Case Study: Jules achieves smarter in-season merchandising and improved sell-through with Nextail Labs

Jules boosts in-season merchandising across 550 stores with Nextail

The French menswear retailer Jules partnered with Nextail's AI-driven merchandise planning platform to transform its core in-season processes. The challenge was to move away from manual, sales-based replenishment towards a more precise, demand-driven approach. This shift aimed to boost sell-through, reduce missed sales due to inventory misallocation, and support the brand's zero-waste ambitions.

Nextail implemented a solution using machine learning for demand forecasting and decision automation for allocation and replenishment across Jules's 550 stores. This enabled the team to base decisions on future sales predictions rather than past sales, drastically improving inventory precision. Results included a potential 80% reduction in time spent on manual work, improved productivity, and strong adoption by both procurement and store teams, setting a foundation for more dynamic operations.

Jules