Realtime AI News
Fanatics rolls out OpenAI-powered Shop the Look with a 10% engagement lift
OpenAI and Fanatics launched an OpenAI-powered Shop the Look that recommends coordinated team outfits on product pages across Fanatics.com and the four major league stores. Testing on roughly 30,000 MLB products showed 10% higher engagement than the previous experience.
OpenAI and Fanatics, a global digital sports platform, are putting AI recommendations directly into the shopping path with a new OpenAI-powered version of Shop the Look.
The feature is now live across many sites in the Fanatics network, including Fanatics.com and the official NFL, NBA, MLB and NHL online stores. When a fan browses a favorite team's jersey, Shop the Look surfaces coordinated outfits on the product page.
The recommendations are not a simple same-category carousel. OpenAI models draw on enriched product data, team information and inventory signals, while Fanatics merchandising rules keep the combinations compatible and relevant, with looks refreshed daily as catalogs change.
The build process is part of the story. Using Codex, OpenAI and Fanatics engineers created custom tools to enrich product and catalog data, find compatible merchandise, evaluate recommendations and generate looks for each product.
Testing the approach on 50 products took less than a day. Fanatics reviewed the results, sent feedback directly to the builders, and approved a minimum viable product the same week after a couple of days of iteration, then scaled it across thousands of products in production.
The headline result: across roughly 30,000 MLB products, the OpenAI-powered experience delivered 10% higher engagement than the previous version.
Fanatics also uses ChatGPT Work and Codex across its corporate, commerce, collectibles, and betting and gaming businesses, which makes it a broad reference customer rather than a single-feature pilot.
What to watch is whether the 10% lift holds across other leagues and categories, and whether outfit recommendations get wired into inventory planning, pricing and personalization next.
Why it matters
It gives OpenAI a retail case study with a hard engagement number, a useful proof point as model vendors compete for commerce deployments.
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