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Episode 48 | Inflation Woes, Economic Realities, and Data Insights with Glenn Hall of SFR Analytics

Episode Summary: 

In this episode, Craig Fuhr and Jack BeVier discuss the recent news about the US consumer price inflation and its impact on the Federal Reserve and asset markets. They question the Fed’s ability to reach its 2% inflation target and speculate on the Fed’s motivations in keeping interest rates low. They also discuss the current state of the economy and the disconnect between the perception of a robust economy and the reality experienced by the average American. The conversation then shifts to Glenn Hall, founder and CEO of SFR Analytics, who shares insights into the company’s products and their approach to data analysis. In this conversation, Glenn from SFR Analytics discusses the importance of industry experience in data analysis and the value of their research-oriented content. They also talk about marketing strategies and the challenges of obtaining certain types of data. Glenn shares insights on direct mail campaigns, radio advertising, and the need for a comprehensive distress data set. The conversation concludes with Glenn providing his contact information for those interested in SFR Analytics.

*The following transcript is auto-generated.

Craig Fuhr (00:12)

Hey, well, good morning, everyone. And welcome back to real estate investor radio. I’m Craig Fuhr joined by Jack BeVier. Jack, how are you today?

Jack BeVier (00:20)

Doing great, man. Good morning, good morning.

Craig Fuhr (00:22)

It’s good to see you. Hey, listen, before we jump in with today’s guests, I wanted to go through a story that you sent me from Bloomberg just a couple of days ago. This was actually published on April 10th. Don’t know when this episode will be dropping, but we’ll just go through this quickly. And it was a Bloomberg article written by Edward Harrison. So Edward, if you’re a listener, just by chance, Jack, thank you for the article.

The article was entitled Bad News for the Fed and Asset Markets, Jack. And the sub headline was CPI was Bad News for the Fed and Asset Markets. I have to be honest, Jack. I’ve been getting calls recently from borrowers, both for DSCR and guys that are out there doing fix and flip stuff. And everybody’s talking about Fed moves, Jack. Everybody’s still wondering whether or not we’re going to see those two to three rate cuts that were promised in the second part of the year.

So this news story was timely and I’ll just read briefly from it says the latest US consumer price inflation reading blows the logic for expecting rate cuts anytime soon right out of the water. Why? Because core CPI has installed just below 4% double the Fed’s target making the Fed’s 2% objective pretty hard to reach in the near future.

goes on to say that Fed officials, you know, have been talking about a 2.5% increase in the price of personal consumption expenditures, giving the institutional market comfort. However, every other inflation metric is north of that figure with core PCE inflation to 2.8 headline CPI at 3.5 and core CPI at a whopping 3.8. Jack, you and I have always agreed that

the Fed isn’t necessarily an independent operator when it comes to politics and keeping the incumbent in the White House, no matter who that incumbent may be, it’s not a political theory that should, or I’m sorry, that’s not a partisan theory, that’s more of just a political theory. And so, you know, I feel like there’s, what Ed is telling us from Bloomberg is that there’s a bumpy road ahead and that there’s no real impetus on the side of the Fed at…

at you know, given what we’re seeing in the economy right now, which most are considering robust for a rate cut. And so that falls in line, I think of what you’ve been saying over the past few months. And I thought you might like to comment.

Jack BeVier (02:52)

Yeah. So the, uh, the, the CPI print came out two days ago, uh, higher than expected and higher than the previous, um, print. And so as a result, you know, I guess both the real estate market and the mortgage market bond markets generally are traded wider on that news because there’s concern that the fed doesn’t actually have inflation under control, that they

And I think that this is congruent with what we’ve been saying since Powell’s dovish comments, where he went from being super hawk, super hawk for the past several years to all of a sudden in a flip of a switch saying that we’re going to have in January saying that we’re going to have three rate cuts inside of a 12 month period in that year. And that was such a reversal, such a fast reversal that, you know, I put my little, you know, tin foil hat on. And I was like, that can’t have been.

driven that can have been driven based off of purely an evaluation of the numbers because frankly, things are moving in the right direction. But you know, to do anything but just wait and see, you know, seem to be really not prudent. And lo and behold, here we are. I mean, so he made those Dove’s comments back in January, the market got super giddy because they were like, hey, rate tightening cycle is over like asset prices trade in mortgage, mortgage rates came down thing, you know, the stock market shot up.

And, you know, it’s what the market’s what the world wanted to hear, right? That the rate tightening is like. Yeah, exactly. And at the time I’m just, we’re scratching our heads because like the numbers just started to come down in a meaningful way. You haven’t even hit your target level once and all of a sudden you’re talking about the rate cuts, like the market.

Craig Fuhr (04:23)

There was a palpable exuberance.

Jack BeVier (04:40)

takes off, right? And everyone’s optimistic again, and spending again, like that’s not what you want to do from a policy from a psychology point of view, like is he, you know, did he ignore the fact that he’s talking to humans, and that humans behave, you know, like, like humans, like, not, not like robots, like, they’re gonna hear that optimism and start spending again, that labor labor, if you’re the whole thesis is that you’re going to get labor rate wage growth under control.

spitting a bunch of optimism into the market is not productive towards that end. And so, the tinfoil hat of, hey, if we’re in a recession though, come third quarter, whoever the incumbent is, is going to be out. That’s where that kind of theory started to come from. So anyway, lo and behold, here we are. He was optimistic in his comments. The economy has started to take off a little bit again.

So, you know, the soft landing has now become, you know, the planes hovering 100 feet across, you know, over the ground. And he’s now the question is, can he touch it down? Like, right? Can he touch? Can he touch this plane down before the end of the runway? Or is this thing just going to have to take, you know, take off and we’re going to have to do another loop around the airport and maybe even talk about increasing rates again to get the economy back under control? None of that is good for.

Business owners who are just looking for a predictable, stable environment. It means that there’s going to be more volatility in capital markets. No one wants to hear that, right? Like that’s frustrating. It’s just, it’s frustrating when we’re trying to just get back to normal and run a business that we’re going to, that I think it’s very unlikely that we don’t see continued volatility in capital markets. So I think

Craig Fuhr (06:24)

I’ll just throw in one more thing here, Jack. It says, you know, the story goes on to say on the business side, and I think this, you know, I’m trying to, I don’t think that the average American feels the robust economy, frankly. I think they walk into the store with one bag of groceries and it’s 87 bucks. I think they fill up their car and it costs 90 bucks. I think that, you know, the cost of education, the cost of housing, the rampant crime, the poverty, you know.

Everything that we see in most major post-industrial cities doesn’t say booming economy to me, Jack. And on that note, he says on the business side, figures released on Tuesday showed small business optimism at its lowest in 11 years. And on top of that household side, figures released on Friday showed black unemployment had surged the highest level since 2022 with employment losses felt the most by black women. And so I just, you know,

You know from we speak to real estate investors every day Jack And I think there’s still a lot of optimism and hope with the folks that we speak with It’s certainly not a pencils down for most of them But I just don’t know if the average American is feeling the robust economy that we’re being told that we’re they were in right now When frankly, I feel like most of it was financed by you know, a seven trillion dollar budget and two trillion dollar deficits

Jack BeVier (07:46)

Yeah, absolutely. And the I think there’s this remain the thesis remains that the labor market is continuing to cool and that that’s going to like soft land us into this 2%. And I don’t know, I just I think it was irresponsible of Powell to be dovish when he was and even at the last meeting to still be talking about free rate cuts, even as the data wasn’t on this glide path down that he that he thought and

I don’t know, it’s a real head scratcher for me because he seemed like he was being like uber responsible in terms of getting this under control quickly. And then he just seems to have thrown all of that to the wayside in the in the election year. And so, you know, I think I think it’s unfortunate because I agree, it doesn’t feel like on the ground that we either have a super strong economy that can handle further rate increases. Nor do we, you know, nor are we seeing relief in, you know, on the consumer side of things. So

Craig Fuhr (08:44)

Yeah, well, Jack, one last thing on this and then we’ll bring in our guests today. Give your take on even if we saw a quarter decrease in the Fed rate, maybe one, maybe two by the end of the year, just to get sort of consumer exuberance and optimism going for coming into the election in November. What do you honestly think that would mean for the average investor

refi, you know, a bunch of rentals or, you know, what is that really going to mean for investor rates, Jack? Do you think we’ll see a commensurate decrease in rates or quickly or do you what do you what give us your outlook on rest of the year in terms of how it how the Fed will affect the average investor who listens to our show?

Jack BeVier (09:39)

I think that the mortgage market is, I mean, interest rates are generally correlated, but it doesn’t mean that the mortgage market follows the Fed. I think the mortgage market follows its own viewpoint on what it thinks rates are going to be and frankly is using a much longer time horizon than the Fed’s adjusting the overnight rate and mortgages are priced off of the five year or the 10 year. And so the mortgage market’s got a longer term view. And so frankly, the movements in mortgage market I think reflect not…

what the Fed’s rate is setting at, but whether the market believes that the Fed can manage economic policy, fiscal policy rather, in a way that can produce a 2% inflation rate. So when you saw the CPI increase and mortgage rates the five year and mortgage rates jump up 25 basis points yesterday, in my mind, that’s more of a vote of lack of confidence that the Fed has

shit under control than it is thinking about what the you know, what the near term movements are going to be. So I think they’re taking a longer view of the economy as a whole and mortgages are being priced off of that. That said, when you see this kind of snafu, where the palace says that we’re going to have three rate cuts in one year in the same year, and then a month later, the CPI is increasing.

The mortgage market responds to that negatively and spreads widen out. And that means the cost of borrowing goes up for not only homeowners, but investors who are trying to add rental properties to their portfolio. So, yeah, that’s it’s unfortunate, but I think that’s the

Craig Fuhr (11:20)

Let’s bring in our guest for today, Glenn Hall, with SFR Analytics, founder and CEO of the company. Glenn, it’s such a pleasure to have you, and thank you for taking the time.

Glenn (11:29)

Yeah, no, thank you for having me. Happy to say that this is my very first podcast, so we’ll see how it goes.

Craig Fuhr (11:36)

Well, we’ll be sure to take it easy on you. I was sitting here the entire time that Jack and I were talking. I’m like, why does this guy look so familiar? And I remember you were at IMN in Scottsdale, correct?

Jack BeVier (11:36)

Nice.

Glenn (11:47)

Yes, I was.

Craig Fuhr (11:49)

I don’t know if we met at that time, but I remember your face. I try not to forget him. So a pleasure to meet you again. If we are, it’s good to have you here. So Jack, let’s go, let’s just jump in and, and talk about this great platform that these guys have built.

Jack BeVier (12:04)

Yeah. So I was super excited to get Glenn on, uh, because I’m, I’m a huge data, data nerd as it comes to housing analytics, though I can’t code a line. Um, and so I just live vicariously through all the much smarter people than me who can, and who actually build really cool, interesting products. Um, and so I get really excited when I meet somebody who is thinking about the market and thinking about the, you know, the technological resources the same way I am and how they can be applied to the housing space. And so.

It was a real thrill for me to meet Glenn and his partner, Phil, because they’re very, very forward thinking in terms of how the data can be used. They’ve got tremendous experience on a national scale that I want to dig in. We’ll talk about that. But anyway, Glenn, I was just a real treat for to meet you and Phil. And I’ve been a big fan of the company and so excited to have you on to share with our listeners what you guys are working on.

Glenn (13:00)

Definitely appreciate the kind work. Go egg, right?

Craig Fuhr (13:00)

Hey, climb before.

Before we jump in, I know you had some past work experience with Sunday and Kiavi, maybe you could expound on that and then we’ll jump into the whys for, you know, building, building SFR analytics.

Glenn (13:17)

Definitely. So yeah, Kyapi was my first job at college and I kind of just stumbled there where during college I actually worked at this very small, or at the time very small startup that was doing microfinance loans in developing countries. So we’d scrape the data off of people’s smartphones because like in Kenya and Tanzania, it’s like 90% of the population has these really cheap Android smartphones. And at the time…

you could get all of the data off of it, people’s text messages, they had this Venmo-like payment system that was all via SMS. So you had this really rich data on basically what’s effectively credit card transactions that you can parse through text. So anyway, I worked there for about two years during college and then from there, they introduced me to the risk.

somebody on the risk team at Kyavi and yeah, just ended up there. I was at Kyavi for about a year on the risk team focused on analytics. So it was funny, like throughout the entire interview process, didn’t know what a hard money loan was, just like didn’t really get it, but it was like, yeah, the people I talked to all, you know, were all really smart and seemed like a fun crowd. So ended up joining.

It was a pretty interesting time at Kiavi where Kiavi was actually also launching a consumer mortgage when I was there. So, a lot of people didn’t know that, but like the original thesis of Kiavi was both, yeah, they’ll use the hard money space to build out a mortgage platform and do it across everything.

So a little bit of work on the consumer side there, mostly focused on the hard money side a lot on stuff like likelihood of loans going to default. My second or third week I joined, there was a massive hurricane in Florida, so I was responsible for trying to figure out potential losses and stuff like that. But anyway, fast forward a couple of years.

joined Sunday pretty much the first month it was operational. The two co-founders of Sunday were both from Kiabi. One was, I forget the exact title, but it was effectively the COO, Josh, who’s CEO, and then their former CFO, Andrew. And yeah, it was funny, it was like 14 of the first 15 employees were all ex-London home people. So.

everybody kind of knew what they were getting into for better or for worse. And yeah, I ended up leading a combination of growth and at the very beginning analytics, and then thankfully we brought on Phil, my partner, to Sunday to actually lead and build out like a full-fledged data science and analytics team. And yeah, it was there for just under three years from one market to about

Jack BeVier (16:18)

So just for those who aren’t familiar with the platform, what it does, so what, just describe some of these.

Glenn (16:22)

25 market or go. Um, but yeah, from one market to about 25 markets by time we left spending tens of millions of dollars a year on advertising and doing a tough work at the intersection of, uh, yeah, housing data analytics marketing. And then, yeah, left about two years ago, started doing some consulting work for a bunch of people and the real estate space, and then found ourselves

Craig Fuhr (16:24)

Yeah.

Glenn (16:51)

building out the same things over and over, start turning those into software products, and here we are.

Jack BeVier (16:57)

Yeah, that’s awesome. So I’ve always been really impressed because you guys have been access, you know, using the national assessor and recorder data, as well as a number, a bunch of other like, you know, nationally accessible data sets and trying to find insights into the data in order to, you know, as both market intelligence tools and as ways of generating new, um, kind of like new activity, right. Generating new business, not just for academic.

reasons, right? Like it’s kind of interesting, all like who are the biggest buyers in the country? Great. Here’s a list of the biggest buyers in the country. But like how does you know, that’s it’s a very, it’s an academic exercise until I can figure out who to transact with, right? And like, so like, if you could just like, give, give us like a quick breakdown on the different products that you guys have come out with and the why really behind each one of those and what you think that, you know, why you chose those, because it’s a big space, you could have attacked a lot of different ways. I’d love to understand you more you’re thinking about that.

Glenn (17:32)

Yes.

Definitely. So I’d say there’s four main products that we have right now. The first one is in the private lending industry, half market research, half sales prospecting. For a given metro area, for a given lender, you can see who has the most market share, who their borrowers are. For a given borrower, which lenders are using over time.

if wonder if specific bars are turning and a bunch of different derivatives of that. That very much came from a prior experience where I have to thank the CEO, Sunday Josh for it, where he was obsessed with that. He called it wallet share at Kyavi and Sunday too because Sunday also operates a hard money wonder but it’s for a given borrower of yours, what percentage of their business are they doing through you?

So we kind of stumbled into this when we first started out doing consulting where, uh, you know, I’ve from working at Kiavi, no people have fair amount of lenders who’ve, you know, since left Kiavi and yeah, one of them basically asked if we could build this for them, right? Absolutely. And then, uh, yeah, it just kind of snowballed from there where all of a sudden had other people reaching out and then started doing some, uh, some cold prospecting on that as well. Uh,

So that’s the first one. The second one, which we’re really excited about, but still, I’ll put an asterisk, kind of in beta, is a self-service tool that you can go to on their website and check out that’s focused a lot on buyer activity. So mostly geared towards wholesalers and flippers to see market activity, but you can search an address.

see, set a bunch of parameters like property type, year bill, and see who the largest buyers are and their contact info. So we have a few of the largest wholesalers in the country who are on their daily finding new buyers. It works really well for, we’ll call it like your non-typical properties you’re wholesaling because most wholesalers have a preferred list who they go through.

often, especially for the larger wholesalers, they’ll get a deal in a neighborhood where they’ve never wholesaled a home to. So being able to quickly see who’s bought a home there in the last two years, who’s a decent size flipper, the main value prop there, we’re looking to build that out pretty significantly where we have a bunch of data internally in our database from various…

work we’ve done, everything from location analytics, rental data to lead scoring for prospecting homeowners. So our goal for that product is basically be the only data product a wholesaler or flipper needs to run their business. Still a decent way away from doing that, but that’s the long-term goal there.

The third product is our rental data. We sell that to a large variety of people. So we sell that to some equity research firms and some banks and some hedge funds for tracking publicly traded companies’ rent growth in real time. So for the publicly traded SFR funds, we can give… Yeah.

every day updates on what rent growth looks like and different derivatives like that. And then the final bucket is, we’ll call it kind of like this nebulous consulting bucket where we have data, nationwide assessor data, deed and mortgage data, building permit data, rental listing data, and consumer demographic data. So for about 260 million US adults.

We have age, estimated income, a bunch of affinity groups, like everything from are they a known gambler? Are they currently seeking a job? Yeah, stuff like that. And we end up, like just this week, we were working with a litigation consulting firm providing them like this very specific subset of building permit plus transaction data. So I’ll stop there, happy to go deeper in any of those.

Jack BeVier (22:21)

Nice. It’s tremendous, man, because there’s a you discovered a lot of ground. Like it’s so how did let me let me ask you this. It’s because you’re running a pretty lean shop over there and you’re covering a lot of bases here on not with using the national sets of data. So how like who’s and you’ve taken on a huge scope, you know, relative to other competitors in the market, right? Like you there’s PropStream and Batch and other platforms that are doing this kind of this kind of work.

How have you guys approached it different? How have you gotten so much done and how have you approached it differently than you think than other folks in the space?

Glenn (23:00)

Yeah. So, yeah, our team right now, there’s about half a dozen of us. Thankfully, me and Phil spent 12 hours a day, three years straight, just beating our heads against this data when we were at Sunday. So we, you know, as soon as we got access to the nationwide data, it’s like, yeah, we were off to races, there’s no real learning curve and we were able to pump stuff out pretty quickly.

We have other people on the team who also have a similar background. Have a couple engineers who’ve helped a lot in just speeding up development cycles and stuff like that. So, small, lean team, but has a decent amount of experience. And yeah, I’d say overall, it’s both a blessing and curse. We’re extremely naturally curious. So, like…

of the stuff we built has come out of just us talking and being like, hey, I actually wonder what that does look like. And then we spend a couple hours going down that rabbit hole, which frankly, not the best strategy for company building, but definitely very good for engaging the curiosity.

Craig Fuhr (24:15)

Personally pleasing. So how would you say that you guys sort of differentiate yourself and the way you parse all of the data that appears to be, you know, fairly accessible these days for most? You know, what’s your guiding philosophy on how you’re different than some of those other competitors that Jack mentioned?

Glenn (24:17)

Exactly.

Yeah, I think to put it…

Bluntly, we look at the data. What we often see, the underlying issue, is you can buy bulk data from dozens of different people, who it’s all effectively the same product. The issue is the data providers give you this bulk amount of data, relatively clean. But the data has like,

Craig Fuhr (24:43)

Ha ha ha.

Glenn (25:02)

amazing amount of gotchas and you can’t just take the data for face value. One great example of this is for hard money loans. Most of your bulk data providers, there’s no classification for what a hard money loan is. It’s just another normal mortgage and they actually just assume that everything’s a 30-year mortgage.

So in our underlying data for all of Dominion’s loans, for example, like they’re all labeled as these 30 year mortgages. And just like the, it’d be very easy. And what most platforms do is they’re just like, okay, like, yeah, what first American or Adam says the data is, is right. And they put that on a, you know, they just resurface that. What we.

aim to do is we aim to go one or two steps deeper, where we know that there’s issues with the data and we know that just tweaking it a little bit can make it a lot more helpful. So what this looks like in a few of our tools is in our self-service tool, for example, we’ve gone and we’ve connected disparate LLCs together to try to get a better view of who a buyer is. So we’ve connected.

Uh, this is a, yeah, on the extreme end, but invitation homes, for example, owns homes across hundreds of different LLCs that we’ve rolled into just one. So when you log in, it’ll say invitation homes, not IH six property fund, you know, one, um, so that’s really our, yeah, our approach and where we’ve seen a lot of good customer feedback is like, Oh, okay. Like

Most customers don’t want to think about the data. They just want outcome. And if you don’t take the extra steps to making the data clean and extremely outcome focused, I think a lot of the value gets left off the table.

Craig Fuhr (27:14)

Mm-hmm.

Jack BeVier (27:16)

And just to, by the way, like just to reiterate to everybody listening, like, we like, I’m just a fan. Like we, we do business with us for analytics. We have no relationship with them. So like when we’re asking them, when I’m asking, you know, we’re asking all these questions about what they’re doing and make some different, like it’s not a commercial actually just like, there’s no like relationship between the two companies other than I’m just like a fan boy and just think that what they’re doing is much better than what everybody else is doing. So I just wanted to reiterate,

that to everyone. So they didn’t think that this is an SFR analytics commercial. Like I just think that they’re actually approaching things in a much better, you know, much better, you know, coming up with much better outcomes. Glenn, something that you, that you mentioned there, but I think makes a huge difference is the, um, that you guys are digging into the data and have curiosity about what it actually means. And yeah.

Glenn Hull (27:58)

I think makes a huge difference. It’s the that you guys are digging into the data and have curiosity about what it actually means.

Craig Fuhr (28:06)

Hold on one second, Jack. Hold on one second.

Jack BeVier (28:09)

So I think that the big differentiator and it makes a huge difference, you can tell with a lot of data companies that they’ve got, they’ve hired, I’m sure really intelligent data people to manipulate the data and to put it in different formats. But you can just kind of tell when you get in there and start playing with it that they’re not real estate guys, and that they really don’t have the industry experience because and then that just turns you off as a consumer of the data. Like as soon as you see something that you know,

isn’t right. You just know it. It’s not right. Cause you like active in the market and just know that that’s not true. Like it just turns you know, you lose faith in the entire set, right? And it becomes a product that you’re just not that excited about excited about using. And given your guys background and industry experience, I’ve always found that your approach to what you’re emphasizing and the product that you guys have put out there is you know,

Glenn Hull (28:40)

Yeah.

Jack BeVier (29:02)

is definitely produced through that lens. And I think it makes a, I think it makes, you know, it’s a little distinction that makes a huge impact on in terms of the quality of the usability of the data and frankly, in being able to turn it into revenue. So I’ve always appreciated that about your guys approach.

Glenn Hull (29:18)

No, appreciate. That’s what we tried to hammer into during sales calls, too, where it’s like, yeah, the market research stuff, like that’s all fine and good. But if you’re not making three times or more money than you’re paying us, we’re doing something wrong. The end goal here is, at least for most of our products, is revenue. We have a few. The newsletter and stuff like that, it’s not. But for our core software products, you know.

Yeah, we’re, yeah. Yeah, we only care about our customers getting the bottom line. So.

Jack BeVier (29:51)

You talked about the newsletter that you guys started putting out. I was really impressed with that as well. You guys are doing this basically like research newsletter publishing it, I think on a monthly basis and it does, you guys have doing really deep dives into. You know, the biggest names in SFR, um, using all of the, using your access to data to actually turn it into a nice narrative as to like, what, what’s going on, what, what matters, what doesn’t, what, um,

you know, where’d you guys come up with that idea and just talk about a couple of the companies and topics that you guys have published on already and what you plan to.

Glenn Hull (30:28)

Definitely. So thankfully Phil, my partner, he has a huge background in writing where he actually got hired at Sunday because he was on his own just writing about real estate data and he had no background other than he’d scraped Zillow a ton and found some interesting things. So one of the things that Phil found out when just having written online.

for five years is it’s crazy powerful. You get a ton of people reaching out to you when you publish high quality content. So we knew once we had a few products that were like, OK, like we’re comfortable selling this, we think they’re in a good spot that, yeah, writing high quality, kind of research oriented content was the best thing we could do to both one kind of showcase the data.

A lot of times we try not to be too aggressive with it, but there will be links to sample data sets or something like that in there where it’s trying to debate people a little bit, while also just satisfying personal curiosity where we’re looking at a bunch of this stuff already and we find it interesting. And when we were first starting, we’re like, yeah, we think other people find it interesting.

And it is honestly, it’s just a really good feedback loop where it’s like the first time we started posting on LinkedIn, got a ton of, yeah, decent, uh, you know, engagement, people reaching out, uh, wanting to talk, stuff like that. And when you get that, it gets pretty addicting to just keep doing it. And the, uh, the types of stuff we write about is almost exclusively focused on residential real estate investment activity and trends. So.

It’s everything from profiles of the largest landlords where there really isn’t all that much information on them. It’s like for invitation homes, Tri-Con and American Homes for Rent, they’re publicly traded. You can figure out some info on their docs, but for the tier below, Predium, Main Street Renewal, there’s no info on them online. It’s data, market research focused.

We put out these quarterly reports on the state of the fix and flip market, the private lending market, and then we’ll do these deep dives on specific markets. We had one in the last month about Florida where Florida is seeing a huge increase in listings, but still a decent amount of investment activity. And yeah.

The end goal of it is really twofold. One, put out more stuff that we would, as consumers, like to read. And, yeah, satisfy the personal curiosity. And two, build a following. Get people who are prospective customers to engage with the content and see what some of the data we have looks like.

Jack BeVier (33:30)

Yeah, I thought that the you guys did one recently on Wedgwood, which is a name that is not become a household name, right? Like everyone knows invitation and American homes for rent because, uh, because they become public greets, but Wedgwood is like the real OG of like, of, of house flipping. And they they’ve been flipping several hundred houses a month for a long time, a big West coast base, but they’ve expanded nationally over the course of the past 10 years. And, um, I mean, they’re like very major investment company that

Glenn Hull (33:39)

Mm-hmm.

Yeah.

Jack BeVier (33:58)

because they’re privately held, you almost never hear about. But, you know, in terms of like trying to emulate a company that’s achieved scale in the flipping space, I mean, they’re like they’re the guy. Right. So I thought that was a really interesting one because there’s someone who generally flies under the radar, but there, I think a lot more interesting than then, you know, than the big pools of money that are just like happened to be that happened to be buying real estate. Right. Like they’re real operators.

Glenn Hull (34:12)

Yeah.

Jack BeVier (34:27)

That was cool.

Glenn Hull (34:27)

Definitely. Yeah, I love Wedgwood as a company. We worked with a lot of people at Sunday who were ex-Wedgewood and got to learn a decent amount about how the company operated and just operational excellence. I can’t imagine even hearing it just the scale and the amount of headaches that, yeah, because they’re flipping across like 25 states. It’s absolutely insane.

And the people who we worked with at Sunday there, just absolutely top notch. People across acquisitions, asset management, everything. And then the other thing is like Civic was a Wedgwood company where Civic was incubated there and then ended up getting spun out. But yeah, just amazing depth. And they’re the largest why I’d consider a true flipper.

Craig Fuhr (34:54)

It’s unbelievable.

Glenn Hull (35:21)

where it’s not like open door offer pad who are just putting a little bit of cosmetic, if anything, while turning over the property. A lot of Wedgewood’s flips are meaty. They’re $100,000, $200,000 of renovation. And yeah, it’s just mind-boggling to me to see. And then one of the interesting things in California is a lot of the largest flippers in California are now people

Wedgwood. So if you look at the network of, it’s probably five of the top ten largest flippers in California are either Wedgwood or at one point, yeah, we’re Wedgwood employees.

Jack BeVier (36:05)

Yeah, it’s really impressive. Uh, and cool that you guys are paying attention to an exposing that kind of stuff, cause that’s the, I think that’s where like the really interesting lessons can be learned for, for investors growing their businesses is emulating those folks who’ve been doing it for decades more and, and already gone through a lot of the battles and learning curve, um, Hey, in the, in a couple of minutes that we have left, I wanted to ask you because you had like a lot of experience, both a Kiabi and Sunday in terms of marketing.

I mean, both of those companies have really big budgets, right? And you guys have tried to build your tools in a way that are usable and accessible for Main Street real estate investors. But my thought is that there’s probably a really good opportunity to learn from what you have experienced at those companies that are operating at larger scale. So I mean, I guess any thoughts on that in terms of the way that you’ve put the data together, what you think is important in terms of analytics?

what media is working or any lessons from just lead generation side of things would be really interesting to hear about.

Glenn Hull (37:09)

Definitely and I yeah, I can ramble on this for the next couple hours So feel free to hop in and anytime as you probably can tell by now a bit of a rambler But anyway, so yeah It’s Sunday’s peak Sunday raised a ton of venture capital over a hundred million with the explicit goal of Trying to take over the wholesaling market where Sunday’s main differentiator was there a flat fee wholesaler?

So you wouldn’t get, especially where Sunday was extremely active in California, where the spreads can often be, it’s not unusual to see a hundred thousand dollars spread on a wholesale deal in California. So anyway, Sunday was like, okay, no matter what, we’re just going to charge 5%. Be very clear. Here’s where all the offers are coming at and get homeowners. Yeah.

the ease of a cash offer with the competitive process was, yeah, it is the thought. And yeah, the raise a ton of money right during 2020, 2021, the real estate market was super hot. And we were basically tasked like, okay, how do we grow 2X in a three to six month period? And the only way to really do that, cause at that time, Sunday was in about half dozen markets and…

in California was expanding rapidly to markets across the country. But we already had a high single digit percent market share, where one of the things we tracked was what percentage of flipped deals were, you know, were Sunday wholesale deals. And, you know, the only way to really increase market share quickly was to spend a ton of money on paid advertising.

Everything else, just agent referrals, stuff like that, just takes too long. So my main focus became, okay, how do we get two, three, four times more people to come to Sunday? So Direct Mail was the largest channel, and I loved Direct Mail because after a certain point, it was all basically a numbers game.

where we found the creative that worked for the markets we were in. Any testing of it might give a very, very small increase, but all of it was in the data. So their peak, we were sending about 3 million pieces of direct mail a month across 25 markets. And a few of the… Yeah, no, just insane operation. And with that type of…

Craig Fuhr (39:52)

It says the forests are crying Jack. There’s just no, like, like.

Jack BeVier (39:59)

I’m sorry.

Glenn Hull (40:00)

So about that, there’s actually paper suppliers who that’s their pitch where it’s like, oh, you can pay a little bit extra, but it’s all like 100% recycled paper. But anyway, so what that basically looked like was me and Phil saying like, okay, like

Yeah, we can buy another $100,000 data set if we think it can increase response rate by like a couple percent. So we got to test a ton of different data. And some of the really interesting things we found were it for large flippers at a certain scale, you’re already hitting everybody on like the best trigger list. It’s like if you’re sending 25,000 pieces of mail in a given county.

with some why I’d call just like normal intelligence, owned the home for a while, in an area that does a lot of flip activity, high equity, small, older home, all of those people on triggered lists are already on the list. So that’s one of the things that is like, pretty interesting is like, we get these new lists, we’d run it through, be like, okay, like, yeah, 90% of these people we’d hit just like on our, you know, pretty basic standardization.

But one of the related to that is like, okay, we need to figure out who’s likely to sell their home to a flipper who, you know, who’s not on all these triggered lists that everybody’s already buying or who we’re not already hitting. So and this is very market dependent. But in Southern California, we had a ton of luck targeting high equity homes.

that were fairly recent built, so like 1990 plus. And we have this great plot of our market share. And there’s some of these neighborhoods where, yeah, we bought half dozen homes in the subdivision. We’re the only buyer there. And they’re all 1990s, like pretty nice tract homes. But the people are just, they made so much money.

because they bought the home for $200,000, you know, 20 years ago that they’re willing to sell at a price where a flipper can make money. So anyway, sent it to our mail. Love triggered lists, it was like the probate lists were fantastic.

Divorce was pretty good, but those, at least in a lot of the markets we were in, get a lot of attention from agents as well. So it can be a little bit tricky. And then your inheritance list worked really well. But at a certain point, it’s just like the ROI of the data isn’t there. If you’re truly a large flipper who’s sending, you know, and scale where it’s like, okay, like any of those people who have, yeah, who are in probate with a home, who they’re going to sell to a flipper.

Like they’re going to be on your list anyway, because you get some, but you don’t get this massive amount of people who own a nice home that’s going through probate who’s willing to take a flipper type offer. I hate billboards and out of home where I just never saw an ROI, had friends who would call me saying they saw my billboards, no customers ever mentioned them.

I know other operators who do a lot of billboard advertising and claim to see some luck there, just never was able to tie it out to an ROI. Radio was really interesting where the key to radio is you have to get the local…

like celebrity endorser where it was night and day difference where we had in LA, we had this guy, Tim Conway Jr. whose dad was an actor and just your typical kind of news talk radio and just crazy performance where people were calling just because Tim recommended us. He had the cult-like following.

So it’s like, I actually heavily recommend radio to people. With the caveat, you need to run it for a while. You need to run it pretty aggressively and only do it if like people really respect that radio host. But if they do, it’s great. Yeah.

Craig Fuhr (44:21)

Bye.

Can I ask you Glenn in the time that we have left here, what’s missing? What’s that carrot of data that you’re not getting now that you wish you could? You know, I’ve actually been playing around with the platform with one of our managers here, John McClelland, and stunning the robust data that we get off of it in such a short period of time. But what do you, if you have that

one or two pieces of data that you’re missing right now that you wish you could get your hands on, what would it be?

Glenn Hull (44:57)

Yeah, so on the private wonder site, it’s term data. Like I wish we could get rates and all of that. That’d just be extraordinarily helpful. Yeah.

Craig Fuhr (45:06)

That would be sweet. Jack, can you imagine? Jack, Jack’s mind is just the marketing that we could do off of that jack.

Jack BeVier (45:12)

Thanks for watching!

Glenn Hull (45:14)

Definitely. It’s like that. Yeah that one I wish one that we get a ton of inbound interest on institutional sides built-to-rent data where built-to-rent data is just a mess where you know for a lot of reasons but and then on the flipper side like I really wish that there is one clean provider for your triggered list data where

Because you’ll see it in like we have some where it’s like, depending on county, you can see some probate, you can see some divorce data and underlying deeds, but it does leave some out where there’s some, like some of the credit bureaus, for example, they sell excellent divorce data. But nobody that I’ve seen, I know a few people are working on it, but I haven’t seen like a true nationwide.

distress data set. And I think there’s a huge market there for kind of playing in the same space as First American. Atom is like a bulk seller of that data because I think a ton of platforms would purchase that. For the couple that I’ve seen, they’re trying to aggregate that data nationwide. They’re trying to sell it to the underlying.

Yeah, the largest flippers, wholesalers in the market, which I just think that’s a tough, that’s tough sell. It’s like, there’s only so much data budget possible for a large flipper and it’s expensive to do. But I’d love like, yeah, here’s actually everybody who got divorced, everybody who’s in probate, everybody who’s in bankruptcy across the country instead of having to piecemeal together across, yeah, hundreds of different sources.

Craig Fuhr (47:06)

Just, Jack, we’re having a little bit of technical issues today with you, Glenn, but I got, just one last question. That’s all right, it’s common. So in taking a look at the data that we generated for particular lists that I was looking at, I noticed that there’s, we can get address data, we can get phone data, obviously, you know, the docs for the loan and stuff like that. It’s…

Glenn Hull (47:14)

apologies.

Craig Fuhr (47:35)

Very robust. Question for you as a user, in terms of like the phone data, the address data, I noticed that there’s always like three phone numbers. And this is kind of getting in the weeds a little bit, but for folks that are interested in the product, I think that they’d be interested in knowing. Like the first phone number that’s listed, is that gonna be generally the best one? Is it a landline? Is it a cell line?

Glenn Hull (47:47)

Yeah.

Yeah, so we do contact info in two ways. The one that’s native in platform, we’re doing it through Skip Tracer. So what it looks like is we scrape the Secretary of State’s website for the principal name to try to get the underlying owner and Skip Trace against the owner. Just because if you Skip Trace against LLC, it’s almost always garbage. That approach that I outlined, it’s, yeah.

Jack BeVier (48:23)

Nothing.

Glenn Hull (48:28)

It’s fine. It’s like a 30 to 40 percent contact. Yeah, like accuracy rate is like what we’re seeing across, which is, yeah, good if you have like a large team of SDRs going after it. But what we also have is we have a pretty large team in the Philippines who is manually going through that data as well and trying to figure out, yeah, what the real

contact data is because the larger the flipper, almost always the worse your skip tracing results are because, yeah, once you go to the corporate level, it’s often, you know, nive in the CEO who’s on the dock. It gets to be a mess. But to answer your question, it’s like, yeah, so when we go through a skip tracer, we provide the three phone numbers.

First one is who our provider thinks is the best. Second and third, yeah, what they think the second third best are. There’s currently no differentiation between if it’s a phone or a mobile or landline. Most are mobile. But occasionally you get a landline there as well.

Craig Fuhr (49:43)

We know you’re coming up on a hard break, Glenn. Can’t thank you enough for your time. Love to have you back on at some point in the future. I hope folks have enjoyed it. It’s SFR Analytics if you’re interested. Why don’t you let folks just know quickly how they can get in touch. Maybe take a look at the newsletter and your really incredible blog that you guys do. It’s honestly, it’s deep data. Love it a lot. So go ahead and let folks know how they can get in touch.

Glenn Hull (50:10)

Definitely shoot me an email. Glenn, G L E N N, at SFRanalytics.com. Um, yeah, that’s probably the easy way. And yeah, thank you guys so much for having me.

Craig Fuhr (50:21)

Yeah, it’s Glenn with two N’s at SFR Analytics. Glenn, thank you for your time. I’m sure we’ll talk to you again soon. That folks that was real investor radio for the day. I’ve lost my ability to talk Jack. Thanks for joining us. We’ll see you on the next episode.

Jack BeVier (50:39)

See you guys.

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