Visual Crossing Blog

Five things to consider when placing a new retail location

Are you a new business owner looking to place your first retail location? Or maybe you looking to expand by adding additional stores? In this post, we are going to use Location Analysis to help identify and analyze possible options for a new store location.

Using Location Analysis to find the best place to find a new brewpub

How can you be sure that you are placing your new store somewhere with the greatest access to potential customers? Where are your existing competitors located? How can you capture their impact on your future customers?

We are going to walk through the process of locating a new brewpub somewhere in Denver or its surrounding areas. To do so, we will use demographic data, spatial analysis, and the Visual Crossing Location Analysis tool to do the spatial calculation heavy lifting.

We’ve already done our initial research and have made a list of three potential locations based on recommendations from a realtor. We’ve also done competitive due diligence and identified most of the current brewpubs in Denver. Our next step is to use Location Analysis to answer the following questions:

  1. What location will give us the opportunity for finding the maximum number of potential customers who are currently unserved?
  2. How many existing competitors are located within the potential trade area of each proposed location?
  3. For key concentrations of target customers, what is the likelihood they will choose my new location over existing competitors?

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Step one – identifying the competition

We will start by identifying the existing competition on a map. We’ve set up this spatial model using an initial estimate of a five-mile location reach. That means that each location is expected to serve potential customers in a five-mile area around that location. In addition to the competitor locations, we’ve also colored the map by the available population. These are colors ranging from red (low population availability within five miles) to blue (high population availability). This allows us to identify areas that have a high level of untapped customers based on raw population.

Place your competitors on a map to help visualize where the optimal location will be

You can see that whilst there is a fair amount of competition, some areas of the city are underserved by existing brewpubs (the areas in blue). Hopefully these areas represent an opportunity for us!

Step two - adding our proposed store locations

Let’s now add in our realtor’s recommendations. We have three locations – one in the downtown district and one each in the northern and southern areas of the city. Location Analysis allows us to easily look at these on the map of Denver so we can visualize the options. We can get immediate insight of the demographic profile around each location.

The scorecard shows you the best possible locations for the population
When we place these proposed locations on a map and calculate the location demographic reach, we see that the North and South locations have significantly more available raw population within a five-mile radius:

This leaderboard quickly tells us that there are potentially many more people who could easily visit the northerly and southerly stores.

Map of proposed locations

However, we’ve only just begun our investigation.

Step three - Using targeted demographic variables

Is raw population the right measure for our brewpub location? If not, we can use a different demographic variable to target more specific customers who are more likely to visit our specific type of business. Since college graduates are typical brewpub customers, let’s change our map to show college graduate distribution in the area.

Now we can see that the southerly location has a significantly higher number of potential clients fitting this profile.

Targeted demographic variables highlight the optimal location

When we focus our 5-mile search on college graduates, the potential customer values change significantly. The leaderboard looks like:

Targeted demographic variable map showing best areas to site a location by the selected demographic

Note how much stronger the southerly location is within this target demographic. In this location, there are 61,574 potential college graduates within range. In the central location there are only 4,176!

In addition to highlighting for us the reach of each potential brewpub location, note how we can also see that how competitors will be impacted. In many retail situations, optimizing the defending against competitor encroachment can be just as important as optimizing for increasing sales. Location Analysis can show where we can place our locations to best maximize this defense.

Step four – choose a location

This analysis suggests that if we want to site our new brewpub in an area of high potential customers then the South University location looks like a great potential location for three reasons:

  1. It is close to the highest number of our targeted demographic (College Graduates)
  2. It is separated from potential competitors
  3. It is in an area of high potential population in addition to the targeted demographic.
Each of these factors suggests that this is best location to open near our optimal customer base.

Step five – use demographic variables for targeted marketing

Once the new location is opened, we must continue to use our local knowledge to help create effective targeted marketing. With this strong demographic profile, we would be able to easily use targeted marketing to drive visitors to our new location. We can use Location Analysis techniques to help identify those people living in locations that we hope will visit our store location and tailor marketing campaigns around the target demographics.

Next time – revisiting the downtown locations

But we still have one nagging question. Why have most of our competitors decided to focus on the downtown area and complete directly against each other? For some reason many of our competitors are located there, but that doesn’t seem entirely logical from the demographics data. In the next installment we will investigate why there is a cluster of brewpub locations together in the downtown location. Given that the competition in that area will be fierce, why would someone want to open a new location there? We will also discuss how to introduce the attractiveness components of locations and how the Location Analysis tool can be used to create a spatial model to help quantify the impact of attractiveness on a proposed location.

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Comments or questions?