The mobile order-ahead space is one of the few seeing an upswing of increased revenue amid the pandemic, as quick-service restaurant (QSR) customers look for safe, convenient ordering services that limit human contact. Restaurants are working overtime to ensure their ordering systems are as friction-free and secure as possible, with many deploying advanced technologies to do so.
Fast food behemoth McDonald’s began investing in artificial intelligence (AI) to give customers unique deals while also obtaining vital data about their ordering habits. These efforts have helped the chain boost sales in Japan by 30 percent, for example. Consumers around the globe appear to support these integrations with a recent report finding that 71 percent of QSR customers are in favor of their favorite 
eateries incorporating AI into their business operations.
The October Mobile Order-Ahead Tracker® explores the latest digital ordering developments, including new technology deployments by Burger King and Disneyland, the growing threat of false chargebacks, and how QSRs like Qdoba are harnessing data analytics to reduce chargebacks and drive sales.
Developments From Around the Mobile Order-Ahead World
Public spaces are gradually starting to reopen, with limited capacity and other social distancing guidelines set up. Disneyland, which recently began to reopen, announced that its theme park will enable more robust mobile ordering options and payment methods at park dining locations than before the pandemic. The move is aimed at customers who are still wary of physical contact that could put them at risk of infection by providing them with alternative ordering options.
Fast food giant Burger King is also exploring alternative ordering options, including a brand-new restaurant concept. The chain recently unveiled a new restaurant design plan that will primarily leverage contactless digital and mobile technologies, with the first location planned to open in 2021. The concept also includes drive-in lanes for contactless curbside meal pickup, outdoor seating features and coded lockers from which customers could retrieve their meals.
Some players in the food service industry are tapping advanced technologies to improve and streamline their ordering operations. Online restaurant supplier Rebel Foods has deployed machine learning to 
enhance its order forecasting ability, for example, which allows it to determine which food items to deliver to restaurant kitchens. The new order forecasting system boasts a 90 percent accuracy rate, according to Rebel Foods, which is enabling it to reduce its food waste and expenses.
For more on these and other mobile order-ahead news items, download this month’s Tracker.
Qdoba on Curbing False Chargebacks as the Restaurant Industry Rebounds
One of the few bright spots amid the pandemic is mobile ordering’s skyrocketing popularity, with restaurant revenues increasing by 82 percent over the past four months. This surge in digital activity has had its drawbacks, however, including growing amounts of false chargebacks by customers.
In this month’s Feature Story, PYMNTS talked with Adam Fox, director of digital experience and media for Qdoba, about how the chain works with its online ordering provider to flag suspicious transactions and reduce chargeback fraud.
Deep Dive: How QSRs Are Deploying Data Analytics and AI to Serve Customers, Fight Fraud
Digital ordering is on the rise, but the restaurant industry has a long way to go to fill the revenue hole that the early months of the pandemic dug. Digital fraud is another problem that COVID-19 has made worse, with bad actors scamming customers by impersonating QSR customer service teams.
This month’s Deep Dive examines how data analytics and AI are helping restaurant chains fight both of these problems and bring the industry back to the pre-pandemic status quo.
About the Tracker
The monthly Mobile Order-Ahead Tracker®, a Kount collaboration, offers coverage of the most recent news and trends and a provider directory highlighting key players across the mobile order-ahead ecosystem.