Double Deals with Half the Mailers | Smarter Lead Targeting for Real Estate Investors

Share via:

Subscribe via:

In this episode of the Investor Fuel Podcast, host Skyler Byrd interviews Fred Castonguay, co-founder of Reworked.ai, a company that revolutionizes lead generation in the real estate sector. Fred shares his journey from flipping land to developing algorithms that analyze demographic data to improve lead scoring for real estate investors. The conversation delves into the importance of understanding potential sellers’ motivations and how Reworked.ai enhances efficiency in outreach. Fred also discusses the company’s expansion into insurance and roofing, utilizing advanced technology to provide targeted solutions for various industries.

Resources and Links from this show:

Listen to the Audio Version of this Episode

Investor Fuel Show Transcript:

Fred (00:00)
what we’re doing is we’re taking

The demographic information of the individual that owns, individual or individuals or entity that owns the property

talking about credit score, income range, marital status, children, properties owned,

the algorithms use that to understand the individual or the entity

the more they look alike, the higher the Betty score.

rather than sending 8,000 mailers, you could send 3,800. You’re going to get the same deals

You’re just gonna save 4,200 mailers, which could be anywhere from $3,000 to $5,000.

Skyler (02:07)
Hey everybody, welcome to the investor fuel podcast. I am your host Skyler Byrd and today I am joined by Fred Castonguay. ⁓ I’m very excited to talk with Fred today. He is in a sector of the business that I know very little about. ⁓ Fred, your company, or you and your company reworked.ai, you’re helping investors out there and everybody in the real estate space kind of ⁓ essentially have a better way to find their leads. Is that right?

Fred (02:35)
Everybody’s selling leads.

Skyler (02:37)
Awesome. All right. So as we kind of get into that, can you give me a little bit about your background? Because you came into this in a pretty interesting way.

Fred (02:45)
Yeah, so Skyler, thanks for having me on. ⁓

I’ve been flipping land for about seven years and five years ago my direct means of outreach was direct mail and a gentleman called in and I was giving him the pitch how we can buy the piece of property very fast, cash, easy and he said, look, I’m not selling the property but I keep getting these letters. What’s it all about? So I had some time. I shared with him what we do and how it works and he asked this very important

to me. He said,

But why’d you mail it to me? I said, well, you’re in the state and the county and the size property that I kind of like. He said, but yeah, but why me? And I said, well, you’re just in that bucket, right? I send 12 to 15,000 a month and you’re in the bucket. He said, but if you looked at my profile and who I am, you’d realize I’m not selling this property for a long time. So I don’t have access to that information. He said, but there’s gotta be some way.

to determine who you want to mail to before you mail it based on who they are, not just the property. And I said, well, if there was, I would use it. And he said, he’s a data engineer and computer scientist.

And so over the next six months, he was in Maryland, I’m in Miami, we were just chatting about the business and how it looks. We realized that there’s a marketplace, there’s a way to get some of the data. We developed the algorithms and I say we, he did, right? Because I’m not a computer engineer. It took us about a year, a little over a year to get the algorithms in place. in the beginning, we focused on land flippers, right? Because I had the data for that. We knew the marketplace.

But we soon escalated that into single-family, multi-family commercial properties. And

what we’re doing is we’re taking

The demographic information of the individual that owns, individual or individuals or entity that owns the property. Again, doesn’t matter if it’s a piece of land or a multi-unit apartment. Who owns that property? Understanding what is their life about, right? It creates a scatter plot of all the demographic points, right? We’re talking about credit score, income range, marital status,

children, properties owned, membership, subscription, buying propensity indicators.

And the algorithms use that to understand the individual or the entity. And it compares that individual and entity to known deals that have transpired over the last two years. The more similar they are, the more they look alike. We’ve all heard that term before, look-alike audiences. The more they look alike, the higher the Betty score, which is our propensity score. So rather than sending 8,000 mailers, you could send 3,800. You’re going to get the same deals ~ were in the 8,000.

you’re You’re just gonna save 4,200 mailers, which could be anywhere from $3,000 to $5,000.

know, Skyler, one of the jokes I like to say is the old adage of who gets rich at a gold mine. The person selling the shovel, right? And people like me in rework.ai, there’s a lot of companies out there selling shovels.

Skyler (06:38)
Yeah.

Fred (06:46)
But what we always say is, we’re not trying to get rich on selling the shovel. We’re trying to put between 7 and 12 times, not percent, savings back in the pocket of the real estate investors, insurance, home services company that use us for their direct mail outreach. It’s just efficiency.

Skyler (07:07)
Absolutely. So basically you came into this you were you were flipping land and you were doing basically trying to find people the same way everybody else was right so I take it your partner was just he was a land owner listed ⁓ in a certain zip code right and that was

Fred (07:21)
Yeah, he was just outside

Austin, Texas. He had bought a piece of property six, eight months before he got it for his future. I think at the time his age was probably 34 with two young children married five or six years. ⁓

you know, a professional had done well and he was currently working for an AI company. So if I could have access to all of his demographic information, I would have seen he’s not a likely seller and he’s certainly not a likely seller of off market below retail, right? know, offer him full retail or premium, maybe he sells because he’s not stupid. ⁓

Skyler (07:53)
Yeah.

Fred (07:57)
But I didn’t have access to that demographic information. And that was one of the key things, as we were talking earlier, is getting access to that demographic information. We don’t scrape the internet. This is not lousy information that ranges. We’re looking at income credit score. We look at the credit score has moved in the last three months. Could that indicate good or bad? Death divorce, one of the Ds, or won a lottery, or something else happened, right? It’s looking at all of these aspects to determine

Skyler (08:19)
Yeah. Yeah.

Fred (08:27)
what’s going on, what could be going on in the mind of that owner at that time.

Skyler (08:32)
Okay, yeah, that is absolutely a much better way to get your data and the more that you can get in front of, you know, the more you can get in front of any type of clientele that would be more motivated. I mean, that’s, that makes life easier for everybody. So that’s that.

Fred (08:50)
You know, it’s,

sorry to interrupt, but it’s the motivation and the knowledge that this person is more likely. And we have clients that will give us a list, right? ⁓ And in real estate, we’ll take a list and score it. And when they get the same list back,

Skyler (09:05)
Mm-hmm.

Fred (09:05)
Right.

But on the right hand side, it’s got the propensity score called the Betty score. It’s got an updated mailing address. If the USPS has an update, if they’ve moved. Well, what they do is, is they look at these scores and a lot of them on the top five to 10 % will do a little bit more work on them. Right. Those are the highest opportunities. So maybe rather than just sending a neutral letter or just a regular mailer, they’ll put a little bit of time and maybe a little bit of more money into saying, I’m going to get them a better

product in their mailbox. And then the next group down so they can plan their actions based on the propensity ⁓ and be smarter and more tactical versus just a spray and pray approach.

Skyler (09:50)
Absolutely. And as you kind of brought up earlier when we were talking, right, like said, well, the barriers to entry to do this aren’t really there, you know, for for anybody else,

it certainly seems like there is, right? For one, you kind of got to get lucky and with a mailer, find your data scientist that knows what they’re doing. And then you got to go out and actually find who you can get the real information from. And like you said, you’re not just scouring the internet for that. So

It seems like there is quite a bit of barrier to entry to this, so I think you kind of undersold it a little bit there. ⁓

Fred (10:56)
Yeah,

and you’re right. mean, how Shaman I met is absolutely our meat-cute, right? To borrow a Hollywood phrase. And the fact that we become really good friends, right? We work well together. We have commonality in our mission, right? We’re not looking to…

We are looking to be profitable, we’re looking to do well, but we’re also looking to make sure that each and every customer, subjectively and objectively, feels good about the money they’re spending. If a customer’s gonna spend $149 a month to score $3,500 in the real estate sector, we want them to be able to get…

$800, $900, $1,100 savings and to get their deals and to think before they would even consider doing a mailer that they would have to do reworked. And what’s happened because we’ve had this approach

We’ve had this approach of putting the customer first. We do very little outreach and marketing for our real estate world now because our biggest advocates are our customers. So I’m going to reach out and I heard someone talking about you on a mastermind. I can sit here until I’m blue in the face, say how great this is, and it’s the second coming. But when someone else says, you’ve got to check that out, I’ve been using it for three months, and I love it, you just can’t beat that. And so by putting the customer first and,

Skyler (12:15)
Yeah.

Fred (12:18)
We’ve had customers that get into trouble, they’re like, look, I’m a little short this month, I’ve, know, something going on. You know, we’re always there to help people out and listen. And it doesn’t matter if we have almost a thousand customers now, when people reach out, a lot of times they’ll talk to me. You know, we have a team that does our customer service success, but a lot of times they’ll get me because I like to talk to customers as well and see what’s going on. And we learn things, right? says, customer says, well, could you do this? And then we build that into the product map.

Skyler (12:46)
Okay, so now that you you kind of bring up who your customers are, can you tell me who’s your ideal customer on the real estate side? Who do you think gets the most out of your services right now?

Fred (12:58)
The one that’s getting the most out of our service is investors, right? And it doesn’t matter if they’re in land, single family, they’re flipping or wholesaling. The ones that have a reasonable…

robust system behind them, right? Talking about having a CRM that they’re using. They’ve got the ability to get large volumes of data. They’re sending the information to us via API. We’re doing the calculation. We’re sending it back via API. So all these systems are automated. They’re sending their information to their mailing house via API. It’s wet lather, rinse, repeat, because at the end of the day, it’s still volume, right? We’re not saying you don’t have to mail 4,000 anymore. You can only mail four.

and that’s where it’s to get you four deals. This is not a silver bullet. It’s just bringing efficiency to your outreach.

Skyler (13:47)
Yeah, yeah, just a lot. It sounds like just a lot more highly targeted individuals. Right? Yeah, absolutely. So how does that work exactly? So if you have an investor, all right, and they want to use your services, do they have to, they come to you with a list or ⁓ of zip codes and who they want to mail to, and then you in fact take that list and put the score on there so they can better target?

Fred (14:10)
Yeah, so

in our real estate sector, we’re only doing lead scoring, right? So someone will either upload a list on our platform, right? And no human eyes see the list. I’m not sitting there saying, where is Skyler looking to invest? So they’re uploading a list with name, mailing address, if the address of the property is different, all of the regular things that people get from DataTree or wherever they’re getting it. A lot of people get it from the county.

then that list is gone. the first thing that we do when I say we, the software does, is they’re doing a triangulation check on the name and the mailing address. They’re looking at the name. Does that person currently reside at this address? And is that address a USPS deliverable address? Have they moved? Have you ever gone to order something online and it says, OK, put your address

and you type in 123 Main Street, Anytown, USA. And then a little pop-up comes up and says, did you mean this? And you look at it.

You’re

like, but that’s what I typed, but you always take the suggestion because we’re not idiots, right? So sometimes the USPS will look at it and say this is what we have and whatever difference is there if you don’t accept that there could be a problem and we see a lot of people doing mailers they’re getting returned mailers So not only not only have you paid for the data you paid for the mailer and then it comes back to you as with that little yellow sticker on it saying Undeliverable just a complete waste of money. So that triangulation we need

check to make sure

we have the right person and we have their mailing address. If the mailing address is different, then we on the list that comes back, we’ll update the mailing address so everyone can see that there’s a difference in the mailing address. And it’s 8,000 in, 8,000 back. It’s in a different order. It’s reworked based on the propensity score that will be on the far right hand side.

Skyler (16:39)
There you go. That makes sense, given the name of the company. That’s awesome. Alright. So I would imagine you would probably find, especially if you’re using somebody that’s a land flipper like you would do, you want to make sure that, okay, the address that you have isn’t just a vacant piece of land that you’re trying to mail something to, correct? Like that must be a big part. Okay. Absolutely.

Fred (16:57)
Yes.

Yeah,

the land flipping world, a lot of the parcels do not have addresses, right? They’re not defined by, but the John Doe will have a mailing address as a place of record as an owner of that property. I mean, those are the two pieces of information, the name and the mailing address. We cannot proceed without those because

Skyler (17:07)
Okay.

Got it. Okay.

Fred (17:22)
We can’t check to make sure we’re getting the right information because how many John Doe’s are there in the United States? But how many John Doe’s are there at 123 Main Street? So when we go to our data providers via API and we’re looking for all of that demographic information to populate and run the machine learning on, we have to make sure we have the right person.

Skyler (17:41)
Yep. Okay. And I really like that because like you said, there can be a lot of returned mailers and that’s just another big waste of money. Right? Yeah. That’s absolutely. I’ve done it myself. I’ve purchased lead lists and all of that. And yeah, you largely feel like you’re, you know, you’re not getting what you put in. So this is, this is excellent. Yeah.

Fred (17:49)
waste. It’s frustrating.

So you know it’s interesting that you mention that Skyler.

you upload 8000 into us, right, it’s important there’s two things I really want to mention here because you said you bought lead list. Your 8000 gets scored. We’re paying for the demographic information to be associated with your file. We run our machine learning algorithms on it and then we have to dump.

Skyler (18:13)
Mm-hmm.

Fred (18:26)
the demographic information. And our data providers have the right to audit us. And they do. They audit our computer code to make sure that information gets dumped so we can’t use it again. And then once we give that file back to you, we’re not taking that 8,000 and saying, hey, let’s sell it to Joe, right? Because we see that a of a lead.

Skyler (18:44)
Hm, yep.

Fred (18:49)
in this world, in any world, is almost a four-letter word, right? Because lead sellers are multiple, they’re selling the same list of multiple people, right? So by the time you’re reaching out to them, three people have already been there trying to sell the same thing, and the person you’re talking to or connecting with is good and upset, right? ⁓

Skyler (18:55)
Yeah, absolutely.

Yeah.

Fred (19:08)
We’re not reselling any of this, right? That list, wherever you’re going, your honey hole, what you’re doing, as I said earlier, there’s no humans, right? If a file fails, we may need to have an engineer to go in there and understand why the file failed, where was the data intact, know, what was wrong, but then they fix it and push it through. I don’t look at it, I’m not seeing where people are going and trying to buy real estate or what they’re doing.

Skyler (19:32)
Yeah, yeah, not trying to get any inside information there, I can understand. Yeah.

Fred (19:36)
Well, and people have asked that. like,

can you, do you have enough information now to say where the hotspots are? What’s going on? Where are people investing? And we would if we were saving the information, but again, that’s not our information. That’s.

Skyler (19:51)
Mm-hmm.

Fred (19:52)
our customers’ information, where they’re investing. So a lot of our customers, our big institutional investors, they’re giving us feedback. Every month, they’re obligated to share with us where they had inquiries and where they had deals. Because we have to use that to constantly train Betty, our software, machine learning. It’s got to be on a feedback loop. And they have to mail the bottom half of the list occasionally. But if we were to start using that in selling ⁓ hot markets, all that would shut down because that’s their information.

hours to sell.

Skyler (20:24)
Yeah, absolutely. You’ve got a lot of integrity there because like you said, it’s absolutely something you can do. It’s something you run into, again, just when you purchase lead lists for basically any industry, the first thing you always ask somebody is how many times are you selling these? And oftentimes you don’t get a good answer. And that tells you everything you need to know. ⁓ Absolutely.

Fred (20:40)
Now, you know how many times you

can sell your integrity, Skyler?

Skyler (20:45)
I would imagine only once and then you’re down. Absolutely. All right. And tell me, I mean, because obviously you, you know, we’re a real estate podcast. want to focus on that, but you’ve got some interesting expansions that you’re doing right now with your business. Can you tell me a little bit more about that?

Fred (20:47)
once. Just once. So you better get a good number for it because there’s no second sale.

Yeah, so we two years ago, we decided we want to continue to grow and we’ve looked at either going into reselling data or creating a CRM. We determined that there’s not a lot of margin in reselling data and there’s a lot of very good CRMs out there. So we decided to stay with our machine learning core competency. We branched into insurance kind of in a luck.

⁓ But now

got a couple of insurance companies, mortgage insurance, car insurance. ⁓ And we got into solar and roofing. And we developed a computer vision program that can look at an image to determine the geometry, the presence of solar shading, presence of roof damage. And the really exciting thing is the imagery that we were getting, that we were buying, was haphazard. One was really good and one was not good. It wasn’t high resolution and it was out of date.

linked

up with the largest and we consider to be the best aerial imagery company in the country. And we’re in the final stages of negotiating our master license agreement with them to be able to use our propensity in their imagery to determine roof damage. And we’ve done about five pilots with some fairly large customers now. And the results have been astonishing because now a roofer or a supplier of roofing materials, instead of sending a mailer that says, I’m a roofer,

they can send a mail that says, hey Skyler, our records indicate that your roof is failing and we’d like to help you out on that before it becomes a major problem for you and your family. And then you get this and you’re like, really?

Not everybody’s looking at their roof, right? So then they maybe go look or get up on a ladder and be like, my gosh, yeah, I do have problem. So they’re going to call it, hey, yeah, come out here. They take a look at it, it’s about to fail, right? Because we could predict what’s going on inside the home with our algorithms. And this company is able to look at the roof and say, it’s either failing or about to fail. We can see it. Because they’re flying, they’ve got, I don’t know, 50 or 60 planes. fly the entire country every single day at 6,000 feet.

And there’s no limit to that because they’ve got 3D images of the house. So we can do roofing, siding, windows, lawn care, pools, right? Because we have that information. Predict what’s going on inside the house with the owners. Predict and understand what’s happening real time on the outside. So we’re really excited at what that’s going to do to our company.

Skyler (23:34)
That is so cool. So yeah, you’re not getting your images just from Google Earth from back in 2017 or anything like that. Yeah, you’re absolutely doing the right way. yeah. And anybody that uses that knows like, okay, that image could be back from like 2016 that you’re looking at. It can be from 2023, different clarity, absolutely.

Fred (23:41)
We were, right? We were.

Yeah,

it’s not, I mean, it’s free, right? So what do you expect? You know, it’s tough to complain when you’re getting a free image, like why is it six years out of date and fuzzy, right? Well, when you pay for it, as we’re going to be doing, we’re able to really zero in and you know, satellite imagery versus 6,000 feet high digital, right? You’re able to pick up, a satellite can’t pick up hail damage, right? But these guys can.

Skyler (24:18)
Yeah,

that is that’s really cool. That’s awesome. And yeah, Fred, we’re kind of coming up on time here. Okay, so before we go, if we have anybody listening to the podcast right now, ⁓ real estate professional investor, roofer, ⁓ anybody in solar, how can they get in touch with you if they’re interested in your services?

Fred (24:38)
So we’re on the web obviously at reworked .ai. We’re on Instagram, LinkedIn, and Twitter, X, whatever we want to call it. ⁓ My email is Fred, easy to spell, F-R-E-D, at reworked, R-E-W-O-R-K-E-D-A-I.

for Reddit Reworked AI and you can drop me a line, you can go to our website, you can book a call. ⁓ We love to talk to potential customers, we love to learn from them, we love to get new ideas, right? We like to make ourselves available. So ⁓ we still do a high touch to bring people on board. All our pricing is on the website, it’s very transparent. ⁓

As I said earlier, we lead with the customer, we allow customers to pause, there’s no minimum commitment, we have pay as you go, we have monthly subscription, but if you want to pause and take the summer to go travel Europe, you can pause, right?

Skyler (25:31)
That’s awesome. Perfect. Well Fred, hey, I

appreciate your time today. ⁓ That was a ton of good information and like always everybody, if you are out there listening and you’ve got some good value from this, please hit subscribe. We have got more conversations with professionals just like Fred coming down the pipe all the time and we will see you on the next episode here.

Tags:

Investor Fuel

Double Deals with Half the Mailers | Smarter Lead Targeting for Real Estate Investors

Show Summary

Resources and Links from this show:

Listen to the Audio Version of this Episode

Investor Fuel Show Transcript:

Tags:

Ready to take your business to the next level? Take the next steps below