Are you thinking about buying a home for the first time? Record numbers of people began their search for a new property online in 2021, but sorting through the thousands of new listings that go up daily can be a huge challenge. Traditionally, real estate has been a heavily human-intensive industry. You need agents to track down properties and set up tours, and inspectors to dive deep and dig up all the hidden info about a property. But going into 2022 and the future, is there a better way for homebuyers and their agents?
At the UpTech Report, we were lucky enough to interview Localize President & COO Omer Granot. His company Localize.city provides a comprehensive solution for prospective homebuyers and their agents looking to navigate the complexities of the current housing market.
Localize aims to make homebuying better for everyone and uncovers data that you wouldn’t find easily online. How much natural light does a home get in summer and winter?? Is there a history of bedbugs at the property? These are some of the important questions answered by their Localize.city marketplace that you won’t find on other popular sites like Zillow, Redfin, StreetEasy, or Trulia.
Omer Granot captains Localize teams in the U.S. and Israel. He engages directly with brokerages to showcase how Hunter is revolutionizing real estate by harnessing the power of AI to make homebuying better for everyone. Prior to leading Localize, Omer was VP of growth at Via, a transformative transit tech company.
He also helmed an Israeli submarine as its Executive Officer for eight years. In his down time, Omer likes to swim laps, read books—from entrepreneurship to Harry Potter—and tinker with technology, especially fitness wearables.
TRANSCRIPT
DISCLAIMER: Below is an AI generated transcript. There could be a few typos but it should be at least 90% accurate. Watch video or listen to the podcast for the full experience!
Omer Granot 0:00
I do think though that there are there’s a bunch of core technologies that will that will significantly disrupt the real estate market in multiple ways.
Alexander Ferguson 0:14
Welcome to UpTech Report. This is our Applied Tech series. UpTech Report is sponsored by TeraLeap. Learn how to leverage the power of video at teraleap.io. Today, I’m excited to be joined by my guest, Omer Granot, who’s based in New York and Tel Aviv, going back and forth between the two. He’s the President and COO at Localize. Welcome, Omer, good to have you.
Omer Granot 0:36
Thanks for having me.
Alexander Ferguson 0:37
Now, localize is in the real estate tech space. Here, you are serving both all of Israel as well as New York, helping buyers and sellers, both solving the data problem I think you shared for the for the buyer, being able to understand how do I know what to buy, whereas the things and then agents giving them technology to help them sell more, but also helping them to focus more on what they should be focusing on, which is the the human aspect. So over how many understand what’s what’s the root problem, you actually have two people that you’re serving that the buyers and sellers. So that’s a unique, fun challenge, I’m sure to have two different people. But what’s the problem that you see, and you guys are focused on solving in brief?
Omer Granot 1:19
So, you know, yes, we have two customers, eventually, they both are tied to the same processor flow, the problem we’re trying to solve is that, you know, it’s towards the end of 2021. And despite that, buying a house, buying a home is still a really tough process. And that is fundamentally the problem that we’re trying to solve. And we’re tackling sort of the two sides of it, we’re tackling the problems and challenges that homebuyers face. And then we’re tackling the problem that agents and brokerages face when they tried to provide excellent service to homebuyers.
Alexander Ferguson 1:52
Now, there’s a sister company to localize modeling, which is the one that’s kind of serving all of Israel, is this kind of come out of that initiation? When did modeling start and then localized? Basically, what’s the history? How did it how did this all begin?
Omer Granot 2:08
Yeah, so Milan was founded and launched in Israel in 2012. And Milan focused really mostly on the home buyer side. So we looked at the market, we said, you know, you want to make this decision of buying a house, probably the biggest financial decisions someone makes in their lifetime. And there’s really no data to support the decision. And so when law was founded, we started to build a topology to help you as a homebuyer make the decision, we understand what it is that you’re buying, sort of make sense of the world real estate data. And then in and then we build the business. And now Milan is sort of the brand name in Israel, it’s, you know, if you buy a home in Israel, you go through Milan, I think that has almost 100% of the cases. And then in 2018, we expanded to New York. And the goal was, again to to do sort of the same to help homebuyers buy place in New York in the US. And then between 2018 and where we are now we sort of expanded and broadened our product offering because we realize there are other challenges that are worth solving as we as we scale as we build our cars.
Alexander Ferguson 3:18
Is it realizing as you’re maybe getting the data and selling these homes, the agents need help as well. So what’s going to sit over there? Like? Did you just start to uncover that? How quickly did that start to surface? Was that very quickly, like 2019? Or is it more like 2020 that that the agent side started to appear as a solution?
Omer Granot 3:39
So we really started to double down on the agent side in 2020. The process is that we launched a will launch our marketplace in 2019, actually early 2019. And and we started to set the scale, right. So people homebuyers came to localize the TV, they started to research the properties that they were interested in. Again, worth mentioning, if you go to look at the city, what we give you is really a very deep understanding of every property, we give you hundreds of insights and data points that you can’t find anywhere else, right things like how much natural light does the apartment get? And what’s the view like and what’s future construction? What future construction is planned out? And how will that future construction impact noise in view in natural light? Is there a history of bedbugs? Does the elevator only work twice a week? How close is it to treasure hundreds of insights that you really can’t find anywhere else? So that’s kind of where we started. And we build that and we build attraction with homebuyers. And then honestly, as we started to think about the business model and how we how we make money, we certainly came to the point where like, okay, there are many marketplaces in the US. Some of them are very known and sort of big Zillow, StreetEasy Redfin Trulia and why marketplaces is different. Really, the way we thought about scale was to was to actually take a step back and not compete with all those other marketplaces on building just a bit of marketplace, but really provide a comprehensive solution, right? Not just give you the data, but actually help you go through that process. And as we started to experience that process with buyers, we realized, okay, there’s this entire, you know, support side or sort of enable enabler side that agents and brokerages and actually also need help.
Alexander Ferguson 5:34
Curious just for my own edification of Israel is that same type of situation different like what’s what have you seen as, as the buying and Home Selling experience different between us, New York and Israel,
Omer Granot 5:51
we actually focus much more on the buyer side, the dynamic, the market dynamics are quite different in Israel in the sense that, in the US, when you buy a home, in the vast majority of cases, like the 90 plus percent of the cases, there’s there are two agents involved in the process. There’s a buy side, a genders sell side listing side agent. And in almost every deal you have bought, in Israel, if you look at how people buy homes, there’s almost never a buy side agent. There’s usually a listing side agent. And again, because he’s really is a much smaller market, I think there’s there’s also many other ways to sort of go in and sort of figure out and there’s word of Mother, it’s really, it’s a smaller market. And so the dynamics are quite different, how it is done.
Alexander Ferguson 6:37
Interesting. So bringing that the concept of the data aspect. This is like, if there’s not buyer agents over there, people are having to do it themselves. So making that be able to get those insights faster is is absolutely crucial. And it’s not that people don’t need that or want that over here. But there’s there’s just a different environment as you guys have found, but the buying experience we’re having to agents, you’re saying that that’s what you’re trying to streamline as on from the seller side, that that’s your business models that you help them sell that home faster or more efficiently.
Omer Granot 7:16
So we do two things, observe, just clarify that if you’re a home buyer, you’re looking to buy a place you go to you have two products that we offer to help you manage this process. One is localized on CD or marketplace, you can go to a marketplace, you can research any listing that you’re interested in, you can do advanced searches, you can basically find other listings. And for every listing, you can go very deep on the listing itself in the neighborhood to really understand what it is that you’re evaluating. Right, what is it potentially, in addition, so that’s locis attorney in addition, we launched Hunter Hunter is an AI that you can communicate with that helps you go through this process. So instead of going to Zillow locales or city street, easy Trulia and sort of putting the filters bedrooms, bathroom and neighborhood, you sign up to Hunter over SMS, and you can start to communicate with Hunter like you would with a human agent. And Hunter helps you through that process. So Hunter asks you all the qualifying questions, what’s your budget, what you care about? What’s your timeline? What are your deal breakers, nice to have Are you pulled approve all those questions, and then he takes your profile, and it starts to smart match you with department. So every morning you will get a recommendation you will say, Alex, Hey, Alex, good morning, I found this listings for you this listing for you. We think it’s an excellent match. Because I know maybe you said you have a dog and so it’s close to dog parks or maybe it has a lot of natural light or it’s in a quiet street, whatever you come up. And then you can interact with Hunter you can say I like this apartment but monthly fees are too high. There is no trading around. There’s no words for whatever it is you want. Hunter understands that updates your profile and immediately sends you a better recommendation. So the whole process of searching and finding and sort of nailing down what it is that you want is much easier and much more natural with Hunter and localized. That is all for the buyer side. If you think now about agents and how they work. We focus at this point mostly on buyside agent if you’re a buyer’s agent, you advertise yourself to get leads to get homebuyers to work with you. Right so you advertise on 3d for example. And then when you Alex as a homebuyer click a listing that you like Zillow or three vz sells that lead to a buy side agent. That by side agent could be from Compass, VHS living or any of those other brokerages. So you’re an agent, you get leads from StreetEasy for Zillow, or Google or Facebook or wherever you advertise yourself. And what you get is a nakedly you get your buyers name and email, but that’s kind of it Usually a zip code that they’re looking for, you then need to give them a call and start to ask them all those things you need to profile them, you need to qualify, you need to ask them all those questions, you need to start compiling recommendations lists and sending them emails following up. And the reality is that all that processes currently extremely manual and extremely time consuming, right. So if you want to manage as an agent, you want to manage 20 people, you need to call talk to 20 people every day, you need to send an email you need to do now multiply that and say you’re an agent that has, you know, the has a budget and spends money on acquisition, you have 1000s, there’s no way that you can engage 1000 homebuyers in a meaningful way. And so that’s when we come in, we work we partner with you. And we basically offer a service to you where you give your leads to localize, and then Hunter reaches out to every one of your leads, we quantify, we nurture, we talk to those buyers, we help them get to a point where they’re advanced enough in the process, that they need a human to work with them. And then we match them back to you as an agent, we give you everything we’ve learned, we, you know, we give you the full buyer profile, the communication, everything we learned about the buyer, by the way, we tell the buyer that we’re going to master with an agent. And so it’s all very transparent. And you as an agent can focus on what really matters, which is building trust, you can hit the ground running.
Alexander Ferguson 11:26
Did you have a mentor already when you can develop this business model?
Omer Granot 11:34
Wheat So Hunter and localization user, the two products that help agents and buyers in this process were launched in 2021. Okay, guys, we started with just the marketplace and we build it out as we went.
Alexander Ferguson 11:47
Got it. Got it because I was wondering if you had Are you had built the hunter, and then you’re like, Oh, we can apply it to two sellers. But you would already that in mind to be able to create this this AI agent, a digital agent to assist the the the sellers, right. So the those who are selling homes, correct that that’s that’s how how the who would pay for access to this type of tool to on on their behalf of qualifying the leads this environment? What’s the pushback that you said? Because often like new technology, I love technology, I love talking about every every time but everyone’s like, Oh, unknown, have concerns what’s like the first thing that you have seen that are popping up and had people have concerns about
Omer Granot 12:36
when we talk to agents, agencies, real estate is a really sort of human, human intensive sort of industry, right? Everything is relationships, everything is trust. And so when we describe what we do to agents, I think, I don’t know if it’s pushback, but the it’s always the first questions is like, Okay, how does that actually feel? Right? He found a buyer, like, how does interacting with your bot feels? Like does it feel like a bot? Does it feel like a human can I actually trust you with giving you my most valuable asset, which is, you know, my buyers my leads. And so usually when we start to work, that’s kind of the biggest concern. And, and when we just started, I think our first partners were sort of, okay, I’ll give you the leads that were hard for me to convert, actually don’t think you can do a really good job with them. But you know, give it your best shot. And so we started with with sort of getting these buyers that were maybe a bit older and maybe less engaged. And we had to sort of showcase that our technology actually works. Pretty quickly though we showed them that the the fact that you can talk to 5005 5000 or 50,000 buyers every day, in a way that feels extremely human to the point that many home buyers don’t actually realize initially, and then they don’t care because the experience is so good that they’re not actually talking to humans, they’re talking to a bot the value of being able to do that supersedes everything else. And so those initial concerns were sort of concerns in the first three, four months, three, four, first month with the first customers, we now have the data to back up our claims that you know, if you give us your buyers, we are able to actually help you manage very very large quantities of buyers in a way that gives everyone sort of an excellent express
Alexander Ferguson 14:40
your business model right now is it based solely on the the agents is or is the the marketplace at all is is there any revenue generation there?
Omer Granot 14:54
So we need for most of the revenue generation comes from the marketplace. In the US The marketplace is completely free. We don’t charge anything from the homebuyers. The business model is we charge a subscription fee from the agents if they want to sign up and leverage the technology, and then we charge a success based fee when a deal closes.
Alexander Ferguson 15:15
Hmm, gotcha. For for for you guys of seeing the market, what was the biggest aha? Because obviously, it’s to me, it’s fascinating to understand as you moved from places, the differences in the environment and but the technology is still applicable. It’s but it’s like morphing, is that what it is? What was what was the biggest aha for you guys? You think?
Omer Granot 15:39
I think when we started to work, initially, we just focus on homebuyers. We said we’ll give them the, you know, an excellent experience. And we’ll we’ll give them better tools. I think that aha moment came when we actually started to work with agents. And so two things happen. One is we we realized we could scale extremely quickly, because when you do acquisition on your own, when you have to do marketing and build a brand, a consumer brand, it is much more expensive and much more time consuming to build a big brand. Versus if you go to agents and brokerages and we now work with teams that complex and VHS and live in New York and the biggest brokerages in New York, you can scale super quickly, right? Because you partner with someone who has 20,000 buyers sign up with a service. And immediately you have 20,000 people using your platform. Right so. And then the second thing is when we when we actually showed them that data, right, so they they gave us 5000 buyers, the buyer leads to start with. And then 48 hours later, we already are able to tell them, Hey, by the way, these 1000 people are engaging with our AI, they’re already all there is experiencing a one on one conversation. They’re all moving further, further along in the process. And the agents were like, Oh, wow, this isn’t chrome like that these numbers are unbelievable. And they immediately say okay, how do we give you more of our lead? How do we give you more of our business.
Alexander Ferguson 17:07
So you guys have focused on the large brokerages and because you are only in New York at the moment in the US. And so you focused on the large brokerages that you can just quickly scale up and who already have 1000s of leads that are coming in, right?
Omer Granot 17:21
We started with agents and team leads. For example, in compass we didn’t we didn’t go and partner with Compass, we partnered with specific teams at Compass. Then they started internally within their brokerages to refer other teams. And so I think that’s how we’re scaling. Now.
Alexander Ferguson 17:38
There’s a few other when it comes to real estate technology, different angles, people are taking both of renting side building stuff, working with agents that that’s its own unique piece, anything, any learnings that you can share just as not being one who’s leading this company and for other tech entrepreneurs, what’s any insight that you can take away from from working in the real estate environment?
Omer Granot 18:06
And then saying, you know, when we started, we talked about providing technology to agents. I often heard that this is an industry that is reluctant to adopt technology. And it’s very hard to move people from the way of business, how they’re doing it today, I think what we found out is quite different, you know, when we look at our partner agents, these are professionals who are who are trying to give an exceptional service to the clients that they serve. And there’s sort of seeing this industries or they’re seeing multiple tech companies trying to get into real estate. And many of those companies, what they’re saying is they’re saying, you know, we, we don’t actually think that that you need a human process. And and so that creates all the friction and sort of antagonism. And what we found out is that we actually work with it. And our business model is built on providing tools for agents. And when we look at the problem, we say it’s not that the human is not needed. It’s just that the human is currently doing many, many things, when they should actually focus on where human interaction is actually important. And when we started to do that, we saw that the adoption was just huge. Our printer agents are super excited to work with us. Again, because we’re not trying to replace anyone. We’re trying to empower them to basically be more efficient in what they do.
Alexander Ferguson 19:36
What do you see the future of real estate tech? What does it look like? You think if you were to just imagine in five years from now, what’s it gonna look like?
Omer Granot 19:47
It’s hard to guess. Ah, you know, I I think if you look at that market today, there’s a lot of promise, but it hasn’t really been disrupted. And so if I had to guess where that market will be In five years, I think it will, it will still be heavily. It will still heavily involve human interaction. So I don’t think you will all go to like, automated ibuying. It’s all done through text over AI. I do think though, that there, there’s a bunch of core technologies that will that will significantly disrupt the real estate market in multiple ways. So one of them is transparency, and access to data, which I think one is now a huge challenge for home buyers, and agents, actually, but but mostly for homebuyers. So, you know, localized, I think is leading that charge, but there will be others that will provide excellent visibility, trust, and thorough understanding of the real estate market and listings. And the second thing is sort of automation, but not automation in the sense that you do drip campaigns or that you automate email communications, automation, in the sense that you actually introduce AI into the parts of the process that that can be automated, like the smart matching algorithms, sifting through the 10s of 1000s of potential listings, really knowing what it is that you Alex’s, you know, you’re looking for, and then finding that one listing or those top five listings that you would really love. I think that is something that machines can do better than humans. And I think that will also significantly stop the process.
Alexander Ferguson 21:22
You bring back a point that it popped in my head earlier of machines, being able to look through all this data and give you what you really want faster. Where are you getting your data, like the fact that you know that the elevators broken in that place? And that it’s a noisy street over here? Where are you getting this data?
Omer Granot 21:40
So it’s a mix, I would say there’s three, three buckets. One of them is we access existing data, right, so we access permit, data permits data we access, like 311 reports, we access, construction and relationship building relations and 1000s of data sources. That’s one, two is we create proprietary data, like natural light and view noise with many analysis that we sort of create proprietarily. And then the third thing is we sort of take a mix of those two, and we create a third layer of insights on top of it. So for example, you could plug in 2311, you could actually ask for all those reports. But just the raw data wouldn’t really help you. And so, for example, the elevator point that you mentioned, it’s like, okay, we take 311 reports, we then filter those specifically for elevator breakdowns, we match them by department by address, and then we weren’t run sort of a predictive model that says, This is what happened in the past. And this is what we think will happen in the future. Right? And then eventually, where they’ll tell you Hey, Alex, the apartment that you’re looking at, on 73rd and Broadway, you know, just a heads up that you’ll probably experience some a little bit of breakdowns, you know, if you decide to move in, again, that’s one of hundreds of incidents
Alexander Ferguson 23:09
a day going back to that middle one a proprietary and even like the amount of natural light are you guys doing like image detection? Are you like looking at photos of listings, and then being able to make predictive models off of that?
Omer Granot 23:22
We pick a GIS model, we take it three 3d model of the city. And then we run a sort of our natural light and shade algorithm that basically simulates how light and shades look like every hour every day of the year on every property. And then we are able to tell you, Okay, you if you’re on the south side of this building, this is how many hours you’re going to get, how many Metro how many hours of direct sunlight, you’re going to get summer winter, how does that compare to other listings, by the way someone is about to build across the street. So we cross reference that with future construction, by the way, that’s going to impact your natural light. So we’re able to give you all those interesting data points.
Alexander Ferguson 24:04
And all this was developed at Midland for when you started already back in 2012. All that data point that collecting it all and creating it nicely, I guess that’s the hardest thing right today is is the data exists but presenting it in the right way in what people need. That’s what businesses are best at when they can deliver that so kind of just circling to just you are do you like real estate like is that are you why are you in this in this job right now? You joined? Localized was a year ago was that or so? Yeah, that’s
Omer Granot 24:39
over a year ago.
Alexander Ferguson 24:41
Okay. Do you like real estate? Like what why are you doing this?
Omer Granot 24:46
That’s a interesting question as long answer. So I try and find quick. You know, I think I like real estate. I don’t think I’m like a real estate. Huge sort of my whole life. Real Estate, I’m I am excited about two things. One is solving tough problems. And, and two is working with excellent people. So when I, my wife and I moved to the US in 2013 to do, I did my MBA at MIT. And then we joined a company called VR, that is reinventing mobility, basically public mobility in the US. I joined when we were 1415 people and left a year ago when we were 800. And, and when I thought about, okay, what’s what’s next? I had a friend who introduced me to Assaf are founder and CO localize. And I saw two things. One is I saw what is maybe the biggest consumer unsolved consumer problem of today, which is, again, buying a house still extremely difficult, even though it’s 2021. With all the technology we now have, it’s just, it’s quite, you know, it’s it’s a quite frustrating and challenging process. And so the impact of solving that would be huge. And then to the team is just excellent. I think, you know, our fire is phenomenal. We have an exceptional team of technology and data people in Tel Aviv. And then we have an excellent business side in the US doing marketing, sales and operations. So I was excited about joining that team and working on that problem.
Alexander Ferguson 26:19
You saw the problem, you like hard problems. So like, that might be a worthy one to pursue and the team behind it. Felt you gave you confidence in how big is the team today? Medline and localize.
Omer Granot 26:34
But none is around 60 people and localize is 7070 People in brain. Wow, we’re going from like eight to 70 within the last couple of years. And we’re actually scaling quite rapidly now.
Alexander Ferguson 26:47
Wow. That’s it. That’s, that’s impressive. When you look at your roadmap, anything that you can share that you’re excited about kind of coming up for localized that you’d want to share?
Omer Granot 27:01
Definitely, you know, this year has been, you know, if I had to summarize, or 2021 was when we expanded from just being a marketplace for buyers to really solving both sides of these problems. So we introduced Hunter, we introduced localized HQ, which is the solution for agents and brokerages, and 2021 was building a team and starting to scale quite rapidly. I think in the next three to six months, we’ll double down on our business, New York to scale, get much more volume, much more traction. And then we’ll start to expand, expand our business geographically and within the US and outside of us.
Alexander Ferguson 27:43
For those that want to learn more, especially very New York, which is where they’re based at the moment, if you’re a buyer or an agent, you can go to localize dot city, and be able to learn more there thank you so much for sharing the journey that the company has been on the future of it, what you’ve been thinking about it and and for this time, really appreciate man. Thank you, Alex. And we’ll see you all on the next episode of UpTech Report. Have you seen a company using AI machine learning or other technology to transform the way we live, work and do business? Go to UpTech report.com and let us know
