2020 is proving to be nothing if not challenging. From scientists laboring intensively on the origins and weak links in the Wuhan coronavirus outbreak to the fires and floods of Australia, it seems there is a new heart wrenching headline reaching out to us every week.
We can, however, be fairly certain that the solutions to the crisis’s we face will be found with the help of technology.
While a restaurant’s every day pain points may pale in comparison to the problems arising on the world-wide stage, the incredible and quickly evolving technical solutions found in this business segment are remarkable. In fact, they are changing the very face and scope of restaurants brave enough to enter the 2020 digital age.
Let’s take a look at just what’s looming in the hospitality technology landscape. Part I of this series will explore Artificial Intelligence in the restaurant industry.
Artificial Intelligence (AI)
According to the recent AdTheorent’s Dining Trends Report, 71 percent of consumers would be open to quick service and fast casual restaurants incorporating AI into their business. Good news for today’s operators, because AI is soon to be found in just about every aspect of a restaurant’s operations. We can blame or bless this on supercomputers like Watson and the “cloud.”
Because of today’s supercomputers and the rise of Big Data, deep learning has become possible. This cutting edge technology includes Machine Learning which uses artificial neural networks (similar to the neurons in our brains) to feed tremendous amounts of data to a system and enables the system to “learn” as more and more data is received.
The impact that AI will bring to the table can be illustrated with this statistic from Statista: From 2011 to 2018, funding of AI-focused companies reached approximately 5.4 billion dollars in the U.S. alone, and almost doubled from 2017 to 2018. Our friend, the robot, is here to stay.
Restaurants and other businesses in the hospitality industry have started using this remarkable technology in numerous ways.
Fast food chains have already started experimenting with this technology, and we expect it to become commonplace in the future. Facial recognition will allow establishments to recommend orders and provide recommendations and upsells for return customers. For new guests, they may recommend items based on gender, age, and even mood. If connected to a payment method, automatic payments can also be processed.
Restaurant incorporating this technology: CaliBurger, a franchise offering Southern California style burgers around the globe, has been using this type of technology at three of their locations: Pasadena, CA, Philadelphia, PA, and Fort Meyers, FL. Customers find PopID kiosks at the counter that recognize their faces. In addition, the Fort Meyers unit has added Flippy, a robot that flips burgers and fries French fries, and a 13-foot interactive gaming Funwall.
Tim Frederic, the operator of the restaurant in Fort Meyers, spoke with Franchise Times about the suite of technology, “To me, it’s exciting because you can see what it can do to handle volume. But what I really like about this tech is it does allow my managers and employees to focus on the customer.”
Businesses in the forefront: Flippy was designed by Miso Robotics while the facial recognition kiosks use NEC’s NeoFace facial recognition software. Other companies offering facial recognition kiosks include Bite, a 2018 tech startup, and Xenial, a restaurant technology service provider that has introduced facial recognition systems at fast casual chains such as BurgerFi, Malibu Poke, UFood Grill, and Wow Bao.
AI technology is enabling restaurants to not only use predictive analytics to give them actionable insights and define their target customer; it is also giving them the ability to expand their brand with less risk and higher rewards. Predictive analytics is, in essence, making a prediction based on the collection and analysis of tremendous amounts of data.
Restaurants incorporating this technology: Two experiential restaurant entertainment concepts that are using this technology to expand include Silverspot Cinema, a high-end dining and theater brand that first opened in Naples and has now expanded across the U.S., and Flight Club, a high-tech dart concept and winner of “The best new venue in London.” This concept opened three successful units in England before heading across the pond where they’ve set up shop in Chicago and Boston, and will be setting their sights on New York, D.C., and Atlanta.
Businesses in the forefront: Acutely, in collaboration with Emerging Concepts, uses predictive analytics to help restaurants and those in the gaming industries make data-based decisions when expanding their brand, and to develop targeted profiles of their customers.
They achieve this by using the POS to build a deep learning model that can then project sales using this data. Their deep understanding of each customer allows them to go into a new market based on the profile of their current VIP and frequent guests.
According to Mathew Focht, CEO of Acutely, “Acutely’s deep learning models are able to project sales within 85 percent accuracy before they even open a unit.”
Another company delving into advanced analytics and AI is KPMG Intelligent Forecasting, a business that provides their services to numerous types of businesses including a global biotech company, an industrial manufacturing conglomerate, and a U.S. national restaurant chain.
With the huge amount of data that can now be processed, categorized, and stored, restaurant operators are able to personalize communications and marketing strategies based on a customer’s behavior, purchases, and preferences. A concise map of the customer’s journey is created, providing information that can create personalized incentives including offers based on taste preferences or time of day. The outcome is an increase in the return of brand-loyal guests as well as higher check sizes.
Location-based marketing, though definitely not in its infancy, is becoming an increasingly popular marketing strategy for restaurants. AI is at the core of geo-fencing, geo-targeting, and geo-conquesting. Geo-fencing refers to sending marketing messages to customers based on their real-time location, while geo-targeting focuses on targeting the right people within that location. Geo-conquesting, as the name implies, targets small areas within a geo-fence—sometimes as small as a single address.
A restaurant may opt for geo-fencing in order to target an area where a college campus is located or one where a large number of businesses make up the population. Within that targeted area, they may use geo-targeting to market specifically to college students. Geo-conquesting then allows a restaurant to target college students that are dining at their close competitor’s restaurant.
Burger King used geo-conquesting to target customers entering one of their biggest competitor’s locations, McDonald’s. Customers could download the Burger King app and order a Whopper burger for just 1 cent. Known as the “Whopper Detour,” it resulted in 1.5 million downloads of Burger King’s app.
Unfortunately, an analysis by Location Sciences found that up to $65,000 of every $100,000 spent on location advertising was outside of the targeted area or poor data quality—leaving nearly two-thirds of spend wasted. For this reason, it’s important to choose best-of-class businesses that are on the cutting edge of technology.
Operators are also using this technology in food delivery services. In order to combat rising third-party delivery fees, restaurants are opting to head to their nearest software developer to obtain a geo-location app, suitable for supporting the delivery process.
Restaurants incorporating this technology: Just a few of the many restaurants using this marketing strategy include P.F. Chang’s, Starbucks, Potbelly, California Pizza Kitchen, and Panera Bread.
Domino’s added GPS tracking to its app in 2019, allowing their customers to see exactly where their order is at any given time from order to delivery. Most of their locations will have this option by the end of 2020.
Businesses in the forefront: Manthan offers an intelligent analytics platform that is built for the restaurant industry. Data, once analyzed, not only predicts what will appeal to customers but also what menu combos will work. This information is also used to enhance digital engagement with customers at the right time and through the right channel.
Other companies with a strong presence in this arena include Simpli.fi, a leader in digital marketing with a comprehensive platform for localized advertising, and GroundTruth, a global location technology company. On their website you’ll find restaurant-specific tactics for targeting potential customers such as targeting within a 0.1 to 3-mile radius around your restaurant, reaching a customized list of competitor’s locations, and reaching groups based on past visitation such as targeted foodies, pizza lovers, or sushi goers.
Predictive Scheduling for Labor Management
The restaurant industry is facing an unprecedented issue with labor and staffing due to record-low unemployment rates and increasing minimum wages. According to Toast’s 2019 Restaurant Success Report, 51 percent of respondents cited hiring, training, and retaining staff as their number one operational challenge. Restaurants are using Machine Learning and AI to enhance hiring strategies and apply predictive scheduling.
It’s been about five years now since regulators decided that employees should be allowed predictable work schedules—a trying if not almost impossible task in the restaurant industry. Known as predictive scheduling laws, they present significant challenges in terms of staffing, costs, and compliance, with failure to comply resulting in substantial penalties. At the core of these laws is a requirement to supply employees with an advanced work schedule, predictable pay, and a sufficient break period between two shifts.
Cities and States that are considering or have already passed these laws include Oregon, Vermont, San Francisco, Berkeley, Emeryville, San Jose, Seattle, New York, Chicago, and Philadelphia.
AI and Machine Learning is enabling restaurants to forecast labor demand as well develop schedules based on the “best person for the job” strategy.
Restaurants incorporating this technology: 7Shifts, a leader in workforce management and scheduling, offers several case studies on their website including Fresh Restaurants, a six unit company that cut their labor costs by 12 percent in one year after using 7shifts. Other success stories include Burrito Boyz, Park Burger, Impact Kitchen, and Revolu Taqueria + Bar in Peoria, Arizona.
Businesses in the forefront: Because of these growing types of regulations, there are a number of digital scheduling platforms that are entering the market. These include When I Work, 7Shifts, and Shiftboard, to name a few. ShiftPixy acts as an employer to “shifters” and matches qualified part-time employees with the employers searching for their skill sets. All this is done centrally through ShiftPixy’s app.
7shifts restaurant scheduling software enables employees to swap shifts, list availability, and request time-off, all from their smartphones. Using machine-learning algorithms, they can analyze past schedules and “learn” not only the number of employees needed per shift, but who would be the best employee based on past performance and availability. Their auto-scheduler fills shifts based on scheduling restrictions and forecasted sales. Seasonal and historical weather is also used in the calculations. Sales are forecasted “with 95 percent accuracy to determine labor requirements for the coming week.”
It’s important to work with a company that understands the rapid changes that occur in this segment of hospitality due to increasing regulations. According to Jordan Boesch, CEO of 7shifts, “The industry has evolved quickly and is frequently introducing new compliance laws that directly impact restaurateurs, big and small. With 7shifts’ core offering being scheduling, it was only natural to go deeper on supporting all aspects related to scheduling compliance.”
Stay tuned for more insights on what we can expect for restaurant technology in 2020. Part II will explore Virtual and Augmented Reality.