How AI Technology is Helping Restaurants Improve Customer Experience

Customer service has been declining as restaurants abandon phone calls. Conversational AI has the solution

Andrei Papancea

  • travel and hospitality
  • conversational AI
  • customer support solutions

The New York Times recently reported that pressures on staffing were one of the reasons why restaurants were moving away from answering client telephone calls. Some reported being just too busy preparing food to answer calls; others said they felt a need to find other quick and efficient ways to connect and speak with customers. Some restaurants were even reported to have abandoned phone lines altogether in favor of booking purely through websites, apps, and social media.

It’s understandable that in the fallout of the pandemic, when 60% of small restaurant operators say they can’t fill open positions (per Alignable), some businesses might just opt for getting rid of a phone line altogether rather than employ someone to answer calls. But this tradeoff comes at the expense of their customer service.

There is a smarter, more inclusive way to do business and maintain happy patrons – pressure on busy front-of-house restaurant staff to answer calls from those looking to book tables, change reservations, or even place takeaway or catering orders is being relieved without compromising the customer experience using conversational AI technology.

This is the latest extension to the use of innovative technology in the US restaurant sector. The first online food order – reportedly a large pepperoni and mushroom pizza from Pizza Hut – was in 1994 and the first online food ordering service, Worldwide Waiter (now, was founded a year later in northern California. But now restaurants emerging from the pandemic are having to change the way they operate again to improve efficiency, enhance customer service, and optimize their ability to take advantage of people’s return to eating out whilst the trend for ordering in continues.

There is also the need for restaurants to reduce costs as menu prices continue to increase due to higher food, staffing, and energy costs. Finding a way of doing that that doesn’t consume existing staff is also important as the National Restaurant Association’s 2021 State of the Industry report said that 3 in 4 restaurant operators were finding staff recruitment and retention to be their toughest challenge.

Conversational AI tools like Voice Compass by NLX enables restaurants to design conversations that create customer trust and brand loyalty through exceptional customer self-service experiences without the need for live interaction with restaurant staff.

Voice Compass enables a restaurant to offer a self-service flow by verbally guiding calling customers through an onscreen journey to complete their mission. So, when a customer calls the restaurant’s number, they will be guided by a voice to use their telephone to achieve whatever it is they wish – to book a table, change a reservation or place an order.

“Walking into your restaurant and engaging with your food is an experience. Don’t miss out on the opportunity to extend that experience to calling customers who may want to make a reservation, order takeout, or check wait times,” says Andrei Papancea, co-founder and CEO at NLX.

“Once you’re set up with Voice Compass by NLX, you can focus on the food, and NLX will handle the phone lines for you.”

See how Le Rivage Restaurant on New York City’s historic “Restaurant Row” uses Conversational AI to enhance their customer contact experience here, and try Voice Compass by NLX for yourself.

Andrei Papancea

Andrei is our CEO and swiss-army knife for all things natural language-related.

He built the Natural Language Understanding platform for American Express, processing millions of conversations across AmEx’s main servicing channels.

As Director of Engineering, he deployed AWS across the business units of Argo Group, a publicly traded US company, and successfully passed the implementation through a technical audit (30+ AWS accounts managed).

He teaches graduate lectures on Cloud Computing and Big Data at Columbia University.

He holds a M.S. in Computer Science from Columbia University.