What’s new since our last report:
- Restaurant sales hover at -34% vs. pre-crisis averages. They’ve steadily crept up since hitting a low point (59% below) the week of April 12th.
- QSR has seen the most notable improvement at 20% below the pre-crisis average vs. Casual Dining at -34%.
- Digital ordering has surged nearly doubling vs. pre-crisis averages. Weekends have driven the bulk of the increases with Saturday and Sunday reaching 406% and 289%, respectively.
The impact on restaurants
Restaurant sales on the Thanx network hit a low the week of April 12th with transactions down 59% vs. the pre-crisis six-week average. Since then, sales have steadily increased to -34% vs. the pre-crisis average.
Weekly volume compared to the pre-crisis average
Variation across service type
QSR drove the bulk of the gains with purchase transactions approaching 20% below pre-crisis averages. Casual dining saw notable improvements, though substantially less than QSR.
Purchase volume compared to the pre-crisis average
The return of sales were not reflected in major U.S. cities, such as New York City and San Francisco, where purchase transactions still remain exceedingly low due to stricter shelter-in-place regulations.
Weekly volume compared to the pre-crisis average in major U.S. cities
Online vs. in-store purchases
Online purchase volumes, already trending up prior to the crisis, have nearly doubled, with a 188% increase versus the pre-crisis average. Though online volume took a small dip in the few weeks after the start of the crisis, it swiftly returned to normal levels and, over the last few weeks, has skyrocketed.
Online purchase volumes
Increases in digital order volumes are most pronounced on Saturday (406%) and Sunday (289%) as consumers seek a break from weeknight cooking.
Digital order volume by day of the week compared to pre-crisis
A note about the dataset:
The Thanx platform is used by customers with thousands of restaurant locations across quick-service, fast-casual, table service and fine dining as well as by grocery stores and other retailers. The dataset references purchases tracked by our system, primarily of loyalty members and therefore does not reflect the behavior of all customers. Store closures may impact the statistical significance of some segments.