How Data Is Being Used in Restaurants and Food

BCG’s 2018 digital maturity survey of top restaurant brands found that 80 percent had access to a wealth of data. There’s a big opportunity there – BCG’s numbers found that data and analytics programs yield five to 10 percent increases in revenue, 10 to 15 percent reductions in store-level operating costs, and 10 to 20 percent improvements in EBITDA (earnings before interest, tax, depreciation, and amortization). Further, digital restaurant leaders’ total shareholder return has almost doubled the S&P 500. And the National Restaurant Association’s 2019 State of the Industry report found that eight in 10 restaurant operators agree that the use of technology provides a competitive advantage and many planned to ramp up their efforts in that area.

In fact, data could be critical to the ongoing health of the restaurant business. An August 2018 report from The NPD Group found that the total restaurant count in the U.S. saw a one percent year-over-year decrease. Unlocking the insights of the reams of numbers available to restaurants could be crucial to their survival.

Here are some of the ways big data has already transformed the food industry, and what further changes might be on the horizon.

Inspire – and Recognize – Loyalty, While Luring Back Lapsed Guests

If it seems like every fast-casual restaurant and coffee chain has a mobile app these days, there’s a good reason – it’s a crucial way to help you order faster while also learning more about you.

And restaurant and delivery mobile apps are indeed more popular than ever. BCG’s study found that the installed user base for three top apps – Starbucks, McDonald’s, and Dominos – has grown from 45 million users to 76 million from June 2016 to 2018, while the number of users with Uber Eats, DoorDash, and Grubhub leaped from 9 million to 42 million over that same period. A survey showed that most diners use restaurant mobile apps to view menus and prices (55 percent), scour deals (38.2 percent), order food (30 percent), and reserve a table (23.8 percent).

According to BCG’s numbers, U.S. restaurant loyalty programs now also have a combined 130 million members, more than double their 2015 level – which means dining is the fastest-growing industry for loyalty programs. More than two-thirds of diners are members of at least one such program, and 25 percent say they’re members of three or more.

Apps generally have the effect of bringing customers back more often. In fact, 40 percent of app users say that they increased their visit frequency after downloading. Research from BCG shows that restaurant companies with “well-defined, strategically executed” loyalty programs can boost incremental revenues by 10 to 15 percent. 

How does your data play into that? Starbucks’ app is a good example. The company’s loyalty program is a gold standard for personalization, with tailored messages and offers being sent to people based on their ordering history. Starbucks often uses the program to get you in the door, whether you’re a regular – for instance, if you ordered a Venti Americano three days in a row, you might receive an email with incentives to extend your coffee streak another few days – or a lapsed customer who might be tempted back with a too-good-to-be-true deal.

“They have made massive investments and made progress on personalization, ahead of what I would say other restaurant brands to date have been able to accomplish,” said Mary Martin, a Partner at BCG.

The result? Their app just keeps getting more popular – according to Starbucks’ 2019 third-quarter results, active Starbucks Rewards Membership in the U.S. increased 14 percent year-over-year to 17.2 million users.

Improve Operating Efficiency

Data isn’t just being used to bring more hungry patrons into the restaurant – it’s also having a major back-of-house impact.

A recent report from Toast found that 78 percent of restaurant managers look at their metrics and finances daily, compared to 46 percent two years prior. And 95 percent of restaurateurs think technology improves efficiency.

One example of that is the fast-casual chain Panera Bread, which unveiled its Panera 2.0 plan to drive digital orders in 2014. Panera collects information about orders on all its digital channels to prepare for in-store labor and product needs, and that data has informed real changes at the chain, including redesigned kitchens and a reworked assembly line. As a result of those changes, the chain – which now expects half of all sales could soon be digital – managed to cut its wait time to order food from eight minutes to one minute.

They’re not alone in leveraging data to smooth their operating process. Domino’s built an algorithm to predict how long it would take to make and deliver a pizza – with factors including number and tenure of staff in the restaurant – while UberEats and DoorDash are competing to develop the best model to predict delivery time, taking into account weather data, sports schedules, and seasonal irregularities.

Data is also helping restaurateurs recognize their star employees – and who might be underperforming. It’s especially helpful for people managing multiple restaurants.

For instance, Charlee Williamson of the New Orleans-based Ralph Brennan Restaurant Group oversaw six managers and 78 servers on the other side of the country, at California’s Jazz Kitchen. She uses the Server Scorecard, offered by the restaurant management software company Avero, which ranks servers on multiple criteria and helps match the right waiter to the right table. For instance, a server who ranks higher in sales might be the right fit for a high-rolling party, while another who excels at tip percentage could be best-suited to handle a difficult table full of rowdy children.

Nailing the Menu (and Finding Flavor Trends)

When Applebee’s made the rather radical shift in 2016 to what was thought to be a millennial-friendly menu, it didn’t work out – to put it mildly. The chain announced in 2017 plans to close over 100 locations, and executives pointed to the fact that the youth-focused offerings had alienated what they believed to be their core guests: boomers and gen-Xers.

When the company went back to the drawing board, they did so armed with data. Adrian Butler, the SVP and Chief Information Officer of Dine Brands (the parent company of Applebee’s), outlined a 4D technology strategy to help the restaurant regain its momentum: Data, Discovery, Dining, Delivery. The focus was on “leveraging data and analytics of our guests and operations to craft personalized experiences,” beginning with the menu.

Applebee’s began to poll its customers via tabletop device surveys, and by the end of 2017, the chain had noticed a 7 percent uptick in overall guest satisfaction. As they dug deeper into data, they also realized why their millennial-focused menu had been such a misfire – their clientele was already evenly split among generations, with 26.4 percent boomers, 28.3 percent gen-Xers, and 29.9 percent millennials.

Data isn’t just useful for restaurants looking to make their menus shine. It also helps us understand what foods are whetting American appetites.

The pork lovers among us might have noticed that bacon is suddenly everywhere – in sundaes, cocktails, and even beer. And thanks to Wired, which partnered with Food Network to analyze 49,733 recipes and 906,539 comments from their website, we learned that everything really is better with bacon. Together, they searched all the recipes that fit a certain description – pizza, for instance – and calculated the average rating for those foods that did not include bacon. They found that the recipes with bacon did score higher – and the only exceptions were among pasta and desserts.

They drilled deeper and looked at other food fads and how they’ve waxed and waned over time, with ingredients like Portobello mushrooms and sriracha seemingly being past their moment in the sun. Lada Adamic, a Computer Scientist at the University of Michigan and Facebook, took Wired’s research even further and found that feta, cream cheese, cranberries, strawberries, and avocado were also reliable recipe hits.

In a separate project, Adamic wanted to see if it was possible to create a predictive algorithm to see how a recipe would turn out. She and her team took nearly 50,000 recipes and 2 million reviews from allrecipes.com and created an algorithm to extract out all the ingredients, cooking methods, and nutritional profiles, then looked at how often two ingredients were paired together in the same recipe. She found that her algorithm predicted with nearly 80 percent accuracy how many stars a recipe would get on the website. 

Initially, Adamic was inspired by her own kitchen frustrations.

“I was having trouble moving beyond literally reading the recipe and then following it exactly,” she said.

“In general, I just believe in data,” she added. “Now I feel more comfortable using spices more freely.”

Improve Customer Experience

Since few are forecasting a big leap in restaurant patronage, many restaurateurs have shifted from focusing on the number of customers to the quality of experience each visitor has – and data has been a big help.

“Total restaurant traffic is not growing, so anything restaurants can do to offer a better customer experience differentiates them from the competition,” said David Portalatin, a food-industry adviser at market-research firm NPD Group Inc. and author of Eating Patterns in America.

And the primary way most restaurants are capitalizing on data to form a better bond with diners is through personalization.

TGI Fridays, for instance, began gathering data from point-of-sale systems, social media, credit-card transactions, and mobile devices to create personalized campaigns for the four million-plus guests who have given the company permission to contact them directly. The result was stark: the chain doubled its to-go business in the 12 months leading up to August 2018 and increased social media engagement by more than 500 percent.

“Gone are the days of trying to figure out what millennials want versus boomers,” said TGI Fridays Chief Experience Officer Sherif Mityas. “We want to know what Mary wants versus Susan, and we need an unprecedented amount of data, analytics, and machine-learning to utilize this data in the best possible way.”

Cloud-based reservation systems allow restaurants to create detailed profiles on patrons with notes on everything from dietary restrictions to beer preferences. That information could be shared across an entire restaurant group, allowing servers to offer a customer their favorite IPA or a not-too-spicy appetizer they might love.

Restaurants have numerous ways to collect that data. McDonald’s and Chick-fil-A dangle free food in exchange for diners filling out surveys rating their experience. Starbucks has always offered free wi-fi, but as of April 2018, the coffee chain required users to submit their full name, email address, and zip code before surfing the web. 

California-based chain Tender Greens, meanwhile, uses the Punchh mobile app to log each customer’s name, email address, and purchase history. 

“It gives us ways to recognize people who’ve been in regularly or haven’t been in for a while or have specific preferences,” said founder Erik Oberholtzer.  “We want to accommodate everyone’s needs, sometimes before they even mention them.”

It’s not just fast-food or fast-casual restaurants that are using data to boost customer service.

Chicago’s Michelin-starred Oriole uses data from the Upserve system to determine who are their top 100 guests (in terms of the number of visits and amount spent) and creates a profile with every first-time reservation. Upserve also tracks the top 100’s dining companions when they divide up the bill, sending a list of credit-card numbers, dates of visits and what was bought. The restaurant matches the numbers to a name, then uses social media to put a face to that name.

“You can’t know that someone’s going to become a regular, so you don’t necessarily keep track of those people. But the system does,” said Co-Owner Cara Sandoval, adding that they’re sure to recognize regulars when they come in.

“It surprises people, in a nice way, when they didn’t make the reservation themselves.”

Then there’s the simple fact that ordering via a mobile device – whether for pickup or delivery – is just faster and more convenient than standing in line.

In fact, restaurant digital orders have grown at an average annual rate of 23 percent since 2013 – now representing 3.1 billion visits and $26.8 billion – and will triple in volume by the end of 2020, according to the NDP Group.

“Digital orders will remain an outsized source of growth for the restaurant industry over the next few years and operators who desire to grow need to embrace a digital strategy,” said Portalatin.