This story is part of Glossy and Modern Retail’s series breaking down the big conversations and innovations at NRF 2024: Retail’s Big Show. Click here for more stories in this series.
AI is the hot topic at the National Retail Federation’s Big Show this week in NYC. And, according to attending executives, the fashion industry — with its complex supply chains, lagging digitalization and growing transparency challenges — has become ground zero for testing new AI capabilities.
With product assortment being many fashion shoppers’ draw to stores and e-commerce sites, fashion retailers have increasingly prioritized the ability to track customer data to get an accurate sense of their brand sentiment. Now, other industries like grocery retail are taking fashion’s lead. For its part, NRF exhibitor Avery Dennison is now tackling grocery supply chains, after proving its ability to leverage data to effectively manage fashion’s complex supply chains.
The original adoption of AI among fashion retailers 5-8 years ago was primarily driven by its ability to enhance personalization, streamline inventory management and provide deep customer insights. Since then, through ongoing analysis of customer data and preferences, AI has enabled retailers to offer highly personalized shopping experiences, thus increasing customer engagement and loyalty. Now, other retailers are catching on.
“Consumers have a passion for clothing, more so than their passion for broccoli,” said Mike Colarossi, vp of innovation, product line management and sustainability at Avery Dennison, while discussing why the grocery industry is leveraging fashion-native technologies like RFID labeling — grocery is now using RFID labels to track grocery products. Colarossi said that, since there’s a bigger consumer influence in the apparel industry adapting and innovating itself, it has become the testing ground for new technologies before other industries.
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But, according to Ritu Bhargava, president and chief product officer at cloud technology company SAP CX, consumers in every category share demands. “Increasingly what we’re seeing is the need for convenience — the same convenience a customer experiences online, but in a store, or the other way around,” she said.
Despite its reputation for being slow to evolve, fashion has learned to embrace technological innovations, and it’s even getting ahead. For example, brands like Esprit and Aldo are currently building their own data science and engineering teams to address technologies, including advanced large language models and generative AI. The companies are early to test these technologies at scale, within their complex supply chains Large language models are being used to manage the inflow of information from suppliers, and generative AI is being used to automate orders.
“The retail experience has been around for 100-150 years and, for the most part, it hasn’t really changed,” said Scott Lux, global technology and digital commerce executive at fashion brand Esprit, which relaunched in the U.S. last year. The Hong Kong-based company reported a total revenue of around $385.1 million for the first half of fiscal year 2023. “That’s what makes it interesting — there’s always this dynamic connection between the brand and customer.”
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Lux has led a team of 10 data scientists at Esprit since May 2023, as well as overseeing a global tech team of 100 spanning IT, technology, data and security. The team is tasked with managing the brand’s data lake across its in-store and online customers and creating computer modeling for AI systems. A data lake is a central hub that handles, processes and safeguards vast quantities of data.
“Fashion is the breeding ground for technology innovation integration because it has the opportunity to learn from the data and then apply it in a commercially effective way,” said Marc Chretien, vp of post-purchase operations and business analytics at the Aldo Group.
Companies in the fashion industry can have millions of data points on their customers. Personal styling company Stitch Fix reportedly collects 90 data points per customer and has 3.7 million active users, adding up to 333 million data points on its customers alone, before factoring in data points from its supply chain.
“There are so many interactions; people are walking in and out of stores, people are browsing on websites — all of these have become data points,” said Chretien. “If the data becomes available, and it’s being handled the right way, the ability to infer and come up with patterns is much more prevalent in fashion retail versus other industries which just don’t have that frequency or volume.”
As for how to manage innovation, Lux said there are advantages to brands running programs in-house. “It allows for more control of data sources,” he said. “We can pull data in from Facebook’s API and filter it according to which attributes we want [included] in our data lake house. It ensures consistency in how we’re integrating and structuring the data. With a partner, we don’t necessarily know how the model is constructed, even if they always say it’s our data.”
Footwear and accessories company Aldo Group, which reported sales of just over $1 billion in 2023, has leveraged generative AI since last year. The company is now building an AI sandbox where its marketing, wholesale and design teams can test early versions of new tools and features, like AI-generated graphics, predictive copy inputs or wholesale management.
“We enlist partners to manage things like fraud prevention and order management,” said Chretien. “But with merchandise — the inventory handling and optimization — if the intelligence is not inherently built in, we work to add the intelligence, or the ‘brain,’ into the muscles of our platforms to augment their decision-making abilities.”
AI also plays a crucial role in predicting fashion trends and managing inventory, helping to minimize overproduction and stockouts which have plagued retailers since the Covid pandemic. Other industries like agriculture and grocery have faced similar challenges, and fashion’s complex supply chains are allowing brands to put predictive AI through its paces.
Aldo is testing it by routing products to where they are most needed. “If a hurricane flew through Florida, those consumers are going to have priorities on their mind other than buying shoes,” said Chretien. “So the positioning of that time-sensitive inventory is important, and if you put it in the wrong spot, you lose it in markdowns and discounts in the future weeks and months. So it’s better to reposition it, and AI is going to help us get those insights.”
