AI/ChatGPT Poised To Add Rocket Fuel To Brands’ Ability To Connect With Consumers

For all the headline hoopla over the latest breakthrough in Artificial Intelligence—e.g., ChatGPT and rapidly evolving iterations—it’s worth pointing out that consumer-facing companies have been using AI in one form or another since the dawn of the computer age. The excitement back then was just as intense, quaintly captured in an episode of “Mad Men,” the AMC series set in the advertising business of the 1960s.

The agency is about to get its first mainframe computer, a monolith that will take up a considerable chunk of the firm’s floor space in a New York skyscraper. It’s a breakthrough in the ability to crunch what were then large amounts of data. The partners, wearing hard hats, are celebrating: “Let every customer coming through our door know that this agency has entered the future.”

It’s taken all of sixty years and untold billions of connected smart devices for that technology to realize its potential as an essential consumer research and marketing tool (although not yet sophisticated enough to realize that if you just bought socks online, you probably don’t need to see a parade of ads for socks). From here, the pace of development is poised to explode, and consumer-facing companies that get it right today will be the future leading brands.

One of the early examples of practical applications is a project by SPD-Group, a customer relationship management technology developer for the retail sector. As described on its website, the project was for a supermarket, using video cameras throughout the store and software that can track individual customers as they move through the aisles. The system was designed to alert staff when a customer lingered longer than usual in one spot so an associate could find and assist them.

Meanwhile, fashion brands like Brooks Brothers and retailers like Bloomingdale’s report sales increases in locations where they have installed Me-Ality virtual fitting kiosks. Step inside, and in 20 seconds, a scanner will measure 200,000 points of your body to help you make a perfect size selection.

The possibilities are limited only by the imagination. One day a customer may be able to go to Nordstrom, open the app on a phone that shows a map of the store and a suggested route to take you down the aisles where you usually choose merchandise. The map would have precise product locations and personalized pricing based on your specific data and store inventory data, etc. And a chatbot for asking questions about the product or even tying into a personal shopper app, and an actual human appears to assist.

At some point, these technologies will be available to all retailers, suggesting that the benefits to any one company will diminish over time. Not so, according to former Facebook executive Chamath Palihapitiya. In an interview this past winter, he used as a metaphor an example cited by Omaha investor Warren Buffett during his decades as a guru of capitalism. It is the story of the development of refrigeration. Buffett noted that the people who invented it made money, but the big money was made by brands like Coca-Cola
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, who used it to build an empire.

“I view these large language models as refrigeration,” Palihapitiya said. “There may be some money made in it, but the Coca-Cola has yet to be built.” So, what will separate the winners from the losers?

“If you take 1,000 of the same inputs and give it to Facebook and Microsoft
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and Google
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and Amazon
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, they’ll all come up with the same machine learning model. But if you have one extra thing, one little ingredient that other companies don’t have, your output can be markedly different.”

That “little ingredient?” Real-time CUSTOMER INPUT. Technology comes and technology goes, but the basics of retailing never change—know your customer.