Optimal Beer Pricing: An Optimization Layer for Price Elasticities
Toronto Machine Learning Series (TMLS) via YouTube
Overview
Explore the intricacies of optimal beer pricing in this 41-minute conference talk from the Toronto Machine Learning Series. Dive into the world of price elasticities with Eric Hart, Staff Data Scientist at Anheuser-Busch, as he discusses how changes in beer prices affect sales volume. Learn about the development of data-driven models for predicting elasticities and their implications across various business aspects, including price setting, procurement, and financial planning. Discover how to create an optimal pricing layer using mathematical optimization to generate specific price change suggestions at different granularities, while considering various business objectives such as profit, revenue, and market share. Examine the use of constraints to balance these objectives and ensure price suggestions remain within the bounds of the underlying elasticity models. Gain insights into a real-world example of advancing analytics from predictive to prescriptive in the context of price setting and beer industry dynamics.
Syllabus
Optimal Beer Pricing: An Optimization Layer for Price Elasticities
Taught by
Toronto Machine Learning Series (TMLS)