Clustering Customers at Chateau
This case was written for the EC course "Managing with Data Science." The course provides MBA students with no programming experience an introduction to the field of data science and its applications in business. Students learn to (1) carefully articulate the business ask; (2) reason carefully from the ask, through metrics and models and outputs; and (3) evaluate outputs from models to (4) develop a plan for action. In this case students explore data through k-means clustering, evaluate the relevance of those clusters to a marketing question, and compare the difference between k-means and Gaussian mixture models. They also learn the value of collaborative filtering for predicting customer preferences.