When the pandemic hit the U.S. last March, forcing restaurants across the country to close their dining rooms, &pizza was one of the many operations to shift all of its transactions to digital channels for the first time.
Previously, orders through its app, website and third-party marketplaces made up about 35% of its overall mix, said Darien Bates, head of technology for the Washington, D.C.-based chain. But as &pizza began reopening its stores, the ratio of digital to in-store traffic had flipped. Now, about 70% of the chain’s traffic comes from online, Baker said.
The ability to accept digital orders was a virtual must for most restaurants to survive the pandemic. The upshot of all those new digital customers, however, has been a massive influx of data.
For &pizza, said Bates, it was like a gold rush. In the span of one month last year, the chain’s number of new “visible” guests—those associated with a bit of data like an email address or phone number—increased by nearly 360%, from about 10,000 individuals in February to nearly 47,000 in March.
“We suddenly had all these customers who were previously invisible … ghost customers from a data standpoint … to suddenly being visible,” Baker said. “Suddenly they show up.”
&pizza new visible guests
Source: &pizza
It is a pattern that has played out for many restaurants that either began accepting online orders for the first time during the pandemic or simply saw a big jump in digital order volume, providing new insight into customers that had been anonymous before. Now chains are diving into that wealth of information to optimize marketing, boost sales and streamline operations.
Before the pandemic, “We couldn’t have told you anything about any of the customers in our restaurants,” said Matt Eisenacher, SVP of brand strategy and innovation for First Watch.
The Florida-based breakfast and lunch chain is among those that underwent a digital transformation in 2020. In a matter of a few days last March, it turned on online and mobile ordering as well as third-party delivery for the first time and was almost immediately flooded with orders—and data.
One of its first moves was to shift its customer relationship platform to a company called Wisely, which allowed it to integrate its various streams of data—POS, waitlist, credit-card processing—into a single customer database.
“We immediately started building a 360-degree view of who our customer was, no matter how they were experiencing First Watch,” Eisenacher said.
“For us it’s more about, how do you meet people where they are and have enough data about them to understand where they want to be in relationship with you.” —Darien Bates, &pizza
One way chains are leveraging this windfall is to engage those newly visible guests to help boost visits and spending.
&pizza, for instance, is working to convert standard visible users into members of its loyalty program. Those registered users have an average lifetime value—or spend over the course of their membership—that is more than double that of nonmembers, Bates said.
The more information the chain has about its guests, the more easily it can begin to build relationships with them and lead them down the path to membership, Bates said. The chain doesn’t expect every customer to become a superfan, but the data is helping it create more personalized relationships regardless.
“For us it’s more about, how do you meet people where they are and have enough data about them to understand where they want to be in a relationship with you,” he said, “as opposed to treating them all like a unit.”
First Watch also gained new insight into the average lifetime value of various customer segments. By analyzing customer data, it discovered that guests who use the chain on both weekends and weekdays have a lifetime value that is 2 times greater than those who tend to visit on one occasion or the other. The same pattern held true for on-premise vs. off-premise users, Eisenacher said.
It’s now working to convert those either/or guests to users of both occasions, using tools like targeted emails and lookalike marketing to expose them to the other use case.
“It’s been eye-opening and allowed us to approach growing our occasions in a more methodical way,” Eisenacher said.
Wingstop, which went digital-first well before the pandemic, is yet another chain using customer data to drive repeat visits—and it has plenty to draw on: As of February, its database of digital guests stood at 20 million individuals.
“Having now an over 60% digital business creates a lot of good information for us to leverage, to interact and engage with our guests,” said CEO Charlie Morrison on the chain’s fourth-quarter earnings call, according to a transcript from The Motley Fool. “And so therefore we're going to be leveraging the investments we've made in a robust CRM platform to engage with those guests—generate those second, third and fourth Wingstop occasions and so on and then to convert them into heavy users in the future.”
“Just like the guy who slices our vegetables uses a sharp knife, we need a sharp knife.” —Mike Speck, Fusian
More data also gives chains more precise tools for driving sales and predicting things like staffing and product levels.
Before the pandemic, &pizza had a one-size-fits-all approach to influencing guest behavior, Bates said. If the chain needed to close out a period with a strong sales week, for instance, it would send a big promotion to its entire database. But that strategy was limited by the size of the pool.
“You can push this button like one time every two months and it’ll work,” Bates said.
Beyond that, it relied on digital ad platforms such as Facebook to send geo-targeted messages, a process that was imprecise and expensive, he said.
The influx of visible guests that began last March has allowed &pizza to refine that button.
“It’s a lot more shaded, and that’s a really useful thing for us,” Bates said.
Now &pizza can filter its database to reach a slice of the population that tends to buy in a certain area. It can engage that group during a slow week, and it can communicate with its operations teams to staff stores accordingly, because the data tells it what to expect.
“We’ve been able to really refine that estimate,” he said, not only in terms of sales but also labor needs and guest experience. “You don’t want to just be slamming shops all the time to where it’s impacting labor retention.”
Fusian, a 12-unit sushi concept in Ohio, has similarly leaned on data to ease operations.
Key to that effort has been its adoption of Microsoft’s Power BI analytics platform to analyze and visualize sales data. Fusian can now predict metrics as granular as how many slices of tuna it will need on a given day, said CEO Mike Speck.
“Just like the guy who slices our vegetables uses a sharp knife, we need a sharp knife,” he said.
That visibility has allowed Fusian’s stores to be 85% to 90% prepared in terms of staffing and stocking on any given week, subtracting variables like weather. And at the end of the day, it has simply made everyone’s job easier, Speck said.
“We just removed all the small obstacles about, do you have enough people and products in the right place at the right time.”