Fanatics and OpenAI Launch AI Tool to Help Sports Fans Build Outfits

Fanatics now lists more than 1.5 million unique products for sports fans, from jerseys and hats to team-branded streetwear and socks. Finding the right item is getting easier through a new feature called "Shop the Look," built with help from OpenAI's Codex.

The company's product range reflects its growth into a major sports-industry platform, with deals across nearly every major sports league and team worldwide. Fanatics Commerce makes more than 45 million items a year and sells to customers in over 180 countries. That scale brought a problem, said Justin Tsai, chief product officer for Fanatics Commerce: shoppers on its hundreds of sites struggled to sift through the huge catalog. Sessions routinely ran over 30 minutes on average, and the time kept growing as Fanatics released upwards of a thousand new products each week.

"Shop the Look" suggests coordinated outfits on each product page, matching items with other in-stock products based on team and intended style. Traditional curation like photo shoots and stylized outfits has lead times that don't keep up with Fanatics' expanding product pool or fast releases such as championship shirts and hats, Tsai said. Random suggestions don't suit sports fans either. "Nobody who is a Los Angeles Dodgers fan wants to be matched with a San Francisco Giants item ... team and player alignment is extremely important in our world," he said.

Team merchandise remains Fanatics' biggest revenue source. Founder and CEO Michael Rubin told CNBC's "Squawk Box" earlier this month that the commerce business will exceed $7 billion in revenue this year, compared with roughly $5.5 billion for collectibles, including Topps trading cards.

OpenAI has experimented with shopping tools for ChatGPT since launch, including a feature last fall letting users buy merchants' products directly within the chatbot. It is ending that Instant Checkout effort and now works directly with retailers to build dedicated apps within ChatGPT, according to CNBC reporting. Rosemary DeAragon, head of industry GTM at OpenAI, called retail personalization "an age-old problem" and said AI allows more deterministic matching.

The feature uses Codex to parse product and catalog data, find compatible items and reevaluate recommendations, suggesting a hat, socks and other accessories to go with a jersey a fan is considering. Tsai said views of recommended items rose 10% after rollout, and the suggestions give shoppers "more conviction" about purchases. DeAragon said there is a "really big opportunity to enhance the existing experience."

Source: CNBC