Case Study: Boggi Milano boosts retail performance with RetailNext in-store analytics

Boggi Milano reduces headcount by 15% with RetailNext

Boggi Milano, an Italian menswear brand with 235 global stores, sought to improve its analysis of store performance in 2018. The challenge was an inability to maximize and streamline labor, a lack of reliable methods to identify high-traffic but low-conversion stores, and limited visibility into shoppers handled per labor hour. To address this, they partnered with vendor RetailNext for its in-store analytics expertise.

RetailNext implemented its platform powered by the Aurora IoT sensor and a predictive traffic model. This solution allowed Boggi Milano to analyze visit duration and shoppers-per-labor-hour store by store to determine optimal staffing. The results were significant: the brand reduced headcount by 15%, lowered payroll expense, increased productivity, and grew shopper yield by 40%. Additionally, RetailNext helped lift the conversion rate by 5 points and increase the average ticket by 15%.

Boggi Milano