AI in Retail: How It’s Impacting the Industry & What You Need to Know

In this piece, learn how retail companies are adopting AI tools and the major AI use cases and opportunities for retail marketing today.

Published on May 24, 2024

AI is becoming the go-to connection between shoppers and shops. And customers don’t mind, as long as the tech works well. Nor do retailers. 

In a Google Cloud survey, 59% of respondents said they want to use generative AI to streamline customer service. Less human intervention and manual busywork, more conversation summaries and automation. And if the AI drives higher conversion rates, all the better for retail.

But AI is going to impact retail beyond the customer service department. There’s going to be an entire sea-change, because AI is already doing even more behind the scenes. 

Using AI in retail: the major benefits

Retail is big business. By 2026, the whole retail market should eclipse $32 trillion in sales. The slightest gain in efficiency (higher conversions here, less manual labor there) can move mountains of money.

But AI’s appeal to retail isn’t simply because retail is such a big business. Generative AI, or AI that can “create” new work like automated customer responses that feel like human words, has retail-specific implications. McKinsey estimates that retail is one of the sectors with the most to gain from AI, in areas such as:

  • Improved customer operations. “Generative AI has the potential to revolutionize the entire customer operations function.” Retailers can scale customer service and order-taking to new levels. McKinsey sees that comprising a $404 billion productivity lift across industries.
  • Productivity. “Machines have given human workers various ‘superpowers,’” said their report. They estimate a ~$463 billion lift in productivity worldwide. AI can help with better, faster content creation and the more efficient use of customer data.
  • Software engineering. Retailers who need to invest in software for both internal and customer-facing applications will get a boost from AI. Software engineering should experience a ~$414 billion lift, according to the same data set. 

Retailers typically think about AI as a new way to interact with customers. And it is. Chatbots and advanced customer recommendation systems are great. But there’s more to the story here, particularly with how retail can reshape itself behind the scenes.

According to Retail TouchPoints, that can manifest in any number of ways:

  • Marketing support. 49% of marketing respondents said they want to use Generative AI to improve marketing skills. Of particular interest? Automatic product categorization and generating customer-centric marketing copy that feels organic and personal.
  • Creativity. Retail marketing can get more creative with help behind the scenes. 44% of respondents want to use AI to help their retail creative teams. AI can step in and build bespoke images and creative content for marketing campaigns. (Remember when Coca-Cola’s “Share a Coke” campaign featured images of uniquely-named Coke bottles? 1.25 million new teens tried the soda that summer. Imagine that level of personalization in the hands of every retailer.)
  • Conversational commerce. If you reach out to a retailer with shoddy chatbots, you’ll get a stock response. Generative AI is far more conversational. It generates user-specific feedback that registers as feeling more organic. According to Retail TouchPoints, 40% of retail decision-makers want AI to provide customer support that goes beyond surface-level answers.

Interacting with customers in new ways

How Walmart used AI in retail to make shopping more convenient

Not long ago, Walmart implemented a Voice Order feature. The idea was simple: connect your mobile device with a smart speaker via your Walmart account. Suddenly you could say, “Hey Google, add a dozen eggs to my cart,” and expect delivery.

We’re all used to—and sometimes frustrated by—smart speakers. But here’s where retail AI helps. Walmart’s AI could access the customer’s buying history to interpret what “buy a dozen eggs” meant. Does the customer always expect free-range, cage-free? Then that’s what Walmart adds to the cart.

AI is making Walmart more user-friendly beyond that, too:

  • Text to Shop. If you’re on the road and nowhere near a smart speaker, Walmart lets customers text their order in. The text chat uses conversational AI technology (read: Generative AI). With that, customers can search for items, add/remove products from their cart, or schedule grocery deliveries.
  • Online AI shopping assistance. An average Walmart associate probably can’t provide comprehensive product recommendations. According to Walmart, an average store might have over 100,000 different items. But Generative AI can process 100,000 different items. Not sure what to buy a seven-year-old nephew for his birthday party? Or how to find an office-appropriate Halloween costume? You don’t have to ask an associate. AI can offer shopping recommendations online. The old method—querying “Halloween costumes” in a spotty search bar and browsing vast results—wasn’t as interactive. AI shopping assistance brings a personal shopper to every online customer.

A better breed of chatbot

Yes, AI helps improve customer support. But that doesn’t only apply to retail. It applies to every industry. How can improved “chatting” AI disproportionately impact retail?

Companies are automating specific types of customer support requests with real-time conversations. AI is particularly good at processing the most typical requests: questions about returns or order status. By outsourcing this work to AI since 2020, Walmart says it’s reduced millions of customer contacts.

Generative AI is going a step beyond that, though. It’s now changing how retailers interface with suppliers. Walmart experimented with a chatbot to handle supplier negotiations. The results, according to Forbes

“The chatbot closed deals with 64 percent, gaining an average of 1.5 percent in cost savings and an extra 35 days in extended payment terms. An impressive 83 percent of suppliers actually liked the chatbot negotiation.”

Matching products to customers

AI in retail is improving upon skin-deep product recommendations

Product recommendations have been a boon to online retailers. To this day, a reported 35% of Amazon revenues come from these recommendations. 

Modern AI can extend those algorithms to far more than your average Customers Also Bought… listing. Some companies, like Il Makiage, turn product recommendations into a bespoke AI experience.

At Il Makiage, a customer can come in and get a recommendation for their skincare needs. It uses “material sensing” via cameras. Think of it like a phone detecting a face or fingerprint to identify who you are. The software weighs hemoglobin, melanin, and even blood oxidation from a simple image. It offers skin and hair properties to better understand what your particular needs are. 

Even more important, you don’t need to step out of the store and into a lab to do it.

What was once an expensive, time-intensive process is now available with a walk-in. That’s the kind of sea-change we’re looking at with AI in retail. According to Lareina Lee, Senior Partner at McKinsey, “The analogy is similar to the move from mainframe computers—large machines operated by highly technical experts—to the personal computer, which anyone could use.”

Omnichannel opportunities and incentives to visit brick-and-mortar stores

New features like skin and hair analysis make brick-and-mortar more appealing. What if you can get a lab-quality report with customized product recommendations from stepping in a store? You might be more inclined to visit.

But AI is helping brick-and-mortar in other ways, too. Many retail marketers think of physical retail stores as one channel among many. Email, social media, online shopping, brick-and-mortar are all common touchpoints for modern customers.

AI can help brick-and-mortar retailers become more relevant in omnichannel marketing. 30% of respondents once said the biggest area of opportunity for AI is in stores, because AI can help with both omnichannel marketing and loss prevention. 

If a customer can walk in the store and feel like you’ve been expecting them, it’s more incentive to shop in person.

AI can also help the in-store shopping experience. Walmart, for example, was using an online personalized shopper assistant. That’s useful for shopping at home, where you can have groceries delivered. 

But what if you’re shopping for a new top? These days, AI can match products with customers already in-store. Using geolocation or geo-fencing, AI can locate and identify a shopper. AI can dig up specifically-tailored messages and recommendations. The resulting output can go directly to customers’ phones—even while they’re still shopping.

How retail marketers can use generative AI in unconventional ways

Helping your in-house team

There are over 2 million Walmart employees. It’s not surprising if one or two of them don’t always have the answer for how to do something inside a store.

One unconventional use of AI is to talk directly to employees. Sure, customers can benefit from generative AI—but Walmart’s “Ask Sam” helps in-store associates with their queries. Rather than kick up unique questions to supervisors, associates can “Ask Sam” about where to find a product—or what its current price might be. A question like “Where can I find a jar of star anise?” might not come up every day. But a quick query to Sam will solve it.

Scaling a retailer’s marketing content

If a mega-store has 100,000 products, that means 100,000 product descriptions online. Copywriters must be exhausted. And a constant influx of new products means adding online descriptions becomes a bottleneck.

AI product description generators take the load off busy marketing professionals. Writing a powerful product feature can help boost sales and increase conversions. But what if you have 150 to get through?

Tools like Jasper can build product pages, explain key product benefits, and start writing. Sometimes, Jasper might even be able to dig up points of added value or product benefits the marketer might have missed.

Adidas used Jasper to help with its product pages, for example. Adidas had 150 shoe models and wanted to test AI technologies. Could AI handle the unique selling points of each product?

It could, according to Siddhi Saraiya, Adidas’ Global Head of B2B Digital Product Management. In fact, Jasper’s AI solutions helped do more than save time. Adidas adapted from a cost-per-shoe-model service agency fee to a technology license fee with Jasper. The result was a scalable, cost-effective approach for Adidas. Humans were still involved with the product descriptions—but it required a lighter touch from their interventions.

Even better, Adidas learned more about the potential of AI in retail. “It's not as numbers oriented, but just the fact that we got to play with an emerging technology in a really practical use case and learn was also quite valuable from an ROI perspective,” said Saraiya.

AI is going to change retail from both ends

AI might place an egg order for you, and that will be fun. But AI’s impact will mean hundreds of billions of dollars of impact that go far beyond the customer experience. 

“The retail industry is in the midst of a major technology transformation, fueled by the rise in AI,” said Cynthia Countouris, Director of Product Marketing for Retail, CPG, and QSR at Nvidia. Nvidia’s study into AI even found that AI has already had a huge impact on retail. 69% of Nvidia’s respondents saw revenue increases thanks to AI. 72% reported decreases in operating costs.

It’s not too late to catch the Generative AI wave, however. As Adidas learned, simply exploring AI as a solution can pay off down the road simply by exposing your retail store to the possibilities opening up. If you want to get in on the ground floor and learn how to explore new revenue drivers—or strategies for decreasing costs—watch our webinar, Revolutionizing Retail.

Meet The Author:

Kaleigh Moore

Kaleigh Moore

B2B Freelance Writer

Kaleigh Moore is a freelance writer for B2B SaaS companies.

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