Create a better shopping experience for customers to improve customer satisfaction, need, preferences 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 leveraging product attributes, like items, history and seasonality.
Build an assortment framework leveraging qualitative and quantitative strategies 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.