Case Study: Shoe Palace lifts conversion 10% with RetailNext traffic analytics

Shoe Palace lifts conversion 10% with RetailNext

Shoe Palace, a major sneaker and streetwear retailer with over 250 stores, faced the challenge of managing its diverse store fleet without reliable traffic data. Operations were run on instinct, as the company lacked a way to measure store performance relative to customer demand, making it impossible to accurately pinpoint peak hours or optimize staffing. To address this, they turned to RetailNext and its Aurora sensor for accurate traffic analytics.

By implementing RetailNext's solution, Shoe Palace developed a simple, actionable metric called traffic per labor hour (TPLH). This allowed for smarter labor planning and fair comparisons across different store types. As a result, the retailer achieved a 10% average year-over-year lift in conversion by its second year using the data. RetailNext provided the accurate insights needed to challenge assumptions and drive measurable performance improvements across the entire fleet.

Shoe Palace