Analytics for an Online Retailer: Demand Forecasting and Price Optimization
Engineering Systems (United States) · Massachusetts Institute of Technology
Abstract
We present our work with an online retailer, Rue La La, as an example of how a retailer can use its wealth of data to optimize pricing decisions on a daily basis. Rue La La is in the online fashion sample sales industry, where they offer extremely limited-time discounts on designer apparel and accessories. One of the retailer’s main challenges is pricing and predicting demand for products that it has never sold before, which account for the majority of sales and revenue. To tackle this challenge, we use machine learning techniques to estimate historical lost sales and predict future demand of new products. The nonparametric structure of our demand prediction model, along with the dependence of a product’s…
Citation impact
- FWCI
- 44.28
- Percentile
- 100%
- References
- 41
Authors
3Topics & keywords
- Revenue management
- Revenue
- Demand forecasting
- Product (mathematics)
- Analytics
- Dynamic pricing
- Pricing strategies
- Point of sale