Why AI Can Be a Traditional Restaurant’s Secret Sauce | Food Newsfeed
Continue to Site

why-ai-can-be-traditional-restaurant-s-secret-sauce-1553608256.jpg

pexels/Burak K
It’s not too late for operators to jump into AI, but time is growing short.

Why AI Can Be a Traditional Restaurant’s Secret Sauce

Underline Image
With the right strategy, restaurateurs can improve service by anticipating demand.
By Anil Kaul March 2019 Expert Insights

As everyone in the restaurant business knows, the competition for guest dollars is intense. For traditional restaurants, the competitive landscape is complicated by the rise of on-demand formats like ghost restaurants, pop-up dining options and food trucks—a sector that is forecast to grow like wildfire over the next dozen years, from $35 billion to a whopping $365 billion.

If you’re a traditional restaurateur, today’s fast-paced change offers an opportunity and a challenge. The opportunity is to grow your share of the $800 billion in total U.S. restaurant sales. The challenge is figuring out how to keep up with emerging trends and evolving guest preferences. In both cases, artificial intelligence (AI) can be your secret sauce.

AI can put traditional restaurants back on the modern menu, not by automating front or back of the house functions like serving and cooking but by helping restaurateurs better understand what their guests want. With the right AI strategy, restaurateurs can improve service by anticipating demand, delivering a great guest experience, and improving operations.

AI Means More Agile Operations

Restaurateurs who’ve operated under the pre-digital paradigm often believe that risk has to be minimized because the cost of failure is too high. That’s why restaurants tend to engage in lengthy testing and detailed planning before they launch new products and services. The problem is, this approach is too slow for the modern restaurant business.

With the trend cycle greatly accelerated, it’s critical for restaurants to move fast. Most restaurants have a lot of data, but they don’t use it properly. In fact, many are intimidated by it. But a mature AI solution can eliminate the fear factor, allowing restaurants to iterate products rapidly, take lessons from both success and failure, and innovate with agility.

To cite just one example, a chain with locations in Chicago and Miami used AI to optimize its beverage options, feeding restaurant data and free information like weather data into its system. The operator conducted A/B tests quickly without relying on time-consuming tests and planning. Using AI recommendations, the chain generated a 3 percent revenue increase in record time.

AI Serves Up a Superior Guest Experience

Millennials—the largest demographic cohort ever—are more diverse than previous generations and use different tools to find restaurants and learn about trends in dining and ingredients. They’re much more likely to discover new foods or find out about a restaurant through a friend or influencer’s social media feed than a TV or radio ad.

That can make it tough for traditional restaurateurs to keep up with emerging trends and reach a group of potential customers who are looking for an authentic dining experience. AI can help restaurateurs see around corners, identifying patterns in data more quickly than humans and offering recommendations to help restaurants stay ahead of the curve.

This dynamic is already at work in the retail sphere, where stores are using AI to spot trends and shift strategies for greater profits. One retailer with multiple outlets recently began customizing promotions based on data patterns in different locations. With AI analyzing location data, the retailer quickly identified new trends, tested concepts rapidly and increased sales.

AI Rescues Restaurants by Focusing on Service

Whether the trend is ultra-convenience options, hot new ingredients or ethnic-inspired dining experiences, customer demand is constantly evolving. What was hot yesterday can become ice-cold tomorrow, leaving restaurateurs who’ve invested in a theme high and dry. AI disrupts that cycle by spotting patterns early and going beyond insights to offer recommendations.

Companies are going all-in on digital business across all industries, including the restaurant sector, and the pace of change is accelerating. How businesses respond today will seal their fate over the next five to 10 years. Restaurants that embrace change now will pull ahead, while those that lag behind will soon find that they’ve been left behind.

Time is a factor in another sense too: AI gets smarter as it receives more data, delivering value in a compounded model like an interest-bearing account. The quicker restaurants start taking advantage of AI recommendations, the sooner the value AI delivers can expand beyond sales and marketing to the rest of the organization, including product development.

It’s not too late for traditional restaurateurs to make AI their special sauce, but time is growing short. For traditional restaurateurs who want to get back on the modern-day menu by responding agilely to trends, improving the guest experience and serving customers in a smarter, more responsive way, there’s no time like the present to embrace AI.

Anil Kaul is the CEO of Absolutdata. He has over 22 years of experience in advanced analytics, market research, and management consulting. He is very passionate about analytics and leveraging technology to improve business decision-making. Prior to founding Absolutdata, Anil worked at McKinsey & Co. and Personify. He is also on the board of Edutopia, an innovative start-up in the language learning space. An in-demand writer and speaker, Anil has published articles in McKinsey Quarterly, Marketing Science, Journal of Marketing Research and International Journal of Research. He was recently listed among the ‘10 Most Influential Analytics Leaders in India’ by Analytics Magazine India and has been quoted as a “Game Changer” in Research World. Anil has spoken at many industry conferences and top business schools, including Dartmouth, Berkeley, Cornell, Yale, Columbia and New York University.