Case Study: Submarket Analysis for Retail Properties
Submarket analysis is the key to making smart retail property investments. Instead of focusing only on general market trends, this approach digs into specific neighborhoods and shopping areas to understand their unique dynamics. Here's why it matters:
Risk/Return Profiles: Retail properties in different submarkets have varying risks and returns due to factors like location, consumer behavior, and competition.
Local Trends: Shifting foot traffic, demographic changes, and e-commerce growth can quickly change a submarket's performance.
Tools for Precision: Techniques like drive-time analysis and GIS mapping help define realistic trade areas and consumer profiles.
Key Takeaways for Retail Submarket Analysis
Use Advanced Tools: Platforms like CoreCast and GIS systems help analyze data in real-time.
Focus on Demographics: Income, age, spending habits, and lifestyle data are critical for understanding consumer behavior.
Monitor Trends: Stay updated on local and national retail trends, like the growth of e-commerce and changing work patterns.
Plan for the Future: Anticipate changes in demographics, transportation, and development over the next 5–10 years.
By combining data-driven tools and detailed local insights, you can make better decisions and maximize your retail property investments.
Retail Market Selection: 5 Steps for Choosing a New Location
Submarket Analysis Framework for Retail Properties
To analyze retail submarkets effectively, you need a framework that integrates multiple data sources to assess demand, supply, and demographic trends. At its core, this process begins with defining trade area boundaries, which act as the foundation for all subsequent analysis. As Community Economic Development explains:
“Defining a downtown or business district’s trade area is an important first step in any market analysis. This step is crucial because it defines approximate boundaries that will serve as the basis for further study.”
Data Sources and Analysis Tools
Today’s retail submarket analysis relies on more than just basic demographic data. Tools like Geographic Information Systems (GIS) are essential, enabling analysts to layer data sets and visualize how various market factors interact.
Two main methods are commonly used to define trade areas: radial studies and drive-time analysis. Radial studies are straightforward, drawing circular boundaries around a property - typically at 1-mile, 3-mile, and 5-mile intervals. However, this method has its drawbacks, as it doesn’t account for real-world barriers like highways, rivers, or other obstacles that might limit customer access.
Drive-time analysis, on the other hand, offers a more realistic perspective. By incorporating transportation networks and GIS mapping, this method factors in traffic patterns and physical barriers to create more accurate trade area boundaries.
Another key component is demographic segmentation, which identifies consumer profiles within the trade area. These tools go beyond basic statistics, analyzing spending habits, lifestyle preferences, and shopping behaviors. Metrics like household income, age distribution, education levels, and consumer spending categories provide a detailed picture of the target audience.
The rise of big data analytics has further enhanced the accuracy of market forecasting, improving predictions by 15.2% [2]. This technology allows analysts to better understand and predict supply and demand trends. Key metrics include inventory levels, absorption rates, and days on market, all of which vary significantly by location.
Aligning Retail Properties with Target Submarkets
Using advanced tools and data, aligning retail properties with target submarkets involves matching property features to the preferences and behaviors of potential consumers. This process requires going beyond basic demographics to consider factors like spending patterns, shopping habits, and lifestyle drivers.
The first step is setting SMART goals (Specific, Measurable, Achievable, Relevant, Time-bound) based on current market data. According to Realmo:
“Investors who define their criteria using market data - such as vacancy rates, average lease terms, and neighborhood growth trends - are more likely to identify viable opportunities and avoid overvalued properties.”
This approach reduces the risk of broad, generic targeting and encourages more precise decision-making.
To position a property effectively, understanding local consumer habits and competition is critical. Where do customers come from? How do they shop? What influences their purchasing decisions? These insights help determine the right tenant mix and property strategy. Complementary businesses can create synergies that boost customer traffic, while an oversupply of similar retailers can dilute market share.
Location-specific factors also play a major role. Features like visibility, accessibility, parking, and proximity to traffic generators (e.g., large employers or entertainment venues) can significantly impact a property's ability to attract and retain tenants. These attributes must align with the operational needs of the retail categories being targeted.
Market trends add another layer to this analysis. For example, the growth of e-commerce is reshaping demand for retail spaces, while shifts in work patterns influence foot traffic in different submarkets. Still, traditional brick-and-mortar stores remain dominant, accounting for 85% of retail sales in the U.S. in 2024 [3]. This highlights the enduring appeal of in-person shopping, even as consumer preferences evolve.
Finally, financial feasibility must be assessed to ensure the submarket supports projected returns. This includes evaluating rent levels, operating costs, tenant improvement allowances, and lease terms typical for the area. While properties in premium submarkets may command higher rents, they often come with greater tenant improvement costs and stricter tenant requirements.
It’s also essential to consider how submarkets might change over time. Demographics, new developments, and transportation patterns are constantly shifting, which means successful alignment requires not only a solid understanding of current conditions but also the ability to anticipate changes over the next 5–10 years, the typical length of retail leases.
Common Challenges in Retail Submarket Analysis
Retail submarket analysis isn't without its hurdles. These challenges can derail investments and rack up significant costs, often stemming from issues like poor data quality, fast-changing market dynamics, and the intricate factors that shape retail performance. Let’s dive into three key areas where these obstacles emerge: data gaps, shifting demographics, and external property influences.
Incomplete Data and Limited Detail
One of the biggest headaches in retail submarket analysis is fragmented data. Over half of retail and grocery businesses struggle with cross-department data sharing, leaving critical insights about customer behavior and market trends stuck in silos - and those blind spots can cost millions [5].
The financial toll is staggering. Poor data quality costs organizations an average of $15 million annually [7]. For retail submarket analysis, this means flawed decisions based on outdated or incomplete information. Ted Friedman, VP and Analyst at Gartner, puts it bluntly:
“Poor data quality is a major contributor to a crisis in information trust and business value, negatively impacting financial performance.”
Outdated data only worsens the problem. With market conditions shifting quickly, relying on months- or years-old information can lead to costly missteps. On top of that, manual data handling introduces errors, making the analysis process even more prone to inaccuracies. This leaves businesses with fragmented, unstructured, and often irrelevant insights [6].
Changing Demographics and Trade Area Boundaries
Demographic shifts are another major challenge, especially as they disrupt traditional trade area boundaries. Aging populations, fluctuating incomes, and the rise of remote work are redrawing the maps analysts once relied on.
For instance, a shopping center that thrived on office workers grabbing lunch may now struggle, while suburban retail spots could see unexpected weekday booms. Population mobility further complicates matters, as people increasingly live, work, and shop across different submarkets, making it harder to define clear trade areas. Ryan Pesch and Bill Ryan from the University of Wisconsin-Madison explain:
“No community has a single trade area. In reality, each individual business has its own trade area.”
This fluidity demands a more nuanced approach to understanding customer behavior and market dynamics.
Impact of Nearby Properties on Retail Performance
External factors, like neighboring properties, also play a big role in retail success - or failure. Anchor tenants, for example, can significantly influence performance. Their presence can boost rents by 5%, while their departure often spells trouble for surrounding businesses [10].
Mixed-use developments add another layer of complexity. Office buildings, residential units, and entertainment venues all affect foot traffic in unique ways. Properties near public transit hubs, for example, typically see a 10% to 20% value bump compared to less accessible locations [9].
Then there’s the challenge of competitive clustering. While complementary businesses can create synergy and draw more customers, overcrowding with similar retailers can dilute market share and hurt profits. Infrastructure changes - like new highway exits or public transit expansions - can also shift traffic patterns, often in unpredictable ways.
Finally, local government decisions on zoning, parking, or incentives introduce yet another variable, creating uncertainty that analysts must account for. Together, these external influences highlight the need for a comprehensive and flexible approach to retail submarket analysis.
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Proven Solutions for Better Submarket Analysis
Taking on the challenges of retail submarket analysis requires tools and strategies that can turn fragmented data into actionable insights. With the right approach, commercial real estate professionals can navigate these obstacles and achieve measurable outcomes.
Using Advanced Analytics Platforms
Advanced analytics platforms are changing the game for retail submarket analysis. These tools go beyond just collecting data - they use artificial intelligence and machine learning to uncover patterns that traditional methods often miss.
For example, retailers that used AI tools like chatbots during Black Friday weekend saw a 15% increase in conversion rates [11]. Additionally, 60% of retail buyers reported that AI-enabled tools improved demand forecasting and inventory management in 2024 [11]. This kind of precision directly influences smarter investment decisions when assessing retail properties.
A standout example is CoreCast, The Fractional Analyst's real estate intelligence platform. Priced at $50 per user per month during beta (rising to $105 post-launch), it offers demographic segmentation and performance tracking - critical features for effective submarket analysis.
When choosing an analytics platform, focus on tools with real-time data gathering capabilities. As Dmytro Tymofiiev, Delivery Manager at SPD Technology, points out:
“Retail is all about understanding your customers and anticipating their needs. It always was, but businesses are better equipped with data now. We’re not just talking about numbers; we’re talking about turning those numbers into an actionable checklist.”
Look for features like unified inventory management, rapid reporting, and AI-driven cross-channel forecasting. While the investment is considerable - brands are projected to spend $31.08 billion on retail analytics platforms by 2032 [12] - the returns are equally compelling, with 92% of global business leaders reporting measurable results from data analytics investments [13].
These platforms are especially valuable for addressing retail-specific challenges like fluctuating foot traffic and local consumer preferences. By integrating performance metrics with inventory data, you can refine your submarket insights even further.
Combining Inventory Data with Performance Metrics
Pairing inventory data with performance metrics provides a deeper understanding of submarket dynamics. This approach reveals not just what’s happening in a market, but why - and what it means for the future.
For instance, sales per square foot combined with inventory turnover rates offers immediate insight into space efficiency. When evaluating a retail property, analyze how tenants are performing relative to their footprint. Properties where tenants achieve high sales per square foot with optimal inventory turnover often indicate strong market fundamentals.
Another valuable metric is Gross Margin Return on Investment (GMROI) paired with occupancy rates. A high GMROI alongside stable occupancy suggests that retailers in the area can sustain profitability - an important sign of long-term investment potential.
Additionally, consider Average Transaction Value (ATV) alongside customer frequency. Submarkets with high ATV and frequent repeat visits demonstrate strong consumer spending power and loyalty, which translates to stable rental income for property owners.
The data underscores the importance of physical retail: 40% of consumers make in-store purchases at least once a week, compared to 27% who shop online weekly [14]. This highlights the enduring value of well-located brick-and-mortar stores.
Vadym Herman, a Datawiz expert, emphasizes the need for this integrated approach:
“Retail is all about competition, so monitoring business performance, optimizing operations, understanding customer behavior, and boosting sales are crucial.”
By combining these metrics, you can segment inventory based on customer demand, categorizing submarkets into fast-moving, slow-moving, and seasonal performance areas. This segmentation helps pinpoint markets with consistent returns and those requiring more specialized strategies.
When to Use Professional Analyst Support
Even with advanced tools and integrated metrics, some scenarios demand professional expertise. Knowing when to seek specialized analysis can make the difference between a profitable investment and a costly misstep.
Complex mixed-use developments are one such scenario. When retail properties are part of larger projects that include office, residential, or entertainment spaces, the interactions between these components create variables that standard tools often fail to capture. Professional analysts can model these relationships and their impact on retail performance.
For high-stakes decisions, the financial risks are clear. With the market projected to grow from $3.69 trillion in 2021 to $5.85 trillion by 2030, even a 1% rise in interest rates can reduce property values by up to 10% [16]. Errors in submarket analysis can carry significant financial consequences.
The Fractional Analyst's direct servicing team offers tailored support, including custom underwriting, asset management, and market research. This is especially useful for complex local dynamics or non-standard property types, where historical data may not provide sufficient insight.
Regulatory challenges also signal the need for professional help. Zoning changes, tax incentives, or infrastructure projects can significantly alter submarket dynamics. Experienced analysts are equipped to evaluate these factors and their potential impact on property performance.
Brian DeChesare, Founder of Mergers & Inquisitions, sums it up well:
“The purpose of commercial real estate market analysis is to generate reasonable assumptions for use in financial models and to ensure that the qualitative aspects of the market and property meet your requirements.”
Professional analysts excel at turning complex data into actionable insights. They can conduct competitive analyses, assess location factors like accessibility, and perform detailed financial feasibility studies. If your project requires custom financial modeling, investor reporting, or pitch decks for intricate retail investments, professional support can be a game-changer for informed decision-making in dynamic markets.
Key Takeaways and Best Practices
Blending data-driven insights with market expertise is the cornerstone of successful retail submarket analysis. This case study highlights three critical areas to focus on for maximizing retail investment returns.
Focus on High-Performance Submarkets
Investing in submarkets with strong fundamentals often leads to consistent returns. These high-performing areas typically show above-average growth rates and maintain higher occupancy levels compared to the broader market [1]. The trick lies in identifying submarkets where favorable demographic trends align with rising property values [1]. For example, areas with growing household incomes, increasing population density, and a youthful demographic mix are often ripe for retail success. Submarkets with a significant presence of millennials and Gen Z consumers - who are projected to make up 67% of the U.S. population by 2030 - are particularly attractive for retailers catering to digital-first shopping habits and convenience [21].
To go beyond surface-level metrics, it’s essential to dive into the economic drivers and consumer behavior patterns that fuel retail success. This means keeping an eye on global retail trends, local economic indicators, competitor activity, and location-specific data. Tools like GIS platforms can help identify top-performing locations, while void analyses shed light on local demand and tenant composition. Understanding these dynamics is crucial for accurately gauging a property's risk and return potential.
These insights underscore the importance of maintaining access to the most up-to-date market data.
Keep Market Data Current
Retail markets evolve quickly, and relying on outdated information can lead to costly missteps. For instance, 73% of shoppers now use multiple channels during their buying journey [20]. This shift has created new patterns that traditional analysis methods may overlook.
Consumer preferences are changing rapidly. Many shoppers now begin their purchasing journey online, often via mobile devices [19]. Experience-driven shopping is also gaining traction as customers look for memorable in-store encounters, while social commerce enables direct purchases through platforms like Instagram and TikTok [19].
To stay ahead, retailers should adopt tools like customer relationship management (CRM) systems to collect and analyze customer data [20]. Predictive analytics can also help forecast demand patterns [18]. By customizing market research to include current demographic and spending data, retailers can ensure their investment decisions align with today’s consumer behaviors. Falling behind on these trends could mean losing market share to more nimble competitors [20]. As David Kennett from StoreTech put it:
“The retail industry is in constant flux, with new and emerging consumer trends driving the need for retailers to adapt and innovate continuously. Retailers who fail to keep up with these trends risk losing to more agile competitors.”
Regularly reviewing market data and seeking input from tenants, property managers, and local stakeholders can help you stay aligned with evolving market dynamics. Routine meetings with key players ensure your strategies remain relevant and effective.
Keeping your data current also highlights when more tailored financial analysis might be necessary.
Consider Custom Financial Analysis Services
For complex investments, custom financial analysis services can be a game-changer. As economic conditions shift and deals grow more intricate, commercial real estate (CRE) firms are under pressure to deliver faster, more precise financial models [22].
This type of analysis is especially useful for mixed-use developments, unconventional property types, or markets with unique local characteristics. Custom financial reporting can sharpen decision-making, improve accuracy, and uncover ways to reduce risk while optimizing resources [24].
In high-stakes situations, custom financial analysis goes beyond standard tools, offering tailored solutions that reveal hidden opportunities. With over 68% of CRE leaders expecting market conditions to improve by 2025 [23], having access to expert analysis can position your investments to take advantage of emerging trends. Professional support is particularly valuable when navigating regulatory challenges, preparing investor presentations, or creating detailed financial models for lenders.
Conclusion
The key to thriving in retail property investments lies in a thorough understanding of submarkets. As Lynna Paradiso from The Cauble Group aptly puts it:
“Thorough analysis is the cornerstone of successful commercial real estate investing.”
Take, for instance, JB2 Investments' Norman Creek deal in Oklahoma City. By targeting a submarket with strong demand and high occupancy rates, they exceeded projections by an impressive 34% [25]. This achievement highlights the critical role of evaluating factors like demand, occupancy, and rent growth potential [25].
Demonstrating the power of market analysis, both local dynamics and broader trends significantly influence investment outcomes. One example is the Orlando-Kissimmee-Sanford MSA, which experienced 25% growth between the 2010 and 2020 census [1]. Such demographic shifts can unlock substantial opportunities, but success depends on the ability to turn raw data into actionable strategies.
Advanced tools like CoreCast are designed to simplify this process by converting complex data into clear insights [26]. This approach becomes even more essential for intricate investments, such as mixed-use developments or those shaped by unique local characteristics. Platforms like The Fractional Analyst offer tailored support through elite financial analysts and self-service options via CoreCast, ensuring investors have the resources needed to make informed decisions. The case study evidence makes it clear: expert analysis leads to better outcomes.
Whether you’re looking for underwriting, asset management, market research, or custom financial models, leveraging expert insights can help you stay ahead of shifting consumer preferences and demographic trends. The key is to focus on high-performing submarkets that align with these evolving dynamics.
FAQs
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Drive-time analysis takes a practical approach to defining trade areas by considering real-world travel conditions like traffic flow, road speeds, and accessibility. Instead of relying on straight-line distances as in radial studies, it measures how far customers can realistically travel within a given time frame.
Radius studies often miss the mark by either overstating or understating trade areas. Drive-time analysis, on the other hand, offers a more accurate view of customer accessibility and reach. This level of detail helps commercial real estate professionals make smarter decisions about where to establish sites and assess market opportunities.
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Demographic changes significantly impact retail submarkets by shaping customer preferences, shifting demand, and redefining target audiences. Factors like population growth, age distribution, income levels, and household dynamics can influence how and where people shop, pushing retailers and investors to rethink their approaches.
Take, for instance, an aging population - this could drive up demand for healthcare-related retail options. Similarly, areas experiencing rising income levels might see an influx of luxury or high-end stores. These shifts often lead to adjustments in retail locations and a fresh look at investment opportunities to meet the changing needs of the market.
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Combining inventory data with performance metrics is a game changer for understanding how retail operations are running. It lets businesses see the bigger picture - how inventory levels align with sales and profitability - so they can make smarter decisions about managing stock and meeting customer needs.
This approach also opens the door to real-time tracking and predictive insights. Retailers can respond quickly to market trends, keeping them ahead of the competition. With this data-driven strategy, there’s potential to streamline operations, improve customer satisfaction, and strengthen performance in specific markets.