Agentic AI shopping journeys are going mainstream, and companies will now need to consider how any AI platform's access to data could affect the human shopping experience.
This will lead to the creation of a new approach to website design, according to Andrew Laudato, EVP and COO at The Vitamin Shoppe.
“For humans, you want to curate the assortment, curate that content, and just give them the things they need so they can transact,” Laudato said at the National Retail Federation Big Show earlier this month. “On the flip side, AI wants really, really clean data on fulfillment and inventory in real time by location.”
Retailers will want to ensure their data is clear and accurate to have it ready for AI agents. However, this is easier said than done — relevant data can come from any number of sources depending on the kind of information the AI is looking for.
While the entire process is complicated, the first step in preparing data for an AI future is getting it clean and accessible, according to Laudato.
“I’m sorry, you've heard this 100 times, but you’ve got to get your data right,” Laudato said. “The data has to be rich, it's got to be clean, it's got to be in a place where it can be consumed.”
The information needs to cover every potential element of a transaction as well, according to Laudato. AI agents don’t just need to know what products are in stock, they also need to know about special offers that may apply to orders and what payment systems are available.
The process of identifying data is just the starting point, according to Laudato. Companies will need to consider the formats in which they present the data and which bots are allowed or blocked from their site.
There is no single source of truth
Retailers have a lot of data-based work ahead, whether they are preparing to design their own AI platforms or preparing to work with third parties, according to Nikki Baird, VP of strategy and product at Aptos.
Details from historic prices to physical location are key to any AI application, whether it’s helping a customer place an online order or ensuring store operations run smoothly.
“You need to bring in inventory, you need to bring in the awareness of where that inventory is,” Baird told CX Dive during an interview at the NRF show. “You need to understand promotion price changes and when that promotion expires and the regular price goes back into effect.”
Most companies are working with multiple relevant data sources, and each is best suited for specific queries, according to Baird. Point of sale data is great if an AI needs current pricing information, while sales audit information is better for historical data.
When a customer’s own data is relevant to their query, the CRM system likely holds the answers.
“You have to have the right context attached to what data source you use at any given point in time,” Baird said. “It's not realistic to say I'm only going to have one version of the truth and that all of the data is going to be here.”
Retailers need to understand the nuances of how their data points fit together, according to Baird. Whether the AI is shopping on behalf of a customer or helping an associate answer a question, the technology needs access to information relevant to the current task.
‘No one has missed the AI train’
The amount of work ahead may seem herculean, but even the biggest players are just at the beginning of their AI rollouts.
Laudato cited a November Harris Poll survey, which found 40% of shoppers were using AI tools in their holiday gift-buying journeys. However, while the technology is popular for product discovery and information gathering, very few people are letting AI agents complete purchases on their behalf.
This is a sign that consumers are just starting to get comfortable with the technology, according to Jack Hilger, senior director of North America Product at Visa.
“Nobody has missed the AI train,” Hilger said during the session. “I think we still have a long run ahead of us in terms of getting consumers comfortable with agents, and getting an ecosystem ready to support agents.”