Optimizing Product Offers with Machine Learning and the Mixed Logit Model

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. This presentation was made to the 2021 informs Business Analytics Conference by John Colias, Affiliate Assistant Professor of Business Analytics at the University of Dallas & Senior Vice President at Decision Analyst and Beth Horn, Senior Vice President, Advanced Analytics at Decision Analyst.

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Would it be possible to access your Python scripts used for the Mixed Logit model?