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Analytics for an Online Retailer: Demand Forecasting and Price Optimization

Analytics for an Online Retailer: Demand Forecasting and Price Optimization

How does an online flash sales company like Rue La La determine pricing for an ever-rotating selection of products it has never sold before? In this powerful research, Kris Johnson Ferreira (HBS), Bin Hong Alex Lee (MIT), and David Simchi-Levi (MIT) use machine learning to predict future demand for new products, including those that are new to Rue La La’s inventory. Using data analytics and machine learning, the researchers were able to increase revenue by almost 10%, making this a must-read article for any retailer looking to leverage the power of analytics and algorithms to impact their bottom line.

 

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  • Kris Ferreira

    Kris is an assistant professor of business administration in the Technology and Operations Management Unit at Harvard Business School.

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