Data-Driven Decision-Making in Real Estate with Jason Lewris, Co-founder at Parcl Labs

Nate Smoyer (00:01.016)
Jason, welcome to the show.

Jason (00:03.824)
Thanks for having me, Nate. Great to be here.

Nate Smoyer (00:06.04)
Twitter delivers, you know, I have been on a mission to get founders onto Twitter. And it's been a long time I've been on this and I have noticed over and over a little bit as time has gone by, more and more founders are finding that it actually can be a beneficial place to be. And that's where we connected. And now here we are doing the show. So I think this is good proof of the pudding for founders out there. You wanna come on the show, get on Twitter. I think that's how it goes.

Jason (00:34.992)
Yeah, it's been a good platform and we don't spend any money on marketing. And so we lead with our content and it's been good to see the dialogue and organically building the following and the platform's grown on me. I wasn't very active in this before doing what I do now.

Nate Smoyer (00:52.696)
We're going to have to come back to that because I have, that how you're not spending money on marketing and you're using your content. And I have some very distinct perspectives on that. And I think that that would be a good discussion. But before we get to that, introduction here is proper. I've got Jason Lewis. He's co -founder of a company called parcel labs. Parcel labs is working to make housing data real time, transparent and accessible. And for everyone thinking.

Okay, Nate, we've heard of data tools. There's all kinds of them out there. A lot of them say the same thing. I've heard something similar to that, of course. But I want to tell you, listen in here, because I think we're going to get into some unique characteristics of what Parcel is building, what they're doing. Of course, the story of real estate data is never really, it's always incomplete, if you will, right? No one really has.

all the data and I think that's one of the challenges here. So before we get into the technical side, let's start high level. Jason, what in the heck is going on in residential real estate these days that I should know about or other founders should know about, especially if it's going to impact their transactionally based business.

Jason (02:12.738)
Yeah, great question. Coincidentally, we released a report a few days ago where we had taken a top -down approach to trying to understand markets in distress across the US housing market. So we started with all metropolitan and micro areas across the country. That's about a thousand markets. And we were specifically looking for three criteria. Supply and demand divergence.

year over year so you can control for seasonal factors, but then also trending so it's not spikiness for one, you know, one off months. And then so it's one thing if you have divergence within supply and demand, if nobody's motivated to actually sell. And then so the second criteria was looking for markets of signals with motivated sellers.

Nate Smoyer (02:56.984)
Mm -hmm.

Jason (03:06.48)
And in this case, we were looking for markets where at least 35 % of the on -market activity were experiencing price cuts. So now we have two sets of criteria, wide SKUs in supply and demand. And what I mean wide, it's plus 50 % on supply, negative 30 % on demand. And now you have an inventory where there is active price cuts from the sellers. And then the last set of criteria,

was outsized price appreciation since the beginning of the pandemic, but they have not given back those prices. So they're still trading at or close to all -time highs. So we start with a thousand markets, we landed on 15. 13 of those 15 are in Florida. And so this covers Tampa, Miami, Lakeland, many, many areas on the coast of Florida.

Nate Smoyer (03:41.144)
Mm -hmm.

Nate Smoyer (03:55.064)
Oof.

Jason (04:06.096)
And then there was two other markets, Daphne, Alabama and Myrtle Beach, South Carolina. I believe Florida has some idiosyncratic factors associated with the shocks on home insurance and fallout from the Surfside condo collapse that's starting to materialize in dollars felt from condo owners.

Daphne in Alabama and Myrtle Beach are likely the story of overzealous home builders. Both of these markets were in census's report. So I'm building up to that. And so what happened was in the 2022 to 2023 census report on fastest growing metro areas, both of these markets were in the top 10.

Nate Smoyer (04:43.992)
You mean they're building too much.

Nate Smoyer (04:49.368)
Okay.

Jason (05:00.4)
And so if you look at where is the supply coming from onto the market today, you know, one in five of those units are coming from new construction. So my thesis is, you know, folks looked at the lagged reports from census, and then they saw how the market was doing because if you remember one of the criteria was it had to have outsized price performance, relatively, since the beginning of the pandemic, it looked like a hot market felt safe with population growth reported by lag data from census. And so they built.

Nate Smoyer (05:06.008)
Mm -hmm.

Nate Smoyer (05:24.472)
Mm -hmm.

Jason (05:30.192)
And now that is coming onto the market at the same time demand is getting crushed, double digit percentages. So I think it's two different stories.

Nate Smoyer (05:39.992)
Gotcha. Yeah. So you have multiple moving pieces here, which, you know, sometimes I like to think that real estate truly is just a, it's a supply and demand issue. But what you're highlighting here is there's also, that can be exacerbated by delay in data or delay in what you don't know, which is part of the risk. It is part of the risk of being a developer. Like it's extremely risky to try and, especially building into like trying to time the market. It seems like,

be challenging. What were some of the other things that you pulled out of that report that you guys put together?

Jason (06:17.744)
These 15 markets, that was the scope of this particular report is we were trying to take a top -down approach to understanding where there were signs of distress within the housing market. With that being said, some of our most popular research to date and why folks use our data is to your point, often housing data is too high level and it's too lagged. And so we have broken apart

housing data into the institutional portfolios. We know what American Homes for Rent is doing, the specific trades, how much they're renting their units for, which ones are in the listing market, who are they trading with. And so you take that bottom up, if you will. And so we see the housing market with respect to the institutional portfolios, with respect to the mom and pop operators, and we know how they're behaving.

Nate Smoyer (07:05.784)
Mm -hmm.

Jason (07:14.832)
with on the rental market, on the listing market and how much they're paying for these units and then what are their buy box criteria. So this gives us a pretty acute picture into where things, where there's shakiness in the US housing market because these actors respond to different things. And so if you start to see cracks in one of these channels, that can be indicative of things to come.

Nate Smoyer (07:28.024)
Gotcha.

Nate Smoyer (07:44.024)
Got it. Now I'm curious. I certainly follow a handful of different people on Twitter for data like this. And I maintain a Twitter list. I'm gonna shout out my own Twitter list for the moment. I've got, I think a pretty good Twitter list of real estate data folks. So if you just wanna follow real estate data on Twitter, ping me afterwards, shoot me a tweet at natesmoyer and I'll get you my list so you can refine your feed and...

There's no politics, almost no politics, I should say, in the feed. Maybe all of us need that for the next six months. But I'm curious, who's buying, who's selling, where is the activity that's happening right now? Of course, you have access to a lot of data and tooling to make that possible. Where are you seeing it as like the hot and cold markets outside of the report you just conducted?

Jason (08:41.296)
be honest, I haven't looked at that. We're very focused on data and we'll do about a report a week. So I don't have anything to say offhand. The last time I took a very close look at the institutional portfolios, Vinebrook was causing chaos in specific markets and they were flooding supply. They were counting for about one in three homes coming onto the market at that time. This was in December, November, December.

Nate Smoyer (09:08.824)
Mm -hmm.

Jason (09:10.672)
On the buy side, from what I recall, 2023, from what I remember was fairly active for what I would consider sophisticated operators. And they have pretty strong data teams, they have their own algorithms, and they were moving into tier two markets, if you will, Columbus, Ohio, not your standard SFR markets like Atlanta, Tampa.

Nate Smoyer (09:38.104)
Mmm.

Jason (09:39.056)
And so we were seeing more activity in these, I guess, untapped markets, if you will. I don't know if that's a good way to describe it because there are, yeah, tertiary markets. That's a better way to put it. So that's where we saw a lot of activity in 2023. So substantial declines in the buying activity for like the tier one SFR markets and more activity in these tertiary markets.

Nate Smoyer (09:46.424)
secondary tertiary.

Yeah.

Nate Smoyer (10:06.968)
I mean, it makes sense, right? If the cost of money has gone up, housing costs have also gone up, which I think most of our economics classes would tell us that doesn't normally happen, but we're in this unique environment with restricted inventory, pushing that. Yeah, tertiary markets represent, hey, maybe there's more capacity for overtime improvement there than there is in a tier one, which may be at the peak. And I think there's some...

There's some data that maybe suggests that could be a storyline there, right? Austin, Phoenix, you know, being some of the leaders and some of those like declines and their prices and I say declines, but like relative to their peak. If we look at overall, like a 10 year hold, they're still up dramatically, but not necessarily from the, from their peak. I do want to get into a little bit about Parcel the Tool.

Of course, you're focused on building and providing this, but it gives you a unique access and view into many different reports. And that's actually what inspired this is you guys were publishing a lot of that stuff on Twitter, which I greatly appreciate. One of the things about real estate data that may be challenging is the fact that there's no real one source. So like for instance, like inventory, I see a myriad of different inventory reports that go out.

And they're not necessarily all like perfectly matching to each other. Can you, can you explain to like why this is such a difficult challenge just to even get an accurate across the board agreement of like, where's inventory at or days on market and such like reports like that, that seemed like they should be relatively uniform, but there's variances from, you know, one reporting source from another reporting source.

Jason (12:00.272)
Yeah, great question. Prior to us in Parcel Labs, most housing data came from a handful of sources. And so they would have vendors that built thin layers on top of the same sources. And these would be county records or MLS aggregators, if you will. But nobody had fundamentally changed housing data. It was just a different

UI layer on top of the same lagged, incomplete housing information. And so the first clue into this was to your point, discrepancies in counts, simple counts, new inventory, total inventory. If you look at Realtor, if you look at Zillow, if you look at the government, which is mostly using NAR data, these counts can be off by 20.

40 % and that's market by market dependent. Zillow will have more, Realtor will have more. And so there's no consistency depending on the market. And that's largely due to business relationships. And so it was obvious that no one knew the actual truth with respect to what was happening in the housing market. And so the thesis at the time was folks have their own inventory and then their shared inventory across these sources.

And unless you can disambiguate the unique inventory per source from the shared inventory, you're not going to get a clear picture with respect to what's happening on the housing market. So we weren't able to prove this out until we actually built the technology to do this. Fast forward to today, we consumed from over 5 ,000 sources of information. And I believe the fragmentation in the housing data space is only going to get worse.

Nate Smoyer (13:27.48)
Right.

Jason (13:50.288)
and Sue, there's a need to understand what's actually happening across housing as a byproduct of this, based on how advanced we had gotten in our indexing system. We were then able to integrate completely disparate sources of information. Rental data lived in a totally different silo from the home sales and the listing information. And so then we were able to create a clean history of a home.

to understand the owner, the listing activity, and then the rental activity. So then you can see for any home in the country, you know, it was owner occupied in 2000. Then it was sold to an investor who then put it on the rental market. This is what they did on the rental market. They changed prices 15 times and then it was on the market for 45 days. And then they owned it as a rental for three years. And then they sold it to another owner occupied unit.

Nate Smoyer (14:24.504)
Mm -hmm.

Nate Smoyer (14:42.872)
Peace.

Jason (14:49.104)
And so that's the level of detail that our data is at. And then we roll up information for easier understanding and reports. But that's how we look at the housing market.

Nate Smoyer (14:57.912)
Mm -hmm.

Nate Smoyer (15:03.448)
Got it, yeah. 15 rental price changes in 45 days, man. That's a whole lot of tests.

Jason (15:12.048)
That's nothing. So there's a huge discrepancy between sophisticated teams in the SFR space, institutional sophisticated teams, and then the laggards. So the sophisticated teams, they're updating prices every two days, and they update prices for about 100 % of their units. And it was fine. You see...

Nate Smoyer (15:32.824)
Really? And that's not just multi -family, like single -family Reynolds 2?

Jason (15:38.192)
single family rentals. And so you see this, we have a report, we have, you know, every top 25 SFR operators across the country, and then we're analyzing the frequency of their rental updates, and then if they're up or down. And so there's about three operators that if you sort on that list that are right up at the top. And then it starts to fray down to the point where some operators are doing this on the back of a napkin.

And so that was fine when the housing market was ripping and everything was up and to the right. That there's going to be consolidation within the institutional SFR space. We're already seeing that Blackstone just acquired another portfolio via Tricon. And there will be more consolidation. There are sophisticated teams that know what they're doing and they will get these homes on pennies on the dollar on the operators that are not able to keep up.

Nate Smoyer (16:36.952)
I'll be honest with you. I feel like I stay pretty attuned to things, but I had no idea that people were adjusting prices like that. That sounds like A -B testing, but what you do for like e -commerce platforms, not for rental prices. Okay, so maybe that's a pretty good time for us to kind of transition because you guys, you just released a new product feature focusing on.

rental data, can you go into that a little bit more? Because I think, and this is something I'm very aware of, that there is a lot of inaccuracies reported when it comes to rental data. Usually the headlines are all based off of what Zillow would report out, but Zillow, you know, historically has only reported out like multifamily data that they were getting. You don't get the mom and pop slice, which is a nine out of 10, eight out of 10.

single family rentals is mom and pop. So maybe you can talk a little bit more about the rental data product and the problems you're trying to solve for with making rental data a little bit more readily accessible.

Jason (17:44.272)
Yeah, great question. So there's two metrics or endpoints that we brought to the API within the last couple of weeks. One is a daily pricing apparatus for the rental market. And so every day we publish what the price per rental square foot is for any given market. And then the second set is

on being able to break out different cohorts of actors within the rental market to understand how the mom and pops are pricing things relative to the institutional operators, relative to the midsize regional operators, if you will, and then comp that to the overall rental market. And then what we will be releasing shortly is the units as well. So then you will be able to identify

all of the on market units in your area, on market for rental and then observe what they're doing with respect to price changes at the unit level. So you know if your neighbor is on market as well, if you're not, you know, because if you follow just Zillow, they don't have all the rentals. And neither does, you know, nobody has all the rentals and now it's becoming more popular. go ahead.

Nate Smoyer (19:02.68)
Correct.

It's gotten, it's the walls went up. The walls, you know, you're right. It used to be a lot more shared. You could syndicate to everyone. Everyone took the inventory and this trend started early 2019, where the walls started creeping up and, and what Zillow was doing, actually, they were implementing this state by state. so they were saying, you know, state by state, they were cutting partners off and saying, Hey, you have to, cause I was at a veil at the time.

You know, so we were trying to, we had our syndication tool to syndicate listings out to all the major ILSs. And what Zillow said was, well, you can syndicate to 47 states now, but these three, you have to have a contract in place. And they did not make it easy. Like we had to actually get our customer on the phone with Zillow, sign a contract with Zillow, then come back to us.

And the contract stated basically that avail was allowed to publish a listing on their behalf. So long as the customer had paid, it was willing to pay Zillow. It was, it was not a fun experience, of course. And there's a lot of friction. Yeah. And then, and then apartments .com, they stopped accepting syndications of, of single family rentals or no, it was, it was an apartment. It might've been apartments. They stopped all syndication of apartments because they wanted all apartment inventory to flow through them.

Jason (20:13.104)
That's a lot of friction to get a listing.

Nate Smoyer (20:31.896)
And so what you see is here is like, you start seeing like, like vast differences in between. And actually, Facebook, maybe a year, a year and a half ago, they had a limited range of rental syndication partners for Facebook marketplace. That was this kind of like secret path on how to get into that product. And then they just suddenly shut it off. So both.

Like there was property managers and individuals could no longer syndicate. And the only way to publish rentals is one by one to go to Facebook directly. So you're right. I mean, there's just such a significant amount of siloing happening in the rental space.

Jason (21:13.264)
And that makes the housing market less transparent. I mean, rentals is, you know, it's the same problem within, you know, the listing and for sale market too. I do think rentals is more fragmented, but which doesn't allow for a transparent picture into what's actually happening with respect to either the rental or for sale market.

Nate Smoyer (21:16.44)
Mm.

Nate Smoyer (21:35.384)
Yeah, it's a challenge. I don't understand how it gets fixed, but obviously someone who's ingesting as many sources as you guys probably are far better prepared than I am, which is why you're doing it. Let's jump into a little bit of a different area because this is something that you and I talked about, pre -show a little bit as well, but on the transactional side.

for residential real estate, the advanced analytics, real time pricing. I wanna get into that a little bit, because I think this is still, you kinda talked about it in the rental space of like changing prices. Let's talk about on the residential side. A lot of debate happening in the housing market. So what are you guys doing with regards to surfacing that data? How's that being used? And I'm curious, what capabilities do you have that is unique?

to the market these days, especially when presenting residential real estate data, because that's on the surface, it all sounds the same, but I know that not to be true. So I'd love to hear from you what makes what you guys are doing at Parcel very unique or new to the market.

Jason (22:49.072)
Yeah, great question. So I'll start from the data, but I will build up through the whole experience with respect to the prior state for even acquiring housing data and then the developer experience. So as I said earlier, nobody has all the information for the on -market activity.

Nate Smoyer (23:12.792)
Mm.

Jason (23:15.856)
And so that was a multi -source ingestion problem and we cleaned that up for users. Then the second problem is the county records. The county records are still important because they have the owner information and then you can use the owner information to disambiguate via very complex algorithms as folks are pretty sophisticated at hiding their transactions.

to roll it up to American Homes for Rent, for instance, or Vinebrook. And so we connect the county records, we roll up these portfolios with the on -market real -time activity. So then that creates one clean lineage across portfolios, whether it's, let's just take it at the highest level. I want to see mom and pop

Nate Smoyer (24:06.456)
Mm -hmm.

Jason (24:08.656)
activity relative to institutional activity across the US right now. So then you can see demand and supply divergences, you can see where that's occurring by market. And then you can look at the actual units themselves to understand who you're competing with. Are you competing against AMH? Or are you competing against another mom and pop in the neighborhood that you're in? And then this also allows you to understand, you know, what's the rental product? And then what's the levels of sophistication?

of the operators for those rental products, things along those lines. So we clean up housing data, we ingest from as many sources and continue to expand those sources as we possibly can to create one clean signal to US housing. So that improves the underlying data. Problem number two is how cryptic and ridiculous the sales cycles were for getting exposure to

Nate Smoyer (24:49.912)
Mm -hmm.

Jason (25:04.784)
housing data prior to parcel labs. One, it was either ridiculously expensive and were measured in thousands of dollars for simple reports or simple data polls, etc. And then two, there was an obscene amount of friction because we went through this at the beginning to even seeing data. Your option was to hop on the damn PowerPoints with salespeople.

Nate Smoyer (25:22.808)
Mm -hmm.

Jason (25:30.64)
And you haven't seen a piece of sample data yet. So you're on these sales calls, you got three or four sales calls, you're sharing all your information, everything about you. And then you finally see a sample file for whatever it is 1530 days. And so that process sucked. And so you can self sign up right now anybody in the world for free and start pulling our data right away. And then on the price point, we are

Nate Smoyer (25:48.184)
Mm -hmm.

Nate Smoyer (25:59.672)
And that's unique, by the way. I don't want to cut you off, but I'm going to stop on that for a minute. You're not wrong. The high -end or exhaustive data sources tend to be this long drawn out sales process where you see static images or you see hypothetical or you see an on -screen demo, but you don't actually get a chance to work with it. And if this is critical to operations, there's high implementation costs or risks oftentimes to your business.

Jason (26:00.368)
are.

Nate Smoyer (26:27.544)
to shut down one thing, switch to another. So the ability to self -serve and sandbox right from the get -go is, I think, is not a trivial thing. It's pretty significant.

Jason (26:41.68)
the people hours to go through these calls. I mean, it's absurd. And so to your point, I mean, we lead with our product. We, you know, it speaks for itself. And especially if you're competent to anything else out there into that. And then the other thing is the entry pricing. So it's $99 a month cancel anytime we don't make you commit. And then there was no

community for folks to share research into my prior life was at Microsoft and tech in general is very good about open source and creating a good developer experience and allowing folks to build on other people's ideas. And so we open source all of our research, we give you the code on how to do it. And then that accelerates implementation time for a team.

Nate Smoyer (27:14.52)
Mm -hmm.

Jason (27:40.432)
or for an individual who's interested in understanding housing in a different way. And we're very motivated right now on the developer experience. As a matter of fact, the only thing I look at is how long it takes somebody to sign up on our platform and start using data in a meaningful way. And until that is as good as we can possibly make it, there's nothing else to really worry about.

Nate Smoyer (28:07.192)
Yeah, very cool. Yeah. And, you know, you, you talked about being product led earlier on when we kicked off the show, we talked a bit about, you know, you're not spending money on marketing, really using your data as content, which is a concept I've written about. and for, for those listening, not on the newsletter, I'm going to go ahead and take this moment to plug my own newsletter, go to, go to tech nest .io, get on the newsletter. I deliver.

I think are high value articles on a semi weekly basis only when articles are good enough. And one of them I've written is the con on the concept of data as content. I've used this. It's successful. I've seen it be successful. It's actually why, I mean, it's why you guys are on my radar. I was looking for data. I was looking for, you know, interesting content that scratches the itch of solving challenges or curiosities I have. And so I'd love to hear your take on like how your

using the data you have in -house to create content that is hopefully driving awareness and engagement for ideal customers for you guys.

Jason (29:18.384)
Yeah, I'm very convicted on this. So to start, we know we are able to understand the housing market in a way nobody else can. And that was very effective while we were building out the API to start dropping insights that people have never seen before. And then that allowed us to build a community. And then during that time, we were making

the access to that data as frictionless as possible. And so as a result, we can now do reports and understand and research the housing market in an afternoon that surpasses the quality of some of the largest analytics institutions in the world. And so in how do we know this? Well, the Wall Street Journal uses us.

land slam bird, who I think is very forward looking. he, he, he's very, he's, he's very forward looking with respect to housing data and understanding, how things need to change. and he, is, an avid user of ours. and, CNBC and to it for folks that know housing and they know when they see something different. and that became, it was very, straightforward for us to,

Nate Smoyer (30:18.328)
yeah, Rezzy Club.

Jason (30:45.2)
to get syndicated out like that. And so now for us, it's based on how we've created this developer experience. We're our first and best user of the API itself. And we publish all of these notebooks, these Python notebooks that we do our own content off of. So it acts as a flywheel for how do you do this stuff while we're producing content. And the only platforms that we publish to right now are LinkedIn and X.

Nate Smoyer (31:08.408)
Mmm.

Jason (31:14.384)
And I'd say, you know, LinkedIn's pretty good. The algorithm on LinkedIn is dialed in.

Nate Smoyer (31:23.384)
You're gonna have to say that a little bit louder for our whole Twitter audience, because the trash talk on LinkedIn from the Twitter audience is pretty significant.

Jason (31:34.64)
I like those, I love Twitter.

Nate Smoyer (31:36.568)
same. I like them both. I don't understand the, you know, the riff, but there is definitely some, man, there was some, there's some targeted feelings against LinkedIn.

Jason (31:50.64)
It's a different vibe. It's a very different vibe. And so I enjoy both platforms. They service different things and we'll probably stay with those. And like I said, when we don't pay, we just publish our own content and then poke some people if we think they're going to find it interesting. And other than that, we just keep our heads down and keep building the product.

Nate Smoyer (31:54.392)
Yes. Yes.

Nate Smoyer (32:17.208)
Yeah, I think that's super cool. And especially because you, when we talk about here, you're using data as content for marketing and you didn't necessarily just like purely say, well, content equals long form blog posts and report. You talked about like the distributing through social media and that's still being effective. And I know this is something that brands have had a tough time with and early startups have had a tough time with of like, how do I get social to actually drive attention or awareness or engagement? And in this case, you know, it's not.

let's do a big banners or like super goofy graphics and skits. You know, we just delivering utility in and in a world where there's infinite scroll, you know, this is a reason to stop for a second because there's, Hey, this is interesting. I didn't know I wanted to know about this thing. and now that I know I want to know more about whatever they know. I think there's just a kind of a natural train of curiosity that goes there. So I think it's super cool. And I, I appreciate seeing that. It makes my feet a little bit better.

Jason, we're gonna jump to, wait, you had one more thing. I don't wanna stop you there and then we're gonna jump down to the bottom of the show.

Jason (33:20.368)
just confirming and create value. And then we don't get caught up in the noise, you know, the signal in the noise. There's a lot of do -mers and there's a lot of optimists. We speak to the data. And then the other thing I'd say is developers are starting to use the API to generate content as well. And to just yesterday, an API user

Nate Smoyer (33:35.032)
Mm -hmm.

Jason (33:49.584)
had used a generative AI and built a fully functional web application off of our API nationwide coverage in 15 minutes. And so these are the things that are, we were very conscious of how we designed our API to allow this type of scale for folks. But then seeing folks come to that realization on their own in the developer community is awesome.

Nate Smoyer (34:05.432)
Wow.

Jason (34:18.672)
Because then if you think about the cost and the time to market, you can spend that time on the experience. The data is taken care of and worry about scale, worry about that positioning of the data that you're really calibrating that experience around. Whether it's the mom and pop rental operator, whether it's the home buyer, whether it's the institutional portfolio, advanced analytics. To us, we just focus on data. We want to empower developers to really home in.

What is that killer experience for various actors within the housing?

Nate Smoyer (34:53.976)
Yeah, super cool. Jason, now we're gonna jump down to the bottom of the show. My favorite segment, I like to call for the future. For the future, we like to ask each guest to give their best predictions based on the following four questions. There is definitely a curve ball in here. Are you ready?

Hey, let's do it. All right, number one, what does Parcel Labs look like one year from now?

Jason (35:23.024)
an active open source developer community. We're hosting hackathons and we are, folks are building not on top of just our work, but on other people's work who have contributed to the overall ecosystem.

Nate Smoyer (35:44.216)
Awesome. All right, here's the curve ball. I promised you a curve ball and we didn't even talk about this in the pre -show. That's how much of a curve ball this is, but I'm curious your take on this. Are we likely to see legislation restricting portfolio or bulk purchases of homes by institutional investors within the next three to five years?

Jason (36:08.048)
Am I allowed to talk a little bit about this? We've done extensive research on this topic.

Nate Smoyer (36:13.24)
I mean, you tell me if you're not allowed to talk about it.

Jason (36:15.664)
Okay. Okay. All right. So I'm going to take you through the journey. So I think the positioning of it right now is off of bad data and misinformation. This is not a national problem. This is very market specific. And Sue, nationally, we're talking about these institutional portfolios owning maybe 20 basis points of all single family home housing stock.

But if you look within their top six markets and they are highly concentrated in just six markets, as a matter of fact, one third of the entire national portfolio of institutions is in six markets. That's Atlanta, that's Dallas, that's Phoenix, that's Houston, that's Tampa, and that's Charlotte. And then within those markets, they're not distributed across the whole market. They're in the same zip code. That's where the problem is.

Nate Smoyer (37:09.432)
Mmm.

Jason (37:09.616)
So if you look at these markets and you look at where they own this inventory in Atlanta, there's this you around Atlanta downtown. And that's where they own one in 10 homes. And that's where they're having an impact. And so trying to legislate this at a national level is just totally misses the point. This is a state or a city issue. And so I do think there's going to be a lot of

be things that go through, but because of how popular this narrative is. But that popular narrative was popularized by a misinterpretation of the data. And then I also think teams are pretty sophisticated. So they'll just figure out how to thread the needle, regardless of what legislation is passed, whether that be through some creative LLC construction or otherwise.

the, it won't, it won't really hit home on, on what the intent is. And the original intent is coming off of bad information.

Nate Smoyer (38:09.752)
Right.

Nate Smoyer (38:13.464)
Yeah, I'm not gonna take us down a rabbit hole on political opinions here. I appreciate you speaking to the data, because I have my own points of view on this, of course. But it's similar to the rental data frustration that I've experienced in the past of trying to get mom -pop data to be talked about and considered, and not just have restrictions and rules based around multifamily data, because there are real...

unintended consequences here to much smaller teams and much smaller operations if you do stuff like that. And I think that that's also itself not really solving the problem that's supposedly intending to solve for. So number three here on for the future, what's one industry trend you think will continue, but you wish would go away?

Jason (39:09.552)
That's a good, that's a very good question.

Jason (39:20.368)
I don't know if I, I don't really have a stake in this, but for sure in industry trend that will continue is consolidation of portfolios with more sophisticated data operators that know how to run this like a fund. so I don't really have a take on whether that's good or bad. I think it's going from a data maturity perspective, it's, it's probably good for us because these folks understand how to use, advanced data.

But then conversely, if we can help create this community and jumpstart teams to really integrate data and consider it a first -class citizen as part of their operation, then that allows us, you know, the playing field is a bit more leveled or a lot more leveled. And so I'm rooting for folks to build on an open source community and, you know,

jumpstart their data operations and catch it up to modern times.

Nate Smoyer (40:27.928)
All right, last one here. What's one thing you believe will dramatically change or fade away in real estate as a result of tech advances?

Jason (40:43.76)
folks that don't know how to use data as an integral part of their operation. I mean, I really, I just, I don't think the housing market is going to be ripping like it's been over the last 15 years. And then that really put, that acts as a force. If it's trading sideways, then all of a sudden was the next thing you're looking at. It's the portfolio and how is the portfolio managed? And, and so the, the people that understand how to use data to get alpha.

Nate Smoyer (40:54.68)
Hmm.

Jason (41:13.04)
when there's less sophisticated operators in the market will win. And they will win big time over the next few years into

I just think that's how it's going to shake out.

Nate Smoyer (41:28.216)
Yeah, Jason, this has been awesome. Thank you for coming on the show. Thank you for setting aside time to talk about real estate data, what you guys are doing to make it more transparent, accessible, and even really taking it to the modern age where it's as close to real time as possible versus looking at stuff that's lagged and behind current times. Before we close out,

For those who want to get in touch with you and for those who want to learn more about Parcel, where do they go? How do they do that?

Jason (42:01.616)
Yeah. So on X, Parcel Labs, and then Jason Louris, and then sign up for our API at parcellabs .com. It's a full self -service experience. We have a good onboarding flow to getting you to using data right away. And then we have a community to ask questions and use our code and all of that's via the parcellabs .com website.

So if you want to get in touch with me, just ping me on X. Otherwise, visit our site and use the data. That's the best way to understand what we do.

Nate Smoyer (42:39.416)
Awesome. Well, hopefully I'll get a chance to see you around. Till then, catch you later.

Jason (42:44.176)
Thanks, Nate.

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