Track: Machine Learning
Optimizing Product Offers with Machine Learning and the Mixed Logit Model
Tuesday, April 13, 1:45-2:25pm EDT
How does one create an efficient analytical pipeline that begins with data for responses (sale or no sale) to real offers made to customers and ends with an optimal offer of product and price to any current or potential customer visiting a retail site? This presentation will outline an analytical pipeline that uses machine learning to optimize a mixed logit model and then applies nonlinear programming to optimize the offer. The advantage of the mixed logit model vs. other popular machine learning models is that the mixed logit model is grounded in economic theory and thus produces sound pricing recommendations. The predictive accuracy of the mixed logit model will be compared to that of other types of models used for machine learning. Data requirements, estimation and optimization methods will be presented with empirical evidence using transactions data.