This dataset provides information about customers of a telecommunications company and whether they churned (i.e., discontinued their services) or not. Churn is a critical business metric for telecom companies, as retaining customers is generally more cost-effective than acquiring new ones.

a) Dependents: Does the customer have dependents or not. b) tenure: How long the customer has subscribed to the company's services. c) OnlineSecurity: Does the customer use the Online Security service or not. d) OnlineBackup: Does the customer use the Online Backup service or not. e) InternetService: Does the customer subscribe to Internet Service or not. f) DeviceProtection: Does the customer use the Device Protection service or not. g) TechSupport: Does the customer use Tech Support services or not. h) contracts: The duration of the contract used. i) PaperlessBilling: Is the bill sent on a paperless basis or not. j) MonthlyCharges: Number of bills charged each month. k) Churn: Has the customer unsubscribed or not.

1° Customer Churn Analysis: Explore the factors that influence customer churn and identify patterns. 2° Predictive Modeling: Build predictive models to forecast customer churn. 3° Customer Segmentation: Segment customers based on their behavior and characteristics. 4° Feature Engineering: Create new features based on existing data to improve model performance. 5° Business Strategy: Inform business decisions related to customer retention and satisfaction.

Link: https://www.kaggle.com/datasets/reyhanarighy/data-telco-customer-churn/data