Dramatic changes in customer behavior shifted orders from dine-in to curbside or drive-thru. Drive-thru restaurant visits increased 26% in April, May and June of 2020 and represented 42% of all traffic, according to The NPD Group. The sudden nature of the shift left restaurant operators little time for training, process reengineering or technology deployments. In many cases, the result has been a decline in the accuracy and speed of order fulfillment.
Simultaneously, restaurants have been forced to contend with a number of other challenges including labor shortages, supply chain disruptions and historic inflation, adding urgency to the need for increased throughput, accuracy and cost savings.
Fortunately, advanced technologies like Vistry, which uses AI with vision, voice and IoT data analytics to help restaurants measure and improve speed and quality of service, offer QSRs an opportunity to enhance their operational and customer service capabilities.
Most QSRs have access to a plethora of data generated by countless devices like the POS, IP cameras, mobile devices and sensors. Vistry AI leverages vision, voice and IoT data from existing devices and any new hardware to provide actionable insights that inform better decision making. Here are three examples of applications for AI in restaurants that can help them overcome critical challenges.
- Drive-thru line abandonment – The growth in drive-thru traffic obviously creates longer queues and – subsequently - longer wait times for customers. Drive-thru abandonment is a common occurrence, but most QSRs are unsure about the specific numbers. Abandonment leads to unrealized revenue, unhappy customers and potentially a breach in brand trust. AI can leverage video from cameras installed at the drive-thru to accurately report on the rate of abandonment. It can also take action to recover from a poor customer experience by triggering a coupon and apology note for customers. The information can also be used to identify process improvements that speed time to order delivery.
- Faster order fulfillment – Speedy and accurate order preparation is also crucial to the customer experience. AI is now being used in collaboration with voice technology to support employees in the preparation of orders. Using AI integrated with beverage dispensers and POS, AI can accurately enter the customer’s order into the POS and trigger automated drink preparation from the fountain. This alleviates the workload on overtaxed employees and also improves the accuracy of orders entered in the POS.
- Ensure food quality – Food safety is paramount in QSRs. Foods need to be prepared in a just-in-time manner to ensure quality and safety. Currently, restaurant employees must visually note the depletion of food items. In the case of items that must be cooked, lead times can range from 5 – 20 minutes. Using AI and a combination of computer vision and IoT sensors, it’s possible to continuously monitor food stocks in bins and provide just-in-time notification that more of an item needs to be prepared or cooked. This eliminates a host of problems, from unhappy customers to lost revenue due to missing menu items, or contaminated food due to improper storage.
These are just three of the limitless applications for AI in QSRs and fast casual restaurants. If you’d like to explore more, tune into the Telaid Tech Connect podcast, where I speak at length with host, Beth Bergmann, about this AI technology and how it is supporting QSRs. Or, if you’d like to learn more about Vistry and our solutions, visit our website. I can’t wait to see what newfound efficiencies and profitability result from the widespread use of AI in QSR.