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This case exposes students to predictive analytics as applied to discrete events with logistic regression. The VP of customer services for a successful start-up wants to proactively identify customers most likely to cancel services or “churn.” He assigns the task to one of his associates and provides him with data on customer behavior and his intuition about what drives churn. The associate must generate a list of the customers most likely to churn and the top three reasons for that likelihood.
Copyright © 2013 by the University of Virginia Darden School Foundation, Charlottesville, VA. All rights reserved.
2013
University of Virginia Darden School Foundation
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