Geographic benchmarking in commercial real estate (CRE) helps investors evaluate property performance by location, uncovering opportunities and risks across markets. Key metrics include:
- Occupancy & Vacancy Rates: Understand market demand and tenant turnover.
- Rent Growth Rates: Gauge revenue potential and market trends.
- Cap Rates: Compare unlevered returns across regions.
- Absorption Rates: Track leasing activity and demand-supply balance.
- Net Operating Income (NOI) & Internal Rate of Return (IRR): Assess profitability and investment returns.
- Population Growth & Density: Identify high-demand areas.
- Foot Traffic & Location Data: Analyze visitor behavior and property usage.
- Delinquency Rates: Spot financial stress and distressed asset opportunities.
Using tools like CoreCast simplifies data analysis, offering real-time insights and visualizations for better decision-making. By focusing on these metrics, CRE professionals can optimize investments, improve portfolio performance, and navigate market shifts effectively.
Top 9 CRE Geographic Benchmarking Metrics Comparison Chart
1. Occupancy and Vacancy Rates
Localized Relevance to Geographic Benchmarking
Occupancy and vacancy rates are two sides of the same coin – together, they always add up to 100%. These metrics are key for gauging market demand and property performance [5]. Across the U.S., these rates show significant geographic differences. For example, in February 2026, office vacancy rates ranged from 12.8% in Miami to a staggering 25.1% in Seattle [4]. That 12.3-point gap highlights why location-specific benchmarking is essential for managing property portfolios with real-time dashboards. It’s a foundational measure that helps decode the unique dynamics of various regional markets.
Regional Market Dynamics
Diving deeper, regional trends tell an interesting story. Sun Belt cities such as Miami (12.8% vacancy) and Phoenix (13.1%) are thriving in the office sector, outperforming West Coast markets like San Francisco (24.2%) and Seattle (25.1%) [4]. When it comes to rental properties, high-cost coastal cities – San Francisco, Los Angeles, and New York City – often have lower vacancy rates (around 5%) due to limited supply. On the other hand, more affordable areas like Memphis and Cleveland typically see vacancies in the 7–9% range [3]. The Southeast and Sun Belt regions also show strong performance, with an average vacancy rate of 7.39%, compared to 8.65% in the Northeast and Mid-Atlantic [3].
Impact on Investment Decisions
Vacancy rates directly affect an investor’s bottom line. For instance, a 5% vacancy on a $5 million property translates to a $250,000 loss in rental income [5]. This makes it critical to factor vacancy rates into underwriting. Many investors plan for a 5–10% vacancy rate to account for tenant turnover [3]. Breakeven occupancy levels also vary by asset type. Apartment complexes typically need at least 88% occupancy to cover costs, while hotels can break even with occupancy as low as 55% [5].
Identifying Market Opportunities and Risks
The "flight to quality" trend has created a noticeable gap in performance between property classes. By 2027, Class A properties are expected to maintain vacancy rates as low as 8.2%, while Class B and C properties will likely face much higher rates [2]. This gap presents opportunities for repositioning underperforming assets. For example, in April 2024, Chicago set aside $151 million to convert four struggling office buildings – totaling 2.3 million square feet – into about 1,000 residential units, addressing the city’s high office vacancies [2].
Applicability Across CRE Asset Classes
Occupancy benchmarks vary widely across different commercial real estate (CRE) asset classes, making it easier to assess performance by geography and property type. As of Q3 2024, national occupancy rates stood at 95.9% for retail, 93.4% for industrial, 92.1% for apartments, and 86.1% for office properties [6]. The office sector faces significant hurdles, with a vacancy rate of 20.4%, while retail has remained steady at 95.9% occupancy despite economic uncertainties [6]. Industrial and multifamily properties tend to be more stable, offering resilience in unpredictable markets. Knowing these benchmarks helps investors set realistic goals tailored to specific markets and property types.
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2. Rent Growth Rates
Localized Relevance to Geographic Benchmarking
Rent growth rates highlight market demand and show significant variation across different U.S. regions, making them a key factor in geographic benchmarking. Take April 2025, for example: the average U.S. office listing rate hit $33.34 per square foot, reflecting a 5.4% year-over-year rise, even as vacancy rates remained high [2]. But this national figure hides a lot of local differences. Class A office rents are now an eye-popping 84% higher than Class B and C rents, driven by a trend where tenants prioritize premium spaces in top locations [2]. These disparities underline the importance of rent growth rates in predicting revenue and investment returns.
Impact on Investment Decisions
Rent growth rates play a major role in shaping cash flow projections and property valuations. They’re a key input for Discounted Cash Flow (DCF) models, which help estimate future Net Operating Income (NOI) and eventual sale prices [8]. Strong year-over-year rent growth often signals healthy market demand and occupancy, but broad averages don’t always tell the whole story. For example, in San Francisco, the median list price of $1.2–$1.3 million suggests a monthly rent of $12,000–$13,000 under the "1% rule." Yet, the actual average rent is closer to $3,100 [7]. This mismatch shows why localized rent data is far more reliable than general formulas. Companies that incorporate real estate cost analysis and rent benchmarking into their strategies can cut occupancy costs by 15% to 20% [10]. Clearly, rent growth rates are a crucial metric for evaluating market performance across regions.
Ability to Identify Market Opportunities or Risks
Tracking rent growth trends can also help pinpoint potential risks or opportunities. While strong rent growth often signals opportunity, it can also hint at risk. Overheated markets might be heading toward speculative bubbles, making corrections or tenant defaults more likely [8]. The gap between "asking rent" and "effective rent" – which accounts for concessions like free rent periods and tenant improvements – can expose hidden weaknesses in demand [11]. Monitoring this spread helps investors spot markets where landlords may be losing pricing power. Metrics like Market Revenue per Available Foot (M-RevPAF), which combines effective rents with occupancy rates, offer a more complete view of market conditions [11].
Applicability Across CRE Asset Classes
Rent growth trends vary widely depending on the asset class and location. Recently, office properties have seen the slowest rent growth among commercial real estate types, with just a 0.7% increase [2]. In contrast, industrial and multifamily sectors have performed better in many areas [9]. Multifamily rent growth often ties to population density and migration patterns, particularly in Sun Belt markets, while office rent growth tends to follow sector-specific job trends [11]. The office sector also reflects a clear divide: Class A buildings in prime locations enjoy rising rents and lower vacancies, while Class B and C properties struggle with aging infrastructure and often have to cut rents or offer significant concessions to compete with sublease supply [2].
3. Cap Rates by Market
Localized Relevance to Geographic Benchmarking
Cap rates can look vastly different depending on the market. As of April 2026, the national average cap rate across 69 metro areas is 5.48%, but this figure masks significant regional disparities [3]. High-cost coastal cities like San Francisco and New York average a low 3.36%, whereas more affordable Midwest markets come in at 6.68% [3]. Among the extremes, San Jose has the lowest cap rate at 2.50%, while Akron, Ohio, tops the chart with 8.90% [3]. These variations highlight a common trade-off: investors in coastal markets often accept lower immediate returns, banking on stronger long-term property value growth [3][12].
Regional trends tell a similar story. The West Coast and Pacific region averages a 3.60% cap rate, with median home prices around $723,333. Meanwhile, the Midwest boasts an average cap rate of 6.59%, paired with much lower median prices of $237,533 [3]. Coastal markets overall average 4.72%, compared to inland areas at 5.81% [3]. With the 10-year Treasury rate hovering around 4.6% in early 2026, the spread between cap rates and “risk-free” rates remains tight, especially in major gateway cities [13]. This kind of detailed analysis helps investors align their strategies with regional market dynamics.
Impact on Investment Decisions
Cap rates are a quick way to measure a property’s unlevered return – calculated as Net Operating Income divided by property value. This allows you to compare properties on an "apples-to-apples" basis, stripping out financing factors [12][14]. For example, a 5% cap rate in Austin could still outperform a 9% cap rate in a declining rural market, thanks to Austin’s stronger appreciation potential and lower tenant turnover [14]. But cap rates alone won’t tell the whole story. With mortgage rates hovering between 6.75% and 7.0% in 2026, properties with a 6% cap rate may generate less cash flow [12]. To avoid negative leverage, make sure the initial cap rate exceeds your debt constant (annual debt service divided by loan amount) [13]. These factors are critical when weighing market risks and opportunities.
Ability to Identify Market Opportunities or Risks
Higher cap rates often point to greater risks, such as weaker rental demand, slower population growth, or an aging housing stock [12]. When analyzing a deal, it’s smart to factor in a 50–100 basis point increase in the cap rate at exit to prepare for potential market changes [13]. Don’t rely solely on a seller’s pro forma numbers – calculate your own Net Operating Income using actual tax data and realistic assumptions for vacancies to determine the real cap rate [14]. It’s also important to compare properties within the same market tier. For instance, a 7% cap rate in a high-cost market might signal distress, while the same rate in an affordable market could be completely normal [3].
Applicability Across CRE Asset Classes
Cap rates differ not only by geography but also by asset class. Industrial properties are currently the strongest performers, with cap rates ranging from 5.5% to 6.5%. On the other hand, office properties are struggling, with cap rates between 7.5% and 9.5% – and even higher for Class B suburban offices, which often trade at 8.0% to 10.0% or more [13]. Multifamily garden apartments average around 5.4%, while grocery-anchored retail strip centers fall within a tighter range of 6.2% to 6.8% [13]. The challenges in the office sector are stark: office vacancy hit a record 19.8% in Q4 2025, pushing suburban office cap rates into double digits. Meanwhile, retail vacancy dropped to just 4.1% [13]. These differences show why it’s essential to evaluate cap rates within both specific markets and asset classes at the same time.
4. Absorption Rates
Localized Relevance to Geographic Benchmarking
Absorption rates help gauge how quickly available space is leased or sold in a specific market. The calculation of net absorption, which is new supply minus tenant leases, is often regarded as the most critical metric for understanding submarket performance [16]. To get a clearer picture, it’s essential to focus on submarket data rather than relying on broader metro-wide averages. For instance, while a city like Austin may see an overall annual growth rate of 8%, some submarkets could face saturation and negative absorption, while others might remain underserved [16].
On a national level, the U.S. commercial real estate market recorded an average absorption rate of 5% per quarter in 2024, but this figure conceals wide variations from one area to another [15]. Positive net absorption typically indicates that demand outpaces supply, which often leads to rent increases and tighter cap rates. On the flip side, negative net absorption suggests supply is exceeding demand, potentially causing rents to stagnate or decline, along with rising vacancy pressures [16]. Markets with consistently high absorption rates – above 20% – signal strong demand and are often seen as top-tier investment opportunities [15]. Such detailed submarket data is invaluable for refining investment strategies.
Impact on Investment Decisions
Absorption rate modeling has proven to be a game-changer for investors. Firms leveraging these models reported a 15% higher ROI in 2025 [15]. For example, a Manhattan developer used absorption modeling to predict an 8% monthly absorption rate for a new mixed-use project, hitting 90% occupancy within nine months [15]. Similarly, an Austin-based firm synchronized construction phases with a projected 5% absorption rate, increasing sales velocity by 15% [15].
When analyzing absorption, it’s also vital to account for units under construction. A submarket experiencing negative absorption alongside a significant pipeline of new units slated for completion within 18 months is likely to face worsening conditions before any recovery. To navigate such risks, professionals often create submarket scorecards, which rate factors like net absorption, rent growth trends, and employment growth on a scale of 1–5. Using scenario analysis for real estate portfolios to stress-test outcomes—such as evaluating the impact of occupancy dropping to 88% or flat rent growth—can also help manage potential challenges tied to absorption rates [16].
Applicability Across CRE Asset Classes
Absorption rates play out differently across various commercial real estate asset classes. For instance, office absorption trends are increasingly shaped by remote work and the demand for higher-quality spaces. In contrast, industrial absorption is driven by factors such as proximity to logistics hubs and the rise of e-commerce [15].
In one example, a Chicago property management firm turned around a struggling shopping center by targeting a 6% absorption rate. By adjusting the tenant mix, they increased occupancy from 60% to 85% within 18 months [15]. These examples highlight how understanding and applying absorption rates can help tailor strategies across different property types, ensuring better outcomes for investors and developers alike.
5. Net Operating Income (NOI) and Internal Rate of Return (IRR) by Geography
Localized Relevance to Geographic Benchmarking
Net Operating Income (NOI) is a vital metric for assessing a property’s financial health. It’s calculated by subtracting operating expenses from revenue, excluding financing costs and taxes. Meanwhile, Internal Rate of Return (IRR) tracks the annualized growth over a holding period, factoring in the time value of money [17][18]. Together, these metrics help highlight how location affects portfolio performance.
The relationship between location and these metrics can be summed up with a simple formula: Property Value = NOI / Cap Rate [17]. For example, a property generating $485,000 in NOI could have vastly different values depending on the local cap rate. Regional factors like supply constraints, employment trends, and population growth directly influence cap rates, which in turn shape both NOI valuations and IRR projections. Understanding these dynamics is essential for developing effective investment strategies and assessing risks.
Impact on Investment Decisions
Using NOI and IRR as benchmarks helps investors set minimum return thresholds for different markets. For instance, in a hold-versus-sell analysis by Adventures in CRE, a property with an initial NOI of $485,000 was evaluated. Holding the property for five years, where the NOI grew to $612,000, resulted in a 14.2% IRR and a 2.8x equity multiple – outperforming the 11.8% IRR from an immediate sale [17].
Another example comes from a Dallas investor who modeled local market conditions. A 5% rental increase added $20,000 to cash flow, improving cash-on-cash returns by 1.5%. On the flip side, a 1% interest rate hike increased mortgage payments by $28,000, reducing IRR by 2% [17]. These scenarios underscore how location-specific factors like rent growth and interest rate sensitivity can significantly impact returns.
Ability to Identify Market Opportunities or Risks
Benchmarking NOI can also expose inefficiencies that affect IRR. For instance, Operating Expense Ratios (OER) typically range between 45% and 55%. If a property’s OER exceeds 57%, it may indicate operational inefficiencies, such as high maintenance or utility costs, that need immediate attention [1].
Geographic IRR comparisons can also highlight timing opportunities. For example, loan origination volumes in the Southern U.S. surged by 50% in late 2021 compared to 2019, while the Northeast office market lagged behind [9]. Investors tracking these trends could identify where to allocate capital for better returns. Even small operational improvements can have a big impact: increasing annual NOI by $50,000 can raise a property’s value by approximately $833,000 at a 6% cap rate [17].
Applicability Across CRE Asset Classes
Geographic benchmarks become even more nuanced when considering different asset classes. As of Q3 2024, cap rates varied widely: multifamily properties averaged 6.10%, industrial 7.60%, office 8.90%, and retail 7.00% [1]. These variations mean that typical IRRs, which generally range from 10% to 20% [18], will differ significantly depending on both the asset type and its location. For instance, a multifamily property in a fast-growing Sun Belt market might deliver a 15% IRR, while a similar property in a slower-growth Northeast market might only achieve 10%.
Regularly benchmarking NOI and IRR can yield substantial benefits, such as reducing occupancy costs by 15–20% [10]. Conducting annual NOI reviews ensures that properties remain competitive within their specific geographic and asset class contexts, helping investors stay ahead in dynamic markets.
6. Market Grades and Custom Scoring Systems
Localized Relevance to Geographic Benchmarking
Custom scoring systems take geographic benchmarking to the next level by standardizing diverse data points, making comparisons between markets more meaningful. For example, rather than directly comparing a 50,000 sq ft Class A office building in Manhattan to a 10,000 sq ft Class C property in Tulsa, these systems account for differences in location, size, and quality. This approach ensures a fairer comparison across properties [1].
The best scoring systems combine multiple metrics, including financial factors like NOI (Net Operating Income), ROI (Return on Investment), and cap rates, along with operational data such as occupancy levels and expenses. Market indicators like rental trends and absorption rates, as well as risk metrics like tenant credit scores and criticized loan levels, are also factored in [19]. These metrics are weighted to produce a single, comprehensive score, allowing investors to rank markets and make better-informed decisions across various geographies.
Impact on Investment Decisions
Custom scoring systems streamline decision-making by helping investors focus on high-priority opportunities. Properties with higher scores warrant deeper analysis, while lower scores provide a broader market context. This is especially useful in areas with limited transaction data or when comparing properties across regions with distinct economic conditions [1].
Risk ratings are particularly valuable because they often signal potential issues before delinquency rates rise. For instance, during periods of economic disruption, risk ratings can quickly adjust to reflect changes in repayment expectations, even if forbearance programs temporarily mask delinquent loans [9]. Monitoring criticized loan levels across different areas can highlight potential problem spots early, giving investors time to adjust their strategies. Organizations that have implemented formal scoring systems report occupancy cost savings of 15–20% [10].
Applicability Across CRE Asset Classes
Scoring systems are versatile and can be tailored to the unique needs of different commercial real estate (CRE) asset classes. For example:
- Office properties: Metrics like labor market availability, transit access, and vacancy rates by class (A, B, C) are crucial.
- Retail assets: Factors such as foot traffic, sales per square foot, and local demographic profiles carry more weight.
- Industrial properties: Proximity to ports or intermodal hubs, clear height, and utility reliability are key considerations.
- Multifamily properties: Metrics like rent per unit, turnover rates, and maintenance costs per unit are central to evaluations [10].
Economic incentives also play a significant role in scoring. Markets offering tax abatements, job creation credits, or infrastructure grants can significantly boost development potential, with incentives often ranging from $2,500 to $10,000 per job created [10]. Mature markets, on the other hand, may score higher for their stability. Regular audits of properties – tracking metrics like cost per square foot and facility conditions – ensure that scoring systems stay relevant as market conditions evolve [10].
7. Population Growth and Density
Localized Relevance to Geographic Benchmarking
Population trends play a crucial role in shaping demand within the commercial real estate (CRE) market. While national averages provide a broad picture, they often hide important local differences. For instance, within the same city, one area might have a vacancy rate of just 2%, while another struggles with 12%. This kind of submarket-level analysis is especially critical for industries like retail, where the surrounding population directly impacts revenue. That’s why understanding trade area demographics is a top priority for retail site selection [20].
Migration patterns are another key factor. Recent shifts from expensive coastal cities to regions in the Sun Belt and Mountain West reveal both opportunities and challenges for investors. By drilling down to the neighborhood or zip code level using geospatial data, micro-trends can be identified that broader city-wide statistics might overlook. These localized insights provide a clearer picture of foot traffic and market dynamics, offering a valuable edge in decision-making.
Impact on Investment Decisions
The story of Cavender’s Western Wear illustrates the power of using precise demographic data. By focusing on trade area demographics, the company expanded from 9 stores in 2024 to 27 stores in 2025. This growth coincided with a drop in U.S. retail vacancy rates to 4.2% in 2025, showcasing how targeted strategies can align with broader market trends [20].
Demographics also shape investment strategies based on generational preferences. For example:
- Millennials and Gen Z: These groups often gravitate toward mixed-use developments, walkable urban areas, and tech-enabled office spaces.
- Baby Boomers: Regions with higher concentrations of older adults present opportunities in senior housing, medical offices, and life sciences facilities.
- Remote Workers: Areas with a significant remote workforce drive demand for suburban office spaces, neighborhood retail, and data centers.
Tailoring strategies to these demographic profiles ensures that investments align with the needs and behaviors of local populations.
Ability to Identify Market Opportunities or Risks
| Opportunity | Associated Risk |
|---|---|
| Sun Belt Migration: High demand for housing and retail in the South/West. | Overbuilding: Rapid supply increases could lead to temporary market saturation. |
| Aging Population: Increased demand for senior housing and medical offices. | Regulatory Changes: Healthcare real estate is sensitive to policy shifts and reimbursement changes. |
| Urbanization: Strong demand for multifamily and mixed-use developments in dense urban areas. | High Entry Costs: Competition for prime urban properties can reduce profitability. |
| Remote Work: Growth in suburban office spaces and service-oriented retail. | Economic Sensitivity: Suburban markets may face greater risks from local employment fluctuations. |
In areas facing population decline or outdated infrastructure, risks of asset obsolescence – especially for traditional office and retail spaces – become more pronounced. By keeping a close eye on these demographic shifts, investors can adjust their strategies early, avoiding potential pitfalls and capitalizing on emerging opportunities. This proactive approach ensures portfolios remain resilient in a changing market landscape.
8. Foot Traffic and Location Data
Localized Relevance to Geographic Benchmarking
When it comes to geographic benchmarking, understanding how people move and behave within a location is crucial. Foot traffic data today goes far beyond simple headcounts. Using advanced mobility analytics, it’s now possible to track movement patterns, time spent in specific areas, and even search intent within property zones. This level of detail provides a clear picture of how spaces are actually used, making geographic benchmarking more actionable than ever before [21].
One major improvement is the ability to define catchment areas using real device movement rather than relying on arbitrary measures like drive-time radii. This approach paints a more accurate picture of a property’s reach by identifying where visitors come from and how they interact with the space [20]. For instance, in retail settings, learning that visitors spend 28 minutes in a food court compared to just 2 minutes in an entrance corridor can directly influence leasing plans and revenue forecasts [21]. These insights transform raw data into meaningful strategies.
Impact on Investment Decisions
Foot traffic data has become a valuable tool for refining investment strategies. By combining demographic data with movement patterns, investors gain a detailed understanding of visitor behavior, which enhances market evaluations [23].
This information plays a direct role in guiding investment decisions. For example, in Miami-Dade, foot traffic in office-heavy neighborhoods is currently 38% higher than in 2019, while in Washington D.C., it remains 40% below pre-pandemic levels [24]. Such trends are essential for identifying where to allocate capital. With U.S. commercial real estate investments reaching $171.6 billion in Q4 2025 – a 29% increase from the previous year – these granular insights help pinpoint the most promising opportunities [20].
Ability to Identify Market Opportunities or Risks
Foot traffic data also excels at identifying market dynamics that traditional metrics might overlook. By analyzing catchment area overlaps, businesses can determine whether competitors are targeting the same audience, which can inform leasing or marketing strategies [22]. Using anonymized mobile geolocation data, this type of analysis can be scaled efficiently.
This data is also useful for identifying which anchor tenants are still driving significant traffic in the age of e-commerce. For instance, brands like Target, Apple, and Ulta continue to attract visitors, while traditional department stores are seeing a decline [24]. Additionally, tracking search queries – such as frequent searches for "ATM" or specific brands – can shed light on navigation challenges or unmet tenant needs, helping landlords negotiate leases or improve property layouts [21].
Applicability Across CRE Asset Classes
While traditional metrics like occupancy rates or rent growth focus on financial outcomes, foot traffic data provides a behavioral perspective. Though retail properties benefit most obviously from this data, its applications extend across various commercial real estate asset classes.
For office properties, mobility data highlights the shift from downtown hubs to suburban areas due to hybrid work models [23]. For industrial properties, foot traffic near distribution corridors can validate assumptions about last-mile delivery efficiency [20]. Even in multifamily developments, tracking pedestrian activity around transit hubs and amenities helps assess location quality relative to competing properties.
The global market for alternative data, including mobility analytics, is expected to grow to $135.72 billion by 2030 [20]. This growth underscores the increasing importance of combining behavioral insights with traditional financial metrics to create a more complete picture for geographic benchmarking across all sectors of commercial real estate.
9. Delinquency Rates by Geography
Localized Relevance to Geographic Benchmarking
Delinquency rates provide a snapshot of financial stress across different markets, highlighting areas still struggling versus those on the mend. For example, the overall bank CRE delinquency rate stood at 0.9% in Q4 2021, with the Northeast slightly higher at 1.3% [9]. These rates are influenced by factors like local economic conditions and the performance of specific industries [25]. The disparities become even more evident when looking at individual metropolitan statistical areas (MSAs). In October 2021, the New Orleans MSA reported a striking delinquency rate of 11.16%, compared to just 2.59% in the New York MSA [25].
"Distress across the US differs depending on several economic factors including population density, unemployment rates, and COVID‑related factors", explained Julianne Cavaliere from Trepp [25].
For investors, these variations are crucial. They help pinpoint areas where capital may be at risk and highlight potential opportunities for acquiring distressed assets.
Impact on Investment Decisions
Combining delinquency rates with criticized loan levels offers a fuller picture of market health. While delinquency rates often lag behind economic changes – sometimes obscured by lender forbearance – risk ratings respond more quickly, providing a real-time lens into geographic vulnerabilities [9]. This dual approach helps investors detect potential problems before they surface in official metrics.
Between June 2020 and October 2021, major markets like New York, Chicago, and Houston saw delinquency rates drop by over 400 basis points, even as individual properties faced significant challenges [25]. For instance, the $328.93 million Palmer House Hilton loan in Chicago was in foreclosure, marking one of the region’s largest delinquent loans [25]. Similarly, the $235.4 million Woodbridge Center loan in New York was over 90 days delinquent and split between two CMBS tranches [25]. These cases underscore how improving overall metrics can mask severe property-specific distress.
Ability to Identify Market Opportunities or Risks
Geographic delinquency data reveals areas where certain property types face heightened risk. In late 2021, retail delinquency in the New York MSA hit 10.17%, even though the market’s overall rate was relatively low [25]. In the Northeast, office delinquency surpassed pre-pandemic levels, while the lodging and retail sectors struggled to recover [9]. These pockets of distress can help investors identify undervalued assets or regions that may be on the brink of recovery.
Risk concentration also plays a significant role. About one-third of the private-label CMBS balance is concentrated in just five MSAs: New York, Los Angeles, Dallas, Washington, D.C., and Houston [25]. This means that distress in these key markets can disproportionately impact portfolio performance, making it essential to benchmark geographically for effective risk management.
Applicability Across CRE Asset Classes
Delinquency trends vary widely by property type and location. The industrial and multifamily sectors showed strong recoveries across most U.S. regions, supported by robust new loan originations [9]. On the other hand, the lodging sector continued to struggle in the Midwest and Western regions, though it nearly returned to pre-pandemic levels in the South [9]. Meanwhile, office and retail properties remained unpredictable, with post-pandemic shifts creating uneven recoveries [9][25].
Regional assessments further illustrate these differences. The Mid-Atlantic region saw elevated risk levels across all major CRE categories, while New England reported the lowest risk for multifamily properties [9].
"It is evident that recovery is happening at different paces across the country and that turmoil still exists in some areas of the U.S.", noted Julianne Cavaliere from Trepp [25].
These insights allow portfolio managers to fine-tune their strategies across asset classes and regions. By understanding these granular patterns, they can make informed adjustments to better navigate the complexities of the market.
10. Using CoreCast for Geographic Benchmarking
Localized Relevance to Geographic Benchmarking
CoreCast brings geographic benchmarking to life with real-time insights tailored for U.S. commercial real estate. It presents metrics in USD, measures property sizes in square feet, and uses the MM/DD/YYYY date format, making it perfectly aligned with U.S. standards. The platform’s integrated map takes it a step further, visualizing properties within their competitive landscapes. Overlays like vacancy rates by ZIP code or metro area help pinpoint trends that might otherwise go unnoticed. Unlike generic market averages, CoreCast’s interactive map focuses on localized data, offering a sharper lens for detailed analysis. This kind of precision is invaluable for making informed investment decisions.
Impact on Investment Decisions
CoreCast simplifies how geographic data is presented, making it easier for stakeholders to act quickly. For example, if the platform shows a 5% higher cap rate in secondary markets like Nashville, TN, compared to coastal cities, portfolio managers can use this data to justify shifting investments from riskier coastal areas to more stable Midwest logistics hubs.
Additionally, CoreCast offers real-time tracking of deal pipelines, enabling users to filter opportunities by location and stage. Key metrics like NOI, IRR, and absorption rates are consolidated into one dashboard. Imagine benchmarking a Dallas office portfolio against similar properties in Atlanta – CoreCast makes this comparison instant and seamless.
Ability to Identify Market Opportunities or Risks
CoreCast isn’t just about supporting decisions – it’s about uncovering opportunities and mitigating risks. For instance, it can map population growth alongside absorption rates. Suburbs of Phoenix showing a +2.5% year-over-year population increase but low absorption could signal untapped retail investment potential. Similarly, foot traffic data overlays can identify underperforming multifamily submarkets in Florida, highlighting a potential 15% NOI increase compared to national averages.
On the flip side, CoreCast helps flag risks. It tracks delinquency rates by geography and offers custom scoring based on metrics like vacancy and cap rate trends. For example, users might spot higher delinquency rates in hurricane-prone areas of the Southeast compared to the Midwest or receive alerts about declining foot traffic in urban centers as remote work reshapes demand.
Applicability Across CRE Asset Classes
CoreCast’s tools are designed to work across all asset classes and risk profiles, all within a single interface. Office investors can analyze hybrid-space demand in tech hubs, while industrial users can monitor logistics absorption in areas like the Inland Empire, CA. Retail professionals can dive into foot traffic trends in suburban power centers, and multifamily operators can track rent growth in Sun Belt markets experiencing population booms. By combining advanced mapping, financial metrics, and operational data, CoreCast delivers a comprehensive approach to geographic benchmarking, aligning perfectly with the needs of today’s commercial real estate professionals.
Using Location Data in Commercial Real Estate Research | Moody’s Analytics
Conclusion
Geographic benchmarking is reshaping how commercial real estate professionals manage portfolios and make investment decisions. By focusing on key metrics like occupancy rates, rent growth, cap rates, absorption rates, NOI, IRR, population trends, foot traffic, and delinquency rates, investors gain the insights they need to pinpoint underperforming assets, uncover new opportunities, and address risks before they impact returns. These data points directly inform decisions about capital allocation and whether to reposition or divest specific assets.
The trend toward data-driven strategies is gaining momentum. By 2030, analytics are projected to influence 85% of CRE investment decisions, a sharp rise from the current 45% [1]. Professionals who embrace geographic benchmarking and data analysis now will be better equipped to leverage these insights for competitive advantage.
Achieving success requires consistent tracking, standardized reporting, and actionable insights. Conducting quarterly reviews of benchmarks ensures strategies stay aligned with shifting market conditions. Blending algorithmic data with local market knowledge allows professionals to account for subtleties that raw metrics might overlook. Prioritizing impactful indicators like NOI and absorption rates helps detect risks earlier, enabling faster and more informed responses. This is where having an integrated platform becomes a game-changer.
Platforms like CoreCast streamline data and simplify decision-making. With features like integrated mapping, real-time metrics formatted for U.S. standards (USD, square feet, MM/DD/YYYY), and automated reporting, CoreCast eliminates the inefficiencies of manual data reconciliation. Its unified approach to underwriting, pipeline tracking, and portfolio analysis allows professionals to benchmark across geographies effortlessly. This level of efficiency leads to smarter capital allocation and stronger portfolio performance.
From tracking occupancy rates to analyzing population trends, every metric underscores the importance of geographic benchmarking in achieving better results in CRE. Whether it’s identifying the next high-growth market in the Sun Belt, optimizing regional capital allocation, or catching early signs of trouble in declining submarkets, systematic benchmarking offers a clear edge. Those who adopt these practices today will be better prepared to navigate future market changes and deliver stronger returns.
FAQs
What are the top 3 metrics for my asset type?
The three most important metrics to monitor for your asset type are Net Operating Income (NOI), occupancy rate, and operating expenses. These metrics are essential for assessing performance in commercial real estate, offering a clear way to measure and compare how well an asset is performing.
How do I benchmark submarkets, not just cities?
To evaluate submarkets with precision, shift your focus to neighborhoods or distinct areas within a city instead of assessing the entire market. Tools like GIS mapping and drive-time analysis can help you outline trade areas and get a clearer picture of local consumer behavior. Pay close attention to key metrics such as rental income, occupancy rates, and foot traffic. Additionally, consider factors like demographic shifts and the level of competition in the area. This approach provides sharper insights, making it easier to make informed decisions tailored to specific submarkets.
How should I combine cap rates and IRR by market?
To assess both cap rates and IRR by market, start by examining cap rates to gauge current property values and overall market conditions. Then, incorporate IRR to evaluate expected annualized returns, taking into account cash flows and planned exit strategies. When used together, these metrics offer a more complete view of market performance and potential investment opportunities.