Definition: Infill locations are vacant lots or lots with underutilized facilities in a developed area, generally between established properties.

Infill locations have the potential to capitalize on trade areas, reshape communities, and expand your retail business to new markets. They can also seal off competitors from taking market share. But they can easily become costly mistakes, too. Whether you’re considering a vacant lot or looking to redevelop an underutilized facility, infill locations take a lot of time, planning, and resources before they start paying off—and with the wrong locations, they never will.

That’s why before you start breaking ground, it’s vital that you take the time to analyze and predict each site’s performance. With reliable sales forecasts and site models that actually represent your stores, you don’t have to question whether you’re making the right investment or wonder how long it’ll take for a new infill location to get in the black.

When you develop an infill location, there’s no historical performance data or maintenance records to make an easy cost-benefit analysis. And you can’t assume an infill location will be profitable just because it’s in a popular part of town or near successful businesses. But by leveraging GIS mapping and relevant datasets, you can evaluate these opportunities and find the prime sites everyone else has overlooked or been unwilling or unable to develop. And just as importantly, you’ll be able to explain your choices with information, rather than intuition.

As the provider of a leading location intelligence platform, we’ve helped businesses like Subway and Northern Tool prioritize infill locations internationally and nationally. Here’s how to ensure you select the best infill locations every time.

Start with market planning

Top-tier infill locations are in well-developed regions with plenty of infrastructure and demand that aren’t already oversaturated with competitors (or your own stores). If you don’t already have specific locations in mind, market planning is the first step toward selecting your best opportunities. Find the demand, analyze the concentration of competitors (or potential for cannibalization), then zero in on infill sites. Whether you use retail void analysis, white space analysis, or another approach, you’re looking for broad areas where there’s room for businesses like yours, or where your business is likely to perform well based on the concentration of people who share key characteristics with your target consumers.

Especially in international markets, census data isn’t reliable enough to guide market planning decisions. You need additional third-party datasets to explore up-to-date and comprehensive demographics, lifestyles, and spending patterns. Tango gives retailers access to a suite of datasets from trusted partners that help you see who actually spends their time and money in the markets you explore.

Once you’ve found possible broad markets, your broker network can bring you the infill options within them. Then it’s time to look at the trade areas surrounding these infill locations.

Analyze the trade area

While market planning helps you broadly identify the best markets to move into, each site occupies a specific trade area within the market, with demand that may vary significantly from  the market as a whole. An infill location’s success will largely come down to the breakdown of consumers who spend time and money within its serviceable area, coupled with the characteristics of the site itself.

It’s common to use a fixed radius to define trade areas (such as distance or drive time), but this will always reduce the accuracy of your sales forecasts and thereby, your comparisons, running the risk that you may not select the best infill options. For example, a freeway overpass running through the trade area you’ve defined will significantly reshape the trade area and affect the demand at a location.

Mobile movement data provides the most accurate picture of who actually spends time in the trade area. This anonymized data collected from mobile devices shows demographic information about the people who pass through the area throughout the day. You can even filter this data by day, time of day, or month to see how trends in activity align with the seasons and times your stores tend to receive the most business.

When you conduct trade area analysis with Tango, we partner with Near Intelligence to layer mobile movement data on our interactive GIS maps, which you can use in conjunction with demographic, spending, and lifestyle data from partners like Experian. You can also see where there are relevant points of interest near each potential infill location, helping you gauge how well the trade area compares to the ones your stores perform best in.

Evaluate the site characteristics

Finding an infill location in an ideal trade area is vital, but the characteristics of each site have an enormous impact on performance as well.

Infill locations are often nestled between established facilities, which can completely change how visible your store will be from nearby roads and intersections. If there are significant visibility issues, signage may not be enough to compensate for it. You’ll also need to consider accessibility to your lot or drive through (assuming you have them) and parking capacity. Does the site have an ingress and egress? Can people only access the site from one side of the street? Is there enough parking to keep up with the number of occupants you’d expect to have during peak hours?

When it comes to the actual infill site you’re considering, you need to understand its position in relation to foot and vehicular traffic as well. On-site visits and manual data collection can give you snapshots, but the most meaningful information will come from traffic and mobile movement data. Tango uses data from INRIX to assess traffic flow, and using geofences, you can isolate Near Intelligence’s mobile movement data to analyze the mobile users who pass through the site’s immediate vicinity.

Once you’ve thoroughly analyzed the infill site and the trade area it occupies, you can bring this information into the context of your portfolio to forecast sales.

Build comprehensive site models

In order to predict how your business will perform at a given infill location, you need site models that accurately reflect your stores. This includes stores which have closed. Building authentic site models requires you to understand the variables that have the greatest impact on performance, and take the time to compile those variables for each store you want to model. At Tango, we guide retailers through a series of about 30 questions to ensure our models incorporate each variable that matters to your business. Then we apply layers of machine learning algorithms to weigh these variables, refining the process until we can accurately predict store performance.

Forecast infill location performance

With your site models established and trained to predict store performance, you can apply the model to your plans for the infill site, forecasting how a new store will perform in the location based on how similar stores have performed in similar locations. It takes time and expertise to prepare your model, but once you’ve fine-tuned it to fit your portfolio and the opportunities you’re considering, choosing infill locations becomes a simple matter of looking at the numbers and weighing the forecasts against your overarching location strategy.

At Tango, our experts work right alongside yours, combining your internal data and insights with our suite of location intelligence datasets and state-of-the-art machine learning algorithms. The end result gives you reliable sales forecasts with the lowest margins of error in the industry, so you can confidently choose infill locations that generate the most sales or block your competitors most effectively.

Execute your infill strategy with Tango

Tango Predictive Analytics is a premier market research and site selection software solution used by retailers all over the world. Our best-in-class sales forecasting tools, paired with our trusted data partners, gives you the most reliable performance predictions in the market. As you look for and compare infill locations, Tango helps you prioritize the best ones.

Request a demo today, and see how Tango’s advanced location intelligence platform can support your infill strategy.