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Rue La La’s "virtual boutiques" offer products for a limited time – typically only two or three days – before customers may no longer purchase the products. Correctly pricing these items is challenging, since the company has never sold the majority of these products before. In the past, more than 50 percent of products quickly sold out, suggesting that the price was too low. For other products, the price may have been too high, leaving the company with unwanted inventory. The pricing-optimization application developed aimed to maximize revenue while maintaining demand for the products. The approach starts with machine learning techniques that develop a demand-prediction model; the resulting data is then fed into a price-optimization model. After implementing these analytics techniques, Rue La La is expecting an increase in revenue of more than 10 percent with little impact on demand.”