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20190203002518customer Churn Analysis Using Machine Learning.edited 1 .edited

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Running head: CUSTOMER CHURN ANALYSIS USING MACHINE LEARNING Churn Analysis Using Machine Learning and Calculating Performance Name Course Date 1 CUSTOMER CHURN ANALYSIS USING MACHINE LEARNING 2 Churn Analysis Using Machine Learning and Calculating Performance Introduction Customer churn analysis has proven to be one of the critical data analysis tools used in understanding the variables affecting the profit of a company. This tool is especially useful in the evaluation of the different issues that arise during the relationship between the company and the customers. The resulting improvement of such a customer relationship through the assessment of the problems identified results in considerable customer satisfaction that potentially increases the sales volume (Rygielski, Wang & Yen, 2002). For example, customer churn analysis has proven critical in identifying those customers that are likely to shift to a new company, such that the company can design a strategy to retain them if possible. Such an application is critical in companies that operate in a saturated highly competitive environment, as the company will likely never recover any lost customer (Ge, He, Xiong & Brown, 2017). Annotated bibliography Ascarza, E., Neslin, S. A., Netzer, O., Anderson, Z., Fader, P. S., Gupta, S., ... & Provost, F. (2018). In Pursuit of Enhanced Customer Retention Management: Review, Key Issues, and Future Directions. Customer Needs and Solutions, 5(1-2), 65-81. Ascarza et al. (2018) go ...
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