Case Study: Churn Analysis for a Telecom Company

Project Overview

In this case study, we are tasked with analyzing customer churn for a telecom company in Southern California. The company provides home phone and internet services, as well as various other services, and faces the challenge of losing customers to a new competitor. The objectives are as follows:

1. Service Performance Analysis: Identify underperforming services to improve customer satisfaction.

2. Churn Factors Identification: Determine variables affecting customer churn using existing account data.

3. Successful Service Identification: Identify services with high customer satisfaction for attracting new customers.

4. High-Value Customer Identification: Identify high-value customers for premium membership retention.

Key Metrics:

1. Customer Churn Rate: The percentage of customers who have discontinued their subscription.

2. Customer Lifetime Value (CLV): The net profit associated with a customer over a fixed period.

Approach:

1. Database Creation: Create a database, define schema, primary/foreign keys, and relationships, and apply normalization rules.

2. Data Refinement: Make necessary schema modifications.

3. Insights Generation: Analyze data using SQL to identify factors affecting CLV and churn.

4. Data Visualization: Utilize Tableau for data exploration, dashboard creation, and storytelling.

5. Python Integration: Connect Python to the database for advanced analysis.

Tools Used:

• SQLite: Lightweight, portable, and easily integrated with Python and Tableau.

• Python: For running queries and complex calculations.

• Tableau: For data exploration, visualization, and storytelling.

Data Source:

The data used for the analysis can be accessed from Below links:

• Intro to the Case Study
• Analyzing Churn and LTV Using SQL and Python
• Creating a Tableau Story