Analyze the telecom customer data to predict churn and retain high-profit customers.
Business Problem: In the fiercely competitive telecom industry, retaining high-profit customers is paramount. With an annual churn rate of 15-25%, it's crucial for telecom firms to predict customer churn and take proactive measures to retain valuable subscribers. This project focuses on analyzing customer-level data, building predictive models, and identifying key indicators of churn to facilitate effective retention strategies.
Definition of Churn: Churn is defined based on usage, where customers who exhibit zero usage - incoming or outgoing calls, internet, etc. over a certain period are considered churned. The challenge lies in predicting churn early enough to implement corrective actions before customers switch to competitors.
Business Objective: The primary objective is to predict churn in the ninth month using data from the preceding three months. Understanding typical customer behavior during churn is crucial for effective prediction and intervention.
Understanding Customer Behavior During Churn: Customers typically go through three phases:
- The 'good' phase where they are satisfied with the service.
- The 'action' phase where dissatisfaction may arise due to various factors.
- The 'churn' phase where the customer ultimately switches to another provider. Identifying high-churn-risk customers during the action phase is vital for implementing timely interventions.
Data Description: The dataset spans four consecutive months - June (6), July (7), August (8), and September (9). Each month provides customer-level information, with the third month representing the action phase and the fourth month indicating churn. Understanding and utilizing this temporal pattern are crucial for accurate churn prediction.
Data File: Filename: telecom_churn_data.csv
By leveraging this data and understanding customer behavior dynamics, we aim to develop predictive models that enable telecom firms to anticipate churn and implement targeted retention strategies, thus maximizing customer retention and profitability.