How Retailers Use Artificial Intelligence to Know What You Want to Buy Before You Do
The Terminator, a symbol of artificial intelligence run amok, famously declared that he would be back. Three and a half decades later, it turns out repeat business is at the heart of AI.
AI and machine learning have long been a part of retail—nearly a decade ago, Target (TGT) could infamously predict when a woman was pregnant. In the years since, consumers have grown more comfortable sharing their data, especially as they crave more personalization. Now, with Covid-19 propelling shopping online—replete with tracking cookies and apps—we’ve reached a key moment. There’s more information, and more computing power than ever before to parse it for patterns that keep customers loyal.
“An AI system needs data in order to become smart. And the more data it has, the smarter it gets,” says Gaylene Meyer, Vice President Global Marketing & Communications at RFID company Impinj (PI), whose products allow retailers to track trillions of items of inventory in real time and respond quickly to changes in demand. “When you can see everything moving through a system, you gain a new view of the system as a whole. So you can find the pain points and eliminate them.”
That’s crucial, as inconvenience is the enemy of sales; the easier the transaction, the more likely people are to complete it. The pandemic played havoc with supply chains throughout the industry, causing products to be out of stock or delayed in delivery. That, coupled with consumers’ reluctance to buy nondiscretionary items, actually drove data down earlier this year.
Yet the strongest retailers, who have seen revenues climb in 2020 and have the money to invest in technology, may be able to sidestep this problem—especially as they use data not directly tied to sales.
“Mobile is the new mall,” says Cowen & Co. analyst Oliver Chen, who notes that machine learning allows brands to build one-on-one relationships with consumers at scale. “It’s how you interact with a retailer online; that’s the secret sauce behind a lot of social media data. It comes back to [retailers] knowing what you want before you know you want it, to keeping you interested, buying, and satisfied.”
That’s part of the rationale behind Walmart’s (WMT) bid for TikTok: The app provides valuable information about how shoppers are engaging with brands via social media, while also reaching a younger demographic. And just like Target years ago, “Walmart knows that the most valuable customer is in the early stages of household formation,” says Chen. From drapes to diapers, they’re on the cusp of prime spending years, making their loyalty still more prized.
Walmart and Target shares have been on a tear in 2020—Target stock has gained 28%, while Walmart has risen 20.3%—but Barron’s has argued before that both can keep winning, as they gobble up market share amid consumers’ tendency to do all their shopping in one place.
At roughly 26 and 21 times forward earnings, respectively, Walmart and Target’s valuations are above five-year averages of 19 and 15 times, but have forward price-to-earnings growth ratios below historical levels, at 3.1 and 2.1 times, compared with 4.1 and 3.4. That suggests the stocks’ now-brighter outlooks leave them more room to run. Returns on equity of 25% and 29% put Walmart and Target ahead of many peers, with that metric expanding for both in recent years.
