Using Data to Rethink Retail Siting and Marketing in a Post-Pandemic World
If the pandemic has taught us anything, it’s that many of the business rules we once took for granted no longer apply. For retailers, shifting shopping patterns, the surge in suburban migration driving today’s housing boom and lingering unknowns are causing many to rethink how they choose new retail sites, decide which stores to close, and find alternative uses for existing properties. The ever-growing presence of big data and analytics to make sense of it can help retailers know what’s available and how they can use it to inform those decisions.
The Big Migration
Among the pandemic’s lasting effects, the shift away from urban centers could drive retail siting and marketing for years to come. As the combination of remote work for parents and online schooling for children stretched on, many families felt the need for more space. At the same time, companies became more comfortable with employees working from home. Large employers such as Facebook, Microsoft and Amazon announced that a large percentage of employees would be allowed to work from home permanently. The need for space, lack of commute worries, and historically low mortgage rates set off the migration from high-priced urban centers to more spacious, less expensive towns and suburbs.
This trend was especially true for first-time homebuyers. According to CoreLogic Fraud Consortium Loan Application data, first-time homebuyers made up 39% of home sales in 2020, a sharp increase from 30% in 2015. The same data shows that the counties with the biggest jump in first-time buyers were located close to major urban employment centers, including New York City, Seattle and San Francisco.
New Shopping Patterns
But the residential shift is only part of the story for retailers facing location decisions. Consumer shopping patterns also migrated in new directions. Before the pandemic, retail siting criteria and marketing centered around driving foot traffic into stores.
While that remains an important consideration as the pandemic’s grip loosens, months of social distancing and working from home radically changed the way people shop. It comes as no surprise that, according to U.S. Census data, e-commerce sales grew by 32% (±1.8%) in 2020. Retailers survived, and even thrived, through the pandemic by adapting to meet consumer demand for curbside pickup and home delivery of online purchases.
Same-day and two-day delivery went from nice-to-have to must-have features. Smart retailers built internal organizations to support online shoppers, with many offering try-before-you-buy or easy return policies to lure shoppers to their brands. And it’s a good bet that neither shoppers nor retailers will completely return to pre-COVID shopping models.
How Shifting Patterns are Reshaping Retail
Retail siting and marketing professionals are a little like astronomers searching for extraterrestrials by finding planets in the Goldilocks Zone—that band around a star that’s not too hot, not too cold but just right to support life.
Today, retailers choosing locations to open, close or repurpose may first need to redefine their Goldilocks zones by examining what “just right” means in an upended market. By looking at housing data, siting professionals can glean information to see if their store is the right fit for an area, and marketing professionals can use the same data to determine the best way to reach the surrounding area. Some examples of how this data can be used:
Economy: To determine the financial stability of a surrounding area, retail siting and marketing professionals can use the following data: unemployment rate, income trends, access to high-paying jobs, nearby retailers, property values, sales price versus listing price, rent prices, and homeownership trends.
The data can assist with price setting, market competition comparisons and regional needs. It can also gauge tactics for marketing when considering questions like, do people tend to stay in homes for 20+ years in the area? If so, it maybe pertinent to build personal relationships. Or is there high turnover in the area? If so, frequent and refreshed annual marketing campaigns may be necessary.
Population: To give retailers a sense of the area they can also look at data around increasing or decreasing trends, percentage of first-time homebuyers, access to high-paying jobs, residential property ages and features, such as pools,and neighborhood comparison. Analyzing population data allows retailers to better demographic questions like, which generation of shoppers should retail siting and marketing professional be appealing to? Does the campaign need to consider the local industries and job professions? Looking at population data goes beyond the economic outlook of an area to help retailers understand who their customers are as members of their communities.
Hazard risk: By considering weather, flooding, wildfire, earthquake and market risk data, retailers can go a step further in understanding if the risk of an area is worth the reward. People living in areas prone to natural disasters see hardship more regularly than others, both economically and physically. Beyond what a store location may experience, it’s important to factor in the possibilities of loss for the communities at large.
There’s an abundance of data to help retailers locate their Goldilocks zones. How each retailer uses the data depends on the target markets they hope to reach.
The ideal site for a new hardware store might include a search for areas of increasing population, a high percentage of millennial first-time homebuyers, newly built homes or older homes that need remodeling, rising property values (equity to fund remodels), gross rental yield, freeway access, plenty of parking and tolerance for natural hazard risk that might make other retailers uneasy.
A retailer considering closing a luxury brand store in an expensive urban location may focus on population migration trends, neighborhood education and income, crime risk, property value trends, rent prices and trends, parking, foot traffic patterns and trends and the composition and movement of nearby retailers.
A hip, digitally native, direct-to-consumer brand opening brick-and-mortar locations could look at demographic data (age, income, diversity, cultural character), walkability, traffic patterns from cell phone data, percentage of first-time homebuyers, population growth, rent prices, crime risk and other criteria related to its target audiences.
Fortunately, there’s ample data and solid analytics available to help retailers gain the insights they need to formulate intelligent siting strategies and marketing campaigns as we move into a post-pandemic world. Finding the right partner to provide the information is step one on the path forward.