Entrance to the expo floor at NRF 2024: Retail's Big Show, hosted at the Jacob K. Javits Convention Center in New York City.

Jan 14 2024
Data Analytics

NRF 2024: 4 Ways Retailers Are Meeting Customer Preferences and Boosting Loyalty

At NRF 2024, experts shared how generative AI and data analytics in e-commerce platforms are helping retailers improve customer satisfaction.

Connected data has the power to unify the customer experience. It also provides a gateway for retailers to understand their customers better. But those two outcomes require that retailers first earn the trust of their users and then leverage that data so that consumers have the contextual information they need to make better, faster decisions.

This requires cross-functional teams within an organization to determine where the data is located, where it needs to go and what key details need to be translated to the e-commerce platforms. Many retailers are still mapping out this data collection process, but it’s a critical step to personalizing the consumer journey.

At NRF 2024: Retail’s Big Show, hosted at the Jacob K. Javits Convention Center in New York City, experts shared how generative AI and data analytics in e-commerce platforms are helping brands find product details faster, convert more shoppers into buyers and increase customer loyalty.

From personalized recommendations to subscribe-and-save features, here are four ways retailers are using AI-driven tools to improve the consumer experience:

WATCH: Meet the list of people shaping retail's future landscape. 

1. Provide Accurate Product Information at Every Point of Sale

According to IBM’s 2024 consumer study, “consumers expect companies to recognize them, remember their preferences, and serve them appropriately. They want to easily access their orders, shopping carts, and purchase histories every step of the way. They crave more choices but less hassle … at the click of a button.”

To meet this expectation, retailers need to create “one single source of truth,” says Mark Steel, a director of retail and consumer industry solutions at Google Cloud. This means that accurate product information is visible and searchable at every point of sale. Natural language processing and generative AI can help retailers locate inconsistencies.

This not only boosts consumer trust but also improves the chance that the consumer’s experience will be as positive online as in the store. 

RELATED: See how leveraging data analytics can give retailers a competitive advantage.

2. Share Personalized Shopping Recommendations

Retailers are leaning on consumer-facing generative AI assistants (like Salesforce’s newest version of the Einstein Copilot) which pulls product recommendations for consumers. Based on existing customer data such as the shopper’s location and preferences, retailers can communicate with the consumer at key moments in their decision-making through digital storefronts and messaging apps.

LEARN MORE: How can artificial intelligence chatbots help retailers meet customer expectations?

For instance, if a consumer is planning a trip, the generative AI assistant can recommend a travel adapter and mobile charger — no wait or hassle. The contextual element of these product recommendations is key because retailers are capturing the consumer’s attention at the right time.

“That’s why this is driving growth,” says Marc Mathieu, senior vice president for AI and emerging tech transformation at Salesforce. “It’s really making that relationship with the customer more relevant, more personalized, and therefore more long-term. It builds more loyalty.”

Source: IBM Consumer Study, "Revolutionize Retail with AI Everywhere," 2024

3. Enable Subscribe-and-Save Features

The more that brands can predict consumer behavior, the better. That’s why retailers are setting up subscribe-and-save features on e-commerce platforms. These use predictive analytics and past purchasing trends.

“Whatever product you use on a regular basis is automatically delivered to you,” says Andy Szanger, director of strategic industries at CDW.

This could include vitamins, toiletries, or any seasonal or recurring purchases that happen on a regular basis. It’s a simple way for retailers to encourage repeat purchases.

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4. Refine Search Terms to Encourage Future Purchases

According to IBM’s 2024 consumer report, “52% of consumers want to receive information, advertisements, and offerings from stores that are relevant to their specific interests.” Data analytics can help retailers address this missed opportunity by segmenting their audience and targeting them more effectively.

These tools are also helping retailers scale one-to-one consumer experiences and retain them longer term. “When I walk into a physical store today, I have a great experience, but online that is not always the case,” says Jenna Flateman Posner, chief digital officer at Solo Brands.

She shared an example of typing in a product name and having to wade through thousands of results. One of the superpowers of generative AI is that it can lend consistency to product copy and make search terms easily discoverable within a retailer’s system.

Retailers can take any number of these steps to improve the customer experience. It just requires getting the data “into the hands of people who will do something with it,” says Google Cloud’s Steel.

Keep this page bookmarked for articles from the event, and follow us on X (formerly Twitter) at @BizTechMagazine and the official conference Twitter feed, @NRFnews.

Photography by Jason Dixson, courtesy of NRF

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