Drive-thru visits grew by 27 percent in the third quarter of 2020. The number is anticipated to grow higher as guests adapt to the convenience of off-premise dining and mobile ordering. However, increased drive-thru traffic and longer lines are critical problems that magnify further operational bottlenecks down the service line.
In 2020, drive-thru wait times increased by an average of 30 seconds across the 10 leading QSRs. Long wait times are not only unpleasant for guests, but can cost restaurants up to $32,000 yearly per store. These losses accumulate from various stages of the drive-thru, as illustrated in the diagram above.
Guest A decides to not enter a drive-thru lane after seeing the line extend out of the parking lot. Guest B leaves the drive-thru lane to visit another restaurant after waiting in line for more than 5 minutes. While Guest C has finally picked up their order, they decide to never visit the restaurant again due to the long wait. While increased guest traffic seems like a boon to sales, it can also result in substantial losses if the drive-thru isn’t optimized for it.
“Would you like fries with your burger?” Cross-selling is one of the most efficient yet underutilized ways to increase average check size and profit. As a testament to the importance of cross-selling, Amazon attributes up to 35 percent of its revenue to cross-selling.
The benefits don’t end there. Cross-selling is also a more cost-effective method of increasing sales than acquiring new guests. Furthermore, a lack of cross-selling can lead to slower service time, resulting in $16,000 in yearly losses per store on top of lost revenue.
Lost revenue is compounded further by unoptimized cross-selling. Even with a plan in place, staff often forget to cross-sell to every single guest they serve. In addition, staff might not be cross-selling the most optimal items if operators lack data on the menu items that perform best together.
Inaccurate orders are a threat that QSRs can’t afford to ignore at the drive-thru. Even if a guest receives their order quickly, their experience can immediately be marred by a missing or wrong item. Guest lifetime value suffers too. Guests are usually unwilling to wait in line again to correct wrong orders, leading to an unfavorable impression of the restaurant.
The problem isn’t just a customer service issue. Inaccurate orders can slow down the drive-thru as staff seek to remedy the mistake with the guest. In the end, restaurants can lose up to $94,000 yearly per store due to inaccurate drive-thru orders.
Solving for long drive-thru wait times isn’t as simple as adding more staff or simplifying the menu. Are these decisions backed by data? Increasing staff for the wrong hours can actually backfire and lead to more costs.
So why is optimizing drive-thru operations so difficult? Firstly, operators lack data that would help them make the most objective decisions with successful results. Secondly, they need real-time data to correct problems on the spot due to unpredictable factors such as weather and events. Finally, this data needs to produce actionable insights that provide operators, managers, and staff clear cues on how to resolve operational challenges.
A technology revolution is underway—and drive-thrus are on the frontlines. In order to thrive among heightened competition, a growing population of digitally-native guests, and rising operating costs, restaurants must adopt new technologies that can both increase operational efficiency and drive revenue.
Presto has designed innovative technologies that help differentiate QSRs from the ever-growing competition. Our customizable solutions focus both on increasing throughput and improving customer loyalty. Restaurants that deploy these solutions can better manage drive-thru lines, deliver personalized guest experiences, and predict—and solve—bottlenecks that occur at certain times or franchise locations.
Don’t wait for the rest of the industry to pass you by. Discover how you can generate real results today. Reach out to us at email@example.com and we’ll help you get started.