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In the past 14 months, overall engagement for restaurant chain TGI Fridays has grown more than 500 percent, says Sherif Mityas, the company’s chief experience officer. And with personalized outreach, they’ve doubled online business in the last year, to the tune of millions of dollars.

“AI has created a tremendous impact in driving our off-premise business in the last year,” Mityas says. “Everything we do that collects, captures, analyzes, and utilizes data for the benefit of our guests is a critical component of our marketing strategy, while using artificial intelligence to help us personalize engagement is critical to our success.”

Personalization here looks a little like high-touch mind-reading that is yielding results that have been seen and believed. The company collects a constellation of data points about customers — a snapshot of who you are, what you like, how you interact with the brand, what taste profiles you fit, when you like to order, and when you go out to eat.

From there, their AI tool helps craft the multi-stage, multichannel personalized communication strategy — for instance, a message about their new salmon salad, to you the salmon lover, just when you’re most likely to be thinking about dinner — that will have the greatest statistical probability of making you open your wallet and hand TGI Fridays your dining-out dollars.

“I’ve now created a personal, relevant engagement through the understanding of your data that’s designed to create a next-best action,” Mityas says. “That next-best action could be, you order from me online. You come into my restaurant. You make a reservation. Something happens because I engage with you in a more personal fashion. That’s what we’re doing.”

He likens it to going back to their roots, in a way — the restaurant chain started originally as a singles bar, the kind of place where one-on-one engagement was what kept the customer coming back for more, the way they would at any place that is special because they know who you are, what you like.

“It’s meaningless to market to segments, millennials versus boomers, single white women in New York or soccer moms in California,” he says. “To differentiate your brand and create that engagement, you have to get to Rachel versus Mark. The only way to do that is to get into and really start understanding the use cases around AI and machine learning, how that can help you as a brand and help your marketing stack make that happen.”

He cautions crawling before you start walking and running, leaping ahead into the technology, but instead carefully choosing some use cases first. The technology has evolved enough where you can pick a small thing and try it, then measure the hell out of it, examine the results, and then build on that, he adds.

“The big piece I’ve also been preaching here is that you can’t be out of balance: the technology, the organization, and the process all have to be in lock step to make this work,” Mityas says. “There are certain things where we’ve had to slow down the technology because our teams weren’t ready to execute it, and that’s where you can get in trouble.”

For instance, the company has an AI tool now that can create one-of-a-kind drinks at restaurants, combining preferences, tastes, even the mood you’re in, to create a drink at their bar. But practically speaking, on the ground, from demanding that bartenders create a new drink they’ve never made to ensuring ingredients are always on hand, that’s no small task, especially executed across 500 domestic restaurants.

“The technology is there to do something that cool, powered by AI; operationally, it’ll take us some time to scale that up,” he says. “You have to be measured in terms of how you scale it, but you have to allow the technology and the organization to learn, and learn at a pace where everyone can be in lock step.”

But your enthusiasm for what the technology can accomplish immediately shouldn’t fade, as there are things that can scale up very fast, he notes — for instance, creating messages and personalizing them can scale as soon as you know what works.

“But the beauty of this, the beauty of the technology overall, is it learns — even when we think we’ve got something right, it continues to get better, because it learns,” he says. “And any brand that has any kind of email or loyalty data around some of their guests, just start sending one-to-one emails and look what happens to your clickthrough rate. Look what happens to your adoption through the funnel. Look what happens to sales. It keeps going and builds. Just start small, do something basic, and you’ll be amazed by what you get.”

To learn more about how necessary AI is becoming to sales and marketing organizations, how to make sure you’re AI ready and start seeing results, fast, don’t miss this VB Live event!

Don’t miss out!

Register here for free.

Attend this webinar and learn:

How to tell if your marketing and IT departments are AI-ready

The fundamentals of an AI-driven infrastructure

The role of clean, definable data goals in successful AI implementation

How to scale the AI workload

Speakers:

Rolf Schromgen s, CEO, Trivago

s, CEO, Trivago Sherif Mityas , Chief Experience Officer, TGI Friday’s

, Chief Experience Officer, TGI Friday’s Michele Goetz , Principal Analyst, Forrester

, Principal Analyst, Forrester Andrew Malinow , PhD., Principal Data Scientist, Zylotech

, PhD., Principal Data Scientist, Zylotech Rachael Brownell, Moderator, VentureBeat



Sponsored by Zylotech