Share with your friends


On today’s show, I chat with Steve MacLaughlin Vice President of Data & Analytics at Blackbaud and author of the bestselling book Data Driven Nonprofits. We discuss big data, its value, and nonprofit culture as well as how organizations can become a bit more data-driven in their decision making. We even sneak in a few hockey references :). Enjoy!

Listen on: iTunes | SoundCloudStitcher | Google Play

Here’s the full transcript:

[00:00:02] Hello and welcome to another episode of the good journey Pod discussing the world of nonprofits philanthropy and social entrepreneurship. [7.5]

[00:00:10] On today’s show I chat with Steve McLaughlin vice president of data analytics at Blackbaud. He’s also the author of the bestselling book data driven nonprofits. We discuss Big Data its value in nonprofit culture as well is how organizations can become just a little bit more data driven in their decision making. [18.7]

[00:00:29] We even sneak in a few hockey references so enjoy the show and thanks for this. [7.2]

[00:00:36] Hi Steve thanks for coming on the show. [1.5]

[00:00:38] Thanks for having me Brady. [1.4]

[00:00:40] Before we get into of your book and data were you always a nonprofit guy were you always a data nerd. How did you become this data czar for Blackbaud. [9.8]

[00:00:50] That’s good. I wonder. Yeah. No I mean my background. I spent a third of my career and consulting world specifically on a digital and e-commerce. A third of my career and pure product management and building products and solutions. Now I’m in the next third which is around a lot of data and analytics and I’m a D calculus student and so I have no business dealing with the amount of data and things like that that I deal with. You know if you were to look at my test scores. So over the years I’ve really had to study learn a lot you know talk to a lot of smart people and really sort of come up to speed on this because it’s not a subject area that I naturally you know come from. And I think what I found over the past few years is that’s certainly true of of your typical nonprofit professional. You know with a few exceptions most of them are not trained statisticians or people who have a lot experience dealing with data and analytics and regression analysis and all that fun stuff. And so I think part of some of the reasons why things I’ve been writing about or talking about or working have have really resonated in the sector is because I think I share the same perspective a lot of professionals come with they know they need to pay attention to data. They are understanding the value of using analytics in their day to day basis. And so I think its an interesting approach that has worked really well over time. [1:36.2]

[00:02:27] And I wonder if because maybe was the most natural thing for you it makes your writing and like your book a lot more accessible to write. Its like coaches Wayne Gretzky is a great example Unbelievable hockey player terrible coach because he was just so naturally good he had no idea what to teach right. So if you really had to work hard to learn it then maybe when you go to reteach it its more accessible. [21.9]

[00:02:49] I mean thats a great analogy. [1.3]

[00:02:50] I mean certainly Gretzky and any real you know superstar player in any sport they often don’t do well in coaching or management roles because you’re right they their talent plus ability often you know transcends their ability to communicate that teach that versus perhaps someone who has had to learn from you know the ground up and it didn’t necessarily come naturally to them. [28.5]

[00:03:19] Interesting. So you’re not the Wayne Gretzky of of data. [2.9]

[00:03:22] I’m not a Wayne Gretzky. No. Maybe Mark Messier. And maybe you know Paul coffee some other player you know. [7.3]

[00:03:30] You know that’s good. I didn’t know how much hockey I’d get out of Indiana guys or South Carolina guy. [7.5]

[00:03:38] I grew up in western New York just south of the Canadian border so I played hockey as a kid and yeah my teams already other the playoffs so we’ll keep moving on in this discussion. [10.5]

[00:03:49] Moving on. So is that maybe what what led you to write a book or what led you to write. Write your book. It was at this understanding of men. There’s a lot for the average nonprofit professional to learn and you know really talking about this or what inspired you to write a book. [14.5]

[00:04:04] Partly that. You know I had worked on two books previously and I had sworn that I would not write another book again. And so I for over a year had toyed with the idea but kept coming back to you I said I would not write another book again you know. Surely there must be some other book out there that you know people all the time were asking me hey how do I get up to speed on this what would you recommend I read and a lot of the books are either highly technical. Right so how to run Hadoop in the cloud. You know something like that or they’re very much come at it from the corporate angle. And there was a Goldilocks problem here either too technical or too corporate focused and nothing just right in the middle. And so what I did was I just started to do some research to see you know what would it be like if there was a book specifically written for nonprofits about nonprofits and the use of data analytics what would that look like. And that started probably a year long journey of a lot of research and writing interviewing a lot of different nonprofits and really trying to understand what was going on. And that turned into the book 1000 words later. [1:10.8]

[00:05:17] And why do you say you didn’t want to write another book. [2.0]

[00:05:19] You know I think I’d worked on two in the past and it’s a lot of work. [6.0]

[00:05:26] And you know I still have a day job and responsibilities and a family that would like to see me every now and then. And so I sort of knew what I was getting myself into I think the other thing was you know I’ve done a lot of blogging and for short form writing over the years. And I will tell you it really kills your ability to write long form you know and you may have seen this too but when you get used to writing in short choppy paragraphs or you get very comfortable expressing yourselves in 140 characters it’s pretty daunting when you have a thousand words a day that you need to crank out. And so what I found early on in the process of doing my research is I would start to see you know could I get down a thousand words on a topic and sort of build up that muscle tone and but also just see how far could I push this topic. And really the breakthrough was I started to do a number of interviews with a wide range of of people of who were at nonprofits of different sizes missions geographies because one thing I wanted to find out was did some type of organization have a monopoly on being good at the use of data like health care or X or higher education. [1:20.2]

[00:06:46] And what I found out is I kept talking to more and more different types of organizations is that NO NO ONE type of nonprofit has a monopoly on doing this really well but it turns out you can be a small organization or a larger organization you can be a health care or a human rights org you can be in the U.S. or the U.K. or Scotland or wherever and you can be successful. This type of stuff. And a lot of it is certainly a big influence culture and all this right. [30.0]

[00:07:16] What’s the organizational culture and their appetite to do this type of stuff. [3.5]

[00:07:20] Yeah and maybe we’ll dive into that a little bit more because in reading some of the stuff and thinking about it as you can you know the mindset and culture side is a huge barrier here potentially but can you just quickly maybe define big data or what. A data driven nonprofit is. [17.3]

[00:07:39] So let’s start with big data. So there are a lot of technical definitions of big data about you know structured semi structured and unstructured data and many of the definitions get into the technology that’s used. But for me the definition I like to use for data is around the analysis of data to extract value regardless of the size of the data. I think a lot of people think Big Data is about how much data you have in terms of volume. Oftentimes when people are talking about big data they talk about the four Vee’s volume variety veracity velocity but there’s a fifth V which is value right which is really what I think you should focus on what’s the value in our data. Regardless of how much data we have. And the reason I focus there I found organizations certainly smaller organizations think oh well this is only for the really big guys. We [57.1]

[00:08:36] don’t have enough data or you don’t mean us. So [3.2]

[00:08:39] yes it’s everyone right. This is about the value in the data not if you have terabytes or parasites of it over time. And in terms of what does it mean to be a data driven nonprofit you me it’s organizations with a focus and a mindset of using data to drive an inform decision making. [22.7]

[00:09:03] And the point there is not that you turn all of your decision making over to the robots or purely the data but the fact that you’re acknowledging the fact that when we make decisions we consciously choose to use data as a part of that decision making process or process as opposed to just the Hippo the highest paid person’s opinion or what we’ve always done or tribal knowledge. And it’s interesting you know over even when I was working on the book and since it’s come out occasionally I’ll get some folks out there in the sector who say I don’t like the term data driven. You know we should not be solely driven by that data. It’s almost like I’m you know implying that we should turn this all over to the data by itself but I’m pushing that right. It’s got to be about how are we moving forward and how are we using data to influence and help drive decision making whether that’s decision making on an individual project or decision making from a strategic standpoint to kind of acknowledge the fact that you know we know a lot of organizations. It’s unclear what they use as a part of their decision making process. And so acknowledging the data has to be part of that and over time the more you use data on a day to day basis the more you should be able to improve your performance over time. [1:22.7]

[00:10:26] Yeah. From my experience the data side has been you know the least used muscle or it’s an oft ignored part of the decision making process so you know taking a stance or even saying you should use this more just so that it’s a part of the conversation as opposed to absent is good. [16.4]

[00:10:42] You’re spot on there and that was something that I wanted to understand. I mean I’m a bit of a history buff and so very early on in the research I wanted to understand well there must be some historical reason why the nonprofit sector as a whole isn’t more data driven. [16.0]

[00:10:58] What is that. And I ended up having to go way back in time to like the early 1900s in 1905 and there’s two fundraisers in North America. Charles Sumner ward and Lyman love pierce. They were fundraisers for the YMCA. And long story short that’s in the book. But they developed a lot of the tactics around modern fundraising the idea of getting a major gift pledge commitment as a part of a campaign. Time boxing that campaign to a limited period of time getting corporate advertising funded by a corporate sponsor. A lot of these things that they developed turned into sort of tribal knowledge very tactically driven fundraising that you would still find in your average nonprofit today. Right a lot of the stuff that they developed still gets used today. [53.0]

[00:11:52] And it’s that reliance on tactics and you could argue tribal knowledge as opposed to well how do we know that. [8.2]

[00:12:01] Like you know how do we know that that’s the right number of days or that’s the right number of steps is an interesting thing that’s happened in the in the sector over really over 100 years. And the other thing that you find is Ward and Pierce then work with organizations in the United States Canada New Zealand Australia and the United Kingdom. [20.2]

[00:12:21] And so it’s also why you can explain war if that’s true why why is it these types of tactics used in these countries well because they went to these countries and sort of spread the gospel of how do you do fundraising. And it just took off from there. Sort of interesting historical context of you know why is it we do things the way we do it’s largely based on two guys from the early 1900s and we’ve just done copy cut paste since then. [25.5]

[00:12:47] And what’s interesting is you have these other kind of confluence of factors where the sector’s been really professionalized in the last maybe you know 30 years or so where we’ve got training programs and I went to grad school and studied fundraising. So you’ve got this sector that’s kind of codifying the knowledge to date and putting it into formal programs and then you’ve got most people that come into the sector especially fund raising you know get training on the job or from conferences or you know they didn’t set out to eat fundraisers and so then they’re also going to conferences and listened to speakers and so there’s kind of this knowledge that everyone needs to have to do their job has never done a lot of it has never really been tested or to your point been you know created in the 19 early in 19 years and so we’re just kind of catching up but my fears. You know we’ve got all these best practices but it’s right at this moment in time when we’ve got so much data or a lot of the best practices are you know potentially not even best practices by the time you learn them. Right like I went to grad school 10 years ago and that we didn’t learn a lick about online giving yet. That’s been my whole career has in the digital side. So there’s this kind of slow cycle and it’s just interesting seeing how some people are going to like but this is what I was taught as well. It’s maybe not even relevant anymore you know. [1:14.2]

[00:14:02] Yeah it’s an interesting point you know and I get flak for saying this sometimes but the nonprofit sector is largely a profession that is not professionalized. It’s not like if you are I want to be an accountant you know there’s formal training formal certifications you know you want to be a dentist you know you want to be anything that deals with people and money. Typically there’s some level of professional certification or education that’s required in the nonprofit sector is a bit of an exception to that and to your point you know Papel probably in the past two decades you’ve seen the growth of more professionalized programs universities doing programs. But by and large most people who are in the sector doing stuff don’t have necessarily that background and if anything that does require you to want to level up your skill set when that comes to digital social data because this is not stuff that you were likely taught you know but that’s probably true of anybody who’s gone through you know the higher education system in the past 20 years. [1:06.7]

[00:15:09] You know there was not a course on social media when I was at university and there probably is now but I think that’s the way of the world maybe in certain cases going to the culture of peace because of one of the things you wrote in a post I thought was great it was you know organisations need to ask the right questions not necessarily start choosing the right tools the tools can come that’s that’s fine but it’s this question or it’s this kind of curiosity of trying to figure out what’s work or what works and what doesn’t work in your interviews and in your research. Like a book. What is it that good nonprofits have in their culture or don’t have to have to really take advantage of of the data that’s out there that they have. [44.5]

[00:15:54] Yeah it’s a good question. You know my my observations over 20 years of doing things with technology in humans I’ve always seen this phenomenon where people want to place the tool in front of the strategy or the decision making process in hopes that if I pick the right tool then I will you know it will do the things I want to and I may not have to make hard decisions or I may not even have to know what decisions I need to make the tool they will do for me. [31.8]

[00:16:27] And you can get away with that. Unfortunately you can get away with that. But what I found where that really just doesn’t fundamentally work is around data and analytics because it’s not like the digital space where yeah you could pick a bunch of tools and you could probably get your way there because the tools the tools are accessible there’s a lot of things you can do. But when you get to the use of data and analysis the likelihood that you’re doing the regression analysis that you’re doing the modeling it’s unlikely you’re the person doing that. [33.1]

[00:17:00] In most cases you either have other staff who have that skill set or you’re working with a partner or a vendor to do that in which case the tool to you is invisible and doesn’t really matter what you really need to make sure you understand is what’s the question we’re trying to answer what’s the problem we’re trying to solve. And what I found for a number of years was that oftentimes people when it came to data want to start with you know interesting approaches. [30.0]

[00:17:30] You know that when we have all this data about our fundraising pregnant we have all this data about our email campaign. Surely there must be something in all the data that would tell us x y or Zed and it’s not exactly how you want a approach. [15.1]

[00:17:45] Right. Like the data science folks will divine if there is or is not something in the data. Don’t worry about that. You should really focus on is again what’s the problem I’m trying to solve. [11.1]

[00:17:56] Is it really trying to address retention. We’re really trying to address how do we improve our monthly sustainers how do we get more out of our digital and advocacy programs. And it’s almost like you’ve got to go back to the scientific method. What’s your hypothesis. How would you test to know if it was true and what are the right questions to ask and culturally. What I think I found was a lot of organizations struggle in that area. Oftentimes there is confirmation bias in those questions. Why. You know we want the answer to be X or Y. [39.8]

[00:18:37] And so therefore go find me the data that supports X or Y is like no that’s cheating. Like that’s not supposed to do it that way. [7.3]

[00:18:45] And but what I found was that in general culture is a huge driver of the adoption of the use of data nonprofit’s and. In particular identified about 7 different culture types like a culture of data sharing a culture of testing a culture of growth. And the good news is there’s at least seven different kinds could be more. [26.5]

[00:19:12] And you don’t have to be all of them you couldn’t just self-identify with one of those cultures right. So for example public broadcasting has. Two decades of building up a culture around the sharing of data station in Boston doesn’t believe it competes with the station in San Francisco and so for 20 years they’ve shared data and done benchmarking. Now not all organizations have a culture of sharing in fact even within the same organization. There may not be a culture of sharing you may have to have a different culture type and that’s ok. [35.9]

[00:19:49] I think it’s more of just identifying what’s what is our culture most like and how to we embrace that culture and then become more data driven over time. [11.8]

[00:20:02] What do you think nonprofits can do maybe in the short term. I mean also the long term but to start making some progress towards being more data driven. Because you know I think organizations that aren’t maybe we’ll just feel so overwhelmed right with the years of records and I don’t know how to do this and how to do that and there’s only three of us and you know there’s this kind of constant sense of of being overwhelmed which is one of the barriers I think to doing things newer innovating or doing this so what are some kind of baby steps or suggestions that you have for maybe smaller but maybe is to kind of get started on more of a data driven past what baby steps are absolutely recommend starting. [43.2]

[00:20:45] I think the recipe for failure is to sort of you know make big bold statements form a giant committee change the mission statement do bunch of stuff about being data driven. [12.0]

[00:20:57] That’s likely to end in disaster because a lot of this is about change management and if you want to cause shock to the system you’ll go you know you know big and bold what I recommend is that you start with some baby steps you make some small bets in particular that you pick a question you want to answer. Probably what I saw within the organization that is big enough that people care about but not so big that too many people will care about. [32.6]

[00:21:31] Right. [0.2]

[00:21:32] Know you want to pick something big enough that people will care about understand the answer but not so big that it may disrupt too many other programs or things that are going up and then the time box yourself making sure you know what I recommend is take that question you want to answer probably want to solve limit yourself to 30 days and say at the end of 30 days we will meet and we will present what we found and we’ll use data to inform and drive a decision even if that decision is no or not to do something because you know if you choose not to decide you still have made a choice. And so I think that is a good way to get started. And then what I found is if you do that people get used to it. Some things work some things don’t. And then at the end you’re able to say look we were actually able to do this that wasn’t so hard. [50.2]

[00:22:23] And then you pick the next project to the next project the next project and before you know it what you’ll be doing is being more data driven. Right. But what you’re also secretly doing is you’re building habits around your decision making and how you do things. And to me habits are the thing that starts to adjust culture or align culture with what you want to do it’s you know so that people say well that’s just how we do things here. Right. It’s just a gradual process over time you get there. [29.2]

[00:22:52] Right. Speaking of the kind of you know what’s the problem we’re going to solve or assumption back to some of the things you’re saying earlier. I know one of the things when we’ve done or I’ve done you know data audits trying to look at these patterns or whatever they just ship us a ton of data and it’s very much you know garbage in garbage out. And so we’re trying to do you know digital fundraising analysis but donations or by online. While we can. [27.3]

[00:23:19] Why would why would you need that. Details details right. [3.4]

[00:23:24] So I think that’s the other interesting thing is it’s not like you know bosses organizations or people in data. Those are the only two assets that nonprofits really have for the most part and they don’t leverage either very well. But the two can work together. Maybe you didn’t podcast. But how much when an organization needs to start. Don’t they need to know kind of what they want to be trying to track moving forward because they can’t just take you know records and records and records for years and years and years and go to work. I mean there’s some stuff that you can mine but if you don’t have a purpose and it’s been all over the place it’s you know pretty hard to track. Is that a true and B regardless. What are some of the key things is maybe on the digital side or on the fundraising side of that you know organizations need to be starting to track or code properly. [48.8]

[00:24:13] Well one of the things that I talk about in the book and spend a lot of time now talking about is I’m meeting with nonprofits and talking about how they become more data driven is this notion of there’s a hierarchy in terms of how you mature and your use of data. [16.0]

[00:24:30] And there’s multiple steps in that in that hierarchy of maturity. And the first one is data right and data answers the question what happened. So for starters if you don’t have data it didn’t happen. [14.2]

[00:24:45] So that rogue spreadsheet that list to get that’s kept somewhere else or the reports that never you know the information is never captured. [8.7]

[00:24:55] It doesn’t exist if you don’t have the data. Pure and simple doesn’t exist. And then after that it’s about what’s the value that your organization places the health of your data. [10.4]

[00:25:05] And you know with that one. You know we in the sector use all not just the nonprofit sector but this happens all over. [6.5]

[00:25:12] Is the term data hygiene like the term data hygiene just feels like like 45 minutes of discomfort in a semi reclining chair like no one gets excited about the term data hygiene. Right. Not even data. Hi Janice. If that’s an evil actual occupation get excited about that right. And so I don’t call it data hygiene. [23.9]

[00:25:37] I call data health right data health is good for you data health is something you can you know prioritize you can invest and you can focus on. [7.7]

[00:25:45] And the other reason why I think it all starts with the overall health of your data is that you know data is a raw material for creating value and if you start out with bad data it never gets better it just gets worse. [15.1]

[00:26:00] It’s like it’s like cooking with bad ingredients or expired milk or whatever you use it and ultimately it gets contaminated and you know worse not better. And so you know I think focusing on data health you know I know people like to talk about you know garbage in garbage out but you know that’s a culture thing right. So it’s almost like you accept the fact that well data is always going to be bad. [26.1]

[00:26:26] And so we accept garbage in garbage out. Like whoa why why do you have to accept that or what do you do about it. And how do you from a from an organizational standpoint make sure people understand that the quality of the data and the completeness of the data is actually really important. [19.7]

[00:26:46] And again that’s what brought me back to why I think a lot of this is culture because it just can’t be someone’s job right. It’s a great example I talked about in the book is is typos. Right. So I am I am someone whose last name is misspelled a lot and so you know what’s that cost something right. What does that cost when there’s a typo in a donor’s name. And Chuck Longfield is our chief scientist actually did some research a few years ago and looked into this and he found a typo on a donors Nien cost you about 10 percent retention and 12 to 18 percent and uplift. So there’s an actual real cost when you mis spell someone’s name. Now whose job is it to make sure there are no typos. Is it the vice president for typos. No. That role doesn’t exist. So inherently It’s got to be an organizational culture that says Wow. Typos cost us something. [59.9]

[00:27:46] Now that we know it costs us something we probably want to do something about it but it’s not something that’s one person’s job it’s really everyone’s job or at the very least analyzing and looking at where does data come from. What are the potential ports of entry if you will and what can we do at those places to ensure that there’s a higher level of quality that we pay attention to this stuff. And in part I think it’s because once you are able you know it’s that old adage what gets measured gets managed. You know once I’m able to understand the value of something or the loss of something because of data suddenly the antenna go up and go oh that’s bad. It’s costing us money. I guess we should pay attention to this and that motivates all too many people to want to do things going forward. [45.9]

[00:28:32] Yeah. Purpose and pain is what we do. And something needs to be very much aligned with a purpose or someone needs to feel the pain. Otherwise things just kind of fall off the place especially when people are really busy and it’s a good reminder. I mean especially as we’re trying to convince or talk to my organizations about this kind of stuff whether it’s a typo example or we’re often talking about conversion rates and how many don’t get lost that you’ll never know of who clicked donate. [26.9]

[00:28:59] So your crappy page and you know the style that’s the last part thats important too because you know in human psychology we know there’s this concept of loss aversion. So human brains are wired to fear losing something more than gaining something which explains all AB testing. Right. You know that when you show the results from testing or data analysis that you’re losing something you’re losing money you’re losing conversion rate you’re losing something. It often gets a lot more attention in organizations in part because humans are wired for loss aversion versus Oh which you can be doing so much better if you only do these things and oftentimes you’ll get. [43.1]

[00:29:43] Yeah yeah yeah I know but we’re busy. Oftentimes I start with examples of here’s what you’re losing because you’re not doing this in a particular way like for example we looked at address data just address data and bet what bad address data costs the nonprofit sector and by our estimate from looking at thousands of nonprofits and some analysis that target analytics. [24.9]

[00:30:08] They estimate that over 21 million dollars a year is wasted in bad postage and mailing costs just because of bad addresses. Like just address data like we haven’t gotten to. More exotic forms like do you have email addresses or social media handles and phone numbers like just Hydrastine alone cost tens of millions of dollars and then again suddenly you will get someone’s attention. Well you know how much are we wasting or losing because of this. So you know there is a bit of you’ve got to understand the human nature and how they might respond and what stories about data will resonate more before you can talk about. Now here’s all the great things you could do if you want to write one. [40.6]

[00:30:50] Just that last bit. Two beautiful terrible ironies of the sector which is what I love. It’s difficult but you know one of them is the last version yet. You know something like a retention for example which is losing by definition losing donors and it still doesn’t seem like it carries enough weight for a lot of organization. At least. But you know that. Why does a loss of vision apply to us when it comes to donors or. That’s one thing. [28.4]

[00:31:19] Actually I feel that that could be a whole discussion of itself. [4.1]

[00:31:24] Yeah but even losing lost virginity. Yes. Yes. Oh but wait. What about the donors because that does not seem to get the same amount of time as oh the second thing was in such a scarce resource kind of world. [13.4]

[00:31:37] For better or worse that’s how some people approach viewing resources. There is so much waste that goes on in the nonprofit sector. Then there’s the address. One is a great example right so we don’t want to invest in data health or our great database or you know some training for a database person or this process to clean up the database. But then like literally millions of dollars just get you know sent out in that maybe ties back to this whole bigger thing around like culture and in mindsets and podcasts upon podcast for hours and hours. But I think I think that is really interesting because if you just sat down and asked people and position at a loss like you did. Yes. Oh absolutely. You know what I used to and were very interested. But when it comes down to actually implementing some of these things you know maybe that’s when it starts butting up against the the culture or leadership or mindset that needs to be in place to actually use it. And that’s where things maybe start to fall down a bit. [1:00.8]

[00:32:38] Yeah. So let let’s play out that retention scenario because it brings up a really interesting point why people are more focused right so we know that last year first year donor retention rate was 29 percent and first year online donor retention was 21 percent. So online is actually worse. [18.3]

[00:32:59] So there’s the what you’re losing right. You know you’re losing seven out of every 10 donors or almost in some cases eight out of every 10. So that’s bad. Right. And you could quickly calculate what you’re losing. But then here’s the statistic I’d throw out that gets people’s brains to flip the other way which is multi-year retention. So two plus year donors that retention rate is around 60 percent. [24.2]

[00:33:23] Around 60 percent for both online and online. Suddenly it more than doubles it bounces back. For both of those channels and so what I I sort of would contend is I think part of the notion of donor retention is focused on the wrong number. If you just stare at that 29 percent of that 21 percent. So if you know that if you get a donor to get make a second gift and then continue to give for multiple years all the numbers get better. [32.7]

[00:33:57] Shouldn’t we then focus everything on the second gift the first gift just table stakes the first gift is left to its own devices you will lose 70 percent of people. So the real trick is if you were to sit down in a room and talk about what would we do if it was all about the second gift I’m willing to bet that you would change things that you do today and that you would improve the overall retention rate because you know that I’m here I’m at 29 percent but I can get 60 percent if I just get to the second gift. The problem contains the solution. Right. And [39.0]

[00:34:36] so focus everything you have on the second gift about your stewardship your engagement your frequency of contact all the things that you do or don’t do today. If it was all about the second gift I think you would manage the numbers differently. And it’s interesting that gets people thinking. I hadn’t thought about that before or until you told me that multiyear retention is 60 percent. [24.4]

[00:35:00] And all I have to do is just get across that chasm. Well maybe I should think about this differently as opposed to yeah retention stinks. [8.3]

[00:35:09] I don’t think there’s anything we can do about it. Woe is me. Everyone’s retention rate stinks so we’re just as bad as everybody else. You know you know the here’s a way to think about it differently perhaps. [10.8]

[00:35:20] But I think that’s a great example of the data driven and not necessarily being like you know the most complex thing in the world because and this is our experience it’s just doing sit down like some of it’s pretty pretty simple like if the donor hasn’t given to you in two years there’s almost zero chance that they come back. Basically like long lapse activation is incredibly rare from the data that we’ve analyzed for our clients in three years a long lapse gets hard. [27.7]

[00:35:48] You know that brings up another good point which is the other thing that data helps you with is participation. So every nonprofit whether you’re really big or small or somewhere in between you only have so many resources you only have so many hours in the day. Where do you focus. Yeah. Right. And if you say well which of your donors are your most important donors and if your answer is all of them then you’re either foolish or you’re just being cheeky. Like I can’t tell you but I think the problem there is thinking well there everyone is all these things are of equal value and they’re not right because the data would say oh somebody who’s long lap spoil your re-activation or a long lapse is really low so no going into it. You may have to spend a lot to get very little wouldn’t you be better off. [45.0]

[00:36:33] You know what are you doing with you know new donors to the organization who are new within six months is very different than what you do with somebody who’s who’s long lapsed they’re very unlikely to come back. [10.0]

[00:36:44] And I think part of this is what’s so great about your guys is research and you know thank you for all that you do for this sector because I use you know research all the time even like first time donor conversion rate. I just use conference in people’s minds like if we sat in a room and we knew the problem was just that you know eight out of 10 people who leave us in a year. But if we can keep them for two years then they’re around 60 percent. You know just saying wow that’s a very clear problem that has some clear benefit and then can we actually put some ideas and resources behind it to do things differently. I still think that’s a bit of a challenge but at least if it’s like most organizations wouldn’t know that that’s the first time or attention right or that the second year retention would be so much higher. [48.1]

[00:37:32] So then there is these aha moments like oh wow. And then the strategy the high level is very simple right. Like get the second gift is a great. Well there you go. And then how you get there then we can get into some tactics or out of the you know invest in resources in here. But it starts from that point of even just understanding and knowing you know some of that data and that’s not very complex. [21.2]

[00:37:54] It’s not overly complex. [1.3]

[00:37:56] I think it’s also changing how you think about data from being it’s not a hammer it’s a flashlight instead of measuring this stuff. It does not beat you on the head and say Oh you’re not really doing good here. E-mail conversion rate low or Yser retention rate. This you know bam bam bam aren’t you doing a better job. It’s supposed to be a flashlight Hey look here here’s something that’s happening. What should we what should we do about that. You know to be fair sometimes the answer is nothing. [30.5]

[00:38:27] Right. Stay the course. You know that we may have expected that or we know that that’s what something is and that’s OK but at least you’re checking in. You know I think there is also a tendency of organizations to want to over measure stuff right. [14.7]

[00:38:42] They read a book on this stuff and then they suddenly want to make you know a metric for everything and oh and believe that if you measure everything and you know you can overdo it too. [10.6]

[00:38:53] I think what I found in writing the book and talking to so many organizations is the really good works are using three to five key performance indicators guys. They they measure other stuff but ultimately they they refer back to those things to steer the ship and you know the analogy they often use is if you look inside an airplane cockpit there’s lots of dials and gauges there’s a lot of stuff going on there. [24.7]

[00:39:18] But ultimately when they’re flying the airplane the only two things that matter our air speed and altitude like all that other stuff doesn’t matter for the most part yet. [9.8]

[00:39:28] And so what I always ask nonprofits to think about is you know what what’s your. Two to three things that if you looked at it every day would you know are you on course or not. Yeah. And you will get some. You know there’s some initial discomfort with that well but it would be these things but we’re not really sure if our data is correct or right or we don’t trust the data which again just comes back to data quality. [22.1]

[00:39:51] All right great. Tom like you. If you don’t believe the metrics sounds like there’s an inherent data quality issue let’s let’s focus on that. Yeah right. And it’s never perfect. Right. [9.9]

[00:40:01] So as part of that is just to just deal with it you know get focus on making it better over time but that data to a certain extent always has some flaws in it. And that’s either an excuse to do nothing or to say you want to do something better. [12.5]

[00:40:13] Right. No I like that airplane algae and I know that’s one of the things that I think can actually shift a lot of the culture and mindset is obviously what you choose to put on the dashboard of if you just have like top line revenue. We just need to raise a ton of money. Well then you know major gifts departments and you’ll just be chasing revenue which is fine but maybe some fundamentals or aspects of your your fund raising department will be lost and you know as we’ve talked about these underlying metrics are some organizations. Yeah absolutely. Oh we’d love to track that but we can’t and I do think that’s where you end up just trying to measure the the easiest things and often the easiest things aren’t exactly the most useful things. [42.5]

[00:40:57] And even if it’s just understanding what is the work effort required to produce the end result. So for you you could chase revenue all day right. And so you might say well we’re just going to really focus on major gifts because three major gifts is worth 300 gifts right. You can get yourself you know your fundraising pyramid can suddenly end up upside down or it looks more like a space needle than a than a pyramid which is what happens sometimes but you need to sort of understand holistically across your data look how many donors do either need to acquire or retain. In any given quarter year in order to hit a financial goal. [40.5]

[00:41:38] Understanding that we will lose some no matter what. And that we have to fill that pipeline and we need to move people through stages and you know you get into more advanced analytics where you’re looking at you know how many in-person visits does it take to close a gift larger than $10000. You probably would want to know the answer to that question because if you’ve got a pipeline but no one’s meeting with people then you know it’s unlikely that you’re going to get the results you want. Now I know that there will be seasoned professionals who will say you know you just can’t measure that. You know I could walk I could meet with someone today and be their first visit and we could walk out with that commitment. But those are anecdotes right and anecdote is not the plural of data. We oftentimes like to use that one anecdote story to make the case for the whole. And those usually don’t stand up to scrutiny. Right. Like yeah that happened one time. How many other times does that happen here. Well never. OK. [57.0]

[00:42:36] So you’re basing the future on the thing that happened that one time Monday in May. [4.9]

[00:42:41] Probably not a good approach. [1.4]

[00:42:43] You know that goes back to the tribal nature of what works or codifying knowledge. And it’s a lot of my experience and verbal which is at one level it’s completely valid you know but at another if we start transferring and building all these strategies based on that one Monday you know we’re in a lot of trouble that happens especially with the major I guess people who run fundraising departments I find that that’s been my experience like it’s so unique like oh we just closed this huge gift and it just happened this way. [30.7]

[00:43:14] That’s great for you. Major Garrett that we’re dealing with you know $50 donors the process is very different but they don’t know that it’s about sustainability. [8.4]

[00:43:23] You know I think there is a need to have a sustainability mindset and that the individual heroic efforts of a few staff members just simply not sustainable. And if you want to grow the organization you’ve got to have some more process and rigor around how these things happen. You just can’t you can’t get the scale you need you know to make it work over time and to your point. The issue of how a major program operates is very different than an annual fun program or even mid-level giving. There’s huge untapped potential in mid-level giving But again you have to be willing to focus on it and you need the data that tells you who really falls into those categories that you should focus on to get that type of balance or things simple as you know overseas and in Canada monthly giving sustainers is a pretty well known process and practice that people use. Right. It’s finally starting to catch on in the U.S. because people I think are understanding that it’s a more sustainable approach. Yeah. Then you know it’s the agrarian method of donor relationship building as opposed to the hunter gatherer right like we did hunter gatherer for a long time and then we learned that if we were to grow our food and. And that was a more sustainable way long term than everyday having to wake up and go find it. So you know I think sustainers there’s huge upside. The data would suggest that even shifting a single gift donor to being a monthly donor has more upside. Right. [1:34.7]

[00:44:58] And in fact you can switch those donors if you are strategic about it and you choose to do that I think we are researchers found. You know especially donors whose annual giving is less than 200 dollars are very good at switching them to become sustainers when you switch on to become sustainers that retention gets better their lifetime value gets better. All these great things get better why wouldn’t you do it right. [23.6]

[00:45:22] Yeah I know. And this is exactly what started about this weekend. So the mindset shifts. And for me again my career is looking at data living mostly in the annual giving world for small and MID’s. But if I came to conclusion that live have values the main thing that matters and if you come to that conclusion then something like monthly giving pretty quickly thereafter becomes incredibly important. It’s more in a year way more a lifetime. And so that’s a big mindset culture shift instantly saying OK we’re going to invest some dollars and it’s going to take longer to get back in the short term. Short term it’s less than six months. [38.4]

[00:46:01] But in the long term run any calculation you are an acquisition cost an arm and you for the most part a monthly donor focused strategy will win out over any other strategy in the long term. [11.7]

[00:46:13] So while you are not investing in it and it’s like you just said once you realize that lifetime value is the thing you can’t unsee it now that you know you may have to get people into that mindset that might take a while but once they see it then at least they lock into that being a mindset of that’s what we’re trying to do here. Yes. It changes your thinking it’s just like one you know what multi-year retention rate is like maybe you’d focus more on second half and not just the first one and that’s what you’re trying to do. And to be more data driven is when you’re presented with data and evidence of something does. How does that drive your decision making to do some things differently or two or at least one improves the result over time. [42.8]

[00:46:56] Yeah. I mean I’m sure we can talk to all kinds of other things and go on and metrics and data. Now pre-Chase so much time and for taking the time to write the book or something that is really needed in the space and sector I really appreciate it. Or can people learn more about you or your book or your work. [18.0]

[00:47:15] A few places. So for starters you can find data driven nonprofits on Amazon and other places where books are sold and the other place I encourage you to check out is Blackbaud blog at. And be engaged. Always publishing insights research. Lots of great stuff so not a shortage of content and things we’re trying to do out there in the sector. [23.6]

[00:47:39] Awesome. Well we’ll be sure to share those in the show notes as well. And thank you again for taking so much time today Steve. [6.4]

[00:47:46] Great. Thanks Brady. [0.8]

[00:47:47] Appreciate it. Thanks again for listening to this good journey part a nonprofit Supply Company production. Be sure to subscribe and get all the past present and future podcast. Good journey padauk. You can get more resources and exclusive content by following this on Twitter and Instagram as nonprofits apply. Good luck on your journey. [23.7]


Share with your friends