Customer churn is a critical issue that telecom companies face in retaining their customers. The ability to identify the key drivers of churn and take action to reduce it can have a significant impact on the bottom line. In this project, we utilized IBM Cognos Analytics to model the customer churn data and uncover the main drivers that affected churn. By exploring the data, we aimed to gain valuable insights into the customer behavior and the impact of different variables on churn.
Our analysis was based on a comprehensive set of customer attributes, including demographics, service usage, and payment information. Through a series of data manipulation and visualization techniques, we identified the top three drivers affecting churn, which were customers with less than 3 months of fiber optic service, those with 10-24 months of fiber optic and electronic check, and those with 10-24 months of fiber optic and mailed check. These insights provided a deeper understanding of the customer behavior and helped us focus on the most critical areas for reducing churn.
In addition to the top drivers of churn, we also discovered some noteworthy trends in customer behavior. For example, we found that customers with no internet service or customers with a DSL churn at a lower rate when compared to the customers with a Fiber Optic from the telecom company. Moreover, our analysis revealed that customers paying with an Electronic check have the highest churn rate, and customers with a tenure less than 3 months and who have a fiber optic have the highest churn rate overall.
In conclusion, this project highlights the value of IBM Cognos Analytics in identifying critical drivers of churn and providing insights to inform business decisions. The findings from this study can be used by telecom companies to improve customer retention, reduce churn, and increase profitability. By leveraging the power of data analysis and modeling, we were able to uncover hidden patterns and gain valuable insights into the customer behavior, which can be used to drive business decisions and improve overall performance.
- IBM Cognos Analytis
- IBM Watson
