Site Selection Analysis: An In-depth Guide

Choosing the optimal location for a new store, warehouse, or other facility can make or break business growth. That’s because adding a new brick-and-mortar location can cost millions and may involve a lease agreement lasting years at a time — that’s a huge investment, even for commercial giants. If that investment doesn’t generate enough revenue in return, it can lead to major losses. 

To ensure positive return on investment, businesses typically follow a data-driven site selection analysis process that helps eliminate bad sites, score and rank potential winners, and clearly justify site recommendations to the final decisionmakers. 

In this article, we cover the key elements to a successful site selection analysis and how you can combine them to guide more confident real estate investments for your business. 

What Is Site Selection Analysis?

A site selection analysis is a data-driven evaluation of potential new locations for investment, usually undertaken by businesses looking for advantageous sites for new real estate assets. This may include store locations, warehouses, offices, fueling and charging hubs, and other facilities. 

While the full site selection process may include additional steps beyond the analysis (such as site visits, due diligence, and negotiation with external stakeholders), a site selection analysis is key to ensuring final site recommendations are based on repeatable evaluation and defensible  comparison to other potential sites. This leads to siting decisions that support positive ROI and earn the support of internal and external stakeholders. 

Many types of organizations use site selection analysis to make real estate decisions, from retail and fueling brands to real estate developers and tolling companies. In this guide, we focus on site selection analysis for commercial real estate investments, especially retail site selection. 

Key Components of Site Selection Analysis

As we dive deeper into the core elements of site selection analysis, we’ll cover a variety of metrics, data sources, and analysis types that are particularly useful for retail site selection. These include: 

• Market demand and consumer behavior analytics 
• Aggregated demographic data, including socioeconomic factors 
• Foot traffic data and mobility patterns 
• Competitive analysis 
• Site constraints, access, and infrastructure 
• Costs, zoning, and regulatory factors 
• Geographic Information Systems (GIS) and mapping 

After we’ve defined these key components, we’ll then explain how they typically come together to inform site selection decisions. 

Market Demand and Consumer Behavior 

To determine the best site for a new retail location, brands often need to first identify trade area markets with consumer behavior trends that can support business growth. For a coffee retailer, this might be a market with a big peak in morning commuter traffic, while a toy store might focus on markets with population growth demographics of families with young children. 

More broadly, brands are looking for markets where potential consumer demand exceeds current supply from either competitors or their own existing stores. 

Many of the metrics explored below, including foot traffic data and demographics, help quantify consumer behaviors in ways that allow retailers to objectively evaluate market demand. 

Demographic Data and Socioeconomics 

Demographic data helps businesses understand where their target market is located. Let’s revisit the toy store example from the previous section: demographic data can help reveal locations where families with children are already living and traveling, helping identify not just where consumer activity is high in general, but specifically where their target customer is most active. 

Likewise, demographic data on household incomes can be used to identify spending power, which helps luxury- and affordability-focused brands alike target locations with ample demand for their product(s). 

However, demographics alone don’t necessarily reveal the most convenient or likely locations for potential customers to visit your new store. Pairing demographics with mobility data, including vehicle and foot traffic patterns, helps bridge that gap. 

Foot Traffic Data and Mobility Patterns 

Understanding how people move is key to choosing a location that drives store visits and sales. One way businesses commonly incorporate mobility insights into their site selection analysis is by measuring foot traffic and vehicle traffic counts at potential locations. Foot traffic counts measure how many pedestrians stop at or pass by a given location during a set time frame, while vehicle traffic counts do the same for vehicles instead of pedestrians.  

While some businesses may be more impacted by walking or driving behaviors than others, both foot and vehicle traffic counts can be helpful in predicting the likelihood customers will visit a potential location. The more often people already stop at or pass by a given location, the more likely a store in that location is to earn enough store visits to support a positive return on investment. 

But foot and vehicle traffic counts aren’t the only mobility metrics businesses can use to evaluate potential store locations. Other helpful location analytics include: 

• Origin-Destination patterns – To understand where people travel to and from, and the top routes they use on the way 
• Travel times – To forecast demand for different products or services based on how far people tend to travel before they arrive at a potential location. 
• Congestion factors – To understand how vehicle delays and traffic surges might impact store visits, logistics, and operations at a given location 
• Traffic by time of day, day of week, and season – To understand how a given location may be impacted by commuter behaviors, tourist patterns, special event traffic, and other traffic fluctuations. 
• Tenant mix evaluation – To identify how your target market interacts with nearby businesses. 

Mobility patterns can also help businesses identify locations that optimize supply chain logistics and associated costs. For example, truck data can reveal the top freight routes and typical travel times on freight corridors, helping businesses better analyze last-mile delivery and find locations that support reliable shipment schedules or minimize fuel usage. 

Competitive Landscape and Competitive Analysis 

An otherwise great location can fail to perform if the local market is already saturated. That’s why understanding the competitive landscape is key to identifying sites that actually drive ROI.  

Competitive analysis involves mapping out existing competitor locations that may capture a portion of the total customer demand in a given location, as well as your own existing locations that could cannibalize new sites. 

Bear in mind that nearby competition doesn’t necessarily mean a site won’t perform, and some co-tenants can even boost store performance at a potential location. Consider whether overall demand is high enough to support multiple businesses in a given location, or if the new site is especially well-positioned to capture a portion of that demand. 

Site Constraints, Access, and Infrastructure 

Even when demand is high, certain site constraints like topography or poor access to utilities can create major barriers to site development and operations, eating away at a site’s performance. 

Similarly, factors like curb visibility, ingress and egress points, and parking infrastructure can make or break a site’s success. If it’s hard for people to find or access a site, you can bet fewer customers will actually make it through the door. These types of constraints can also impact performance for non-customer-facing, industrial facilities like warehouses and freight hubs. 

Costs, Zoning, and Regulatory Reality 

Local zoning, development costs, workforce availability, and regulations can also impact ROI, both positively and negatively. These factors contribute to a site’s “feasibility” — essentially, how practical it is to invest in a particular location, and how much work it takes to drive a profit there.  

In some cases, these factors may become deal-breakers for a potential site. For example, high development costs or specific permitting requirements might create insurmountable hurdles for your business, or lead to a site that has to perform extremely well just to break even. 

In other cases, market dynamics like high customer demand or available incentives may outweigh the downsides of a complicated regulatory or economic landscape. Talking with local governments can sometimes be a key factor in determining the feasibility of a potential site. 

Geographic Information Systems and Mapping 

Geographic Information Systems (GIS) are tools that businesses can use to combine multiple spatial data layers into a map format. This can help visualize trade areas and catchments as well as geo- or topographical features that may impact feasibility and performance. 

One of the key benefits to GIS tools is their ability to turn abstract location data into mapped visualizations that can lead to clearer insights about how a site’s physical environment might impact its future growth. 

Benefits of a Data-Driven Site Selection Analysis

Choosing a site is a high-stakes decision that can dramatically impact business performance. That’s why decisionmakers look for objective, defensible measures of site potential instead of relying on instinct alone to guide the site selection process.

A data-driven site selection analysis helps with: 

• Risk mitigation: Data can help identify potential risks from unreliable supply chains, dangerous traffic patterns, accessibility concerns, and more. 
• Higher performance: From mobility patterns to development costs, data helps quantify the expected ROI of potential sites and forecast where customer demand is most likely to support future growth. 
• Operational efficiency: Data on spending behaviors, traffic by time of day, and more can inform operational decisions like store hours, staffing, and shipment schedules that maximize efficiency and minimize costs. 
• Defensible decisions: Before a final site selection decision is made, the site selection team must defend their recommendation(s) to decisionmakers. Data-backed reasoning is key to earning the support of internal and external stakeholders as they evaluate whether a potential investment is worthwhile. 

The Site Selection Analysis Process

While each component explored above is a vital part of any site selection analysis, no single part stands alone. A strategic site selection analysis process typically follows a few key steps that help project teams turn these analytics into data-driven site decisions. 

The site selection analysis process typically follows these four basic steps: 

• Define goals and success metrics: Agree on what a “successful” site looks like for this project, and how that success will be measured. 
• Gather and map data: This might include demographic data, real estate data, market data, foot and vehicle traffic metrics, costs, and constraints like the ones covered above. 
• Compare and score sites: Give each site a numerical score based on the metrics gathered in the previous step (you might choose to give different metrics different weights based on your project goals). Consider including competitive and trade area analyses in your scoring system as well. 
• Validate and finalize: Identify one or more of your highest scoring sites for final validation steps including a site visit and due diligence. This is typically the final step in determining official site recommendations to be considered by company decisionmakers. 

Common Site Selection Analysis Challenges

There are a few common challenges project teams may encounter during a site selection analysis, many of them stemming from data limitations. Watch out for problems like: 

• Outdated datasets – Demographics, traffic patterns, land use, and other factors change over time. Try to ensure you make decisions on the most recent available data. 
• Inconsistent geographies – Different datasets may segment analytics differently (e.g., by zip code vs. by road segment or by metro area, etc.), making it difficult to synthesize datasets into a single analysis. GIS tools may be helpful for normalizing these different geographies into a single view. 
• Overreliance on radius buffers – Proximity to certain points of interest or areas of high activity can bode well for a potential site, but proximity alone doesn’t ensure a site will benefit from nearby advantages (or suffer from nearby disadvantages). Combine these insights with more granular analysis specific to the site location whenever possible. 
• Analysis paralysis – A lot of information goes into a site selection analysis, and information overload combined with a fear of making the wrong decision can easily stall site selection decisions. Using a numerical scoring system can help, as can reviewing the goals you outlined at the beginning of the process to keep in mind the most important factors. 

Why StreetLight Helps You Make Site Selection Decisions Defensible 

Throughout the analysis process, clear, granular, and reliable data is key to identifying the best sites for your business. StreetLight offers the deepest and most comprehensive data repository available on the market, helping to streamline the site selection analysis process and leading to more confident site decisions. 

StreetLight’s location intelligence data combines vehicle and foot traffic insights with demographic and infrastructure data to help you: 

• Analyze customer demand and demand generators 
• Understand the competitive landscape 
• Avoid cannibalization of your own existing sites 
• Identify site constraints 
• Easily rank potential sites based on objective, defensible insights 

StreetLight’s data is rigorously validated by both internal experts and third parties to ensure reliable insights. Businesses and other organizations are already using StreetLight to identify optimal sites for new stores, charging hubs, and other infrastructure. 

For example, a nationwide coffee and breakfast chain uses StreetLight to analyze morning commute patterns and reveal locations with high customer demand. 

To learn more about StreetLight’s site selection analytics, reach out to a team member today.