CASE 

STUDY: JEANS

Our task was to generate automated future assortment optimization recommendations to match inventory and pricing with customer demand, to  increase profit margin, and to improve the customer experience

TRENDS

Accurately forecasted wide leg jean trend 6 months in advance

DEMAND

 92.3% accuracy

of demand forecasts

PRICING

Identified price gaps at $20-30 and >$60 price points

PRODUCT

Identified fabric and fit improvement opportunities, in 6% of styles

 

Generated assortment optimization recommendations six months prior to season start with projected 100+ basis points increased profitability