Case Study: Guess boosts full-price sell-through with Nextail Labs AI inventory optimization

Guess boosts full-price sell-through by 5pp with Nextail Labs

Guess, a global fashion retailer, faced challenges with rigid store clustering, high initial stock allocations, and manual inventory adjustments, limiting their agility. They partnered with Nextail to revolutionize their in-season merchandising with AI-driven, demand-centric solutions designed specifically for fashion retail.

Nextail implemented automated replenishment with hyper-local forecasting for Guess. This approach allocated a significant portion of stock for in-season needs, boosting SKU availability. The results included a 5 percentage point increase in full-price sell-through, a 7.5% reduction in store coverage, and a scalable merchandising model, all while improving product availability for customers.

Guess