Utilizing Local Data Intelligence with Vincent-Charles Hodder, Co-founder and CEO at Local Logic

Nate Smoyer (00:01.981)
Vincent, welcome to the show.

Vincent (00:04.574)
Thanks for having me, Nate.

Nate Smoyer (00:06.159)
Okay, I'm going to put you on the spot here because you told me English is not your first language. If I were to say that in French, how would that go?

Vincent (00:13.374)
Bienvenue à l 'émission.

Nate Smoyer (00:16.381)
That was way too fast for me. And, oh, there's one more time. One more, Bienvenue?

Vincent (00:17.31)
You gotta do it. Bienvenue à l 'émission. You gotta do it. You gotta do it, Nate. Bienvenue. Welcome. Bienvenue à l 'émission. To the show. À l 'émission. À l 'émission. You gotta practice. Yeah.

Nate Smoyer (00:28.925)
Okay. Well, if it's not obvious, I am not here to talk about language interpretation or to demonstrate my multilingual skills. I'm excited for today's guest we have on the show, Vincent Hodder. Vincent is co -founder and CEO of a company called Local Logic. They're a location intelligence platform digitizing the built world.

focusing on the purpose of consumers, investors, developers, and even governments. And this blew my mind. 100 billion unique data points on their platform, the largest data set in both the US and Canada platform creating the digital twin of cities, quantifying the built world and offering predictive, precise analytics to help inform present and future possibilities for addresses all across both countries.

That is hard to wrap my head around. I'm not a big data type person in a way of like, I can grasp that. I imagine you guys have quite a few computers in house.

Vincent (01:38.078)
Yeah, we do. And I mean, I wasn't a data person a few years ago either. And I think that's something that's interesting about our team is, you know, we like to say we're urban planners turn data scientists working in real estate. And, you know, it's it's we're using data because we feel like it's the best, most objective way of really getting a deeper understanding of what location is all about in the context of real estate at scale. So, yes, now we have a ton of

Nate Smoyer (01:51.261)
Oh.

Vincent (02:07.294)
amazing data nerds at LocalLogic, having a lot of fun with a lot of data.

Nate Smoyer (02:12.061)
That's very cool. So let's start big picture here because I'm genuinely not really sure where the lines are, right? So as a location intelligence platform and just in the name of the company, local logic, right? So we'll start here on the topic of local data. Where does that start and stop? How do you define the lines around something like that?

Vincent (02:37.054)
Yeah, so, you know, like I alluded to, we started the company while studying urban planning at a master's level in McGill here in Montreal. And as urban planners, we were really trying to find a better way of understanding and quantifying cities. And when we kind of went down that road and looking at the data that was available and kind of traditional, more traditional real estate data, we realized that

Nate Smoyer (02:54.941)
Mm -hmm.

Vincent (03:04.67)
The data that existed on our cities wasn't necessarily at the right scale of analysis. And what we mean by that, our perspective on that was that, you know, we experienced the city one street corner at a time, right? When you're standing outside your house or your office, you're only seeing a very small sliver of a neighborhood or a city. And so we felt like it was important to build a data set that was really at an address by address level.

And we build data points to essentially tell the story of that specific location. And so when we think about local data for us, it's saying, well, it needs to be at that hyper local level of this specific address. Where are you on a block? What side of the street are you on? That's going to have a huge impact on the experience that you have if you live there, if you're investing there. And so for us, local data starts there. But then the beauty of doing it that way is that.

we can extrapolate and go for, okay, well, what is this zip code or what is this sub -neighborhood or this social neighborhood? How do we take that data and go broader and go to a city level, a state level, a national level? And so local data for us is about understanding what's there and telling the story of the built world through data in order to help different stakeholders investing in real estate make better decisions.

Nate Smoyer (04:10.365)
Mm -hmm.

Vincent (04:31.806)
Now, you know, telling the story of a location is broad, right? There's so many things we could do. There's so many things we could say. And so that was really the first kind of the first huge challenge for us is saying, okay, well, what matters? What do you need to look at? What creates the experience that you have? And so it's things like canopy coverage, traffic patterns, the setback from your house to the sidewalk, the...

Nate Smoyer (04:46.173)
Mm -hmm.

Nate Smoyer (04:56.093)
Mm -hmm.

Vincent (04:57.694)
the sense of enclosure, the ratio between the height of the building and the width of the streets, the density of commercial offering. All these things create the vibe, the feeling that we kind of intuitively understand as users of the space, but we're trying to replicate that same thing with data.

Nate Smoyer (05:11.165)
Mm -hmm.

Nate Smoyer (05:15.389)
I had a funny visual just come into my head. And this is like, may really reflect more on me and the amount of caffeine I've had today. Have you ever seen the evolution of dance?

Vincent (05:18.046)
Go for it.

Vincent (05:23.358)
You

Vincent (05:29.79)
I don't think I have, no.

Nate Smoyer (05:31.005)
Well, there's an episode of the office at least, and Andy does an interpretation of this. And basically you do like you, you do dances and the music changes to where you're like, you, you show the evolution of dancing. I want to see that for real estate data. Like even just what was available to consumers and what was available to the real orders to be able to share. Because obviously if we go back to just like, it really wasn't that long ago when a book was required to see them.

Vincent (05:40.51)
Right. Okay.

Yeah. Yeah.

Nate Smoyer (05:58.141)
the listings and some of the first websites, there was always so much you could share. Whereas to today, where do you stop? And I think that's where I struggle when I think about this, because we do have so much. Like where do you draw the line of like, what is helpful and what is interesting?

Vincent (06:15.614)
Yeah, so I'll answer that question two parts. So the first thing is like when we first, so like I said, we were, we were kind of external to the real estate industry for the most part, like residential real estate, where I had, I had experience on, on the finance side and commercial real estate. But for us, it was kind of fascinating that we all know that location plays a huge part in the value of a home and the experience we have in a home. Like, you know, the old real estate adage, location, location, location, like we all know it's important. Yet when you look at traditional real estate data.

Nate Smoyer (06:24.605)
Mm -hmm.

Nate Smoyer (06:41.085)
Right.

Vincent (06:44.862)
It's all about the asset. It's bedrooms and bathrooms, square footage. Yeah, exactly. And yet, like, we're like, okay, well, where's the other half? Like, where's all the information about location? And location is so critical in the sense of the lifestyle it will enable you, your family to have. But it's also so critical from a financial risk perspective where, look, you can renovate your house, you can remodel your kitchen. You can't pick up your house for the most part.

Nate Smoyer (06:48.253)
It's a four one, you know, it's got a backyard, it's a 10 ,000 square foot lot.

Nate Smoyer (06:58.685)
Mm -hmm.

Vincent (07:13.694)
and change neighborhoods, right? So you better understand. Yeah, exactly. Yeah. Well, it's and so it's like, you better understand prior to buying a house, where the neighborhood's going, what risks you're exposing yourself to, how much of a fit between you and the lifestyle you want and what that neighborhood or that location can enable. So for us, it was kind of like, holy shit, there's a huge opportunity to bring that intelligence to market.

Nate Smoyer (07:16.125)
Yeah, the older homes he could.

Nate Smoyer (07:26.013)
Mm -hmm.

Vincent (07:39.294)
And help consumers help agents help professional investors make better more informed decisions now. That's the first part The second part is yeah, I agree with you there's a ton of data and data overload is not helpful and throwing data at people is is is Not the way for it, right and that that's true for the home buyer home searcher to the most sophisticated real estate investor so Our perspective has been okay. It's great to have a ton of data and

Nate Smoyer (08:02.525)
Mm -hmm.

Vincent (08:08.222)
But we need to do the work to provide insights for people. We need to answer questions. And so we do sell APIs with some data points, but the majority of our business are products that we've built on top of our unique and proprietary data that enable consumers out of the box to understand what they're getting in that location to help consumers or agents or investors position themselves with regard to our data. And I think that's where

we do really well is we are the experts of our data and it's up to us to demonstrate why it's valuable, up to us to kind of decipher the data and answer your questions.

Nate Smoyer (08:49.053)
Yeah. And how much of that, you know, and I, you know, I, right now I'm kind of like stuck on a vein to think about the residential market. Um, and I think, you know, there's a common theme amongst agents and the last two years is like, look, you have to find an edge. Has to be some edge, but there's also some restrictions on what you're allowed to say as an agent from your perspective. And I'll give you an example of one, uh, you know, so when we bought our house in South Dakota, we were looking at.

Vincent (08:57.086)
Mm -hmm.

Vincent (09:10.686)
Sure.

Nate Smoyer (09:18.941)
a house not far from here and I'm looking at the price of it. And I said to my wife, this doesn't make sense. I was like, this house is like $50 ,000 less than what it should be five miles up the road. And I'm doing the Google street view, trying to collect the data of the neighborhood, if you will. And I couldn't, I was like, there's something that like no one is telling me. There's something that doesn't make sense here. And I asked my realtor and I'm not local to the area and he doesn't give me any clues. He's not telling me anything.

He's like, yeah, you know, it's just, it's just that neighborhood sells for less. That's all he sold. That's all he told me. I didn't find out until I moved here that it's because not far from that neighborhood, there's a corner of it that is totally condemned because a mine collapsed underneath the homes a year ago and there's literally a giant massive hole in the street. And so all the homes in that entire development are permanently devalued because nobody wants to live over top of a mine that is collapsing. And there was,

There was nothing for me to get ahold of that. And the only reason I think we steered clear of that was my prior experience in knowledge and real estate. Otherwise it would have been like, hey, this is a smoking deal. Let's go get it. But even for consumers, when they're presented with data, like what have you guys heard back from brokers is a most helpful form or even data set to like make decisions. Cause like I said, there's no end to that of what you could gather.

and tells them.

Vincent (10:47.166)
Yeah. And I think it's tough because, um, you can interpret data many different ways, right? And not everyone is data literate. So there's been areas where we've been really, really careful, like crime data, for example, where it's easy to improperly interprets data. Um, and so we, we felt like we weren't doing, it was difficult for us to do a good job of kind of presenting that information in a purely objective point of view.

Nate Smoyer (11:03.485)
to Hot Topic.

Vincent (11:16.158)
but also give people a point of comparison or an ability to kind of interpret it. So something, you know, those types of areas we've, we've been able to kind of stay clear of, but like in our, in our more recent product or product feature, we started comparing. So saying, for example, you know, this area is quiet. It's a nine out of 10. Well, what does the nine out of 10 mean? Well, let us compare it to other properties, but let's also compare it to averages in that neighborhood, in that city.

So it enables you to say, okay, well, it's more quiet than most areas. So there's, it's better because I'm looking for that quiet environment, whatever it is, right? So points of comparison. Other areas, and maybe you're alluding to this, is like, I think there's going to be major risks that consumers are going to be wanting, or want to be aware of prior to buying or looking at a property. And I think there's a ton of opportunity to build really interesting products for consumers.

to go and vet those opportunities themselves. I think agents can be amazing partners, but I think it's an opportunity for companies like ours to really provide that agent or that consumer directly with kind of an objective view on the market and the objective view on opportunities, specifically around climate, for example, right? Flood risk, all these things, but also indirect risks in climate of saying, well, hey, maybe your property isn't directly in a flood zone.

But the infrastructure that feeds that specific neighborhood or property is very much prone to fire risk or flood risk. And so maybe in 10 years, well, the highway you get to, you know, you used to go to your house is going to be permanently flooded. Well, suddenly that neighborhood is going to be devalued. So understanding those kinds of intricacies in how another part of the city's ecosystem might impact the home or asset you're looking to purchase. I think that becomes really interesting.

Nate Smoyer (12:57.757)
Mm -hmm.

Vincent (13:12.414)
data problem, tech problem, AI problem to help inform consumers in an objective and comprehensive way.

Nate Smoyer (13:20.605)
Well, that directly impacts insurance prices. I mean, we've been seeing that, you know, I don't know the Canadian market all that well, although I do want to thank you guys for all the smoke last year. Thank you very much. But you know, the risk of, of wildfire, for instance, in certain areas has already really had a pretty, you know, significant impact in local areas.

Vincent (13:31.23)
You're welcome.

Nate Smoyer (13:47.485)
And so being aware of that and knowing that, Hey, this is a factor that's kind of like a hidden cost to ownership and to living in those areas, you know, and even, even with, uh, you mentioned, uh, flooding, I, I, the last I checked, uh, is a large, I believe it's a large majority of flood insurance claims come from homes that are not in floodplains. And so, like you said, like there may be, um, you know, some, Hey, you're not a floodplain, but.

The infrastructure here tends to imply that you really could have a risk here and it's worth mitigating that risk.

Vincent (14:23.23)
And that's where we see an opportunity for innovation at Localogic, where look, like cities are super complex ecosystems, right? And everything is intertwined. So like the example I give in Montreal is we introduce a new bike lane, like a separate bike lane on a street. Well, sure, that'll impact cyclists. It's going to be safer for them to commute to work on that bike lane. It's going to impact...

Nate Smoyer (14:31.485)
Mm -hmm.

Nate Smoyer (14:41.469)
Mm -hmm.

Vincent (14:51.102)
negatively. There's less parking because the bike lanes taking on that thing, that space. But it's also going to have an impact on retail, where now suddenly the bikers are more likely to stop and survey or studies have proven this and actually shop in those stores. And so increased commercial activity has impact on residential real estate because suddenly it's a thriving neighborhood and that independent coffee shop makes it cool. And that's going to be captured in the value of your home.

Nate Smoyer (14:55.197)
Hmm?

Vincent (15:20.83)
And so that small example demonstrates that, hey, all of these different elements of the built world are intertwined and impact real estate values. And so I believe data and AI and these new technologies are incredibly valuable in understanding how cities actually work, deciphering the links, and then helping consumers, you know, and I think of consumers as investors.

Nate Smoyer (15:28.413)
Mm -hmm.

Vincent (15:49.374)
you know, you're investing in a home, helping consumers or professional investors understand how their investments are going to be positively or negatively impacted by those changes. Climate, again, is another example. It's a new variable that might not change your little piece of the city, but might have an impact on you anyways.

Nate Smoyer (16:04.413)
Mm -hmm.

Nate Smoyer (16:11.229)
Totally. I want to shift a little bit here because I know that you kind of talked about those opportunities and the evolution of the product and you guys have actually done quite a bit of shipping this year with two solutions, I'll say not necessarily features. So let's kind of jump into the first one here, neighborhood wrap. Let's talk about what neighborhood wrap is, and who's using that and how you see that driving impact throughout real estate.

Vincent (16:27.07)
Yeah, sure.

Vincent (16:42.878)
Yeah, so neighborhood wrap, what we saw is that there was a need for a comprehensive solution to really build compelling neighborhood level pages on our partners websites. So essentially give a real good understanding of what is this neighborhood? Why would it be relevant for a specific user? How does it compare to other neighborhoods? And so we saw a lot of our customers try to build it themselves using different data points.

we felt there was a huge opportunity for us to actually do it and do it really, really well. Again, like I said earlier, like we are a hundred percent focused on building those products off of our data. And so essentially we built out the technology that enables us to, for every single neighbor in the U S and Canada, build a compelling page that has all of the elements of a high quality neighborhood page. So looking at things like,

Nate Smoyer (17:21.245)
Mm -hmm.

Vincent (17:38.206)
Well, what is this? What is this neighborhood? Who is it for? What are the highlights of that neighborhood? Pictures, et cetera, but also having the ability to explore your neighborhood. So what are the restaurants, the businesses? How is it? What are the major characteristics in terms of livability, in terms of of wellness, but also comparing it? So what are other other areas that are similar? How does this neighborhood compare in terms of affordability, for example?

Nate Smoyer (18:06.813)
Mm -hmm.

Vincent (18:07.454)
So really helping consumers that are in that search discovery phase go a little bit deeper in the funnel on our partner websites and actually find listings and then contact an agent. So that was really the premise for Neighborhood Wrap.

Nate Smoyer (18:23.133)
And I love that actually, you know, an accidental, I would say like an example I've seen of this working in an accidental way. I remember running a report for our, I was doing some SEO research for Avale and I ran a report and I was like, why are we ranking for crumble cookies? Like I was trying to figure this out. And so it was actually, it was crumble cookies in Philly. And,

Then I was like dug into it, found the listing page that was ranking for it. And it turns out, because this landlord was smart, they talked about the local amenities and what was near them. And I was like, if only we could have every landlord write this well, we would have such good SEO, you know? But they captured it. They were like, hey, look, this is an area where demographic tends to be a little bit younger. They're staying out late.

Vincent (19:09.182)
Yeah, exactly.

Nate Smoyer (19:19.133)
And they want snack foods and things. And so they talked about the Starbucks, the Trader Joe's, and the crumble cookies, stuff like that, of what was all in that area. And obviously, they were trying to pull people in. And I think that that was very effective. But genuinely, as an agent, or even just at the brokerage level, it's very hard to have the time to do that in such a detailed way.

Vincent (19:45.374)
Yeah, exactly. And I mean, like, look, like our, our, our partners come to us for three main reasons. Like the value props of our products are either, Hey, we want more traffic on our site. Like we're investing millions of dollars on our website. It's like, we want more traffic. The second one is we want more engagement. So we want people to really get access to the information they need to take the next step in the funnel. So that's where a lot of our neighbor level pages are is saying, okay.

Now Google is going to recognize you as an expert of real estate in this area, but also real estate in this neighborhood, real estate in this city. And we give you the content to rank that way. And then engagement and then finally conversion. And so what we're seeing is our products being present throughout that funnel actually increase the likelihood of a user to convert into a lead for our brokerages. So.

There is a 36 % increase, which is a significant increase. And the rationale for that is, hey, you're not going to Google Maps. You're not going to Street View. You're not going to a blog. You're not going on another website. You're staying in the funnel. You have the information. And you are confident this brokerage or this agent is the expert of that location. And you're willing to take the next step.

Nate Smoyer (20:43.933)
Mmm.

Nate Smoyer (21:03.805)
Yeah, yeah, I totally see that. And then the second solution that you guys have recently launched here, and that was, I think a little bit earlier this year was neighborhood Intel, which kind of like related to some of these things we talked about, but kind of covers like bigger topics, not necessarily local like neighborhood details. That's like the demographics or climate risk or location insights. I actually wanna like, if we can...

Go back into the climate risk and I'm gonna go a little bit deeper there. Can we talk about some of the things that I could learn using neighborhood Intel and how that's really powering other businesses at that local level so they can talk intelligently about the climate necessarily, bigger picture versus, oh, well, last year we had a really hot summer and so we'll probably have a cold winter.

Vincent (21:52.19)
Yeah, so our product, kind of the way we're laying out our products is saying, okay, well, we want to inform consumers from, hey, I'm just trying to figure out where to live, kind of discovery phase all the way through to this is the right property and confidence is the right decision. So those are kind of the web applications we've built, consumer facing web applications. We have the same philosophy on the agent side of saying, okay, well, we need to help agents with a variety of tools.

Nate Smoyer (22:11.261)
Mm -hmm.

Vincent (22:19.742)
at different stages of the buyer journey and give them the right insights for them to give that context to their consumer. And it does two things. It allows the agent to be perceived as a neighborhood expert, as an expert on kind of the risks, climate is one of them, when they're going to try to get a seller lead, but also when they're marketing that property.

Nate Smoyer (22:28.061)
Mm -hmm.

Vincent (22:46.558)
And then it also enables them to provide value to consumers and saying like, look, I'm unique. I have this thing. I have this super detailed understanding. I'm providing value to you that otherwise you wouldn't have justifying my commission, justifying the, the, the, the relation I have. Um, but then we're able to also go really, really deep at the listing level and explain concretely, what are the risks? What are the benefits of that listing? So it goes from.

neighborhood level all the way down to listing. And yes, comment is one of them, but it's also saying like, hey, what's the school your kids are going to go to? What's the closest grocery store? How many grocery stores do you have? That's actually important. Maybe the one down the street isn't, you know, doesn't have what you're looking for, but you have three of them. And so there's a diversity of offering. What's the noise level? Those are the things that I know when I bought my house. It's like, Hey, am I on a, on a, on a, on a street that has a ton of traffic in the morning? And I don't know about it. Cause I've been visiting and on it, you know,

3 p .m. on a Saturday afternoon. So that's the level of detail that we give in that report that enables the agent to really be seen from the consumer's perspective as kind of knowing and being the expert of that location and doing that at scale. And that's the beauty of data is you can do it for every single address in the U .S.

Nate Smoyer (24:05.149)
This kind of reporting and insights hasn't always been available to at the agent and brokerage level. I think that's, you know, the obvious of like, there's the market opportunity here, right? We know consumers ask these questions based on search patterns and you know, SEO research, like we can see it. And there's probably some sort of complaint after the fact of why didn't you tell me? I have one now. Why didn't anyone tell me my house was built on an ancient river bed, which what's the government, what's the government agency that does the flood? FEMA.

Vincent (24:15.774)
Mm -hmm.

Vincent (24:21.566)
Mm -hmm.

Nate Smoyer (24:34.653)
FEMA and our city is like fighting at the moment. They're like trying to determine if this is a floodplain. There's literally not a creek within a mile, but anyway. So, but with that becomes, there's a go -to -market challenge there of like, how do you get this in front of people if it hasn't been previously available? And like sometimes you have to create the category of what this is and what it solves for. So I'm curious actually how you guys have been

Vincent (24:44.382)
Right, right.

Nate Smoyer (25:04.893)
solving for that of getting this in front of the agents and broker partners so that they know they can use something like this to answer some of those questions that do come up in conversations.

Vincent (25:16.03)
I think it's a great question, Nate. And I think this is kind of hits to the fact that like the dirty little secret in real estate is that everybody has the same data or has had the same data, right? All the different data providers are reselling each other's data. And there hasn't been all that much innovation in new data points going to market. And so naively when we first started, we're like, of course people are gonna care about location. Like,

Nate Smoyer (25:26.685)
Hmm.

Vincent (25:45.182)
location, location, location. Like it's, it's obvious, right. And quickly realize like, no, no, that's not how that works. Right. But we were able to get early customers to believe in that vision and, and, and see, see it the way we saw it, believe in our products. And then, and we were able to be on some big platforms in Canada and the U S and that kind of gave us the stamp of approval saying like, yup, this is, this is, this is where we're heading. And this is important context that we need to give consumers.

Nate Smoyer (25:48.861)
Alright.

Nate Smoyer (26:10.781)
Mm -hmm.

Vincent (26:14.654)
And I think there's been openness since then of, and there's been interest in new data points. The conversations we have with partners though, and this goes from the biggest portals in the U S to a small brokerage is, well, I want to make sure that I'm, I'm presenting that information in the right way. That's legal, but also that's going to. You know, market the property in its best light. And so if you're saying that it's, you know, a.

Nate Smoyer (26:21.309)
Mm.

Nate Smoyer (26:39.261)
Sure.

Vincent (26:43.966)
a noisy neighborhood with zero access to shops and services, that's not helping me, it's not helping my realtor sell that property. So we've had to kind of dance through that of building an objective view on what's there, but also understanding that we're trying to market properties here. So that's kind of been one of the points.

Nate Smoyer (27:03.293)
Mm -hmm.

Nate Smoyer (27:09.405)
That's a very interesting dance because as a data person, the data is the data. But then obviously on the sales side, it's like, yeah, but give me the good numbers. What are the good ones?

Vincent (27:20.222)
Yeah, exactly. Yeah. But the response to that objection often is like, look, every location has something great. And essentially what we're trying to do and what the industry is trying to do is match the right consumer, the right homeowner with the right property. And so if you have enough breadth of data and data points, well, you can find the really cool attribute of that specific neighborhood or property, right?

Nate Smoyer (27:35.549)
Sure, yeah.

Vincent (27:46.974)
It might be on a noisy street, but guess what? There's a high vibrancy and there's tons of opportunities for nightlife. And maybe somebody is looking for that, right? So that's kind of how we've navigated that. And then the other piece is just being super objective. It's like, this is the facts and this is it's not an interpretation. It's just the reality of this property. And another cool thing we've realized is like, and this goes to my first point, we.

we're super interested in trying to better understand the financial implications of location. So what is valuable? What are the very valuable characteristics of a location? And one of the things that we found, which is obvious in retrospect is, well, guess what? A specific characteristic for an asset could be accretive in value in certain instances and actually reduce value in others. So for example, a...

noisy, a noisy, uh, asset or a noisy house in a super vibrant neighborhood might actually be a good thing. Cause it means that you're close to shops and services and you're kind of in the heart of it. Whereas a noisy location in a rural or semi rural area is probably a bad thing. Cause you're close to a highway or railroad track or something like that. So understanding that there's incredible nuance in what is valuable in different contexts is actually super important.

Nate Smoyer (28:58.237)
Yeah.

Vincent (29:15.102)
and needs to be understood in order to properly market that property and find the right fit, the right buyer.

Nate Smoyer (29:20.637)
Yeah, if you could take out the part about the railroads and interstate that's near my neighborhood, I'd appreciate that. We have beautiful mountain views on either side. Okay, let's just really zone in on that and the sunsets. Okay, I would absolutely be doing everyone a disservice here if I don't ask this one last question here before we jump to the bottom of the show. We cannot talk about data, data aggregation, integrations, reports, summaries.

Vincent (29:27.454)
Hehehehe

Vincent (29:32.478)
Right. Yeah, exactly. Yeah.

Nate Smoyer (29:50.749)
without talking about the role of AI here. Obviously that's, I mean, there's a true genuine race to some degree. I think we're not, real estate's maybe just a little bit different than some of the other AI tools out there. I'm curious to hear from your perspective, what role does AI play in all this? And if and what are you guys doing with consideration to AI and how it may advance your vision as to how...

localized data and overall real estate data can impact and drive decisions.

Vincent (30:21.662)
I mean, it's going to be a game changer for sure. And our philosophy on this has been like, well, the raw materials of AI is going to be data. And so if we can bring a unique and proprietary data set to market and then leverage AI technologies on top of that, we could build really, really innovative products. And so we've been leveraging, you know, machine learning for years now in the way we're processing our data, combining our data, creating new data sets. Like you said, at the top of the show, we have

Nate Smoyer (30:45.501)
Mm -hmm.

Vincent (30:50.27)
billions of data points, we're looking to streamline and optimize the way that we're ingesting that data, cleaning it, combining it in meaningful ways. On top of that, there's clear product opportunities. So we've been using, we've been doing natural language generation, so CHAT GPT -like applications for years now, where we take our data and then we write text on top of our data to describe neighborhoods, for example.

Nate Smoyer (31:10.717)
Mm -hmm.

Vincent (31:18.11)
And so with new models being available, with more models being available, the quality of that text increases, but fundamentally, and we've proven this recently, we perform better than CHAT GPT because we have better, more unique, more specific data. And so we're very, very focused on keeping that edge, adding to the proprietary nature of a data set.

Nate Smoyer (31:38.173)
Hmm.

Vincent (31:47.006)
adding in terms of scope of the types of data that we capture and then saying, well, let's use all this, you know, this new technology to productize that data into something that's usable. That's like a front end almost to our backend. And I think that's going to be a game changer in real estate. And it's going to be a game changer on the residential side and the commercial side as well.

Nate Smoyer (31:52.061)
Mm -hmm.

Nate Smoyer (32:11.229)
Yeah, I saw a hilarious Twitter thread the other day that was basically making the case that consumer facing AI tools. Here we thought we were all going to get smarter, but because people have been interacting with them too much, the tools themselves are getting dumber. I mean, I had to laugh at that. I don't know if it's true. I'm not truly a scientist on that, but it does make kind of sense. You're talking about all this training. I'm like, well,

Vincent (32:28.19)
Yeah, yeah.

Nate Smoyer (32:39.037)
I guess it's not changing the data it has, but the constant query of it, if that adjusts how it looks at or evaluates, you know, I don't really know the intricacies of some of these models. Sure, I can make that logical leap that maybe the tools are getting dumber and that's going to be an ongoing problem.

Vincent (32:41.918)
Yeah.

Vincent (32:55.294)
Yeah. But I think it's, it's also, so it's the quality of the data in, and also how creative can we be in generating new data sets to feed these models? That's, I think one area that we're not talking enough about. And I think there's a lot of things to do there. And then the other piece is like, I do still believe that there's going to be a human element to real estate transactions for a long time, because.

Nate Smoyer (33:06.877)
Mm -hmm.

Vincent (33:24.254)
It's an emotional component. Like if you're buying a home, it's where your kids are going to grow up. It's where your family's going to live. There's kind of that, there's that element of it. And I think it's going to be hard to remove that or replicate that with AI tools. So I do think it's going to be human augment, like we're going to augment our ability to transact or be smarter about it or the financial element or.

matching element but fundamentally there's going to be this je ne sais quoi, this element that's going to stay for a long time. But that being said I think it has a huge thing, it's going to continue to be a huge thing and there's going to be so much cool innovation coming up soon.

Nate Smoyer (34:09.309)
Yeah.

Nate Smoyer (34:13.181)
Yeah, I tend to agree. Well, Vince, we're going to jump to the last segment of the show, which I like to call For the Future. Oh, we got to do this. How do I say that? It's Katra. Oh no, what would be, what would be like, what would be future? Yeah.

Vincent (34:27.166)
for the future.

Nate Smoyer (34:30.621)
Futur de catra? Is that how you say it? De cat? Futur de cat? Futur de cat? I don't know, man. I'm trying to say it in French. I was doing my best. For the future, it's when I get to ask each guest who comes on the show to give their best prediction based on the following four questions. It sounds like you're ready to play. Let's do this. Question number one, what does local logic look like one year from now?

Vincent (34:34.718)
Des quatre? The future? What does that mean? Des quatre? Say it in English, because I have no idea what you're saying in French.

Vincent (35:01.854)
I think we're going to be on more websites, more partners. I think hopefully we're going to bring more innovation in more elements of the transaction and more elements of the search process. Bring that insight, the deeper insight, that deeper understanding of location, why it matters at those different elements.

Nate Smoyer (35:20.829)
Number two, what's a data set that has yet to be developed to help inform local real estate decisions?

Vincent (35:28.734)
That's a good one.

Vincent (35:33.662)
I'd love to see like a mass personalization match. So like an algorithm where, or a data set that allows me to understand, okay, for me, what are the best areas? What are the locations that I should look at? Essentially like a, maybe this is a twist on your question, but like a match in the sea of Nate in this city. Like what's the perfect fit for Nate?

Nate Smoyer (36:02.525)
Well, one, it's not in the city. It's very far. I learned that one. All right. Number three here on For the Future. What's one industry trend you think will continue, but you wish would go away?

Vincent (36:04.574)
Okay, fair enough.

Vincent (36:22.494)
Mm. Ah.

Vincent (36:29.886)
Well, I think there's some of this, and we talked about it earlier, but more data for the sake of data, I think that's not the right move. I think we want less data, but higher quality, more kind of interpreted data sets to help consumers make decisions, more actionable data.

Nate Smoyer (36:52.381)
Yeah. All right. And the final on for the future, what's one thing you believe will dramatically change or fade away in real estate as a result of tech advances?

Vincent (37:04.542)
I have a hope. Does that count? I have a dream. Look, like I said at the beginning, we're a bunch of urban planners and working in real estate. And the reason we're working in real estate is because like it or not, it's not governments that are building our cities. It's this industry that are building your cities. It's consumers decisions as to where they live that impact the sustainability of the cities, the vibrancy of our cities. And so,

Nate Smoyer (37:07.741)
Hey, the hope is there.

Vincent (37:33.15)
The hope I have is that we as consumers, we as an industry, investors investing in assets, have a greater understanding of the implications of their decisions on cities themselves. Where you build, what you build in certain locations has huge impacts on the future of our cities. Where you choose to live as a consumer with regard to where your kids go to school, where you work, has huge implications on transit patterns and emissions.

Nate Smoyer (37:46.525)
Hmm.

Nate Smoyer (38:02.781)
Mm -hmm.

Vincent (38:02.91)
And I think if we can build tools to properly explain and make it obvious the impacts of those decisions, I think we'll build better cities. And the decisions we take today, so what to build where, where to live, will have impacts for the next hundred years. And so we need to realize the influence we have as an industry on the future of our cities, of the built world, of the environment. And that's...

a big responsibility, but it's a huge opportunity to do things better, differently, and make money doing it, right? And I think we could do all those things together.

Nate Smoyer (38:41.469)
Vince has been awesome. Thanks for coming on the show, sharing how you guys have been building this. I love the, we're city planners who work in real estate, really putting you guys at the foundation, if you will, for how real estate data is leveraged and used to drive and inform decisions, both on a national and local level. Before we close out, for those who want to get in touch with you and or learn more about local logic, where do they go and how do they do that?

Vincent (38:50.014)
I'm going to go ahead and close the video.

Vincent (39:07.934)
They can hit me up on LinkedIn. If not, happy to share my email, vincent .locologic .co. Shoot me an email. Yeah.

Nate Smoyer (39:15.837)
Perfect. Well, please keep all the smoke and wildfires to yourselves this year. I do appreciate that. Or don't have any. I think you can eat a year off. But it has been great. Hopefully we'll have a chance to meet in person. I don't think we've had a chance to do that. I've met much of your team though. And yeah, until then we'll catch you later.

Vincent (39:20.99)
We'll try it, we'll try it. Yeah.

Vincent (39:36.542)
That'd be great. Thanks, Nate.

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