Chateau Winery (B): Supervised Learning
This case builds directly on “Chateau Winery (A).” In this case, Bill Booth, marketing manager of a regional wine distributor, shifts to supervised learning techniques to try to predict which deals he should offer to customers based on the purchasing behavior of those customers closest to them.
Topics include supervised learning; collaborative filtering; K-nearest neighbor as a modeling technique, collaborative filtering with cosine similarity of customers, collaborative filtering with cosine similarity of products, and comparison of different prediction models.
Topics include supervised learning; collaborative filtering; K-nearest neighbor as a modeling technique, collaborative filtering with cosine similarity of customers, collaborative filtering with cosine similarity of products, and comparison of different prediction models.
Keywords: data science; clustering; Data and Data Sets; Customers; Marketing; Analysis;
Citation:
Datar, Srikant M., and Caitlin N. Bowler. "Chateau Winery (B): Supervised Learning." Harvard Business School Supplement 119-024, August 2018. (Revised April 2019.) View Details
