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Walmart’s bold plan to bring greater scale, speed, immediacy and insight to every in-person and virtual customer interaction is transforming its customers’ retail experiences.
The Emerging Tech group at Walmart has worked with conversational AI for two and a half years, while relying on augmented reality, spatial computing and spatial awareness technologies to deliver the best customer experiences possible. Conversational AI use cases at Walmart include shopping assistance, customer care automation, and improving associate productivity.
“Approximately 50 million Walmart customers are interacting in some way, shape or form with our conversational experiences, and over a million associates are interacting on these experiences as well,” Desirée Gosby, vice president of emerging tech at Walmart, told the audience at a VentureBeat Transform Fireside Chat, on how Walmart is successfully adopting conversational AI. The session was moderated by Dr. Joan Palmiter Bajorek, founder and president, Women in Voice.
How Walmart achieves global conversational experiences at scale
The company’s goal is to use conversational AI to enable every Walmart department and facility worldwide to “speak retail,” and thus to improve customers’ and associates’ shopping experience at scale and speed. Walmart has seen strong results from its customer care automation, including its conversational AI efforts. These have reduced the time that customer care agents spend with customers, by having 66 million assisted contacts supported and enabled by conversational AI.
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The Emerging Tech team enables teams across the company to create their own conversational experiences at scale, capitalizing on the lessons the company has learned about natural language understanding and processing, including large language models. The team’s approach has allowed it to experiment quickly and learn from its experiences, using its retail knowledge and its data to improve customer experiences.
“When it comes to conversational AI, what we’re really focused on is taking a step back and thinking about how we can actually leverage this across the company to enable all of the different parts of Walmart to speak retail, and do that in a very simple and easy way,” Gosby told the audience.
As the world’s leading retailer, with $622 billion in revenue for FY2023 and $152.3 billion for Q1 FY2024 — revenue that was strengthened by a 27% jump in ecommerce sales — Walmart relies on its Emerging Tech team to reduce the barriers its customers face in finding and buying the products they want. Gosby explained that her team relies on various technologies to take on these challenges.
“We’ve developed experiences including voice assistance, as well as something you might have heard of, Text to Shop, which allows customers to simply send a text of what it is that they need or what it is that they want to do. And that allows them to get their shopping done quickly and easily, removing friction for them,” Gosby told the audience.
Walmart Chile up and running with conversational AI in weeks
Walmart’s focus on building a platform that can be used at scale has allowed it to expand its use of conversational AI outside the U.S., with teams in other countries, such as Chile, able to use the platform within weeks of onboarding. Walmart has been able to scale conversational experiences internationally because of its years of experience with conversational AI and with tailoring technologies to improve customer experiences, Gosby explained.
The Emerging Tech team was able to onboard the Walmart Chile operations in weeks by virtue of its standardized, scalable platform built for speed, customizing the platform for the country’s unique requirements. “For example, with the Chile team, they were seeing different issues from a customer care perspective, but they were able to onboard to the platform and customize what they need to do from a language perspective,” explained Gosby. She told the audience that the Chile team could get everything on board without the need for a natural language expert on their team.
“They were able to create over 60 different flows and saw customer satisfaction increase by about 20% as a result. This ability to move at speed and experiment quickly is one of the key advantages of Walmart’s approach to conversational AI,” said Gosby.
When asked about the challenges of operationalizing large language models, Gosby said Walmart’s challenges are common across the industry. “Making sure we are creating a trustworthy experience, if you will, as part of what we do are a few things we’re working through.” Gosby also mentioned managing costs and dealing with problems such as hallucination as areas the Emerging Tech team is working on.
Ask Sam empowers employees with conversational AI
Walmart’s Emerging Tech team also created Ask Sam, a conversational AI tool designed to boost store associates’ productivity by enabling them to answer customer questions or check their schedules. Gosby says Walmart has over two million associates using the application today, and that it has improved productivity.
“So if you go into a Walmart and if you have a question about something related to shopping, you could go to an associate, and they might use Ask Sam to ask the question about how to find out where something might be located in the store,” Gosby told the audience. “But they also use it themselves to understand what tasks they need to do, their schedule, and things that are related to their productivity. So we’ve seen much value in unleashing these conversational experiences across all parts of our business.”
Delivering real-time experiences at scale
Walmart’s systematic approach to bringing greater scale, speed and AI-driven insight across multiple channels is transforming retail. What’s most fascinating about how Walmart created its conversational AI platform is how quickly deployments in foreign countries can be achieved without extensive language programming or expertise needed.
Walmart’s Emerging Tech team is succeeding in orchestrating leading-edge technologies to anticipate customers’ needs and provide the contextual intelligence they need before they ask for it. That reflects the team’s accumulated knowledge and experience in removing friction before it affects a customer’s buying experience.
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