Retailers and commercial real estate analysts are no stranger to site selection. The success of a brick and mortar store is often dependent on its location and the market conditions of the surrounding area. For example, a quick service restaurant that has popular lunch options has a higher chance of success if located near office buildings than it does if located in a rural, sparsely populated area. Identifying the right spot for a new brick and mortar location often comes down to identifying success factors for other stores and finding lookalike markets to expand into. For years, retail analytics platforms have been increasingly adding local market data into their solutions to give their users an edge in site selection.
But what about when a business is looking to close locations? Sure, they can evaluate store performance and close locations that are losing money. However, this method involves relying on a lagging indicator rather than taking a proactive approach to cutting costs. Retailers who truly stay ahead not only have a site selection strategy, but also a strategy for site deselection. When a brand is struggling or anticipating economic uncertainty, retail analytics become even more important as they reveal insights that can make or break a business.
As with choosing new locations to open, deciding where to close an existing location requires thorough investigation and analysis, and is often conducted using analytics platforms powered by location data. Site deselection involves looking at trends in how consumers are interacting with a brand’s stores, their competitors, and their complementary brands to anticipate which locations will underperform in the future and take action. Combined with the latest market landscape data, including which businesses have opened and closed nearby and how they intersect with trade areas, these insights enable brands to make strategic decisions before a location truly starts to underperform. In many ways, site deselection follows the same steps and requires the same inputs as site selection, but focuses on risk indicators instead of opportunities.
Having a solid site deselection strategy is critical for any brand in any economy, but in particular during (or ahead of anticipated) times of economic downturn. For example, the pandemic economy drastically altered the quick service restaurant industry, resulting in some brands experiencing increases in demand and others closing up shop due to a lack of customers.
So with some economists warning we may be headed for a recession, how can brands best prepare to weather the storm? While a recession economy is different from a pandemic economy, there are some learnings brands can glean from their COVID-19 experience to develop a strong site deselection strategy for the possible recession ahead. Insight into where competitors and complementary businesses are opening and closing (and have over the past few months) can indicate how trade areas are changing, and consumer behavior data indicating how people are interacting with brands and types of places can serve as a clue for how demand will change in coming months. Whether leveraging data through a retail analytics platform or ingesting it into their own analytics processes, retailers who have a data-driven site deselection strategy are best equipped to handle economic challenges.
First, we look at overall place closures by state. States shaded blue saw less closures, while states shaded orange saw more. Hawaii had the most closures with .36% of all places open in March being closed in the month of April. However, at the state level it seems businesses stayed relatively stable.
When drilling down to a more granular level, we can see more distinct regional trends. Auburn - Opelika, Alabama and Michigan City - La Porte, Indiana had the highest percentage of places close in the month of April, at 0.56% and 0.54% respectively. More variation can be seen at the MSA-level as compared to the state-level, especially within each state. For example, at the state-level it appears that California was on the higher end of place closures, but when breaking it down by MSA it shows that different regions of California varied in place closures during the month of April.
Now that we can see regional differences more clearly, we can filter by business category to see if there are industry differences. Looking at restaurant closures by MSA, we can see that the restaurant industry isn’t changing much in some regions, but is changing significantly in others. The Casper, Wyoming metro area saw 2.23% of restaurants close in the month of April.
However, the same metro area only saw .23% of retail stores close during the same timeframe.
With these regional and industry insights, retail analytics platforms can show retailers which markets are likely to expand or contract in coming months, enabling them to develop proactive site deselection strategies to stay ahead of the competition.
Each month, SafeGraph pulls similar insights for the retail and restaurant industries to provide a snapshot into how they are performing.
The SafeGraph team sources our Places data from a variety of sources, including the publicly available store locators that many brands offer online. So when a brand updates their store locator to reflect a closure, that change gets ingested into our pipeline. You can learn more about our opened_on and closed_on columns here.
Ready to learn more about the data needed for effective site deselection? Here are some resources to help you get started - everything from high-level methodology to the data needed to perform site deselection for yourself.