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Methods of Business Analysis in Customer Churn Rate Improvement

Student: Belousova Elena

Supervisor: Andrey Savchenko

Faculty: Faculty of Informatics, Mathematics, and Computer Science (HSE Nizhny Novgorod)

Educational Programme: Business Informatics (Master)

Year of Graduation: 2017

This thesis is devoted to the study of business analytics methods in customer churn rate improvement. The application of logit regression and neural networks in forecasting is considered.

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