7 Secret Lead Sources

Mike Hambright (00:00.672)
Hey everybody, welcome back to the show. Today I’m here with my buddy David Lecko, Deal Machine. We’re going to be talking about seven secret data lists to go after that you might not be targeting right now. In fact, you’re probably not. So going to be an interesting conversation. Maybe we’re going to find a couple of jewels in the rough here. David, how are you my friend?

David (00:17.019)
I’m doing really well. for having me, Mike. It has been.

Mike Hambright (00:18.934)
Yeah, good to see it’s been a little while. You’re out racing cars and doing all kinds of cool stuff.

David (00:25.255)
That’s right, and focusing on lot of investor data. And I did seven real estate deals as well last year. So I think it was my best year yet.

Mike Hambright (00:30.988)
Yeah. Yeah. Awesome. Hey, before we kind of jump into this, maybe talk about a little bit of your background, how you got here for folks that don’t know you.

David (00:40.849)
Yes. So man, back in high school, I noticed some kids had nicer cars than I had. had a 96 Chevy Lumina. It was a great car. But why did this guy, Max, have sports cars? You know, I just, knew I wanted that stuff. So I had to go seek answers. I ended up reading books like For Our Workweek, Rich Had Poor Dad, and really got turned on to the idea of business. It wasn’t till after college and I got my first job for an entrepreneur who had 20 person company. I noticed he had rental properties. And I was like,

why do you have rental properties instead of stocks? And he said, well, the stock market goes up and down, but if you buy the rental property right, you manage it well, it’s always going to cash flow. And his goals to hire by 40. And I thought, man, that sounds pretty good. So I set on a journey to go figure that out myself. I couldn’t find any houses that would cash flow, but luckily end up going to a real estate meetup. said you need to go off market. So I was doing that, writing down addresses of houses and a notebook, but ended up

you know, missing out on what could have been a great deal. It was rundown houses I was looking for, but I drove by a couple months later and it was being worked on. So I rushed home to see if somebody bought it. They did. It was a great price, but I hadn’t even like reached out and sent a postcard. you know, seven years ago is where that timeframe is now. I built this tool for myself. It would let me pin the house, send mail to the property owner so that I would never have that problem again, where I kind of struggled with the follow through.

And so, you know, to, I found out, that person who ran that real estate meetup, they, they wanted to, they heard about what I had created for myself. They were like, how I want to try that. I’d spend a thousand bucks to do any new marketing. And I was like, shoot. Okay. Figured out. I put it on the app store. It was never meant to be a business, but you know, she paid like 700 bucks for certain number of postcards and people started slowly finding out about it and it became deal machine. And we became known for the driving for dollars app. was, it was a.

Mike Hambright (02:34.222)
Yeah.

David (02:37.735)
perfect app that it was just good product market fit, right time. We attracted thousands of customers with no marketing, just word of mouth. But as markets mature, there might be a limit to how many people drive for dollars. I one of the things that we learned was driving for dollars is a great strategy. A lot of beginners are using it. They’re being told to do it.

there wasn’t an app for that. So because we made their job easier, we made doing what they were already doing easier, it was perfect, right? It just caught fire. And so that was really great. But when it came to the more advanced investors like yourself, members of Investor Fuel, et cetera, I think that they all know driving for dollars is a good thing, but they weren’t already doing it, right? Because it’s not like a…

a strategy that’s easy to scale. So they weren’t already doing it. And we spent a good year or two developing a system for advanced investors to go build Driving for Dollars teams. You could have 300 people in the app, and we invested a lot of time building that product so that we could help advanced investors do that. And it didn’t really go so well, Mike. So we actually wasted millions of dollars building that out, and it never…

Mike Hambright (03:37.432)
Mm-hmm.

Mike Hambright (03:44.749)
Right.

David (04:01.165)
Took fire and we’ve actually pulled it back and not really in our system anymore so that it’s easier for us to Maintain right the more features you have the more cluttered it can become the harder it can be for somebody to know what’s what? and that was a big learning lesson for us and On that journey. I really discovered that if you make it easier to do what people are already doing That’s a good idea, but if you’re trying to change their behavior That’s not a good idea

Mike Hambright (04:05.486)
Hmm.

Mike Hambright (04:10.348)
Yeah.

Mike Hambright (04:25.153)
Right.

David (04:30.023)
You know what I mean? And that’s what I really learned from that. But I would say what I want to talk about today should help a lot of investors on my humble learning journey was, so we figured out a lot of investors, big or small, they need a really great data on phone numbers and on properties. And so, you

Mike Hambright (04:30.936)
Yeah.

Mike Hambright (04:54.642)
Right. Because David, hey, correct me if I’m wrong. So on Deal Machine, I know you’re talking about mail, but you could, as you evolve, you could call and message people from the app. Is that correct?

David (05:07.101)
Well, we, I mean, historically, we always had the traditional button where you could pay eight cents and now you have some phone numbers related to the property that you can call, right? So we really put our head together to figure out, how can we make that better? So, you know, I think pretty much everyone under the sun is just kind of passing through a five cent cost. If you pay eight cents, you know, whoever you bought that through is getting charged five cents somewhere else. And the way you could tell is you don’t see the data until you click the button, right? There’s a little bit of delay and then.

Mike Hambright (05:14.594)
Right. Yep.

David (05:36.157)
Bing, now you have it. So we really put our heads down and we now were able to put together the database of every single person in the United States. And what’s great about that is we don’t have an incremental cost to go look it up. And we can also browse through it all. I could look up Barack Obama. I could look up Elon Musk. Everybody’s name is there. Now, some of their numbers are redacted. So Elon, as I did check, he didn’t have a phone number listed in there.

He’s in the database is what I’m trying to say. And so then we were able to provide and the really tough thing that we were able to do is match it to who currently owns what property. And so those matches we were able to make, now we could offer really great data that’s presented a unique way. Because I don’t think any other place where you could filter and browse through that type of database, especially match the properties. And about a year and a half ago, it’s really started to drive a lot of growth.

and save like nine, it’s like $9,000 worth of old skip tracing that you might get in like a $599 plan with Deal Machine. So, you know, then the next challenge was like, okay, great. I mean, but people still think about us as driving for dollars. So how do I make sure they know? And I just started asking investors or reaching out and say, hey, what’s some hard to get data that you, you know, just haven’t been able to find that would be really useful. And so I learned seven things.

Mike Hambright (07:02.092)
Yep.

David (07:04.637)
five, six, seven things that I just wanted to share with you because the use cases are really cool that I haven’t heard about. And the first one, I’ll just jump right into it, is a lot of land flippers. You have land flippers in Investor Fuel. Yeah, so what’s really important for them is they want to find scatter lots, are, at first, people do infill lots, which is like in a subdivision.

Mike Hambright (07:19.074)
Yep. Yep.

Mike Hambright (07:31.448)
Yeah.

David (07:31.541)
But they also want to make sure that they’re not getting lots that are like out in the open with no road connecting to them or a landlocked property for whatever reason. So right there like, well, we want to make sure that these properties have road frontage, they’re kind of flat topography and have lake waterfront. And so I was like, can I get that for you guys? And so I kind of like played with some of the data we have behind the scenes and figured out, well, you could do municipal sewer, first of all.

Mike Hambright (07:38.274)
Hmm. Right. Right, right, right.

David (08:00.071)
to get a road frontage property because they don’t build sewers anywhere but under the roads, right? So that was one of the things I was able to point out for them. And then there’s like a flat topography filter and the lake waterfront was a tough one. We didn’t have that exact thing in the data set, but we connected OpenAI to be able to look at the satellite images of the address and it can say, yeah, there’s like, looks like there’s like a lake shore or something like that.

Mike Hambright (08:05.175)
Right.

David (08:28.985)
on the property. I don’t know if you’ve heard of that struggle with land flippers, but that was like something unique I learned that the land flippers are always looking for.

Mike Hambright (08:30.52)
Wow, that’s cool.

Mike Hambright (08:37.442)
That’s great. And people just search for that by, I know a lot of land folks too are a little less particular. mean, there’s people that will buy across multiple states or in entire regions or things like that. And so people can go in and filter that by whatever geography they want.

David (08:52.625)
Yeah, so a lot of people plug in either the county name or a zip code. And then the next thing they would do is municipal sewer. They hit the vacant land button, of course. There’s the topography button. And then once you’ve got it narrowed down like that, then you could basically take that list. then you could ask AI, look for waterfront. Look at the satellite image. Look at waterfront for this list. And that’s how you could narrow it down.

Mike Hambright (09:16.608)
I see. Cool. Cool. That’s awesome, So what’s the next one? What’s number two?

David (09:21.031)
So the second one is real estate agents that sold more than one new construction home in the last year, but not too many, because they have the relationships with independent builders, which you can display your vacant land to for top dollar. So this one was from a land flipper, and they noticed that once you sell a vacant piece of land to a builder, by the second or third or fourth piece of land that you sell that builder, they’re going to want a discount. And that’s not what you want when you’re trying to maximize your profits as a wholesaler.

What they wanted to do was create a strategy for their team to build relationships with the realtors that tend to represent the many, many independent builders that are out there, right? So you can’t do this in Deal Machine, but with the data set that we have of all the transactions, I think this will be a feature that we add because we have the data, right? So anyone listening to this podcast, you could DM me at DLECKO on Instagram and I could pull this for you, no cost.

Mike Hambright (10:01.102)
Yeah.

David (10:18.789)
just because I want the awareness to be there that we’ve got some really helpful data. And yeah, so basically they wanted me to pull the real estate agents in their zip code that had sold more than one new construction in the last year. But like if there was a guy who sold 136, we filtered him out because he must be representing like a big builder, right? If he’s doing that many new construction homes. I thought that was really, really cool that I was able to help them get that that they’d never been able to get before.

Mike Hambright (10:47.118)
How do you know if it’s new construction? I mean, guess just based off of the year of the, yeah. Yeah.

David (10:51.121)
Year built, yeah, no, year built is the filter in there. That’s the cool thing about this exercise when I was asking people, like, if I could wave a magic wand and give you any data you want, what would it be? And then I’d just take what they said and try to figure out, well, the data I have, like, how would that translate, right? So it’s year built, current year, or last year is how you would do that. Yeah.

Mike Hambright (11:12.202)
cool. That’s awesome. And also for land, also for land folks, right? I mean, that’s primarily who is using that. Yeah. Yeah. All right. What’s the next one on your list?

David (11:17.573)
It was another one for land. These are not all for land folks, but yes, those two happen to be for sure.

So the next one was asked by my buddy Noah in Indianapolis. He’s like, you couldn’t by chance pull the list of property managers, could you? And I was like, well, I think I can, because we have people’s profession, and we also have every LLC. So I could filter all the LLC. The good thing about property management companies is most of them have the word property management in the company. I found like 320 LLCs with the.

Mike Hambright (11:49.389)
Right.

David (11:52.733)
word property management in them, and then it’s matched to that database we have of every person in the US, right? So I was able to give him at least the people who were the officers or owners of the LLC. Sometimes there’s one or more. And so that was really cool to go pull that list and give it to him because I think he was like, yeah, I was thinking about buying Zoom info for $16,000 for the year, but you really came through. I just gave it to him for free because I was like,

Mike Hambright (12:20.302)
Yeah, so that was 320 just in Indianapolis or Nathan like yeah yeah.

David (12:23.643)
Yeah, exactly. So many of them may be just management companies that didn’t go anywhere, know, et cetera. So some of those probably not going to be the best leads. But I was thinking like, why does he want those properties? And curious what you think. But I think that the reason why those relationships were valuable for him was because, I mean, they’re always trying to do flips, right? So if they’re going to sell a done-for-you rental property, I guess the property managers know who owns lots of properties.

Mike Hambright (12:29.912)
Sure. Right.

David (12:52.023)
And on the flip side, if you have somebody with a portfolio of like 30 properties and they’re elderly, they retire, you know, they may not want to list it, right? They may just want to ask their property manager or their real estate attorney, like, hey, do you know anyone who could just give me a good price for this portfolio so I could just, you know, retire, be easy, don’t have to go through the whole process of being public with all these listings and tire kickers. So.

I’m pretty sure that one of those two reasons why I want to build the relationships with the property managers. What do you think?

Mike Hambright (13:24.312)
Well, we’ve got a guy in our group that buys a lot of packages from through property manager, I mean, through their clients. And so that’s his primary sources, networking with property management companies to find somebody that has 15 or 20 that prop, know, whatever number, whatever the number is, but wants to sell. then sometimes if he keeps some, he’s like, I’ll allow you to continue to manage them, which is good for the property manager. have an incentive. And so there’s, you know, there’s ways to kind of source properties through there. mean, let’s be honest.

A lot of it depends on the property manager. There’s some that manage for investors. And the reality is, is if you think about this, about 35 % roughly of the houses in America are rentals.

Like one in three houses in America is a rental, right? And so, and a lot of them, like 90 % or something are people that own one. Like we talk about the institutional players and stuff like that, but they ultimately own maybe eight or 10%. So maybe it’s 80, 85 % of the properties in America are somebody that just owns one. It’s like they grew up in the house, they inherited it, or they moved up to a second house and kept it, or they’re in the military and got relocated and kept that other one as a rental. So it’s a lot of people that own one or maybe two, right?

for those guys. You talk about the definition of a tired landlord. I mean, if you have one or two properties, it’s either okay for now or a nightmare. Like it’s never like going great, you So it’s just a matter of time before they think about selling like every day or every week, you know. So

David (14:45.714)
I know. Yep.

David (14:52.187)
Yeah. So if you just have one or two, you’re typically not going to be following the best practices or you inherited on an accident.

Mike Hambright (14:56.462)
Yeah, or you’ve got, you know, I mean, in my portfolio, every once in a while we have a 20, 30, $40,000 make ready and it sucks, but I’ve got a whole portfolio of them that offset that. If you’ve got one and you have a $30,000 make ready, you’re like, you’re ready to burn it down, you know?

David (15:11.953)
Yep. Yeah, for sure. So those are good leads and that’s a good story about why property managers are useful relationships to have. So yeah, the fourth one was homes on double lots that can be flipped for break even. And then you could make maybe $80,000 profit by splitting off the second lot. So I had a customer in North Carolina who was like, hey, good deals are hard to come by these days. But I could actually buy a deal that’d be too expensive for me to make money on.

Mike Hambright (15:19.308)
Yeah, for sure. Yeah. What’s the next one you got?

Mike Hambright (15:31.522)
Yeah.

David (15:41.437)
if it has a double lot that I could split off. So can you filter properties that have double lots? And again, I was like, well, there’s not a filter for that, but what would I do in the data that would allow me to do that? And so this is what I learned. At first, I was looking at legal descriptions. And so a lot of counties will put lots, the word L-O-T-S in the legal description, and they’ll have like three hyphen four, or you know what I mean? So.

But not all counties use the same legal description format. So it doesn’t work in all counties. Then I discovered some actually will abbreviate it LTS. So there’s a filter in Deal Machine or whatever your tool is where you can just filter the text of the legal description. So that’s what I was doing. But then I noticed, well, some counties just don’t do that. But there is a lot number field that, as far as I could tell, every county in the whole United States, all 3,200 of them,

Mike Hambright (16:12.514)
Right.

David (16:37.425)
They have lot number field and if there’s multiple lots, it’s gonna have a comma or a hyphen. So we just changed our filter on Deal Machine because it used to be a lot number numerical filter. So you could say less than four, more than eight. I don’t think anyone ever used it. But I found this great new use for it. We switched it to a text filter. So now you can have it in Deal Machine, say lot number contains a hyphen or a comma and that’s gonna give you all your double lots. So that was a good breakthrough for me and a really smart strategy.

Mike Hambright (17:06.86)
Yeah, that’s cool. You know who else likes not necessarily a double lot, but big lots is builders. There’s a lot of people that doing new construction now. And I was talking to somebody here recently that was on the show that was a builder. And he was telling me, he’s like, hey, I bought a house. Like there was a wholesaler selling this house and like the numbers didn’t make sense for me or anybody else. But then I realized that it was this massive lot.

and he was able to basically tear the house down and build like eight town homes on the lot because it was large enough for that and most cities especially the larger cities are.

David (17:38.097)
Mm-hmm.

Mike Hambright (17:41.192)
are all on board for more dense construction because they’re trying to get more affordable housing in there. And so you might consider doing something that’s more for builders that’s like, it has a large lot relative to the size of the house. And that tells you that you can, in high price markets like the Bay Area, you can add on or add on to, or in builders, you could maybe dose it and build multiple houses there.

David (17:41.789)
higher density laws,

David (18:04.221)
Yes, so I started doing that. would say some of these double lots, they’re not big enough still. So let me do living square footage less than 2,500 feet. Because if it’s a mansion, you’re probably not going to make it a high density place. So I did less than 2,500 square feet and bigger than 0.35 acres to then kind of cut out the properties that, yeah, be big lot compared to the size of the house in that case.

Mike Hambright (18:30.358)
Right. Yeah. Yeah, that’s cool. Awesome. Well, what’s the next one on your list?

David (18:35.181)
The fifth one, and by the way, just made me think, I think in Seattle and surrounding areas, I think everything’s becoming higher density starting like July 2025, right? And so basically if you have like a $600,000 lot, it’s now worth like three times as much. You could pay three times as much for it, knowing you could build four stories up instead of just the single story house. A couple of people were telling me, Bentley Pug over there was saying that that was coming. So it’s pretty exciting. So five is…

Mike Hambright (18:55.713)
Yeah.

Mike Hambright (19:01.346)
Yeah, yeah.

David (19:04.903)
You know, if somebody wanted to input their 40 previous deals and reverse engineer the property and consumer data to generate a lead list of, 10,000 leads or so that they could market to, right? So I thought that was pretty cool. We just gave, went through it in AI. It’s like, hey, these are the past deals this person did. And can you look at every property in this county, look at the consumer info that we have, including their age, you know, their spending habits, their credit card utilization.

if they have pets or not, if they have kids or not, et cetera. And also the property characteristics. When was the house last purchased? What did the county assessor say the condition was? Take a look at the street view image. Look at that. See if that looks like any similarities with the houses that they actually did deals on. And so we did that for a customer and the cost of the AI compute was like 800 bucks. So we pass it through and I thought that was really creative, cool way to help somebody out. Never did that before.

Mike Hambright (20:01.454)
That’s pretty cool, yeah. Yeah, that’s cool. AI is, it’s amazing, it’s kind of hard to imagine where that’s gonna be even a year from now, let alone 10 years from now, you know? Yeah, yeah. Awesome, number five. So what’s number six?

David (20:10.375)
Right.

David (20:15.037)
Yes, and I think that resonated too because once you’re a big enough investor, you don’t really want to deal with filters and stuff. You know, people spend $11,000 a quarter for premium data and it’s like, well, what is that premium data doing if it’s not looking at having AI look at it and just say, well, these look really similar to the deals you did from the past owners, right? So I think that’s got to be as good, but for like a 10th of the cost. And so it was exciting to see that and excited to see what the results are.

Number six is an emergency list of rundown houses. So I had a customer, he’s like, man, Q1 is about to end. This was like, you know, the second week of March. He’s like, we didn’t get the amount of leads that we needed to have our Q1 goals hit. So we got two weeks. We need to really hammer something home. I know that driving for dollars is a great list. Can we have AI look for rundown houses? And so we did it, right? So there’s a compute cost to that. But what we did was

we narrowed down properties in his buy box in terms of square footage. And then what we did is had the AI look at the Google Street image, which is up to a year old, but just say, hey, do you notice any signs of distress? Do you notice any signs of peeling paint or overgrown bushes? And the AI did a really great job actually looking at those photos and narrowing it down so he could immediately start calling and marketing those properties to get Q1 done with the amount of leads that he needed done.

Mike Hambright (21:40.974)
So we’re not going to have time to talk about this today, but I’m fascinated by the idea of having AI look at Google Street View images in mass. Like, that is fascinating. As you know, I run a data company too. So I’m like, what? Yeah, interesting.

David (21:49.905)
Yes. So yes, it’s awesome. Yeah.

David (21:59.389)
There’s a compute cost to having it look at each image. So you want to narrow it down as much as you can first before you actually have it go through and look at the images. So that’s what we did with him.

Mike Hambright (22:03.032)
Yeah.

Mike Hambright (22:11.488)
Yeah, yeah. That’s fascinating, man. Okay, cool. And then last but not least, what’s number seven?

David (22:18.845)
top performing real estate agents ordered by listings last year, right? And then somebody was like, can I get their LinkedIn profiles as well? So we could reach out there. So the top performing agent is pretty easy to pull for us. Just look at all the transactions in the zip code and then group it by the agent that was in the transaction as the listing agent and reverse engineer that. So I know that a lot of people like Paul Myers and Augusta Georgia, know, agent outreach is their number one way.

And he’s always like, well, if I market to homeowners, I do a deal, but then I’ll never do a deal with that homeowner again. So he’s like, I want my efforts to give me multiple deals. So I like to build relationships with agents. And I love doing that because they can hear about a deal, refer it to me. I can close on it, fix it up, let them list it again. And also, they’ll think of me the next time that happens, right? So it’s like,

Several people wanted this list of agents and their personal phone numbers and emails so they could start building relationships with them and LinkedIn in this case. So you can’t pull LinkedIn profiles in Deal Machine, but what I did, and I’m happy to do this for any listeners if you reach out to me on Instagram, is I just wrote a custom script and just Google searched their name in the city and then the first link that came back is most likely their LinkedIn profile. Put that in the spreadsheet for them.

Mike Hambright (23:41.806)
That’s fascinating. So where do you think things are going from here with ability to use AI and all sorts of other tools, machine learning and stuff like that? where you’re into real estate data, I’m into real estate data. There’s a lot of people that are fascinated by this. Where are we going from here?

David (24:00.253)
Oh, it’s a great question, man. I know some people are calling outbound calling with AI. I don’t know that it’s like quite enough good enough to do that for my own business, but I think it will. Right. And then so when there’s any type of change, it’s really easy to dismiss it and say, ah, it’s not good enough. Right. I catch myself doing that too. So got to respect for people who are pushing the envelope with the AI technology. And I think you’ve really got to embrace it. Otherwise. I mean, that’s the, that’s the one thing.

that you always expect in life is change is always gonna happen. people laughed at the Blackberry because people liked feeling where the buttons are. Now there might be one or two people with a Blackberry in an audience of 500. So that’s kind of what I think of. You know, are there negative things like, oh, people might lose their jobs? Well, I mean, you could see driverless cars here at Austin and I’m sure Dallas where you’re at, right? You got the Waymo’s going around.

Mike Hambright (24:43.148)
Yeah, probably less than that, yeah.

David (24:58.569)
And I know Tesla just said this year Elon’s confident that the Model Y will drive itself straight from the factory to the user’s home. And they’re opening their ride sharing app as well. So you could put your Tesla on there and get a ride. So I mean, it’s already actually here. So you’ve got to think a lot of people doing those gig jobs are going to need to do something else. But it kind of frees you up to do something, you know.

more proactive. If you look at farmers, know, everybody like was doing farming jobs a hundred years ago and then we had, you know, the tractor invented and now what, 5 % of the population might be doing something related to farming. So it’s just elevated all of us to be able to then drive Ubers and you know, do real estate and just all kinds of other stuff. So I’m excited to see what comes of that and working on embracing it and using AI every day. Whenever I have a search,

query instead of going to Google asking chat GPT is one thing I’m doing to make sure it’s on the forefront of what I’m using.

Mike Hambright (26:00.716)
Yeah, cool buddy. Well, if folks want to learn more, you guys have some really cool things going on. If they want to more about you or Deal Machine, where can they go?

David (26:07.773)
If you want to learn more about Deal Machine, dealmachine.com. And again, if you want any of this like custom data stuff, me on Instagram. Not all of it’s available in Deal Machine, like the real estate agents, for example, but I could pretty easily put that together for you and would love to. for that stuff, no cost. Would love to just get that out and help you guys.

Mike Hambright (26:24.942)
Cool, well David, thanks so much for spending time with us today. Always good to see you. Yep, and everybody, if you’re not, like we said here, if you’re not embracing AI, if you’re not embracing technology, you’re gonna get left in the dust. you know, it doesn’t mean that it’s easy, it doesn’t mean that it’s where it needs to be yet, but the early adopters are the ones that are gonna come out ahead. So make sure you’re staying on top of it. So appreciate you guys a bunch. We’ll see you on the next show.

David (26:27.409)
Yeah, thank you, Mike.