current donor but they've been giving for 3 years in a row or 4 or 5 years consecutive donor or has it been a couple of years since this donor has last given.
Or is this donor just totally inactive, like it's been you know three plus years since this person has last given any money. So that's the recency dimension as I see it. Frequency of giving I take to mean and how many gifts did the donor give to their nonprofit in their most recent year of giving. You know, one gift 2- 5 gifts, 5 -10 gifts whatever. Monetary level of giving I think is fairly self-explanatory, so you know it was in the donors most recent year of giving, did the donor give $1-25, $25-50, $50-100 and so on and so forth.
And I mean the thing to remember about charitable giving is you're going to have quite a few nonprofits for whom the average or typical gifts are you know, maybe $30 to $50 and so once, once you get high enough beyond that interval you're talking about people who are probably well within the top 10% of the entire database. Maybe the top 5%, maybe the top even higher than that, so really overall when you have this information it enables you to be much more cognizant about what's going on with charitable giving in your database.
And than, very importantly you can go from analytics to action by using this information to inform the way that you communicate with these donors because perhaps your most loyal or your highest giving donors should be spoken to or written to as whatever the case may be, a little bit more differently. You know for someone who's in the top 5% of your database, you maybe should start talking to them in terms of thank you so much for your incredible generosity. Whereas it would kind of feel a little bit, it can be arguable that it's a little bit of a joke to talk to someone who's given like $5 in terms of thanks for your incredible generosity. So being a little bit more sophisticated in terms of your communications using the data that you have I think can go really quite a far or long way.
The other sort of example of using this data in order to inform your communications is in terms of how long it’s donor has been since the donation happened. So if it’s been over 3 years since the person last gave to you communicating with the donor in terms of saying "thank you for your continued loyalty”.Well the donor probably doesn't even remember your organization, so getting a direct mail piece or you know telemarketing or email marketing piece in their inbox or phone, you know talking about how loyal the donor is when they really have not been so loyal. It's just, it reaches a level of irrelevance which just serves nobody well at all, so anyways that =’s Donor Fam. So it's really all about database segmentation, and knowing how the nonprofit is doing at its cardinal or most important function which is fundraising.
Now moving along to Donor Focus, Donor Focus will take a gift history file and use it to automatically create predictive recommendations as to what to do with each donor in the following year. Does the nonprofit renew a particular donor with the same ask amount, to renew an upgraded ask amount, reactivate with the same ask amount or are there donors who are a turn risk or risk of lapsing and therefore they should steward them carefully.
And the way that it creates these predictive recommendations is that it actually automatically creates these four very helpful machine learning models on the basis of giving behaviour. So, one is just you predicting likelihood of renewing in the following year, the other is predicting likelihood of upgrading and the next is predicting likelihood of reactivating given that it's been at least a year since the last donation, and finally predicting the likelihood of lapsing in the following year. So this is really neat because basically it takes a lot of the guesswork out of direct marketing. You know that the people who it’s grouping into each predictive recommendation are really your best bet in terms of what it's recommending you to do. They’re the highest scoring and when you follow those recommendations you really reduce by a significant degree the number of people who you're just sort of making the wrong move with.
And when you do that you cut the cost of solicitation by quite a lot, and in some cases like in terms of the people who he recommends you upgrades or the people who you treat a little bit differently because there is a turn risk your actually helping to bring in more donation money then you would otherwise. Does that does that make sense?
Sabrina: Yeah, so it really helps with your communication strategy and knowing how to communicate with different donors
Mathew: Yes, exactly
Sabrina: What is the biggest mistake or discovery your clients discover when they start working with you and see visual representations of their donor data. Do you find that there is a common mistake or is it different for every organization?
Mathew: So I mean really there are different issues or mistakes or whatever or depending on the organization that I work with but if I could identify a commonality not in terms of mistakes, but in terms of discovery, its that the primary discovery my clients find is that they have a way forward. Now every analysis I do is based on a foundation of strategic utility, the key question to ask is how will this be useful for my client in terms of helping them to build or maintain a fundraising strategy. And in every case there's always some nugget of information that ends up being useful.
So one story that I can tell in this regard, was there was this one nonprofit I work with out in Alberta. It’s like a faith based social services agency, for them I was doing a major gift statistical model. While I was creating these donor data insight graphs and such as that showed some sort of bad owner data insight on the basis of my analysis. And so on one of them the graph was showing the extent to which donors went on to give $10,000 or more on the basis of prior monthly giving.Like on one side of the grass was how much money, did donors give through their monthly giving program in total over the prior two years before the $10,000 was given. And then the height of the bar graph had represented and what percent of those donors have gone on to give $10,000 or more. And the really neat thing is that donors who had given, I think it was somewhere around $1,000 to $2,500 through the charity's monthly giving program were incredibly likely to go on to give $10,000 or more in the following periods. So this was a very, very predicted results and basically what this showed to the organization was that their monthly giving pool or their monthly giving program was this stupendously valuable source of up-and-coming major gift prospects. And so these donors who, you know maybe they weren’t quite thinking of asking them for such high donation amounts following any level of giving through their monthly giving program.
All of a sudden they, their eyes were opened in terms of "wow you know we really should be prospecting from this monthly giving pool” and asking these donors to sort of step up their giving game. So I just I thought that was really cool.
Sabrina: Ya it probably helped them realize that they should be putting more effort into that sustainable funding source and it probably saved them a lot in the long run too.
Mathew: Um, yes I really do think that saved them a lot in the long run and just provides them with a level of focus and confidence in a new strategic direction. Which is really sort of the point to hammer home.
Sabrina: Definitely, so we talked a lot about the importance of the data, how - um you gave a really great example now but what are the other ways you’ve seen your clients use the data that they've found through your software in order to change or adopt their strategic plan.
Mathew: So another example that I can think of off the top of my head, was there's this one nonprofit, it’s a relatively small but still national scale nonprofit that I worked for early on. I created this donor data insight graph for them that had shown the length of time that donors have been on file for since their first gift, since their first possible gift. And one thing that this graph showed them was on their active donor file they had so many donors who had been on file for over a decade I mean, you know, you’d think that they would know this information beforehand. This is not the most sophisticated analysis I've ever done in my professional history, but they actually didn't. So they were just, they were floored when they saw the extent to which that you know, that they had these very long-term reliable donors.
What they did following that presentation of results was, they said okay, in our next campaign we're going to target these people who have been on file for so very long.
You know, we're going to call them out. We're going to talk to them very specifically using very grateful language to tell them how grateful we are in terms of how long it's been since their first guests and you know what their support means to our organization. And you know, all of that good stuff that a nonprofit will do to express its gratitude to its most loyal donors.
And one of the things that they found, was I mean they got more money from these people. More of these people renewing in that campaign and of the people who had given in the most recent year but decided to give again in this campaign. These donors gave new donation dollars, they increased the giving level. So that was just another example of a change or an improvement that happened on account of the insights that I was able to deliver with my nonprofit clients.
Sabrina: Yeah that’s fantastic cuz, you know if a donor’s sticking with you for over a decade that must mean that they're a really great contribution to your organization.
Mathew: Yeah, yeah exactly. But you know, even if the donors not giving so much money, it's a meaningful milestone that you know someone has kept you in their pocket books for so long. That they care about what your nonprofit does, and so I think that you know regardless of whether this is a $10 or $10,000 donor that you know these people deserve to be thanked in some way shape or form.
Sabrina: What are some ways that you've seen clients use the software to grow. Have you seen a lot of growth since organizations have joined your company till recently?
Mathew: One example that I can think of, there was a nonprofit I guess it was a faith-based nonprofit that was building an online tool to organize faith-based organizations in terms of their faith activities but also to organize them on the basis of their fundraisers. And they have brought me on to do some data insights work basically creating graphs of the nonprofit industry on the basis of so many different indicators of nonprofits performance. Anything that had to in some way, shape or form relate to faith organizations, and they had appreciated the data work that I had done so much they realized they had to hire someone in house to do analytics work. That it was just a little bit too much for them to be going back and forth with an outside person, that it would just be easier for them to go back and forth with someone who was in house.
So, I guess that's an example that I can think of in terms of how a client organization used to work that I did to help them grow their organizations because they had justified the value of this kind of work by seeing first hand exactly how much of it there was to do.
Sabrina: So thank you Matthew so much for being on the show! For those listening you can check out Donor Science and get more information on what they do at donorscience.ca. If you want to get in contact with Mathew you can also reach him through their website. Thank you so much for listening and we'll see you next time on Fundraising Superheroes!
Mathew’s clients at Donor Science have discovered the power that lives in their data and that clean, accurate and easy to manage data software is the key to success. With powerful insights reports built in, Donor Engine’s software will transform your data and the way it is used, putting it to work to raise more funds and create better relationships with your supporters.