Fanatics and OpenAI Collaborate to Launch AI Shopping Recommendation Feature
CNBC
1h ago
Ai Focus
Fanatics launches a new feature named “Shop the Look”, utilizing OpenAI's Codex to recommend matching products for sports fans. The company claims that since the launch of this feature, the browsing volume of recommended products has increased by 10%.
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At any given time, Fanatics offers over 1.5 million unique SKU items for sports fans to purchase – ranging from team jerseys and hats to streetwear and socks with team logos. With the launch of a new feature called “Shop the Look”, finding these products has become even easier thanks to the OpenAI and its Codex.

The product portfolio of Fanatics reflects its growth into a massive sports industry platform, with collaborations with nearly all major global sports leagues and teams. Fanatics Commerce produces over 45 million items annually and sells them to customers in more than 180 countries.

However, Fanatics Commerce, the Chief Product Officer, stated that this growth also presents challenges for the company.

"One issue we've always seen is that customers come to our website, and we operate hundreds of such websites... The difficulty for them is that they have to browse through our very large catalog to try and figure out what they can buy," he said.

Tsai indicates that the average shopping session for customers typically exceeds 30 minutes, and with Fanatics launching thousands of new products each week, this duration is continuing to increase.

“Shop the Look” will recommend well-matched clothing on each product page, and match these items with other available products based on the team and desired style.

Tsai says that traditional shopping curation methods, such as taking photos and styling, don't always allow for enough preparation time to keep up with the rapidly growing product pool of Fanatics. These methods are also not suitable for products that need to be launched quickly, like championship memorabilia shirts and hats.

He stated that random recommendations are also ineffective for sports fans. “No Dodgers fan in Los Angeles would want to be matched with products related to the San Francisco Giants... In our world, the matching of teams and players is very important.”

Although Fanatics has grown into a company with a market value of several billion dollars, merchandise related to the team remains its largest source of revenue. Fanatics, the founder and CEO of Michael Rubin, stated earlier this month in CNBC's Squawk Box that the company's business revenue this year will exceed 7 billion dollars, while the revenue from collectibles, including Topps trading cards, is about 5.5 billion dollars.

Since its launch from OpenAI to ChatGPT, __BJWKEEP__ has been experimenting with shopping tools, including a feature introduced last autumn that allowed users to directly purchase products from merchants within ChatGPT. However, according to reports from CNBC, __BJWKEEP__ is ending its Instant Checkout initiative and is instead collaborating directly with retailers to create dedicated apps within ChatGPT.

The new feature of Fanatics is another way in which OpenAI applies its technology to shopping scenarios. According to the person in charge of GTM in the OpenAI industry, the issue of personalization in retail is "a problem that has existed for a long time." Although the rise of e-commerce has provided retailers with new ways to "understand customer characteristics"—whether it's past purchase records, the locations where users browse websites, or logged-in accounts—these efforts can sometimes still be inaccurate.

“In the past, we tried to put together content that was suitable for presenting to customers,” said DeArago. “With AI, you can achieve personalization in a more definitive way, through a higher level of matching.”

"Shop the Look" uses the Codex created by OpenAI to parse product and catalog data, find compatible items, and re-evaluate recommendations. Ultimately, this process generates styling suggestions that may recommend fans to purchase jerseys along with hats, socks, and other accessories.

Tsai indicates that after the launch of this new feature, the views of recommended products increased by 10%. He also said that these recommended products allow shoppers to be 'more confident' about the products they are considering purchasing, as they can see how they match with other team-related merchandise.

DeArago indicates that although there will always be more carefully crafted looks and in-store fitting opportunities in the shopping experience, an integration like AI – which can help narrow down the vast range of product choices and show what high-value items such as authentic team jerseys might suit – suggests that 'there is a very great opportunity to enhance the existing experience.'

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