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Over the last two years, nonprofits have seen digital marketing and fundraising accelerate at lightning speed. In this season of Group Thinkers, we’re dedicating each episode to discussing digital advancement with some of the industry’s leading experts.
On this episode, we sit down with Beth Kanter and Allison Fine, co-authors of The Smart Nonprofit: Staying Human-Centered in An Automated World, to discuss how nonprofits can humanize digital fundraising. Tune as we talk about:
- What is smart tech? 6:05
- Arming your organization with the right technology 13:45
- How AI applies to fundraising 18:56
- The role data plays in AI 23:50
- Organizations who are doing this well 32:16
Meet our guests
Beth Kanter
Co-author of The Smart Nonprofit: Staying Human Centered in An Automated World
“Let's define smart tech. And in the book, we describe it as advanced digital technologies that identify patterns, and they use something called algorithms. And that's kind of a scary word, but they're just basically mathematical equations that sweep through a lot of data and either analyze it to solve a problem or to trigger a task, such as cutting and pasting information from one document to another, just as an example. So basically, they're recipes or recipes of mathematical equations, and it takes a lot of work to make them work well, and they need to be tested and cultivated.”
Allison Fine
Co-author of The Smart Nonprofit: Staying Human Centered in An Automated World
“You can use smart tech to do all of that work and free up your development staff to build relationships, cultivate donors. Ask them questions. See how they feel. Find out stories. Why is this cause meaningful to you? Why is it important to your life? What would it take for you to be an ambassador for us to other people in your networks, right? All of the human work that could help you pivot from being transactional to relational.”
Podcast transcript
Justin McCord: OK, so, you know, Ronnie, I want to say just at the top today, I don't think it's a goal to be a household name. But I do think that being a household name carries some value. Like, I would imagine that it's, that, you know, there are many times that I walk into a restaurant, and I think, man, I'd like to be Norm from Cheers, like at this place.
Ronnie Richard: Everybody knows your name.
Justin: Yeah, where everyone…. And so that's my weirdly awkward intro and segue into our guests. So welcome to Group Thinkers where we have Norm and Norm in some ways. No, but welcome to this episode of Group Thinkers, the podcast from RKD Group, where we don't encourage groupthink, but we encourage really good thinking, advanced thinking.
And so, I'm your host, Justin McCord. Got Ronnie Richard with me. And on today's episode, we do have what I would contend are two household names in the nonprofit marketing space. So Norm and Norm, as we may, may think of it. But we've got Beth Kanter and Allison Fine, and we're here to talk about digital advancement as we are in this current season of Group Thinkers.
But more specifically, we're here to talk about digital advancement through the lens of their new book, which is The Smart Nonprofit: Staying Human-Centered in An Automated World. So, Allison and Beth, welcome to the show.
Allison Fine: Thank you for having us, Justin and Ronnie. It's nice to be here.
Beth Kanter: Yeah, great to be here, Ronnie and Justin.
Justin: Yeah, we're excited for our chat today, and where I want to lead off is just like the cat sitting around the bar at Cheers or in any other relationship. Relationships take work, and they're nuanced, and I'm curious about the working relationship and journey for the two of you. This is not your first book. And so, I would love, Allison, if you would maybe lead off and tell us about the journey of both you and Beth collaborating originally, and then what led you to this second book and that process of working together?
Allison: That's a lovely way to start, Justin. Thank you. We have been called the Lennon and McCartney of the non-profit space, but our collaboration actually is much longer than the Beatles. And I know that because my husband is a Beatle-ologist. So, I wrote my first book, called Momentum, about digital tech and social change. It came out in 2006, and Beth was the very first blogger to review it, and we didn't know each other when she posted the review, but then quickly got to know each other and began to work together because we were both so early on in the space. And it was clear that we had a very nice way of being together, and we have very, very different strengths.
I think Beth is very strategic and very practical and understands the technology in ways that I don't necessarily do, and I get that strategy and leadership, and I would float off into the air, Justin, if she didn't keep me anchored to it. So, we wrote a few papers together, and then we wrote The Networked Nonprofit in 2010.
And then a few years ago, the Gates Foundation asked us to take a look at the ways that AI and other smart tech were opening up generosity and fundraising and giving. And it occurred to us that what we're calling smart tech, which we'll talk more about, was exactly where the place where social media was 10 years earlier when we had written The Networked Nonprofit, and it is the next chapter, and we thought, why don't we explain this again. And we know for sure, having worked together for over 15 years, the one thing we know without a doubt, Justin, is both of our work is better when we work together.
Justin: Boy, that does feel very Lennon and McCartney without Yeah, no, that's, thank you for that. That's very, that's very well said. One of the things I hope we accomplish on this episode and in our conversation today is to make the idea of AI less scary because I do think that it feels unapproachable in some ways.
And so, you know, we're hopeful that through our conversation, and again thinking about digital advancement, that we can make smart tech less scary, more approachable for our listening audience. And so we've put together a series of episodes all around digital advancement, and I'll tell you both, the through line and theme that we've felt is that it's one step in front of another. We, you know, we think a lot about the ideas from the Bill Murray movie, What about Bob, that it's just like baby steps, right? But it's just one thing, one step at a time; that you don't have to leap all the way to the end of being advanced, as it were.
And we have seen AI and automation play a very significant growing role, and so, can you, Beth, tell us at a high level what nonprofits can do with this technology? Like if we're taking baby steps, but we're introducing AI, connect those two things for us.
Beth: Sure, great question, Justin. So just a step back for a moment. Let's define smart tech. And in the book, we describe it as advanced digital technologies that identify patterns, and they use something called algorithms. And that's kind of a scary word, but they're just basically mathematical equations that sweep through a lot of data and either analyze it to solve a problem or to trigger a task, such as cutting and pasting information from one document to another, just as an example. So basically, they're recipes or recipes of mathematical equations, and it takes a lot of work to make them work well, and they need to be tested and cultivated.
And the other piece of this is that the algorithms eat data for breakfast, right? Lots of data. And Allison's really fond of saying, Library of Congress size data sets. So those are the components of what makes up smart tech.
But what it does is that it's really making decisions for us instead of by us. You know, it's not digitization that we're talking about. It's really, you know, decision making. And I'll give you a quick, accessible example. You know, I had a car problem, and I had to rent a car, and I had a really old car that wasn't a smart car. And it had one of those camera things, you know, in it. I don't know if you're familiar with those. And I was backing up, and it had rained, and there was some water drops in the camera. And it was interpreted by the algorithm or the computer visioning as something was in the way, and it slammed on the brakes. And I'm like, what? And I couldn't figure out what's happening here. So, it was actually making the decision for me. I mean, there was a default setting in the car that I didn't know that was set. But, you know, there wasn't a manual override.
And so, and that also illustrates another point with this technology, is that there always needs to be kind of human input. It's not that the smart tech is going to take over for us or eliminate jobs. We're really going to be co-piloting. Co-botting is the term we use, and what that takes is really a good understanding of what the technology can do. That starts with going slowly, right?
We're in the last phase of digital technology: social media. It was, like, fast, fast, fast, you know, jump in the water, experiment, scale it fast, fail fast. But this, we have to be a lot more careful, and Allison's really great at talking about why we need to be more careful, but it's a more reflective, knowledgeable and thoughtful approach.
Justin: And you mentioned, Alison, you know, you've both mentioned that there's some level of efficiency, some level, there's so much of this that comes back to being efficient that, you know, because the smart tech eats data. You know, you get the picture of Pac-Man, and that you can turn that towards certain applications and tasks or functions, as someone at a nonprofit, to handle certain things for you.
What are those things? Where does this come into play, especially in this great new digital-first frontier? Where, where … where are the best places for this to come into play?
Allison: So, the reason why we're having this conversation today, Justin, is because AI and other smart tech is what we call the heel of the hockey stick of adoption, right? So, it got developed, developed, developed, built, and then all of a sudden adoption goes straight up in the air because the technology became much more powerful and much less expensive at exactly the same time. And we've seen this in other tech eras.
So, in a minute, what feels like a minute, organizations can use the kind of technology that only Nasa had access to three or four years ago, and it is what we call an equal opportunity disruptor. Smart tech is going to be embedded in every functional area of an organization: Development, HR, Comms, direct services, everywhere.
And what makes it especially challenging for organizations, Justin, is that it's invisible, right? You can't see smart tech at work. It's built into, say, the HR product. That screening resumes, right? It's powering that in invisible ways and selecting some people and excluding other people, right? Or it is helping people, staff, fill out their expense reports automatically in real time, in the same as budgeting. Or it's going through enormous data sets and identifying prospective donors, right? It is everywhere.
And that's why it's so important that the C-suite leans in with smart tech and takes charge of an organization getting its arms around what this stuff is and when and how we're going to use it. We say it's hot sauce. It's not ketchup, right? You're going to use it sparingly, you're going to use it strategically and wisely. And that can only come from the C-suite in figuring out how and when to do that.
Justin: So interesting, and especially because when you reflect on, let's say, the last 15 years of digital and tech in the nonprofit space, there’s this shiny object syndrome that sometimes originates out of the C-suite.
Allison: Yes.
Justin: We have this idea of ramping up social media, but they don't have any idea what it means. We've got to do this.
Allison: Or a chat bot. Everybody's got a chat bot. Go get one.
Beth: Or we need an NFT now.
Allison: We’re going to have an NFT fundraiser. We don't know what that means, but everybody else is doing it.
Beth: And we're going to get rich from it.
Justin: We’ve got someone on our board that's at a big tech company, and so they're telling us that we need this. So, so how … so how does the C-suite, how do we make them aware of the opportunity and then empower them to apply the right resources. So that, you know, as you said, HR can better use these things or communications or marketing or even inter-departmentally within an organization to break down some of those silos. How do we best arm the C-suite?
Beth: So, you know, that's a really great question. I'm going to start, and Allison will, of course, make it better like she always does.
So, you know, my thinking about this … you know, I've been reflecting on this, and because the pandemic has been, you know, an equal opportunity disruptor too. And it's almost been like a disruptive technology because it's affected everybody and the way we work, right? And we've been living through this, you know, fast-paced pivot to, you know, becoming distributed remote teams and trying to figure out how to deliver our programs digitally. You know, many nonprofits that I know kind of advanced in their digital transformation, a whole decade's worth, you know, and in a matter of a month and, you know, way back in March 2020. And we did it, you know, because we had to. It was a matter of health and safety and life and death, getting COVID.
And there was a lot of stress in that initial shift. We started to settle in, you know, and as we have, the sort of covered whiplash of, hey, we got vaccinated, we can go back into the office. Oh, no, we can't. Oh, we're going to have to go back in hybrid. Look, no, we can't. But now we're kind of like, well, yeah, we have to go back into hybrid. And now here, oh, I got used to all this flexibility of work. You know, this is a much better way to work for some people, not all.
So, we have all of this disruption going on in the workplace. I think this is the time. And I think a leadership challenge now is kind of like the pacing. OK, so maybe before the pandemic, the pacing could be, yeah, let's get all those shiny objects. Let's be at the cutting edge, you know? But now I think we have to do a Great Reset. And I think we need to really think about, like, what are the ways that we can use technology to give our people space, right? And to really focus on a culture of well-being, to reconnect social capital in the office, to reconnect with the people we're working with.
And that's where smart tech gives us this dividend of time that we talk about in the book because there is the efficiency piece. You know, there's that piece. And when I say efficiency, it's killing off that soul-sucking, repetitive, exhausting, horrible cut-and-paste work. You know, where, you know, I'll just say one word: shared hard drive. You know, you try, you know, if you want to get something done, you have to spend an hour trying to figure out where that information is and then cutting and pasting it, like, I mean, that's exhausting. And it it's in HR. It's in fundraising. It's program delivering.
So, smart tech can cut a lot of that away, right? And that opens up time. Time to really develop relationships with donors. To actually, if you're in the office, to breathe, maybe to rethink things like a four-day workweek, right? That's what everybody's asking for and more flexibility at work.
So, I think this is the great opportunity. And if we can make that shift, it's not going to be easy because it's more than just the technology, right? It's culture, it's workflows. It's everybody … nobody has the answer yet. If we can get to that spot, we can get better impact. I think we can stop the leaky bucket problem with donors. We have a leaky bucket problem right now with staff, with the great resignation.
And then if we can get beyond that, then the next step is this: our work changes for the better. Our work becomes more meaningful because it's more cognitively exciting. We're closer to, like, why we got into this work. And I think this can be extraordinarily incredible, maybe a Renaissance for the nonprofit sector, if you will. I mean, but that's like, I'm getting to be like Allison now; she's teaching me that, to be up on the balcony and see the great things, so I toss it over to Allison.
Justin: Yeah, Allison, here's the thing, is that I really, I'm so fascinated with the idea of the leaky bucket that we've talked about. And so, homing in on that aspect, and specifically as this applies to fundraising. And just as you're going there, let me tell you that, you know, as a professional services company, a marketing company, there are different scopes of relationships. And I'll tell you that there are some relationships that we have to, where we've even evaluated how to fix that leaky bucket so that as a partner we're not using resources for the mundane, right, but so that you do make space for critical thinking, strategic thinking, elevated thinking, and that you find ways to either enable technology or other options to take care of the mundane. So that makes sense in my mind. Well, I want to connect it. Where I'm hoping you can help is, how does this apply directly into fundraising because the benefits across the organization are there? But what about helping increase our net revenue as an organization?
Allison: Yeah, I love this topic, but let me just pause for half a second just in and just say Beth’s answer before was magnificent.
Beth: Oh, thank you.
Allison: How lucky I am to be her partner. You can't be her partner because I am
Beth: No I'm her partner. Now listen to wait for it. Allison's going to make it better.
Justin: I guess if we're rounding out the Beatles, we have to figure out if you're Ringo or I'm Ringo. Yeah you know, and then who's …?
Ronnie: We'll sort it out.
Beth: Are you? Are you John, or are you Paul?
Allison: So, we've never really discussed that. So, we're just going to leave that open ended.
Beth: OK, well, we'll, yeah, we'll discuss that at some point.
Allison: It can change every day, too. Yeah, yeah. So when we first started to look at AI for fundraising, Justin, under that, you know, project with the Gates Foundation, when we began to talk to the C-suite about the possibility that you could have smart tech do research on prospects that was taking hours and hours of development team time and do it literally in minutes, you could see the wheels turning of, Ooh, I get to cut head count, right, automatically. We can move our development, cut our development team from eight people to four using smart tech, right?
And the question back to them I always have is, Oh, you think your fundraising is good? The reality is, your fundraising sucks. And let me tell you why. Because you have this leaky bucket. You get 10 donors in year one, and only two of those donors are going to be with you in year two. Right? And then by year five, you're down to maybe one of those donors. And because of that, you start to frantically send out the emails and create this transactional fundraising. You know, a program that is racing through donors; it feels crappy to people on the outside who were treated like ATM machines.
Organizations never, ever ask us how it feels to be a donor. The thank-you's are just rote things. You know, I can't tell you how often I hear from donors, I didn't feel thanked. Even if you technically got that stupid thank you email, you don't feel thanked. Right? And this keeps happening over and over again, and it's just a sprint, you know, to keep filling up that empty bucket, that leaky bucket.
So now we have technology that can take that 25% of time spent on either research and/or administrative things and smart tech can find prospects. Smart tech can draft communications with donors, right? The Rainforest Action Network uses smart tech to communicate with brand new donors, using stories that would appeal directly to them, right, to cultivate donors directly and individually using smart tech. And it increased the amount of donors that went to become monthly donors, The Holy Grail of fundraising, by eight times what they usually did.
Right, so you can use smart tech to do all of that work and free up your development staff to build relationships, cultivate donors. Ask them questions. See how they feel. Find out stories. Why is this cause meaningful to you? Why is it important to your life? What would it take for you to be an ambassador for us to other people in your networks, right? All of the human work that could help you pivot from being transactional to relational.
That's what the leaky bucket was, and that's what it could become, this garden of Eden of abundance, if we could use the tech well. But it requires leadership willing to make that pivot from what they've known forever in that transactional world to a deeply relational model.
Ronnie: Allison, I really love that. You know, it kind of takes me back to the title of your book about staying human centered in an automated world. You mentioned the C-suite and the decisions they have to make. All these great things that both you and Beth are talking about. Ultimately, this all comes down to being rooted in data, right? So, you have to have good data, clean data, effective data to make this work.
And we've seen this with so many nonprofits we work with where data can be a little bit of a problem. Clean data is not always the best in the nonprofit space. According to Salesforce, only 76 or 76% of nonprofits lack even a data strategy. So, knowing all that, Beth, I'll throw this question to you: How do we get started getting the data in the right place to begin this push?
Beth: You know, that's a really great question, Ronnie, and I'm going to back up just a moment, and I'm going to lead with, you said everything is rooted in data. I want to say, everything is rooted in people, and that we have to be human centered first before we get to the data because the data maybe is at the second stage.
So, we really have to think through, like, what's the problem we're going to solve? What's that exquisite pain point that we want to address? Right? And it can't be just us, the fundraisers or the staff sitting in a conference room, saying this is the problem and then running off and collecting data and doing all the data management things we need to do. We really need to go out there, and we need to use, like, design-thinking methods, and we need to interview those end users, talk to the donors and really understand the problem from their point of view. And maybe, and maybe be open to knowing that, well, maybe we didn’t define this quite right. Maybe we need to think about it in a different way.
I mean, that's step one, and step two before we get to the data is we really have to lay out a good path, or some people use the term, ‘customer journey,’ ‘donor journey.’ And when we're thinking about smart tech, what is the stuff that the humans are going to do or that they do well? And what is the stuff we're going to delegate to the machines and always make sure that the humans are in charge? And that also takes thought. It takes concept testing, it takes conversations, it takes an element of learning about what the tech can do and what it shouldn't do, looking at other examples.
And then we get to this point where we can start to think about the data. And when we think about the data, there's going to be a couple of different ways to think about it. There's the data that the nonprofits have, and there's a whole ladder of … what's the word? I want a ladder of data wellness, for lack of a better word. You know, it has to be accurate, it has to be complete, and a lot of nonprofits just don't have the capacity in-house. They don't have a data manager, right? Somebody who's making sure that it's being collected and cared for.
And then there's another skill. Once you've collected it, that's great. But it has to be turned into some insights. And that's like data scientist skills. And many nonprofits just don't have the resources to have that kind of expertise in-house. So here they're maybe relying on and bringing in data scientist volunteers, or maybe there's collaboration with other organizations. Or a lot of organizations are going to be relying on the vendors who will be collecting data or conjoining data that the nonprofit has. And here is where I'm going to shift it over to Allison to sort of take up the points about, you know, responsible use of data and ethical use of data.
Allison: So, there are cautions about using smart tech. And again, this is why we need the C-suite knowledgeable and comfortable in this arena. And one is that we will be swimming in even larger oceans of data, Ronnie, than we have been in with the digital tech we've known to date, right? We're talking about magnitudes of hundreds of amounts of data that will be available to people, and we need nonprofit organizations to raise the bar on the ethical use of data for privacy concerns, right?
We think that nonprofits are perfectly positioned to adapt, adopt the data privacy rules of the European Union, GDPR, things like the right to be forgotten. So, you allowing somebody to unsubscribe from your newsletter is not the same as the right to be forgotten, the right to get rid of their information, and nonprofits have followed the general standards of the commercial sector, which is to do the least possible protection of privacy of individuals. And we think they ought to do the most. And become a model for how to do this.
In addition, there are really serious issues around bias built into smart tech products and processes that people really need to be aware of. So, for instance, if you begin to use smart tech to screen people for jobs for services, there are two places where gender and racial bias may have been built into that system.
One is that programmers are actually people, and they build their own assumptions and biases into products. And the second is, again, because it does take Library of Congress-sized sets to train smart tech algorithms. Those historic data sets are generally biased as well. You put those two pieces together into a commercial product, and whatever you're pulling off the shelf probably has some bias built into it, and you can't get the bias out. All you can do is be aware of it and try to mitigate it in your efforts.
This is where the knowledge piece comes in. You need to be asking hard questions of vendors, right? What are the assumptions that went into this product? How was it tested for bias? Now, if you're working with a vendor that says, Uh, this is proprietary code, and we can't let you peek under the hood. Then I say, you tell them to go take a hike. It would be, Justin, like going to a bakery and asking for a carrot cake, having them hand it to you, you saying, I have some allergies, you know, I have an egg allergy, are there eggs in here? And they're saying, Oh, the recipe is secret. We can't tell you. Unacceptable answer. So we really need people to understand where and how there can be problems in using the tech and how to be responsible stewards of it.
Justin: I don't think, it's not cliché, but it is: Look, before you leap. Like everything that you mentioned there about the cautionary tales is, Allison. Don't get caught up in the idea of this is either cool or this is something that we should chase because we should chase it. Really think through your use cases and your needs as an organization prior to committing, diverting or leveraging resources towards it.
Allison: Well, let me just add, Justin, there is a tendency people have of looking at smart tech and bots and thinking that they can't be biased because they are these computer systems. The opening story in our book is about an assessment tool used by social workers to provide help to people who are at risk of homelessness. The paper tool got turned into an automated computer system, was used by thousands and thousands of organizations around the world for almost 10 years and turned out to be deeply racially biased. But people were using this automated system on the screen and just went with it, even when the results didn't make sense to them.
So, we can't go on autopilot just because these systems are run by algorithms.
Ronnie: Allison, are there any organizations doing this really well right now? Or, as we just mentioned the hockey stick earlier, are we ahead of the spike, and it's coming? Or, you know, are there any organizations that you can think of, or Beth, same to you, that, that, hey, they're kind of ahead of this curve, and they're on it right now?
Allison: Yeah, there are great use cases, Ronnie. I'll tell you about TalkingPoints, and then Beth can tell you about a group called The Trevor Project, which is doing an amazing and awesome …. Yeah, Yeah. Yeah, well, we've been doing this a long time.
So people, there are people that are really beginning to integrate smart tech into their everyday use, Ronnie. So, TalkingPoints is an organization, a nonprofit based in the Bay area, run by a woman named Heejae Lim. And the exquisite pain point she was solving for is the fact that teachers have difficulty communicating with parents for whom English is not their first language. And that turns out to be a key success point for kids in school, is that communication link between parents and teachers.
So Heejae began to build a smart tech app that would translate between teachers and parents in many, many languages, and they are deeply human centered. They had a pilot effort. They have people, human beings, always overseeing the interpretation because it can be jargony and building this system, beginning in 2015, and improving it and improving it. And right now, it is translating 20 million conversations between parents and teachers, and this is an absolute game changer for those families that are using the technology.
Justin: As the husband of an assistant principal, that absolutely boggles my mind because even in public school settings, I completely understand where you're coming from in the power of using technology to help with that. Beth, Allison mentioned another example. I think it's a little more on the program delivery side, right? So, talk to us a little bit about The Trevor Project and how they're using smart tech.
Beth: Sure, so, so I don't know if your audience is familiar with The Trevor Project. They provide crisis counseling to LGBTQ+ people, young people often that are in crisis, that are in danger of perhaps suicide, harming themselves and other issues. And it's been actually since the pandemic this has really escalated. I just saw an article the other day in The New York Times about the increase in mental health issues of teens and young people is just going through the roof. So, that is, they do important, important work.
So, as you can imagine, the demand for other services are going through the roof, and it was even like that before the pandemic. And to deliver the counseling service, counselors have to be trained, you know, and they use actually volunteers that can be trained. But it's a very rigorous kind of approach. It's very human centered; it's very empathetic. And so, they have this problem where they had this very specific kind of counseling service that needed to be delivered, but they didn't have enough people or the humans to deliver it, right?
And so, one could say, Oh, well, let's just use chat bots and have them replace the counselors on the front line. No, you know, this is a human-centered task. So, as they kind of went through that first step of defining that exquisite pain point and talking to end users and thinking about this, bringing in technical advisers, I believe that they were a winner of the Google AI for Good Challenge. So, they have a lot of technical partners who are working with them, but in this very human-centered way. They decided that, well, we could use a chat bot. And they named it Riley. But we're going to use a very sophisticated chat bot that can actually learn from interacting. But we're going to make sure it's responsible, and we're going to use only expose it in very controlled training simulations with counselors so that they can be trained more flexibly. Which means that this could start to scale the number of counselors that can be trained without adding more staff. And their staff jobs kind of shifted from training delivery to more oversight and quality control of the counseling.
So, I think this is a really great example of thinking through that problem, being human centered and responsible use, which I think is so, this is what we're talking about. And this is, you know, if you think about it, just think about, like, you know, the past 10 years, how when nonprofits take on a tech problem, a tech transformation, a digital transformation project, I mean, it's such a different approach than, kind of, let's run and, like, do it at scale, at scale.
You know, we can't get to scale really fast. With this, we have to go slowly at first. Yeah, that's fine.
Justin: Yeah, the problem is, we don't have much time, but we need to go slow. And in fact, you know, it makes me think of one of our colleagues who helps oversee our data practice and words that I've heard them use, which is, we're intentionally going to move slow on this versus moving … or move too slow versus move too fast because we want to make sure that we are staying human centered in our approach.
And we do strongly, we believe strongly that, you know, no matter what aspect of the nonprofit marketing continuum you're on, that you are an analyst, that we are all stewards of data at this point. But to the great point that you made throughout the conversation today, both of you, and through the book itself, that you have to stay human centered; that first and foremost, starting there.
Beth, Allison, we truly appreciate your time and joining us today. The book is called The Smart Nonprofit: Staying Human Centered in An Automated World. It's available on Amazon and other places. Beth and Allison, you can find all sorts of great content that they've put out across The Chronicle of Philanthropy and on their own blogs, and just do a simple Google search on either of their names. We'll leave the Lennon-McCartney debate to the listeners, ok? But Ronnie, I'm claiming to be Ringo. So, just so you know.
Ronnie: Well, I was going to claim Ringo because I've already got two R’s in my name, so I thought, I just get that one. OK, that's fine. We'll talk about it.
Justin: Well, yeah, we'll talk about it. Beth, Allison, thank you all for joining us today. We really appreciate your time.
Allison: Our pleasure. Thank you for having us.
Beth: Yes, thank you so much. It's been a pleasure.
Justin: Alright. So, you can check out other episodes of Group Thinkers wherever you listen to your podcasts. And don't forget to hit up the Group Thinkers blog on rkdgroup.com, where we're tracking through and continuing conversations on digital advancement and, and honestly, how to take one step forward in 2022. So, thanks for checking out this episode. We will see you later. See you down the road.
Group Thinkers is a production of RKD Group. For more information, visit rkdgroup.com/podcast. Special thanks to our production team, including the talented Ryan Mellinger for his work on mixing every episode. Also, a shout out to the content team that helps pull together research and guests, puts the marketing efforts behind Group Thinkers, Suzanne, Ronnie and others, for their work on this and every episode of Group Thinkers.
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