Predicting Customer Churn at QWE Inc

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Compact case

Predicting Customer Churn at QWE Inc

Case

Reference no. UVA-QA-0806

Subject category: Case Method and Specialist Management Disciplines

Authors: Anton Ovchinnikov (Darden School of Business, University of Virginia)

Published by: Darden Business Publishing

Originally published in: 2013

Version: 2 April 2014

Revision date: 16-Apr-2014

Length: 4 pages

Data source: Field research

Topics: Logistic; Regression; Churn; Churn probability; Retention; Utility of choice; MLE; MNL; Data visualization; Predictive; Analytics; Big data; Regression trees; Ratio of exponents; Quantitative analysis; Management science; Decision analysis; Forecasting

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Abstract

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.

Industry:

Technology