Mastercard is joining a growing list of major ecommerce players that are using the explosion of generative AI technologies to improve the shopping experience for consumers, many of whom now are scouring retailers’ websites to find the right gifts for the holidays.
The company this week introduced Shopping Muse, a generative AI tool retailers can use on their websites to create a more personalized online shopping experience. Shopping Muse ingest shoppers’ chatbot prompts about product, services, prices and similar concerns and creating recommendations, suggestions and shopping bundles that fit in with their interests.
It uses natural-language processing and image recognition capabilities and personalization algorithms to communicate with shoppers, translating what Mastercard calls “consumers’ colloquial language into tailored product recommendations.”
Such features “are the next natural step in the retail revolution and are core to putting the consumer back at the center of the journey,” Raj Seshadri, president of data and services at Mastercard, said in a statement. “We’re putting technology and machine learning to work to deliver better outcomes for both brand and consumer.”
Mastercard, the world’s second-largest payment processing company, said Shopping Muse can help buyers find the right item even if they can’t properly describe it and recommend – using image recognition tools – products based on their similarities to others. It also uses what it knows about the shopper, including their session browsing history or past purchases, to anticipate future buying desires.
Data Is Key
According to Mastercard, Shopping Muse is best used by companies in industries with large and diverse product catalogs, such as furniture and fashion. The platform can use data from the ecommerce company using it and the industry they’re in. It also ingests contextual data, such as the weather at the user’s location.
“Shopping Muse can be launched from any place on your website, as a chat icon, as a widget, or even in the navigation bar to complement search,” according to Mastercard.
Shopping Muse is based on Mastercard’s Dynamic Yield, a personalization platform and decision engine that the company bought from McDonald’s last year. At the time, Seshadri said Dynamic Yield would grow the personalization capabilities of e-tailers.
“The notion of going into a store or opening a webpage to find an experience perfectly tailored to you is no longer farfetched,” he said. “It’s a reality that more brands are deploying and more consumers expect.”
Better Than Bots
“Consumers have been using search engines for more than 20 years now to find what they are looking for, and it is still something that does not always work for them,” Todd R. Weiss, senior analyst with The Futurum Group, told Techstrong.ai. “That is because consumers sometimes do not use the right search terms to find things on their own.”
Tools like Shopping Muse “could be much more effective than bots that get confused after just a few words are entered and quickly cannot figure out what humans are trying to do,” Weiss said. “This is very frustrating for shoppers. If the bot can’t help, then what is the point of them?”
Shopping Muse will be welcomed by retailers and shoppers as long as it follows through on its promises to provide useful search results regardless of the quality of the users’ chosen terms and is easy to use.
“If it works here, it will likely work for other industries as well, so there is a lot at stake in making this a successful tool from the start,” he said. “But the first version must work from the outset.”
Ecommerce and AI
Shopping Muse enters a booming global ecommerce market – Vantage Research analysts expect it to grow from $7.8 trillion last year to $26.6 trillion by 2030 – that is rapidly embracing AI and machine learning capabilities.
According to a Salesforce report, 17% of shoppers say they’ve used generative AI to get inspiration for product purchases. In addition, 62% are very or somewhat interested in generative AI researching electronics and appliances, while 44% said the same for getting outfit or wardrobe inspiration and creating meal plans. About 39% said they’re interested in the technology for beauty recommendations.
Retailers are all in on generative AI, including 96% that said they are using or plan to use it for creating a conversational digital shopping assistant to help shoppers find the right product or service. Also, 92% said they are investing in AI more than ever to improve the shopping experience.
Others Jumping In
Mastercard isn’t the only vendor that is rolling out generative AI tools to personalize the shopping experience. In October, Walmart unveiled work it’s doing to use the technology for shoppers in a variety of ways, including bringing a better understanding of context to the search experience, enabling search by specific use cases, and helping customer with complex purchases like finding an age-appropriate cell phone that works with the customer’s wireless carrier.
The retailer also is looking at features for its mobile app that would allow customers to shop using voice commands, engage in conversations with the AI assistant, and booking pickup and delivery times.
In May, grocery delivery and pickup company Instacart introduced Ask Instacart, a generative AI-powered search tool using ChatGPT and Instacart’s own AI technologies to answer users questions about topics like food and meals and then to quickly gather and deliver the ingredients the users need. It helps make the billions of shoppable items in more than 80,000 Instacart partner retail stores more easily searchable.
“Ask Instacart is a reimagined yet still familiar search experience directly embedded in the search bar in the Instacart app, providing customers with product recommendations that are intuitively organized, as well as additional useful information about food preparation, product attributes, dietary considerations, and more,” Instacart Chief Architect JJ Zhuang wrote in a blog post.
Zhuang added that the search experience also now includes “personalized question prompts into the search bar that anticipate customer preferences, remind them of their needs based on their shopping history, and inspire them to discover new products.”