 Welcome everybody to another episode of the nonprofit show. We are really excited. I've been excited for a long time because we booked Sean Oles quite a while ago and we wanted him to come on and talk about artificial intelligence and what could be a sexier show title then is AI coming for your nonprofit job. I can't wait to hear what Sean has to say and how he can share his knowledge and his journey with us. It's going to be a great show. If we haven't met, I am Julia Patrick, CEO of the American nonprofit academy and I'm thrilled to report that Jared Ransom took a big spill this morning but didn't break any bones on her mountain bike. You know, I don't know if a lot of you know but every morning she gets up crazy early no matter where she is pretty much in the planet and does some sort of bike or hike experience. So we'll have her back on shortly and we'll get her to witness about her big fall this morning. But anyway, Jared Ransom, CEO of the Raven Group and the nonprofit nerd herself. We are here each and every day almost 850 episodes now because we have amazing partners and they include Bloomerang American nonprofit academy, your part-time controller, nonprofit thought leader, fundraising academy at National University, staffing boutique, nonprofit nerd and nonprofit tech talk. These are the folks that join us day in and day out so we can have these amazing conversations and these amazing conversations make sure you download our app. It's super cool. Our team from the American nonprofit academy led by Kevin Pace crafted this technology so you can take this show on the road with you. You can also find us on all of our streaming broadcast platforms as well as our podcast format. If you like to consume your information while you're on the go as well. OK, Sean Oles, I've done my housekeeping. Now it's on to you, my friend. Talk to us. I mean, Boodle AI, great name. Talk to us about what Boodle does. So Boodle, I'll start with the genesis of Boodle. My co-founder and I jokingly say are basically lazy. We had spent, in addition to everything we did professionally, we spent 20 plus years serving on nonprofit boards and essentially we're tired of beating our heads against the wall trying to raise money. And as you know, raising money in the nonprofit space can be very ineffective and very inefficient. And so both of us being technology people wanted to find a way to bring technology, specifically data science and machine learning to nonprofits. But we knew we had to do so in an easily consumable manner. And the analogy I like to use with the pandemic, most of us have spent a lot of time on Zoom. I tell people when I speak to them that I'd be willing to make a bet with a good bottle of wine and a good steak dinner that 90% of the people you've spoken to on Zoom could not explain to you how video over IP works. But they don't have to because Zoom made it the press of a box. And so that's what we wanted to do with data science and machine learning. And so with the title of the show is AI coming for your jobs. I'm here to tell you yes, but just the really boring bad parts. What AI is going to do is take the things that would take us weeks if not months to do the analytics, the diving through data, the collection of data, and it's going to do it in hours. So where, you know, we work with consulting firms that would do a 12 month capital campaign and historically spend 90 days in the trenches digging through data and analytics, and then only have nine months to fundraise. Well, now they can get a machine to do it in a few days, and now they've got 12 months to fundraise. And so it was that idea of leveraging and harnessing the power of AI, as well as data, both the data that nonprofits have and third party data to allow them to become more effective and efficient in what they do. I love this conversation, Sean. And I think that it is such the technology aside, just the theory that we are going to amplify how we build our relationships is really at the core of this. Because a lot of times we work with fund in the fundraising capacity thinking that it's just, you know, it's luck, it's knowing the right people, and it's being brave enough to ask. And we discount all of this additional support and information that will really help minimize our luck, if you will, that will make us stronger. So I love, love, love that you've taken your experience and melted it with technology. So I got to ask this question and you mentioned this about taking the data, understanding where it's, you know, how can impact you and making it not such a slog. It seems to me that we can do this quickly. But at the same time, I got to ask you this question. Do we really know what we're looking at and how do we retrain our teams to know how we take this information and make decisions from it? Absolutely. Are you finding that there's a problem with that? There is and it's largely because the industry has grown up a certain way over a series of decades and they've gotten used to what they've gotten used to. Nothing is more frustrating to me than, hey, I'm going to do a major gift fundraising. Let's just go find all the rich people because they'll give to us. If tomorrow, Julie, I make you the head of the All Things Apple Foundation and I give you a list of potential donors and Bill Gates is on that list, you and I both know he's not going to give you a dime. It doesn't matter how much money he has. So the other big problem I ran into as a board member that was frustrating was the thirst for more data, but with no idea with what they were going to do with it. So I would watch boards that would, or organizations that would come to us as a board and say, well, we need to invest and buy all this data. Okay, well, what are you going to do with it? I don't know, but we'll have the data. And in a large part, part of the reason we built Boodle the way we did is we knew that most organizations would actually tell us that they either had messy data or skinny data, very limited data. And so we actually built the platform to be able to do identity resolution with just a name and an email address or just a name and a postal address. And then what we wanted to do was we focused in, there's a several decade old statistics that 80% of first time donors never come back. Right, they come in via the ice bucket challenge, the roommate runs a race, whatever it may be, they don't come back. But if you look at the 20% who do they come back because they have an affinity for the cost, they care about the cost. And so as we built our platform we started in 2016 we spent four years $5 million building the platform we didn't want to build the cars it was rolling down the road. And while our development team was building the tech stack, our data team scoured for all the data they could find about how individuals focus on affinity. So what we actually did was we built a proprietary database of all 250 million Americans, and we enriched all of them with 1200 data points. And so now what that allows us to do is even the smallest nonprofits with the skinniest of data, as long as they have a name and an email or a name and a postal address, we can then match those names into our proprietary database and then switch with all of that data to then allow them to build models about what their best donors look like and start to understand their donors in a much differently than they used to. You know how hard is it to get. I love this piece of the technology and what you've what you've determined is the right course. I want to ask a curveball question and that is how hard is it to get those development teams and dare I say leadership or the boards to understand how to use this data because you're talking about things that most people never ever had even known that it was possible. But you know, do they know how to use it and so having that enhanced donor management piece, there's got to be a degree of education moving up right to get people to understand how to use it. There absolutely is. I jokingly tell people you know with the advent of chat GPT AI is now cool. When I would get speeches over the past six years to two things would always strike me I would always begin my speeches by asking people how many people in the past seven days have used AI and invariably in a nonprofit crowd less than a third of the hands would go up. And then you asked the crowd okay for those of you who have not who think you've not used AI, have you used Google Maps, have you watched Netflix, have you and you go down the laundry list of things people are doing in their daily lives, and they don't realize that AI is so pervasive and everything we do that starts to break down a little bit of the barrier but because before chat GPT when you talked to nonprofits and you said AI, what they pictured was a steely head with red eyes coming at them. It was it was scary to them as they start to realize that hey Google Maps makes my life a heck of a lot easier hey I've watched programs I never would have watched on Netflix that were really great because of AI. They start to realize that maybe there's something this can do in my work life that's it's already doing in my personal life with the advent of generative AI in a public forum I mean generative AI has been around since 2017. But it took a public face with chat GPT. Now people are looking at it much differently and one data point I'll give you. I was at the AFP icon conference in New Orleans in April. And there was only one session on chat GPT out of either 60 some odd sessions, but I went to it and what's interesting so a an industry that usually doesn't adopt technology quickly. There were 300 seats in the room, it was standing room only over 500 people packed in there. And the speaker asked a very similar question to what I asked he asked how many of you have used chat GPT since it launched over 90% of the hands went up in a room full of people who don't adopt technology, they had used chat GPT because it was easy. And then they found it useful. And so that's been one of the big problems and take bootle out of it you take a CRM you take a wealth insights platform anything 1.6 million development directors walk in every morning and they have a question on their mind. And we as technology providers make these beautiful dashboards and all these reports. But what we're relying on was that that development director could build the bridge from her question to our dashboard. And if she couldn't, no fault of her own but if she couldn't, our technology was useless to her. They had been a gendered of AI. Now these individuals can walk in, ask the question they want. And with the right company with the right insights behind it they can leverage generative AI to go into those insights or that data and find her the exact answer she needs. And that accomplishment that ease of use is what's going to drive adoption a lot faster. And I think the other thing that's happened and there's not many people who would say there are positive things that come out of the pandemic. But one of the most positive things in the nonprofit space is you saw nonprofits adopt technology faster in years and they had the previous two decades. So you've got nonprofits that are already getting a little bit more comfortable with technology and now you introduced gendered of AI, which makes it really easy. And I think you'll see a lot more adoption and benefit to the community. Right. I absolutely agree with you. I think that that COVID pushed the nonprofit sector, you know 1.8 million nonprofits registered in this country that hadn't changed things up very much until they were forced to right because they're so busy trying to achieve their mission vision and values and carry on their work. Understanding the organizational structure and how to work hadn't really come to the forefront. One of these things that I think that we worry about so much with technology and of course we're here talking with you about AI, but is that loss of personalization and the outreach and that engagement. And, you know, we've been talking so much about the passion and we got to sell the story and we got to, you know, have that tear jerking moment. And there's a sense that in which is manipulative, I think, but there's a sense that with technology, we lose that can you share with us why that's really not. That's not true. We don't believe that and as I said, you know, yes, AI is coming for your jobs, but only the bad part, it still needs the human. And the example I always love to use is and we always talk about the human machine team being the most powerful AI team there is. Because the machine is going to be able to do things the human would take weeks or months to do. The machine is going to lack that experience the intuitiveness and the empathy that an individual has. So example, Julia, if we give a machine the power to look at a list of potential people, and you're at the top of the list as a potential major gift donor. And they call you and say, you know, the machine says Julia, how are you doing today and you say, well, I just had a big fall. My husband just had a car accident. Our daughter has COVID and I've got to get this board deck done. The machine's going to say, oh, sorry to hear that, Julia, would you like to give $5,000 today? That's going to fall flat and it's never going to work. But the development director who found Julia's name in three hours instead of three months and picks up the phone and gets that same response from you is going to make a note to call next Friday a week later to check in on you not to ask for money just to check in on you. That development director is going to ask if there's anything they can do to be helpful. And then maybe a month or two down the road, they'll actually ask you for a gift. Once the household is settled again and everything's in place, that's when the development director will do. So in the meantime, though, that development director can leverage the machine to find the next five Julius, who haven't had accidents and kids with COVID and everything else. And during those three months, they're waiting to ask you, they've got five of their major gift donors that they picked up. I love it. And I love how you've woven this example because there's anybody watching or listening to the nonprofit show today that's had any engagement in fundraising or relationship building. This is what happens. What you just laid out happens and then you can hit a wall and you're not creating more of a pipeline. So I love what you've said. It's absolutely fascinating. It also tells me that it goes back to the very first thing that you said that AI is going to be taking the crappy parts of your job so that you can do the things that you're good at building the relationships, understanding, communicating things at that level. Talk to me a little bit about campaigns and programming and all of the metrics and the things that we are really trying to navigate and understand. How does that fit into what you're seeing? Yeah, I mean, this is the beauty of being able to leverage large amounts of data, even if it's third party data, being able to leverage the success of your own campaigns. So let's say we're doing DREP mail. DREP mail is not going any place any time fast, but we are seeing DREP mail that has gotten a lot worse. So if you're able to look back historically at DREP mail appeals that have done well, inform the machine, this is what's done well, then get even better with here is the list of people I'm going to reach out to. And in the case of Buddha, what we're able to do is allow the machine to identify who those are against our database and now build a profile of those people. So the machine has the ability to look at the profile of the individuals and then look at your most successful campaigns and now generate a letter based on that. Now, could a human do that over time? Of course we could, but if a machine can generate a first draft of that letter for you in an hour, rather than you taking a month to do all the analytics on the list to start drafting and all of that. In one hour it produces a draft for you so that by the next day you can fine tune it and have it ready. And it's informed based on the actual individuals you're sending out to not just on a gut feel of what you think is right. That becomes a lot more powerful in your campaign efficacy and allowing you to not only be successful in that particular campaign, but then start to branch out to other forms of reaching out to people. Right now, one of the biggest mistakes nonprofits make is I'm only going to do DREP mail, I'm only going to do digital. And the reality is omni-channel fundraising is essential, right? We don't know necessarily what's going to get the person there. And I've never in 25 years of fundraising walked up to a person who's never heard about a charity and said, here's my charity, here's what we do, give us a donation, and they donate. They've got to be cultivated. And so if you can get the right messaging out over multiple channels, that person's going to get touched several times. And then what the key is, is understanding those individuals and what channel they act upon. Because then that's where you put your big force. You may do little digital ads that get your name in their presence. You may do a DREP mail piece to get some a little bit more information. But if you know that at the end of the day, the phone calls what's going to push them over the edge, then at the end of a 30-day omni-channel campaign where you hit them at several points, now you get a development director on the phone that gets them over the edge and makes that donation. Right. You know, Sean, this is such an interesting conversation. I could talk to you about this for days because I do believe what you're embracing is where we need to go as a sector. And that those that lean in and invest mentally, physically and financially, I just feel are going to be like leaps and bounds. It's not going to be a small separation. It seems to me it's going to be a huge separation. And I'm wondering if you could kind of comment on that, if you're seeing that already. Well, I think you're definitely going to see it. I mean, we see it not just in fundraising. You see AI being used programmatically. So two of my favorite examples, United Refugees. They used to literally take a dozen person team and a big book of faces and then walk through a refugee camp thumbing through it trying to find matches. Today they can send a two person team with an iPad using facial recognition, which is a branch of artificial intelligence. And they're making 10x the number of identifications that they used to make. Now, when I go to a potential donor, I can say to them, hey, it's going to cost me $100,000 to make 10 matches, or it's going to cost me $10,000 to make 100 matches. Well, which organization do I want to donate to where's my money being better spent. And so if we as organizations as nonprofits and as fundraisers are able to show our donors. If we're using the latest and greatest in technology, we're being the most efficient with your dollars. We're much more likely to get sustained that that and steward that person along but potentially get them to be a bigger donor down the road. And for the organizations that choose not to do that, they're not going to be able to raise the money and be able to stay in place. You know, this is a follow up question to that and I'm kind of curious what your your comments are. Do you see this as working with one certain demographic more than another, specifically age related demographics, demographic tracks where they'll say, you know, I think there's this sense in the nonprofit sector that it's older people that have more money and will invest more. And then the younger folks they have maybe time and they can volunteer, but they don't have, you know, the economic capacity. I don't necessarily think that that is true. But do you see this component of communicating about technology and using technology being favored in one demographic group of donors over another. I don't actually I think what what what we really get fascinated about is being able to leverage AI and the data that we bring in you start to understand who your donors are better. And we as humans will insert our own biases into what we think we get it wrong. I'll give you very quickly we had an organization 30 years old, raise money for children based in the US but they worked internationally. And when we went in the development team and it was a big development team this wasn't you know they raised $30 million a year they had a good size team. And they said to us, we already know who our best donor is. And I said well before you tell me who it is, what is your best donor look like who are they. Well, my best donor was someone who donates three times at least, but every time they increase. So whether it was $1020 $30 or 1000 10000 1000 that's what they wanted more of. So okay, what does that individual look like they said we already know it's a married white man in business who's between the ages of 45 and 55, and he likes to be communicated with either by phone or email. Okay, they took 30 years of data, put it into the machine actually is 20 years of data but 20 years of data put it into the machine. And we showed them within an hour by their definition, their best donor was a single woman between the ages of 25 and 35 who like to be communicated with by text. And so two follow ups to that so the next month they redid all their creative and mind you they'd spent five years of marketing dollars towards this mythical married white man. The following month they redid all their creative towards that demographic and they sent out a text appeal over a 30% increase year on or month on month in revenue on their monthly appeals. So they asked them, Why did you think it was this mythical white man, they all kind of shrugged and said well, that's who we talked to every day. And what came out was, it was the businessman who had time on his hands, who could pick up the phone, and could and generally wanted to be thanked for what they done, whereas the young woman who their mission resonated with her. She was too busy building her career to need to do and didn't need to be thing. She just wanted them to do their job well. And so, I think it's the demographic is going to be nonprofit by nonprofit, and what this technology is going to allow nonprofits to do is better understand who is their core demographic if they have one. And then even more powerful is, if you know what that core demographic is, and you really want to grow as an organization, why not take that core demographic out and understand who the the upcoming demographic is. Because if all your appeals are to your core demographic, you're going to lose that lower demographic. Right. That's a fascinating concept and spot on because we just tend to, you know, preach to the choir, and we never look, you know, down the road at how things can change. Wow. You know, Sean Knowles, you have been riveting. I have really enjoyed this and our time is up. We need to get you back on and have you talk more about what's going on. You need to check out bootle.ai, their website. It's really interesting. They have an amazing team doing fascinating things. But I loved talking to you as a co-founder and learning about how you've been in the trenches and sitting around that boardroom having discussions that we've all had. We've all had. And so kind of reframing it has been fascinating, really, really interesting. Talk to me about what's the best way for somebody to learn more about your company and try to understand how maybe their nonprofit can fit in with with your work. Are you recommending like a certain budget size or team size? Do you have any kind of ideas that you could share with us about what's going to make a good fit? Absolutely. So first and foremost, really, thank you so much for having me today. This has been a pleasure. Really, really enjoy my time with you. We are actually in the midst of an evolution of our platform. We had a very enterprise-focused platform that was built directly for nonprofits. We still offer an enterprise solution, but with the advent of generative AI, we are introducing and we'll launch post-labor day, what we call bootle box, which is leveraging generative AI so an individual user from a development team doesn't even need to be the development director could come in, log in and use the platform. And we'll have a freemium version so that anybody can log in and use it and get comfortable with it. But then as they want deeper insights, want to be able to perform identity resolution, things like that. There will be a fee, but it won't be an out-of-budget fee. It's not tens of thousands of dollars. It's not even thousands of dollars. And so, and it will be on a monthly basis. So as people see the benefit from it, they can get comfortable continuing month-on-month. The best way to get any information about it is at our website, bootle.ai. And my background has all my contact details as well and people can feel free to reach out to me directly. I love it. I'm really fascinated by this and good for you. We do need to get you back on and talk more about that as that's coming to market so we can understand it more. You've given me so much to think about and it's really something that we should all be having these conversations and thinking about. Because this is where we need to go in order to, I believe, fulfill our mission, vision and values. And we don't use this mindset and we don't shift our mindset. The technology will just be at our feet. Actually, it'll be at someone else's desk down the road and another non-profit in the beginning that she uses, we like to say. So yeah, Sean Olds, it's really been fabulous to talk to you and learn more about bootle. Again, I'm Julia Patrick, CEO of the American Nonprofit Academy. Jared Ransom, the non-profit nerd herself will be back with us shortly. Again, more than 800, I think we're close to 850 episodes, amazing guests from all over the world and they come to us five days a week because of our partners. Bloomerang, American Nonprofit Academy, your part-time controller, non-profit thought leader, fundraising academy at National University, staffing boutique, non-profit nerd and non-profit tech talk. Again, these are the folks that are with us day in and day out. Wow, okay Sean, you've given me a lot to think about. I really appreciate that. A great way to start a week in a Monday. I'm sure I'm going to have lots more questions for you and I can't wait to see the next phase of bootle and how you become more accessible to smaller non-profits. Thank you. Thank you, Julia. Pleasure to be here today. It's been a lot of fun. Hey everybody, as we end every episode of the non-profit show, we want to leave you with this message and that is to stay well so you can do well. We'll see you back here tomorrow everyone. Thanks Sean.