Create a better shopping experience for your customers, improve customer satisfaction, and increase sales.
Build a localized assortment with machine learning guidance based on customer affinity for products and touchpoints.
Use data science to predict new item ROS (Rate of Sale) for each product and touchpoint by leveraging product attributes, like items, history and seasonality.
Build an assortment framework that considers qualitative and quantitative strategies by incorporating insights and historical data.
Visualize a complete season with holistic view of product offerings. Quantitatively measure at aggregated levels like class or category and reconcile plans.