Why is “complete the look” one of the most natural ways to apply AI in fashion? Because a single product instantly implies others — and showing the full outfit while a shopper browses turns interest into a bigger basket and a longer session. Levi’s built exactly that with its Outfitting feature.
The result: Levi’s AI-powered ‘Outfitting’ feature recommends styled looks during browsing and learns from customer choices, reportedly achieving a 30% increase in off-hours engagement — with higher satisfaction and loyalty among shoppers who use it.
Styling the browse experience#
When a shopper views a pair of 501s, Levi’s Outfitting surfaces a “Complete the Look” section with suggested denim outfits — assembled from inventory data, aggregated purchase history, browsing behavior, and product imagery. It updates daily, noting what fans buy together and prioritizing recent trends, with seasonality and merchant input layered in. The effect is that browsing becomes styling: shoppers don’t just look at one item, they see how to wear it, which deepens engagement and grows the basket.
The reported 30% lift in off-hours engagement points to something useful: a styling feature gives shoppers a reason to explore even when they’re casually browsing, not just when they’re ready to buy.
How browse AI works#
Browse AI personalizes the exploration experience, surfacing relevant products as shoppers browse. Levi’s version focuses on assembling complete, styled looks.
Three mechanics drive it. The engine assembles outfits, surfacing complementary pieces as a complete look rather than isolated items. It learns from choices, refining recommendations based on what shoppers engage with and buy together. And it stays fresh, updating daily with trends and seasonality so the looks feel current.
Why styled looks deepen engagement#
The lesson is that styling transforms browsing from a transaction into an experience. A “complete the look” feature invites shoppers to imagine outfits, explore combinations, and engage even outside peak buying moments — which is why off-hours engagement rose. And engaged shoppers buy more: seeing the full look both grows the basket and builds the satisfaction and loyalty Levi’s reports among users of the feature. Styling turns a product page into a reason to keep exploring.
What this means for your store#
Any store whose products combine can apply this:
- Assemble complete looks or sets during browsing, not just isolated recommendations.
- Learn from what shoppers buy together to refine the combinations.
- Keep the looks fresh with trends and seasonality so they stay relevant.
Shoppers engage with outfits, not just items. Styling the browse deepens engagement and grows baskets.
Bring browse AI to your store with CartAmplify#
CartAmplify brings styling-style, complete-the-look browse AI to any store — Shopify, dropshipping, or marketplace. Turn browsing into styled discovery, the way Levi’s Outfitting deepens engagement.
Related reading#
- How Amazon’s Browse Recommendations Drive Cross-Sell
- How Zara Uses Browse Data and AI for 2-3 Week Cycles
- How Spanx Uses Browse AI to Reduce Choice Overload
The +30% figure is as reported for Levi’s Outfitting; Levi’s also reports higher satisfaction and loyalty among users of its personalization features. Results vary by catalog, traffic, and implementation.
