Posted by David
Bairstow

It’s no secret that the ease of online shopping and free two-day shipping has become an increasingly attractive alternative to shopping at traditional brick and mortar retail locations. In 2018, more than 60% of consumers reported they’ll be shopping online for their holiday gifts. And with big store closure announcements coming from household names like JCPenney, Macy’s, and J. Crew, it’s clear that online shopping has had a big impact on in-store sales.

Shopping in real life is not dead, but pressure from e-commerce does mean that retailers need to be smarter than ever at identifying store locations with the highest profit potential. Rather than using hunch-driven methods for choosing site locations, retailers need an accurate and data-driven process for retail site selection analysis so they can make educated decisions. To do this, they are turning to location intelligence and foot traffic analysis. This technology helps retailers:

  • Determine heavy foot traffic areas
  • Identify popular days of the week and times of the day
  • Find an area that is popular among a target market

This article will take an in-depth look at this technology and give you some actionable advice on how to incorporate location intelligence into retail site location analysis and selection so you'll know how to choose the most optimal location for your store. 

Retail Store Location Analysis

As a retailer looking to expand to a new location, there are multiple ways to use location intelligence and foot traffic analysis to enhance retail store location analytics and inform site selection. These include uncovering consumer demographics, understanding customer behavior and gaining insights into competitive performance. 

Before we dive in, we'll discuss what both location intelligence and foot traffic analysis are. Location intelligence is described as "the collection of insights we can gather from the interaction between people and physical locations". At Skyhook, we define location intelligence as a methodology that marries location data and business data together to help solve a variety of business problems. Foot traffic analysis is derived from location intelligence and helps better understand how people move around certain physical locations. This allows businesses to analyze movement patterns around specific venues, like retail stores, to extract meaningful insights. These insights are then used for the use cases below:

Better Understand Customer Demographics

Since a trade area, or geographic area from which a brick and mortar store gets its customers, is vital to the success of a physical store location, your retail team needs to be sure that you’re opening stores where your target customers live or often visit. Instead of relying on broad census data or making assumptions based on competitor stores, location intelligence gives you real-world insight about the people who live and travel around specific retail site locations.

By using location intelligence for retail site analysis, you’ll gain insights about the customer demographics around your area of interest. In addition to the demographic information, you can see where else consumers like to shop or visit in their free time. And if you collect this data over time, your team can measure trends, like whether or not the target demographic is growing or shrinking in a given area and the rate at which the population is changing in a given area.

Location intelligence and foot traffic analysis ultimately gives you a data-driven method for measuring who visits specific locations, so you can more confidently choose a retail location that will last for years to come.

Learn More About Customer Behavior

Location intelligence and foot traffic analysis also gives you the ability to analyze consumer behavior to better understand potential customers at new retail locations. Whether you’re trying to decide between two different sites within an outdoor shopping center or opening a store in a completely new building, location intelligence can help you with retail site analysis by giving you the ability to look at how and where people shop.

With location intelligence, you can even monitor the behavior of people around certain areas to measure if there is enough foot traffic to open a store in that location. And for retailers who are trying to decide between two different storefronts in similar locations, foot traffic analysis can provide more information about the demographic makeup of people who tend to cluster around specific areas.

Analyze Competitive Strength & Market Opportunity

For retailers who are performing retail site selection analysis in a market with known competitors, location intelligence can be used to measure competitor market penetration and share, as well as overall customer loyalty. By having a clear sense of the competitor’s strength, your retail team can find locations where you can leverage your company’s unique competitive advantage to grow your share of the market.

To get information about competitor customer behavior, location intelligence helps you look at the pattern and frequency of store visits from their existing shoppers. If their customers tend to shop with other retailers, then this may be a sign that there is an opportunity to win over less loyal ones. And if the frequency of visits is less than expected for an industry standard, this may suggest that those customers are going elsewhere to find the items that they need and are in the market for a viable alternative.

Conclusion

The retail store location and site selection process is difficult, but having accurate and up-to-date information from location intelligence and foot traffic analysis makes it easier. With a clear understanding of local customer demographics, their day-to-day behavior and the competitor performance within an area, you can find retail site locations that have the best opportunity to succeed.  

To learn more about how Skyhook can work with you to help you find your next best retail location, read about our location intelligence for retail site selection solution.

Topics: location data Foot traffic Location Intelligence

   

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