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Nonprofit Lowdown
#386- How to Actually Use Wealth Screening (Without Getting Burned) with Tina Duong
00:36:34
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- [00:00]
A
Hey you, it's Rhea Wong. If you're listening to nonprofit Load on, I'm pretty sure that you'd love my weekly newsletter. Every Tuesday morning you get updates on the newest podcast episodes. And then interspersed we have fun special invitations for newsletter subscribers only and fundraising inspo because I know what it feels like to be in the trenches alone. On top of that, you get cute dog photos. Best of all, it is free. So what are you waiting for? Head over to riawong.com now to sign up Foreign. Welcome to nonprofit Lowdown. I'm your host, Rhea Wong. Hey podcast listeners, it's Rhea Wong with you once again with nonprofit Lowdown. Today my guest is Tina Young. She is a founder of Impact Pro Tech and a veteran of fundraising, 25 plus years in the fundraising industry. And and today we are going to talk all about wealth screens. Tina, welcome to the show.
- [00:59]
B
Thank you so much. This is one of my favorite topics.
- [01:03]
A
Excellent. I am so ready to get into it because I feel like at some point the tech companies are going to come after me. But I have often said that I have a love hate relationship with wealth screening. So we're going to get into that. But before we do, tell me a little bit about yourself and your company and why you are qualified to speak on this very topic.
- [01:23]
B
Yeah, you know, I'm qualified because I've been doing this for 25 years and across every single nonprofit organization I've always worked at, there was this one kind of nagging problem that every single person or every single org had, which was the inability to really find the right donors in their pipeline to focus on. Like everybody has their methodology, you know, giant spreadsheets. And I was doing that. And then along the way, all these beautiful donor intelligence wealth screening companies came along and promised me the moon. Right? And I started using them and I realized that there was some serious flaws in how they portray some of the data that they provide us. And as I dug into it, I realized that it was creating some serious issues for me and I wanted to resolve it. So when I was working in the nonprofit space, I would just create my own in house tool. And I'm sure a lot of other organizations do that. And then, you know, fast forward. A couple years ago I started my own company which does exactly this thing and I've learned even more as I went along and talked to more and more clients about it and they, they are all still facing the same issue.
- [02:41]
A
So.
- [02:41]
B
So I want to thank you so much for giving me a platform to just at least educate people on what's happening out there. And whether they come to me or not as a company doesn't matter. I just want them to be aware.
- [02:52]
A
Yeah, let us dig into this because this is my pet peeve. I just feel like it's so wrongheaded when organizations come to me and they say, you know, we want to start our major care program. We've done a wealth screen, so we know exactly who we want to be talking to, who we want to target. I hate that word target as well.
- [03:10]
B
I know.
- [03:11]
A
So talk to me about some of the flaws in the analysis, because you said in our initial conversation that these big companies know that there are problems, and yet they continue to sell the same thing over and over again. What are the problems?
- [03:27]
B
The biggest problem, the biggest aha moment for me was when I was using iWave, which is now called Kindsight. And I'm not speaking out of term. They've already heard all this from me before was when I was looking at their capacity scores for individuals. And they have. They have many. They have, like, affinity score, capacity, propensity to give all those great things, but the most problematic one was capacity. And I asked them, I said, well, how did you formulate this? And they said, oh, yeah, well, we take an average of all of the gifts that we are able to source from public records, and then we do the average and we look at what that might look like over five years. And I say, oh, that's interesting. And so when I look into the profiles, if you ever spend any time in any of these tools, you'll see that they consolidate gift records from anybody who has a name that is similar to the person that you are trying to research. And that's hugely problematic if you have a very common name. So, for instance, Jonathan Lee, I literally was looking at this record the other day with someone just to show them how it works. And if you look inside Jonathan Lee's records, you'll see all these gift histories, like over 3,000 gift records. But then if you look at the name of the donor in each record, Jonathan Lee, you see John Lee, you see Jonathan D. Lee, you see Jonathan H. Lee, Nathan Lee, and Jonathan Smith. So it's not looking for the precise name. It's looking for anybody who has any part of that name. Right. And so basically, they're giving you an average of a bunch of random strangers, and it is not useful. Yeah, so that was the biggest aha moment for me, and I was literally jaw dropped. And they are. They. At that time, I was a nonprofit client to them. And they told me that they have all this information available on their tech support pages. There's a really detailed outline of how they formulate all their scores. So it's right there. You just have to know they ask the question. And a lot of people don't.
- [05:41]
A
Yeah, well, in my beef with it, so, you know, similar to aggregating the wrong data, I also feel like there's a lot of data that is not available. Like for example, particularly here in New York City, a lot of people buy co ops. They don't buy, say condos or houses that are publicly available information. So first of all, that data is not available. Second of all, especially here in New York, you have a lot of people who buy like real estate via LLCs. That's not going to be available. You also have a lot of people increasingly giving through dafs that's also not available. So I just feel like more and more there's almost this arms race of like people trying to protect their privacy at the same time that these data companies are trying to transact and extract the data.
- [06:29]
B
Yeah. And it's sometimes I feel a little creepy, I'm not gonna lie, knowing how much information is out there and available. And yes, again, all of these sources, whether it's kind sight, you know, research point, donor search, they are all using publicly available information. So it's not like they're digging through people's trashes but bags. Right. But it's the consolidation of it all in one place that makes it so easy for someone with any talent or skill and profiling. People can tell a story from all the various different collection points. And in fact, you can see their LLCs that hold real estate. You can find that. And it's because of how they triangulate all the different parts of, of that person's public profile to assess. Oh yeah, this is their llc. This is the trust that holds their address. Right. And most non profits, for instance, do have their addresses. Because when donors make a gift, they are sending a check which might have their address on it. They might be filling out a form which asks for their address. So there are many ways to find that information. DAFs are tricky. Absolutely. That's nearly impossible. It's very opaque. It's a common criticism of the daft holder, Deaf sponsor, community, community foundations. Right. Because it's, you know, we talk about transparency in the nonprofit world, but there's very little transparency on that side.
- [08:00]
A
Yeah, the issue, we don't want to go down this daft circle, but yeah, I think one of the issues is that it's very counter to this idea of relational fundraising and the fact that most nonprofit folks do want to be relation. They do want to be able to say thank you to a person. They do want to be able to show the person the impact of the gift. But if they don't get any information, if all they get is a check and it says fidelity Charitable, like, what do you do with that? Yeah, Separate conversation for a separate day. But let's talk about this, because I, I say this a lot. I think wealth screening is a data point. It is not the data point. And so what is the danger of a busy fundraiser looking at the wall screen data as the single source of truth?
- [08:44]
B
There's so many dangerous steps that could be taken after reading that information. You know, if you don't, first of all, do this assessment, right, make sure that the capacity propensity, all that information is really zeroed in on your specific target. What could be. I mean, imagine sitting in front of a donor and saying like, oh, I see that maybe you are really supportive of this cause. And the donor's like, what are you talking about? I've never done it to them ever. Right. Like, how embarrassing could that be? And how detrimental could that be to your relationship? So there's that dangerous kind of risk. The other is oftentimes, as you were saying, when there is a lack of information about a gift history, the donor intel apps will share real estate use real estate as their primary kind of source of truth. But we know that just because you own a $10 million home doesn't mean that that donor is going to mortgage their home to give to you. And in some cases, at least with kindsight, it's clear when they say that this rating is based on real estate records, they'll just tell you right out front. Some of the others apps don't necessarily tell you that. So if you're strapped for time, like you, how do you go and verify all this information? At least with kinds that you can see it all, they kind of. It's all there, the stew, all the ingredients are there so you can figure out what went into the stew. But in a lot of cases, it's not. So it's hard when you don't have time to double check it.
- [10:20]
A
Yeah, I was literally just talking about this the other day with someone that, especially in, you know, expensive areas like New York Bay area, Louisiana, when it's baked into this room, like, yeah, so someone might, to your point, have a $10 million house, it doesn't mean that they Actually have liquid to get to you.
- [10:38]
B
They're mortgage to the hill, right?
- [10:39]
A
Like so anyway, you could be cash, you could be cash poor and housed rich, especially, you know, New York City, as an example. What other pieces of data do you recommend that fundraisers consider in the in addition to the wealth screen to really assess whether or not someone is a real prospect? And I have an opinion on this, but I'd love to see what you think.
- [11:05]
B
Well, for me, I mean, going back to what you were saying, I think these wealth screening services are a fantastic starting point. It helps you get to a certain point faster because you don't have to go and find all this information yourself, but you still need to verify. First and foremost, trust but verify. Then once you've done that, then hopefully you've narrowed down your list a little bit so that you can start with 500 names and then you narrowed it down to maybe 100 names. Once you've done that, then you have to go and do some really deep research. A lot of that information is really just qualitative. It's not even something AI can do very well, just to be clear. And so you go and you find what are their motivations, how are their philanthropic decisions made, what are some of the benefits that they are getting? If they are the kind of donor that likes to give big gifts because they get things named after them, that's a very telling point. Right? You have to assess for yourself if you are willing to offer something like that. If you see that some people are giving on a regular cadence, you can see all their giving history by year, you know the type of gifts, then you can assess, okay, well maybe they're just really a strong annual fund type donor. So you want to understand the donor's behavior and it's all revealed in the data. I always say the data always shows you the way. You just got to know what to look at. So for me, I look at those things, I look at, okay, why are they giving? If they are big enough donors, they're going to have articles written about them, right? So that's valuable. In the absence of that, which is a large part of our donor base, you have to look at which other vehicles are they giving to. Do they, do they participate in things? Are they a volunteer, are they serving on boards? Right. If they're serving on a board and you can see their giving over time increase based on their board tenure, that's also very telling. You might consider then recruiting them for the board and then kind of growing their relationship to you then so A lot of that will come from just experience, which is why I don't think AI is the best tool for this kind of research, is because they don't. Unless you know how to really program your prompts very well, it won't understand motivations. It's such a human behavior. And so if you haven't done a lot of fundraising and you know, face to face conversations with donors, you wouldn't know to pick out things like that.
- [13:37]
A
Yeah, I mean, to add to that, I also think a really important component is the relationship, which again, I don't think AI can really tell you. Right. Even if you're stalking them on LinkedIn. And I had this happen so much is people reach out to me and they're like, hey, it looks like, you know, so and so, can you introduce me? I'm like, oh, I actually don't know.
- [13:58]
B
Right.
- [13:58]
A
Like LinkedIn says I do, but like they just whatever, followed me random. And then timing. And I think we, we overlook timing as a key driver because all the other things could be true. Like it could be the right. Cause it could be something I care about, it could be, I could be connected to it. But if the timing is wrong, like maybe something is happening in my life, maybe, you know, I have a health thing, like whatever, none's going to happen. So I think, and these are, I think decisions really made with human discernment because to your point, like AI can't pick up the nuances. Like if I'm having a conversation with you and like your face changes when I ask a certain question, AI is not going to pick that up.
- [14:41]
B
No, not yet anyways. Definitely not yet. Even some humans can't do it. Right. So it's not every human either.
- [14:51]
A
I would hope, though your average fundraiser is highly emotionally intelligent, hopefully. So talk to me a little bit about what other assumptions are baked into these scores. You talked about real estate, you talked about if you have a common name, maybe it gets pushed into this jumble of a score. What other assumptions are there that folks looking at these scores may not be aware of?
- [15:13]
B
Yeah, I mean, a lot of the scores look at total giving and the scale of giving. So you can see a lot of detail. Right. Literally gift by gift. And if you get a donor that's very prolific like they are, so they're so philanthropic, but they give to a wide variety of causes. Unless you can unpack that, you might assume that just because they gave, you know, a million dollars to the opera, they're going to give you a million dollars if you're school. And so there's a lot of that is masked inside these scores. And so you have to get in there and really extract the gifts that are specific to your cause. You know, let's say you're a climate change organization. You go into their gift testers and you find all the relevant organizations that are kind of tangential to your space and see how that donor gives to those organizations, not just overall giving. And so in some cases, you, you can see so clearly a donor's proclivities, right? You can see clearly they love the arts. It's their top top donors. Donations are made there. You can also really understand their education giving by the years in which they give. So you can easily see, oh, it's because it's for their children. Like in this year, this, this decade it was for elementary schools and private schools. In this decade it was for high school, or this decade it was college. So you can see that that education giving is tied to their children. And so if your school or education program doesn't align to the children in some way, you're not going to get the same level of giving from them. So being able to unpack at that level is so important. And that's where also wealth screening apps have a huge problem. They use sometimes their own codes. So for those of you who are really familiar, the IRS has all these codes. It's called NTE. It's like national taxonomy of something or other. There's six, almost 700 codes which probably has the most, has consolidated all that down to 30. So for instance, in education, they have higher ed as a subcategory and primary and elementary school is the second, you know, the other subcategory. But if you look at the IRS codes, there's like dozens of sub codes under education. Because if you're in the education world, you know that these are very different. Higher ed fundraising is a very different beast than scholarships for elementary schools or, you know, youth kind of programs or elementary schools. So you need to be able to parse that out so that it can really, you can tie a donor's affinity to precisely to your organization. And I was just reminding myself about this too, that Candid has a completely different set of codes. Like, Candid uses 835 codes. And if you look at them, they've kind of parsed them out in their own way. I don't know how they do it. And so they must have to go in and reassign codes to every single 1.8 million nonprofits in the US and, and so none of this information lines up because the gift records that come out of these apps are tied to usually tax records, and so the codes don't line up. So you might be missing out on some information, right? Yeah. So it's a real hot mess. I don't know why they don't just
- [18:39]
A
standardize, because that would be too easy.
- [18:42]
B
Well, I think it goes. It comes down to competitive mode.
- [18:46]
A
Right? Because if, you know, if I Wave has their thing and Candid has their thing and whoever else has their thing, you want to. Competitive mode is exactly right. So, Tina, as I'm listening to you, I'm like, man, like, are well screens good for any. So how. How are well screens actually helpful? What are the. The pros and the cons?
- [19:09]
B
Yes. No. As much as I criticize them, I am a fan girl of them. And it's because I think, as I said earlier, it is a fantastic starting point. There is no way I could collect as much, amass as much data about individual donors as these organizations have. There's no way. I mean, you could try to do it yourself with AI, but it is. These are extremely complex systems that they've created, and so I have zero interest in competing with them. I do think sometimes that they think I'm trying to compete with them. It's like, no. If anything, I'm trying to unlock the value of the data that you've already amassed, and I'm trying to help. Don't the clients use your information more wisely? Right. And so, absolutely. They're so valuable. Right. Find the one that works for you. Everybody has different needs. You know, Research Point is tied to Razor's Edge. So if you're in Razor's Edge, use Research Point. Right. But again, be careful about integrating those scores into your database because of, know, the mis aggregation of data. I like. I honestly, I do like iwave because I can extract a lot of data with spread into spreadsheets. So that makes it easier for me to do my own analysis. Donor search is so funny. I don't know why they do this. They have the exact same kind of table formatted info, but they only allow you to export it as a PDF file. So it creates an extra step for the client. I. And believe you me, every single one of these companies has heard from me. Every time I go to a nonprofit, family fundraising or tech conference, I go to all of their booths in the exhibit hall and say, what is going on with this? Right.
- [20:49]
A
Yeah.
- [20:49]
B
So they know. I think they're afraid to see me coming down the hall during these events. But I don't know why they make it so hard. Right. For their clients to use their information. I would think it'd be the opposite. I don't know.
- [21:03]
A
Yeah. And I wonder too, in the age of AI if that will change. Because AI now has made it so easy to access data and to analyze data.
- [21:12]
B
So easy, I would say, but not perfect. You still have to validate every single fact.
- [21:21]
A
Yes, correct. So let me ask a different question because you and I, when we first spoke, said you said that you had a client who, who CRM was sitting on a donor who was giving a million dollars to a competitor org and they had no idea. And they had the well screens, they had Razor's Edge, they had the fancy tools. What was actually missing? And how do you walk teams through surfacing these potential gold nuggets?
- [21:50]
B
Yeah. You know, nothing hurts my heart more than to see a stale house list. Because this client, not just one, mind you, it was dozens of amazing donors over the years. This organism, this org's been around a long time, many, many years worth of incredible contributions. They had a donor that was giving them 500, but meanwhile giving 5 million to another similar organization. It's like what? And the. The problem is not the tools. Right. The problem is not the systems. Your CRM, that's not the problem. You could put a tool in anybody's hand, but you give me a hammer and chisel. That doesn't make me a Rembrandt. So. So what it comes down to is strategy. Do you have the strategy in place first? Do you know what you want to do with information before you go out and buy a system to collect that information? Do you know why it matters to collect certain information versus others? You have to make all of that assessment first and before you buy a tool. And I fear that oftentimes the nonprofit tech community has some of the best salespeople in the world. They are really smart, they're really strong and they are very influential and they really create a sense of urgency and a sense of excitement, enthusiasm about their tools and oftentimes potentially over promising, you know, some benefits. And this, the. I'm sorry, but the non profit community just gets yes. Stars in their eyes. Like, yes, that's what we want. You are going to solve all our problems.
- [23:36]
A
Yeah.
- [23:37]
B
And there's no way. There's no one tool out there that will solve all of a fundraiser's problems. Yes, I've tried, believe me. I've been doing this for a long time and I am a tech person. And I can't. You can't find it.
- [23:50]
A
Yeah. Well, let's back up because I, I, you're, you're singing for my playbook, which is in the absence of a system and a strategy, you could have all of the tools in the world and it's not going to help you. And I think to your point, and look, I have also been the recipient of buying stuff, right? Because I'm like, yes, this CRM is going to change our life. And like, yes, if we buy this app, it's going to solve all of our problems and it doesn't. Right. It's almost like, I don't know if maybe you don't do this, but like I'll like research things and on Amazon and it'll be like it does all the things. I'm like, yes, I'm going to buy it and it's going to change my life and it shows up and I use it for like a couple weeks and then I never make it again. Right. So I'm curious because I think you also said there's a pattern where a nonprofit gets hard sold on whatever it is, a donor intelligence tool, an automation tool, whatever, in December because the sales rep really need to hit 30 their quota and then it'll just sit on a shelf for four months. What is the honest conversation a fundraiser should have with themselves and their team before buying anything? And how do you know if you're genuinely not ready? Because obviously your salesperson is going to tell you whatever they're going to need to tell you to sell you the thing. So how would you advise a nonprofit?
- [25:09]
B
Yeah, I mean I've literally been having this conversation for months with my current client and they went through this recently and they bought something that bought onto something that they weren't ready for because their data wasn't ready, their CRM wasn't ready and the tool relied on that data. And so it was an, it's an AI tool and it does, it is promising. But they weren't ready because just, they just didn't realize they weren't ready and because they didn't have a full time development person that was an expert in this kind of stuff to tell them that. And I had asked them at the time being, wait for me, wait for me to come. But unfortunately, you know, my start time with them started too late and so they already bought on. So now we're literally, this thing has been sitting on the shelf for four months and nobody's used it. I've had other clients come to me one Currently, who actually has asked about my advice about whether or not they should renew one. And I tell them, I ask them, honest, you need to tell me, do you think you, you're going to use that information again in the next few months? If not, don't do it. And if you do, but they're like, well, maybe we want to go back to them in a year. I said, great, use that to negotiate with the company, the tech company. It's like, look, we're not going to, you know, we've got everything we needed out of you for now, but we'd still want to come back to you next year. Can we renew a year later? What happens to all of our data? Can we lock in something now as a price with a guarantee to start in a year? You know, you can negotiate with them. And so I play that role oftentimes for my clients, even though these are not my tools, right. And I've even turned my, some of my clients away because my tool does, does rely on good, clean data. And if they don't have the minimum, I tell them, you don't, you're not ready, but here's how you can get ready. And I think oftentimes these tech companies, you know, not all of them, but many of them don't really come from the nonprofit space, right? They don't, they're tech people mostly, especially the sales side, and they don't understand what a nonprofit goes through. I've lived and breathed it for 25 years. I was a one woman show for much of it. I know the pain points that these nonprofits face and my hearts are with them. And so finding a company that has that same, your interest at heart is hard if the person just doesn't understand your world and they're not incentivized to understand your world because it might mean a delay in their sales commission.
- [27:42]
A
I have to tell you, not that I'm going to call anyone out, but I'm going to call this out salesforce. So we, oh yeah, we did a whole sales force CRM. Very, very expensive nonprofit package. Nonprofit package. But we spent about a quarter million dollars customizing the whole thing. When I left, I think to be honest, it probably is just like a glorified spreadsheet at this point. Like I, I haven't checked in, but of course, you know, at the time they promised me the world, they were like, this is going to do everything and like basically, you know, do your laundry for you. And it sounded great, but I do think, and I'm not going to Describe bad intentions. But I think, to your point, like, they don't really have a clear understanding of how limited the capacity is on the nonprofit side. And you're like, sure, if we had a full time database manager, like, we could make this work. But we don't.
- [28:35]
B
Yeah. I mean, I don't. I don't think they're. They have bad intentions. Right. It's just incentives are misaligned, and they just don't have that deep customer knowledge. And I've always said, and I've learned this from a lot of other entrepreneurs too, that before you, if you're going to design a new tool, make sure you understand your customers well. In fact, the best products out there are founded by entrepreneurs who lived and breathed the problem for a long time.
- [29:08]
A
Yeah.
- [29:08]
B
And they were solving the problem for themselves because. And if they can do that for themselves, there's plenty of other people out there who are just like them. Right. So I think that's something to look at. If you are a nonprofit, ask the questions. Ask them who developed the tool, what's their background, you know, who's the head of sales. What is their background? You know, try to get a feel for the people behind the tool before you buy in, because that'll tell you a lot about what it's really capable of and what you can handle. A lot of these tools have way too many bells and whistles, and I. You know, it always makes me sad to hear stories about the Salesforce integrations that just flop. Because Salesforce is powerful.
- [29:48]
A
Yeah.
- [29:49]
B
And I've done it. I've done Salesforce integrations. I love Salesforce too. But it can be overkill.
- [29:54]
A
Right.
- [29:55]
B
Because if you're not ready for it, it's just overkill. Yeah.
- [29:59]
A
I mean, the vast majority of the clients that I work with, I get the CRM question all of the time.
- [30:05]
B
All the time.
- [30:06]
A
And for the vast majority of it, Salesforce is overkill. Right. I'm like, you should go with a less expensive, lighter weight tool. But I think it's hard because everyone wants the Cadillac. You're like, but I'm gonna, like, I'm growing. I'm gonna be there. You're like, yeah, but not if you actually don't use the tools. So, yeah, slow it down.
- [30:27]
B
And then it's like marathons. You know, it's marathon season here. Right. So I've been thinking about it, and it's like, you don't run a marathon the first go. Right. You build up to it. I don't run. I'm not a Runner. But I have a lot of friends who are marathon runners, and they tell me about their training program, the regimen they go through. They do a little bit at a time, a little bit more, a little bit more, every time, a little bit more. And then finally, you know, they actually run a full couple of marathons before they actually enter the marathon, just so they know they can do it.
- [30:55]
A
Oh, I know.
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B
That's the mentality that the nonprofits really should have. Like, start with something really small and tactical that meets your current immediate need. Build the muscle slowly over time that then, then you can go on to the next level. Right. Because your muscles are better and you keep going. You keep going. But if overnight, you're not going to run a marathon.
- [31:16]
A
Yeah. All right, last question for me. So what is it that your company does? Because we've talked a little bit about, you know, you're using tools to extract the value or unlock the value that, that these big wealth screening companies do. What, what is it that your company does? And, and how can folks get in touch with you?
- [31:33]
B
Yeah, well, the, the thesis for my company is that past behavior predicts future behavior. And in the world of fundraising and giving, it is giving history. And as we said before, finding all those gift histories, that's what these wealth screening companies do. Well, but then pulling them out, finding, making sure it matches your donor, that part is extremely difficult. And just so you know, no company out there has to resolve this. I have a friend who does exactly the same work, but for corporate executives in enterprise sales, big, big contracts, and even they haven't figured that part out. So getting the name matches, very difficult to do. But I can do that for my clients. And then once I have those gift histories, I run them through a tool called Pro Distiller, which effectively helps my nonprofit clients review just four key pieces of data, not everything. Like, even in I Wave, there's like 80 sets data points per record. It's like, whoa, that's too much. I said there's only four. You really need to know, who have they given to? Does that cause line up with yours? When was the last time they gave and how much have they been giving in that time period? That's all you need. And you can do this manually yourself. You can extract the spreadsheet and you can do it manually if you only have a few dozen, but if you have a few thousand, you, you just don't have time. And so my tool automates that whole data mining process. And so they can run filters and reports easily for no matter what campaign they're running, whether they're looking for an annual fund list, whether they're trying to figure out who, you know, who to invite at what event, who should their top executives prioritize and talk to. So my tool helps them figure out all that literally, like in seconds. So I used to have to do this myself. I would just sit there and stare at spreadsheets all day long, and it would take me months and months. Right.
- [33:30]
A
And with my tool, finance bro of you.
- [33:33]
B
I know, but that's what you got to do. Right. And so. But my tool can literally trim that down to a matter of days. So imagine your top fundraisers. Wouldn't you rather they be out there talking to their donors and staring at spreadsheets? Yeah, so that's what I do.
- [33:49]
A
Well, and you said something really interesting about the integration of AI and how prospect researchers might be a thing of the past, which, you know, I think we, we're all out here hearing about, well, AI is going to replace people. But your thesis is actually that AI will replace prospect researchers.
- [34:09]
B
Possibly. Right. Because for the most part, most of those researchers haven't spent a lot of time in front of donors. And that the nuances of relationships, what moves people, you can't really benchmark that. You can't really put that into a statistic. And the AI models rely on that. It's a model. It's a logic model. There's no logic. Humans don't have a lot of logical thinking. They're. First of all, any purchasing decision is very emotional.
- [34:40]
A
Very emotional.
- [34:41]
B
And then philanthropic giving, even, like, even more so. So how do you tell a model what that is? Right. It's hard.
- [34:50]
A
Yeah. All right, well, Tina, thank you so much for being on the show and I'm glad we had this conversation because I have been on this particular topic of wealth screen scores forever. And so I'm glad that someone was able to actually put some detail around my vibes because I was like, my vibe says these aren't right. Because I've read my own name through and I'm like, it tells me this person could give a fifty thousand dollar gift. And I was like, I don't know who that person is. I would love to meet that person. But what?
- [35:20]
B
That's not me.
- [35:21]
A
That's not me. Which only for. And then I think I ran a couple of my top donors through just as a test. Again, completely off. And I was like, yeah, this tells me that you trust me. Like, I don't trust this because I verify.
- [35:36]
B
Yeah.
- [35:37]
A
So, I mean, I think it's like I tell my clients, well, screens are a data point. They're not the data point. So just buyer beware.
- [35:47]
B
Yes, absolutely.
- [35:49]
A
All right. Well, thank you, Tina, for being on the show. We'll make sure all of your information is in the show notes or for folks who want to get in touch with you. And in the meantime, fight the good fight.
- [35:56]
B
Thank you. Good luck.
- [35:59]
A
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