Your brand’s core customer profile and trade area is likely changing—a post-COVID fast casual case study
A time-series study of consumers visiting a national fast casual operator with more than 1,000 locations shows clear evidence of a post-pandemic shift in both the core customer profile and the drive-time trade area. These shifts—which we anticipate will sustain to one degree or another until a COVID-19 vaccine is widely available—require the full attention of not just restaurant executive teams but also multi-unit operators across all sectors.
This study is a follow-up to an earlier conversation with Jim Sellers, Intalytics’ Senior Director of Marketing Solutions, where he urged multi-unit brands to invest in understanding how their customers and their driving patterns are changing. Brands that fail to monitor these structural changes will miss significant opportunities.
A: I’ve been looking for evidence to support or refute my initial thinking. Working with Intalytics’ data scientists and analytics consultants, we tapped our Massive Mobile Data (MMD) dataset, and assembled a pre- and a post-pandemic dataset to study consumer behaviors across one national restaurant brand’s ~1,000 locations. Here’s just a sample of what we found:
Notable changes in customer profiles
While there was stability in the customer profile in many generational groups, two significant shifts emerged. First, total share of visits from GenZ households (ages 18-31) increased 12%. This group represented 22.2% of the brand’s post-pandemic customer visits. However, GenX (ages 46-55) share of visits declined 10%, and GenX accounted for 25.7% of pre-pandemic customers. Visit share for Millennials (31-45), Boomers (56-75), and Seniors (76+) all stayed relatively stable.
This shift is important for operators to note, as GenZ households don’t have the family size and spending power of GenX households. The risk is that average ticket size will decline along with visit frequency—a financial double whammy.
We saw a similar phenomenon when analyzing household income, with potentially even more troubling implications. Visit share from customers where household income is less than $50,000 increased by 15%, while visit share from customers with incomes of $100,000 or more decreased on average by 14%. These wealthier households represented 40.4% of visits in the pre-pandemic period.
Marked shifts in customer visits were also observed based on household composition. Households with multiple adults present—regardless of whether they have children—saw visit share declines, while those with single adults capture a higher share of visit. As noted earlier, the impact here is likely to be a decrease in both visit frequency and average ticket size.
Conclusions regarding customer profile shifts:
These conclusions are also supported by shifts in psychographic segment profiles. The chart below indicates changes using Experian’s Mosaic segmentation group profiles. Letter designations at the top of the alphabet indicate higher levels of wealth, affluence, education, while those further down in the alphabet represent lower wealth, affluence, and education. These more affluent groups with the highest decline accounted for 47.7% of pre-pandemic visits. Those less affluent groups with the largest increases represented 34.7% of pre-pandemic visits.
Notable changes in distance-based trade areas
As with the shifts noted in core customer profiles, trade areas changed significantly as awareness of COVID-19 grew and as shelter-in-place orders were imposed. Across all the brand’s locations, the median distance driven from home to restaurant decreased by 10%, from an average of 4.2 miles in the pre-pandemic period to 3.8 miles post-pandemic.
Cutting locations by urbanicity uncovers additional differences in driving behaviors. Urban locations, which account for 25% of the total network, experienced the steepest distance decline. Compared to the prior four-week rolling average, urban customers drove up to 14% fewer miles from home to the restaurant.
Suburban locations represent 61% of the network, and median distances driven decreased up to 13%. It should be noted that there was a clear rebound observed in the last week for suburban customers, indicating that these consumers may have simply settled in to a new normal.
It’s important to keep in mind that these decreases in median distance driven from home to restaurant don’t fully capture the impact of this contraction in trade area size. Measured by the change in percent of total households present in the smaller post-pandemic trade areas, the contraction would be even greater. This is an area that warrants future analysis, and should be of particular importance for marketers. Shifting trade areas must be taken into account so they align with post-pandemic plans for local and addressable marketing tactics as the economy opens up and promotional activity rebounds.
Conclusions regarding trade area shifts:
Implications and considerations for marketers in light of these changing patterns
The next chapter in this exploration of changes in customer profiles and trade areas will focus on a selection of several distinct geographic markets: New York City, Los Angeles, Chicago, Dallas-Fort Worth, and Cleveland. We’ll also take a look to see how these changes are playing out across different dayparts.
Jim Sellers’ career spans multiple industries and brands, including senior marketing and sales positions with FedEx, FedEx Office, Procter & Gamble, Coca-Cola, and Royal Bank of Canada. He can be reached at email@example.com