Predictive Analysis for Customer Churn: A Case Study on Uber

To apply predictive analytics techniques to identify and predict customer churn within Uber's user base.

To analyze the financial implications of customer churn on Uber's revenue and profitability.

To develop strategies for mitigating customer churn and increasing customer retention within Uber's business model.

Collect and clean relevant data on Uber's customer base, including demographic information, usage patterns, and financial transactions.

Utilize machine learning algorithms to develop a predictive model for identifying customers at risk of churning.

Analyze the financial impact of customer churn on Uber's revenue and profitability.

Identify key factors contributing to customer churn within Uber's business model.

Develop data-driven strategies for reducing customer churn and increasing customer retention within Uber's user base.