Real Estate Modernized: From Conventional Wisdom to Data-Driven Insights

Speaker A: M welcome to the Esri and the ScienceOver podcast. Everyone thinks they know a good real estate deal. Realtors, sellers, landlords and tenants want to trust their gut, even when they're wrong. By, uh, using the sophisticated tools within location technology, Will Para is changing minds at the New York based commercial real estate firm Ripco. He's showing people how this technology helps them better understand stores, houses and neighborhoods.

Speaker B: What's most important is that the insights that we're generating are spurring conversations and challenging some of the anecdotal things that might be discussed about a given market or a given neighborhood or a specific site where we can now start to quantify some of these things and say, oh, what we thought used to be true might not be true anymore.

Speaker A: Will Para talks to esri's John Lenahan about how location intelligence has helped double the business of Ripco Real Estate.

Speaker C: Hi Will, and welcome to ESRI and the Science Aware podcast.

Speaker B: Thank you for having me, John. I appreciate it.

Speaker C: In your role, Will, how are you working with commercial realtors and what services do you offer and what does your, uh, firm provide?

Speaker B: Sure. So our two main business lines at Ripco are tenant representation and landlord representation. And what that means is our real estate agents will team, uh, up with retailers who are looking to either open locations or expand their existing portfolio into new locations. And on the flip side, we work with landlords to help landlords get their vacant commercial space leased. Now you could imagine that there are a lot of decisions that go into these transactions and location decision making is a big part of that. So our geographic information systems team, um, help our real estate agents understand dynamics of markets. And we try to provide quantitative answers based on spatial data and spatial intelligence to our real estate agents to help them make the best decisions possible.

Speaker C: Okay, so you're, it's really about the facts, selling the vision, um, for itself. But do you think it also has an element of how the information is presented?

Speaker B: Absolutely. I think spatial analytics does give us that assistance that we need to help convey the facts of the demographics or the market analysis that we are doing. Being able to present this information in map form or detailed reports using charts and good visuals, the presentation is just as important as the information in it because it allows people to, to quickly absorb the data that we're showing them. So when we're talking about some of our clients, like Chipotle, for example, they, uh, really need to know a few key metrics that they look at for every piece of site selection. So we provide those for them. Um, but we also Use it to inform our brokers on growing trends in markets. Our population's changing. Are markets gentrifying? Is there a wave of new businesses opening or development happening? Those are all sets of data that we create either maps or reports out of and provide to our brokers as well for their knowledge. Because brokers do a tremendous amount of research into the markets that they operate in. They have a tremendous amount of market knowledge and relationships. So the data that we provide helps them, uh, continue that knowledge and continue to stay an expert on the markets that they operate in.

Speaker C: Well, in my experience, experienced Realtors don't like to be told they're missing something in one of their markets. Is the request for additional or more analytical information about a location coming from buyers or Realtors or a little bit of both?

Speaker B: It's certainly a little bit of both. We have teams that operate in specific neighborhoods of Manhattan, specific boroughs of New York City, and specific markets, uh, across the country. It's really important that they stay up to date with the trends in their given markets. Now, a lot of that information is gathered, um, through their own market knowledge by the, uh, relationships that they have, understanding vacancies and comings and goings of tenants. But also it's important for us to keep them up to date with more quantifiable data as to what the trends are in a given market. Whether that's changes in population, changes in demographics. So many different data sources that we're able to provide reports to our real estate agents to help keep them abreast of the trends in the given market. It's also important for them to have access to this material as well, so that when they're evaluating potential sites to go to, they have all the information they need at their hands to make the best decision. So it is kind of twofold.

Speaker C: So will you mention you identify some trends that maybe the local broker isn't aware of? What kind of trends do you identify or surface for the Realtors?

Speaker B: The most common is demographics. We're always providing, um, insights and reports as to what the demographics and the consumer base of a given market look like and how those are evolving over time. We, uh, look at trends for things like foot traffic to help understand how certain intersections or storefronts are seeing either increases or decreases in traffic. That helps with the site selection process. We also look at some internal data that we're collecting as to what vacancies are coming on the market. Is there an increase or decrease in vacancy and, or price?

Speaker C: Do they like the information you're providing? They have More questions. Are they pushing back?

Speaker B: We are getting overwhelmingly positive feedback from our brokerage team and our management team. And I think what's most important is that the insights that we're generating are spurring, uh, conversations and challenging some of the anecdotal things that might be discussed about a given market or a given neighborhood or a specific site where we can now start to quantify some of these things and say, oh, what we thought used to be true might not be true anymore.

Speaker C: So you mentioned. I like that idea of real estate being very anecdotal. I think of personalizing that. Right. Uh, in the residential market, let's live on this nice street, let's live in this neighborhood that, that has, uh, these good schools. But in commercial real estate, how does that really apply?

Speaker B: Sure. So a good example, at least in New York City, is the neighborhood of Williamsburg, Brooklyn. Now, Williamsburg, um, 20 years ago used to be an industrial neighborhood. It's now kind of the New SoHo of New York City. I mean, all the luxury brands are now in Williamsburg. The, the demographic has completely changed. And anecdotally our brokers can come to us and say, well, this neighborhood or this site is going to be in the next Williamsburg. This neighborhood is the up and coming neighborhood. So how do we quantify that and start to understand is this neighborhood anecdotally an up and coming neighborhood, or is it truly an up and coming neighborhood by all the measures that we look at?

Speaker C: So going further with the idea of these anecdotal, um, perspectives, how does location intelligence will help, I guess, disprove maybe a romantic or, ah, a, um, perspective that a buyer might have on a certain neighborhood, um, that the data really proves to them isn't accurate.

Speaker B: Yeah, for sure. So the anecdotal nature of commercial real estate is always an interesting one. And as spatial analysts, we have the ability to actually quantify some of these anecdotes that commonly get thrown around. Spatial analytics allows us to look at things like building permits, look at things like changing demographics, increases in population, all these attributes that can help us quantify whether a neighborhood or a site is what people think it is. It's very common for people to say, well, this neighborhood is going to be the next Williamsburg. And Williamsburg historically is, uh, a neighborhood that has gentrified tremendously over the last 20 years. Things like looking at building permits and ingesting those into ArcGIS, looking at population trends, looking at the increase or decrease of retail vacancies, are all indicators that we use to understand and quantify if an anecdote is actually true or not, and then in turn relay that message to our brokerage teams.

Speaker C: Earlier, Will, you mentioned that, you know, some of your main customers are retailers trying to determine kind of locations and where to grow their market. How do you help retailers determine what they're missing in their market? Um, analysis.

Speaker B: Most retailers have a general idea of who their customer is. We can leverage the data and the tools that we have to help them hone in on who that customer is. It also depends on the life stage of a specific retailer. For retailers that are more well established, that have a larger footprint or a longer history of data, we are actually able to integrate their data to understand who their customer is directly and then we can start to use some of the geospatial tools to, number one, identify where their customer is and also where are gaps in the market for them. And from there we can develop a strategy for them as to either expansion, relocation, or just general site selection.

Speaker C: One of your largest customers, um, that I've seen mentioned on, uh, some of your online articles is Chipotle. Everyone knows Chipotle. So can you kind of dive into that and help us understand the work you've done for them?

Speaker B: Yeah, so Chipotle is, um, one of our bigger clients. Obviously they have a very large footprint nationally. We represent them in the New York tri state area and we do a lot of work with them helping them understand where those gaps are. GIS technology allows us to help them visualize that and allows us to guide our brokers as to where they should be looking. Another example is a supermarket retailer that we've been working with named Uncle Giuseppe's. They have around 10 locations in the northeast and they're slowly expanding now. They have a long history of, uh, operating in the supermarket business in the Northeast, which means they do have lots of data and they're able to transfer that data to our GIS team. We're able to then ingest that and understand exactly what makes a successful Uncle Giuseppe's location. We can match up some of their performance data with some of the other data points that we have to understand the derivative attributes that make up a successful store. And then we can start to look for that in new places where there might be a void of supermarkets and things like that.

Speaker C: I'm sure will, in the case of Uncle Giuseppe's, they have probably really good local market in their 10 store vicinity. But as they look to grow nationally or even super regionally, they're probably flying a little bit, um, blind.

Speaker B: Yeah, absolutely. So the way it works is they will hand us data and they will ask us to essentially do an exploratory study to understand what is affecting performance. So we can start to look for correlations between performance and certain things, whether that's performance versus average household income in a market or performance versus competition, the number of competitors or the distance to competitors. Those are all things that we will look for to identify if they play a role in performance. And once we understand what those derivative attributes are that drive performance, we can start to model for that in new markets. And then we're able to say this site in Pennsylvania, which we have not been to, we don't uh, we don't really know the market, but the data shows that this is very similar in terms of these four or five attributes to places that we know that we're performing well.

Speaker C: And by attributes you could mean, um, it's a, it's a zip code with a high population of um, um, single earning families with children between the ages of 10 and 15. And you're at least 15 miles away from your nearest large competitor.

Speaker B: Exactly. It could be just like that. And we do the work to figure out exactly which one of those attributes matter in terms of driving performance. Excuse me. And then we look for that in new markets.

Speaker C: So taking a step back, using geospatial tools with your brokers, what difference have you seen, uh, in terms of time and money, um, that both you're providing, but also that the brokers are spending on researching and um, bringing new sites to market?

Speaker B: Absolutely. I think the first thing that jumps out to me is the efficiencies in which we operate that the ESRI platform has kind of allowed us to achieve. Um, if you think of a broker who is trying to research availabilities, they're now able to interact with applications that we build to visualize and quickly search and research um properties for their particular use case. But also then take it a step further and start performing analytics on the data that we're collecting. Um, has number one, saved lots of time, but also it generates great insights from, for our company as well.

Speaker C: And your business has more than doubled.

Speaker B: Yeah, so I joined Ripco, um, 2021. So coming up on Five Years now and since I've started we have grown tremendously in our brokerage space. That's attributed to great leadership. But also we can lean on the scalability of the infrastructure that we've built to support a growing business like this. So if we were to onboard a uh, brokerage team in the middle of the country, an area that we've never worked before. We have all the tools at our disposal, um, to perform the same types of spatial data analytics that we are now.

Speaker C: I wanted to ask you about AI, um, and the growing influence of AI and geospatial AI in all markets. And I think an appropriate way to close is to ask for your perspective on what the future holds for Realtors and their interaction with AI and AI based tools and what's that dynamic look like?

Speaker B: Uh, for us, we know that AI is never going to replace a real estate broker or agent. AI does a really good job of, in certain use cases, identifying patterns and trends that might not be seen otherwise. So that's another, that's another big thing for us is allowing it to have, have a look into certain data sets and tell us, um, maybe some things that we've missed or insights that we should be quantifying or aggregating.

Speaker C: Well, Will, thanks so much for taking the time joining us. I'm sure the audience is going to love the information you shared and your insight on the commercial real estate market, so thank you again.

Speaker B: Oh, it was a pleasure. Thank you for having me, John.

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