In
practice, firms are often faced with pricing challenges including high demand
uncertainty, limited inventory, and restrictions to conduct price
experimentation. In this talk, I will discuss models and algorithms that
combine machine learning and price optimization. The key idea of these
algorithms is to use real-time sales data to improve pricing decisions. I will
report simulation and field experiment results that show significant revenue
improvement using these methods.