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Data-Driven Churn Prevention Project by pallavtyagiofficial is a document available to read on EtoBox.
The research project aims to develop a data-driven model for predicting customer churn and optimizing sales strategies at Stadtwerke Bielefeld, addressing high customer turnover in the energy market. Students will analyze existing data and create predictive models to identify at-risk customers, ultimately enhancing customer retention and satisfaction. The project involves collaboration with various departments and focuses on integrating data science methods into operational systems for sustainable business
- Author
- pallavtyagiofficial
- Language
- EN