Location data can unlock new insights that enable commercial real estate companies—and their tenants—to bounce back in a post-pandemic world.
Data has recently become a game-changer for commercial real estate companies. Many have started relying on location data, specifically—including point of interest (POI), building footprint, and foot traffic data—alongside first-party data to conduct advanced market analysis and investment research before making major business decisions. This is critical knowing that many of those decisions come with potential long-term financial implications.
Using location data in this way has, therefore, made it possible for many commercial real estate companies to not only mitigate the potential risks of their investments but also build a more ROI-positive investment strategy from the get go. Plus, with the world quickly reopening after a challenging pandemic-ridden year, there is momentum building around an urgent need to invest in highly valuable and attractively-priced commercial real estate opportunities, following last year’s ‘domino effect’ of store closures.
Access to the right data will be the key to understanding which commercial real estate opportunities hold the most promise in the post-pandemic world. And it’s up to commercial real estate companies to use these insights to inform their own portfolio management strategies and also influence how they encourage future tenants to lease the spaces available.
Unfortunately, not every commercial real estate company knows exactly what to do with all this location data or even how to use it correctly. In this guide, we’ll explore the reasons why commercial real estate companies should put location data at the heart of their investment strategies as a way to drive long-term ROI and mitigate potential financial risks.
Although big data is a relatively new territory for commercial real estate companies, we’ll take a close look at why it’s quickly becoming a game-changer in a predominantly traditional industry:
Technology is affecting every aspect of our business and the tipping point is here. The gap is growing between those who adopt technology and those who don’t.
Especially now, with a lot of vacant properties up for grabs, it can be difficult for commercial real estate companies to narrow down the list of all available investment opportunities and then be able to single out only the most potentially profitable properties with a high degree of accuracy.
Fortunately, data (of all kinds) can help get a more targeted search underway, making it easier to discover properties that meet specific search criteria or align to established investment goals.
Among the many ways that data is already fueling the success of the commercial real estate industry, here are few areas that you may not have considered:
It should come as no surprise that the most successful commercial real estate agents tell you that a big part of real estate investing, in general, requires trusting your gut. But today, they also know that having the right data to support and validate those instincts is critical for building confidence during key strategic planning and decision-making processes.
As Ryan Passe, VP of Operations at Sands Investment Group (SIG) puts it, “The time when brokers could lean on gut feelings to get the best deal is gone. Today, if you’re not paying attention to the numbers, you’re losing money.” That’s why companies like SIG have doubled down on making commercial real estate investment decisions more data-driven.
It goes beyond simply making better and quicker “matches” between buyers and sellers. It’s now a matter of pricing deals correctly, having a better grasp of capital flows and inventory levels, mitigating credit risks, and establishing accurate property valuations. “That’s empowering our teams to find opportunity in the market, make quicker decisions, and embrace new technology in a world that is mostly reliant on gut feel,” reiterates Passe.
Throwing location data into the mix can, therefore, help answer questions around potential foot traffic, opportunities for revenue generation—including cross-pollination from neighboring businesses—inventory management, resource planning, and more. These are the kinds of insights that can turn a gut instinct into a more viable long-term investment decision.
Many real estate firms have long made decisions based on a combination of intuition and traditional, retrospective data. Today, a host of new variables make it possible to paint more vivid pictures of a location’s future risks and opportunities.
There is a lot that can be done with location data within the commercial real estate industry. Here are just a few of the most common use cases to keep top-of-mind:
Market analysis is a general best practice that every commercial real estate company should master. It’s an objective way to assess whether a specific business location, zoned to specific business types, will be positioned to succeed and, thus, command a higher lease value.
It’s also a great way to reduce potential risks before investing too much money. There are a number of factors that go into commercial real estate market analysis, including:
All of these factors play a big role in determining the ultimate ‘rentability’ of a property and need to be taken into consideration by commercial real estate companies upfront when making investment decisions. Failing to do a thorough market analysis can leave you with a dud of a property that could potentially sit vacant and collect dust for months on end.
We use a funnel approach for real estate investing. We start by researching markets, asset classes, and cycles...to determine what state an individual market is in and what state a particular asset class is in within a market.
Data Driven Real Estate Investment (SMARTCAP)
There are multiple ways that location data can support commercial real estate site selection and portfolio management. It comes down to the property types being considered for purchase.
For example, in retail site selection, location data can help you hone in on the exact spots that will drive the greatest amount of success—in terms of foot traffic and potential revenue generation—for businesses interested in leasing those properties. In many ways, retail site selection for a commercial real estate company is all about thinking a few steps ahead: The ROI driven from that investment will be realized only when a successful tenant sets up shop. Therefore, it’s critical for commercial real estate companies to be able to paint a picture of what success will look like for tenants in order to fill vacancies, fast.
When commercial real estate companies invest in office space, they are typically less concerned with foot traffic, per se, and more focused on a property’s proximity to things like cafés, restaurants, hotels, post offices, supermarkets, and other “daily essentials” that office workers would like to have easy access to. Taking a property’s surrounding environment into account enables commercial real estate companies to price “convenience” as a premium perk when developing leasing packages. Understanding the implications, both good and bad, of a property’s location is the best way for commercial real estate companies to hedge their bets and build a solid portfolio strategy that drives long-term revenue growth.
Advanced analytics cannot serve as a crystal ball. In most cases, it should only support investment hypotheses, not generate them.
According to Deloitte, “Big data can help automate due diligence, as the technical records and current conditions of building components can now be generated in real-time and reliably.” This has quickly become a competitive advantage for many commercial real estate companies when conducting investment research. Data available today allows them to not only to predict potential profitability but also to measure performance in real-time at a granular level.
However, this advanced use of data is not widespread across the commercial real estate industry. The industry, in general, has been slow to get on the data bandwagon. The primary factors stopping commercial real estate companies from embracing data include:
Conventional analytical methods and data sources make it challenging to draw clear hypotheses and build robust business cases.
Layering on location data and other non-traditional data sources to so-called traditional commercial real estate data can drive increased clarity around a property’s nuances.
McKinsey provides a clear way of thinking about this: “Two buildings that are seemingly identical when evaluated by traditional metrics can ultimately experience very different growth trajectories. It is easy to imagine how this disparity at the individual building level, when applied across a series of investments, can drive dramatic results at the portfolio level.”
Location-based data can add depth to data sources about market performance, property features, and property performance, giving investors new and better ways to evaluate a property’s potential for long-term success. These insights provide additional, and oftentimes necessary, context to both drive sound decision-making and mitigate risk significantly.
The SafeGraph Places dataset, updated monthly for utmost accuracy and precision, provides the in-depth POI, building footprint, and foot traffic data you need to fuel more informed and accurate decision-making around commercial real estate investments and strategies.
Here’s a quick overview of the three types of location-based data within this powerful dataset:
1. Points of Interest (POIs)
Places includes base information—such as location name, address, category, and brand association—for the places where people spend their time and money. It also sheds light on the relationship existing between adjacent POIs. Therefore, POI data is important because it provides a unique perspective for understanding the types of places target audiences visit throughout the day or week.
When applied to the commercial real estate industry, POI data can set a foundation for mapping, inform market analysis, and offer a ‘birds-eye view’ of the environment surrounding any given place (i.e. Is that area already saturated with similar businesses or property types? Is there anything in the vicinity, like a trash dump, for example, that could devalue a property or make it less attractive to lease?).
2. Building Footprints
Geometry offers building footprints for POIs derived from spatial hierarchy metadata to allow for geofencing as well as a more precise and accurate understanding of attribution. For commercial real estate companies, more specifically, Geometry can provide precise building attribute details—like building heights and parking lot adjacency—to help map out and truly understand all aspects of a physical property. Check out this great overview of the ins and outs of building footprints for geospatial analysis to learn more.
3. Foot Traffic Patterns
Patterns data measures hourly foot traffic to and from POIs precisely—powered by aggregated anonymized mobile device activity and other demographic data—to determine how often people visit certain POIs, how long they stay, where they came from, where else they go, and more. This helps real estate planners and analysts hedge smarter bets for where to invest and can also proactively identify real-time consumer trends that may influence a property’s long-term value.
And by layering SafeGraph’s Neighborhood Patterns foot traffic data onto the SafeGraph Places dataset, it can layer on even more insights about how people move around—and, ultimately, transact—at a macro level in a given trade area. Not only is this information critical when doing initial investment research, but it can also give commercial real estate companies a cutting edge in pricing and contract negotiations with potential tenants.
Therefore, by combining all of SafeGraph’s location-based datasets with traditional commercial real estate data, urban planners, real estate investors, and market analysts can visualize catchment analysis, understand market penetration, and make smarter investment decisions.
Only a joint effort among all real estate stakeholders can optimize data to create insights that improve performance and profitability.
Location data is revolutionizing the commercial real estate industry for the better. Not only does it add new kinds of value to traditional real estate data sources—around both property and market performance—but it also helps pinpoint the nuances that can make one property a smarter investment over another. The power of location data, therefore, has the potential to transform how commercial real estate companies make better, more profitable investments.
However, we understand that using and analyzing location data may seem intimidating at first, especially if you haven’t used it in this way before. But it doesn’t have to be. With the right tools and techniques in place, location data can give commercial real estate companies a competitive edge in any local market—especially at a time when the industry is about to experience a massive boom. And if you’re still not quite sure where to start, our team is always here to help!