Due to the COVID-19 Pandemic, the University has instruction to cancel all in-person events through the Spring semester to adhere to city and state orders limiting public gatherings. Events still running must now take place Online— listed events will include a link in which one may access the Online webspace:

To view Ms. Kenney’s defense, enter her Online chatroom via Microsoft Teams— it will open at 2:30 pm on Tuesday, May 5, 2020.

Predicting Customer Churn

Ms. Maddillon Kenney
University of Wisconsin-Milwaukee
MS Graduate Student – Teaching Assistant

“A primary goal for most businesses is to generate revenue to make a profit. Businesses need customers in order to do so. When a customer leaves or churns from a business, the opportunity for potential revenue is lost. Thus, an important factor in business is gaining and retaining customers. The cost of acquiring a new customer is more expensive than retaining an existing customer. Additionally, long-term customers can be worth more to a company than newly recruited customers. Ideally businesses should identify potential churners before they leave and employ customer retention strategies. To predict customer churn, previous customer transactions are analyzed. This paper demonstrates how information about customers can be used to predict whether they will churn or not from their phone company.”

Committee Members:
Profs. Gabriella Pinter, David Spade (Advisors); & Istvan Lauko

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