Location Data in Commercial Real Estate: Future of CRE

Who Is This Guide For?

This guide is built for commercial real estate investors evaluating new opportunities, urban planners assessing how a location fits into a broader development plan, and market analysts who need a clearer, more current read on a property before recommending a move. If you’re trying to understand what location data actually adds to a CRE decision, beyond gut instinct and lagging market reports, this is for you.

Why Location Data Is Now Central to Commercial Real Estate Decisions

Data has become a defining factor in how commercial real estate companies operate. Many have started relying on location data, specifically point of interest (POI) data and building footprint geometry, alongside their own first-party data to conduct market analysis and investment research before making major decisions. This matters because those decisions often carry long-term financial consequences that are difficult to reverse.

Real estate has always been about location. What’s changed is how much can now be known about a location before a single dollar is committed.

The numbers tell the story. U.S. office vacancy posted its first year-over-year decline in over five years in Q3 2025, falling to 18.8% as demand outpaced supply for a sixth consecutive quarter. Retail tells a tighter story still: overall retail availability dropped to 4.8% in Q4 2025 as net absorption hit 11.3 million square feet. And capital is following the data: global proptech investment rose to $16.7 billion in 2025, a 67.9% jump from 2024 and the strongest year since before the pandemic. Against that backdrop, having access to granular, current location data is less of a nice-to-have and more of a baseline expectation for serious CRE investment teams.

Access to the right data is the difference between guessing which commercial real estate opportunities hold promise and actually knowing. It’s up to commercial real estate companies to use these insights to inform their own portfolio strategies and to shape how they pitch available space to prospective tenants.

Still, not every commercial real estate company knows exactly what to do with all this location data or how to use it correctly. This guide breaks down why location data belongs at the center of CRE investment strategy, and how it helps drive long-term ROI while reducing avoidable risk.

Data Gives Commercial Real Estate Companies a Competitive Edge

With a wide range of properties available at any given time, it can be difficult for commercial real estate companies to narrow down opportunities and identify the ones most likely to perform well, with any real confidence.

Data helps narrow that search. It makes it easier to surface properties that meet specific criteria or align with an established investment thesis.

Here are a few of the ways data is already shaping outcomes in commercial real estate that may be easy to overlook:

Strategy development
Access to data alone doesn’t move the needle. Teams need accurate, well-sourced data to build strategies they can actually rely on. Flawed inputs lead to flawed conclusions, and in CRE, flawed conclusions tend to be expensive.

Cost reduction
Working with the right data can shorten the gap between starting a property search and filling a vacancy. Beyond speed, it also drives operational efficiencies that compound into real savings over time.

Tenant satisfaction
Using location data to support market research or trade area analysis means walking into leasing conversations already equipped with the insights that close deals. A clearer view of a property’s surrounding context makes it easier to build a compelling case for the right tenant in the right space, which adds value across the entire CRE chain.

What about gut instinct?

Experienced commercial real estate professionals will tell you that a lot of real estate investing still comes down to instinct. But increasingly, they’ll also tell you that instinct needs data behind it to hold up under scrutiny.

As Ryan Passe, VP of Operations at Sands Investment Group (SIG), has put it, brokers who once relied purely on gut feel to land deals are now expected to back that instinct with numbers, or risk losing money to those who do. That shift has pushed firms like SIG to build more data-driven decision processes.

This goes beyond matching buyers and sellers faster. It’s about pricing deals accurately, understanding capital flows and inventory levels, managing credit risk, and arriving at property valuations that hold up. Passe has noted that this kind of data discipline helps teams spot opportunity, move faster, and adopt new technology in an industry that has historically leaned on instinct alone.

Layering location data into that process helps answer questions about revenue potential, including the effect of nearby complementary businesses, inventory and resource planning, and other context that turns a gut call into a defensible investment decision.

According to McKinsey, many real estate firms have historically combined intuition with retrospective, backward-looking data. Today, a wider range of available variables makes it possible to build a much more current picture of a location’s risks and opportunities going forward.

What Kind of Analysis Can Be Done with Location Data?

There’s a wide range of ways location data gets applied across commercial real estate. Here are the most common.

1. Market analysis

Market analysis is foundational. It’s how commercial real estate teams objectively assess whether a given location, zoned for a specific business type, is positioned to succeed and command a stronger lease value.

Enriching POI data with other datasets, such as purchasing power per capita, lets real estate companies assess specific markets and estimate a property’s potential ROI before committing.

It’s also one of the most effective ways to reduce risk before spending heavily. Several factors typically go into CRE market analysis:

• Supply: How many vacancies of a given property type exist, and how many construction projects for that type are underway or awaiting approval?

   

• Demand: Is there pent-up demand for a specific property type in the area, or is the market already saturated with options for tenants?

   

• Location: Is the property easily accessible from major roads or highways? Is parking sufficient?

   

• Pricing considerations: What are average rental rates, occupancy and vacancy rates, square footage, zoning restrictions, and any unique features or required improvements?

   

• ROI potential: What income has the property generated historically, and what is its income-producing potential going forward?

   

All of these factors shape a property’s ultimate “rentability,” and skipping a thorough market analysis can leave a company holding a property that sits vacant for months.

As one real estate investment approach frames it, teams typically start by researching markets, asset classes, and cycles to understand what stage a given market or asset class is in before going further.

2. Site selection and portfolio management

Location data supports CRE site selection and portfolio management differently depending on property type.

For retail site selection, location data helps identify the specific spots most likely to drive strong revenue for the businesses that lease them. Retail site selection is fundamentally about thinking ahead: ROI on that investment only materializes once a successful tenant moves in. So commercial real estate companies need a clear picture of what tenant success will look like in order to fill vacancies efficiently.

For office space, the priorities shift. Commercial real estate companies are typically less focused on foot traffic and more focused on a property’s proximity to cafés, restaurants, hotels, supermarkets, and other day-to-day conveniences office workers want nearby. Understanding that surrounding context lets companies price “convenience” as a premium feature in leasing packages, and helps build a portfolio strategy positioned for long-term revenue growth.

McKinsey notes that advanced analytics shouldn’t function as a crystal ball. In most cases, it’s there to support an investment hypothesis, not generate one outright.

3. Investment research

According to Deloitte, big data can help automate due diligence by generating technical records and current building conditions in close to real time. That’s become a meaningful advantage for commercial real estate companies conducting investment research, allowing teams to estimate profitability and track performance at a granular level.

That said, this level of data maturity isn’t yet widespread across the industry. A few factors tend to hold companies back:

Lack of awareness
Many teams simply don’t know what datasets exist or how to turn them into actionable insight. The industry still lacks broadly accepted standards around data definitions and governance, though that’s beginning to shift. Deloitte has noted that managers can spend a significant share of their time just gathering and preparing data for analysis, which discourages many teams from going deeper.

Resource constraints
Many commercial real estate companies don’t have the tools, technology, or in-house expertise to source, clean, and extract meaningful insight from available data efficiently. That gap becomes a real obstacle when trying to enhance proprietary data with location-based datasets, and the fear of a slow payoff can make the investment feel risky.

Risk aversion
Adopting new data sources can feel risky, especially in a traditionally conservative industry. Investors who’ve built success on a familiar set of data sources are often reluctant to tie major decisions to anything new. Deloitte points out that investors and managers need to verify data provenance carefully to manage privacy risk and build transparency, which adds friction to adoption.

A relationship-driven culture
Real estate has long been built on relationships and instinct. Deloitte’s research suggests that as new business models emerge, relying on intuition alone won’t be enough, and that analytics can reduce subjectivity even within a traditionally relationship-first decision process. That requires a mindset shift many firms are still working through.

McKinsey frames the core challenge well: conventional data sources and methods make it hard to build a clear, defensible hypothesis or business case.

4. Risk mitigation

Layering location data and other non-traditional sources onto standard CRE data sharpens the picture of a property’s specific risks and advantages.

McKinsey illustrates this with a simple example: two buildings that look identical by traditional metrics can end up on very different growth trajectories. At the portfolio level, that kind of disparity, multiplied across many properties, can have a significant cumulative effect.

Location-based data adds depth to existing data on market and property performance, giving investors a better way to evaluate long-term potential and the additional context needed to make sound decisions while reducing risk.

Traditional CRE Data vs. Location Data

Traditional commercial real estate data remains essential for evaluating factors such as pricing, vacancy rates, lease terms, and historical performance. However, these datasets often focus on what has already happened. Location data adds another layer of insight by revealing the real-world context surrounding a property, helping investors and analysts understand not only where a property stands today, but also what may influence its future performance.

The illustration below highlights how two investors can look at the same property and arrive at very different conclusions depending on the data available to them. Traditional CRE data provides the property’s historical story, while location data adds the surrounding context that can shape future outcomes.

The table below breaks down the key differences between traditional CRE datasets and location data, including how frequently each is updated, the level of detail provided, and the types of insights they support.

While traditional CRE data remains the foundation for property evaluation, location data helps fill critical context gaps by revealing nearby businesses, accessibility, building footprints, and other factors that may influence long-term performance. Used together, these datasets provide a more complete view of both opportunity and risk.

3 Ways SafeGraph Data Can Enrich Investment Strategies

SafeGraph provides Places, Geometry, and Address data designed to give commercial real estate teams a more accurate, current foundation for decision-making.

1. Points of Interest (POIs)

SafeGraph Places includes core information, including location name, address, category, and brand association, for the places where people spend time. It also reveals the relationship between adjacent POIs, which gives a clearer sense of what types of businesses operate near any given location.

Applied to commercial real estate, POI data helps establish a foundation for mapping and market analysis, offering a clear view of what surrounds a given property. Is the area already saturated with similar businesses or property types? Is there anything nearby that could make a property less attractive to lease?

2. Building Footprints (Geometry)

SafeGraph Geometry provides building footprint data, including spatial polygons in WKT format, for more precise geofencing and a clearer understanding of attribution. For commercial real estate companies, Geometry can surface details like building footprint shape and parking lot adjacency, supporting a more complete picture of a physical property.

3. Address Data

SafeGraph also provides structured global address data for validation, routing, and analytics. Clean, validated addresses reduce errors when matching a property to the right building footprint and POI records, which matters since a single mismatched address can throw off an entire site selection or market analysis workflow.

Combining SafeGraph’s Places, Geometry, and Address data with traditional CRE data allows urban planners, investors, and market analysts to better understand market penetration and surrounding context, supporting more informed investment decisions.

As Deloitte has noted, getting real value from data ultimately requires a joint effort across real estate stakeholders, since better data alone doesn’t create better outcomes without the collaboration to act on it.

Real-World Example: Avison Young

Avison Young, a commercial real estate company, works with clients who regularly ask a deceptively simple question: what’s the best location for my business? In practice, that question covers a lot of ground, including accessibility by highway or transit, nearby amenities, and for retail tenants, proximity to the right consumer base.

Avison Young turned to SafeGraph’s POI data to give clients deeper, more current insight into what’s actually happening at ground level around a given property, rather than relying solely on historical market reports. With local market conditions, including available inventory, shifting quickly, having access to current location data has helped Avison Young support faster, better-informed site selection decisions for clients.

Key Stats at a Glance

• U.S. office vacancy fell to 18.8% in Q3 2025, the first year-over-year decline since Q1 2020 (CBRE)
• Retail availability tightened to 4.8% in Q4 2025 on 11.3 million square feet of net absorption (CBRE)
• Global proptech investment reached $16.7 billion in 2025, up 67.9% year-over-year (Center for Real Estate Technology & Innovation)

Better Real Estate Decision-Making Starts with Location Data

Location data is changing how commercial real estate companies evaluate opportunities. It adds context that traditional data sources can’t capture on their own, around both property and market performance, and helps surface the nuances that make one property a stronger investment than another that looks identical on paper.

Getting started with location data can feel like a lot, especially if your team hasn’t worked with it before. It doesn’t have to be. With the right tools and approach, location data can give commercial real estate companies a real edge in any market.