How AI-Ready Retailers Are Embracing More Personal Customer Engagements

Personalization and superior customer service have been at the heart of retail for as long as it has been around.  While face-to-face encounters still matter, interactions between the retailer and customer happen in countless places, both physical and digital.  This past week, I attended the ICX Summit, the annual conference expo devoted to showcasing the innovative ways technology can be used to create transcendent customer experiences.

A common thread that ran through the entire summit was the observation that customers are demanding the same touch points with brands they have always expected, although now, they want it whenever and wherever they are. This often becomes problematic for retailers that lack the resources to do this at scale.

This also presents an opportunity for retailers to optimize the customer experience.  Through adopting machine learning and artificial intelligence capabilities that match customer expectations, retailers can dramatically increase their ability to deliver exceptional personalization at scale.   

Retailers embracing AI and automation are making their processes smarter and creating the opportunity to scale information across their organization seamlessly. Specifically, with AI, companies can now create more relevant, personal, and timely engagements with the customer, which enhances the overall user experience. Through automation, companies are no longer limited by the amount of staff serving customers.  Interestingly, retailers are finding that sales increase when humans are not present. This theme came up repeatedly, specifically in the restaurant sector (e.g. Wingstop, TGIF, Pie Five Pizza, Urban Air), as these brands have seen an uptick in sales and employee satisfaction as they leaned into automation.

Here are two speaker examples that showcase the success of leaning into AI and automation, recognizing that relevancy, personalization, and timeliness are essential to delivering a great CX experience:

CAESAR’s Las Vegas
Speaker: Brenda Barre, Director of Mobile & Digital Innovation]

Caesar’s created Ivy to handle every task that a guest can achieve by calling the hotel.  The automation allowed them to work on real-time guest recovery – if a guest is upset, they can work to resolve the problem prior to the guest leaving the premise. Ivy also benefited the staff members, removing monotonous tasks from their day-to-day jobs, and allowing them to focus on the high touch tasks.  According to staff members, Ivy “brought the joy back to their jobs.” While acknowledging that the AI was not perfect out of the box, Ivy’s unique machine learning platform has allowed her to get smarter over the years and is constantly being QA’d. The implementation of Ivy had profound effects on Caesar’s rankings & placements on Trip Advisor, and the automated service increased Nobu rankings by 40+ spots. 

TGIF
Speaker: Sherif Mityas, Chief Experience Officer TGIFridays

“You have to create 1-1 personalized engagement or you will lose.”

TGIF is in a unique position as they find themselves in an increasingly cluttered landscape.  As a test to understand their systems and their customers better, TGIF texted order suggestions to 10,000 existing customers based on their previous ordering patterns to see if they could create “no friction ordering.”  For example, if a customer has displayed a pattern of ordering a certain dish at a certain time, such as buffalo wings at 6 pm on Fridays, TGIF texts that customer at 5:50 pm to see if they are thinking about placing that order again.  In this test, TGIF converted 76% of customers on eating patterns, because their text message recommendations were timely, relevant and personal. They evaluated this no-friction ordering technology based on three concepts: 1: Is it right for the guests? 2: Can we execute this integration seamlessly? 3: Will this technological capability grow our bottom line? 

Through the success of these two companies, we can clearly see that the future of scalable personal engagement with customers isn't through overextending customer service teams, but by using AI to automate timely and relevant interactions. 

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