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:
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Service Performance Analysis: Identify underperforming services to improve customer satisfaction.
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Churn Factors Identification: Determine variables affecting customer churn using existing account data.
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Successful Service Identification: Identify services with high customer satisfaction for attracting new customers.
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High-Value Customer Identification: Identify high-value customers for premium membership retention.
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Customer Churn Rate: The percentage of customers who have discontinued their subscription.
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Customer Lifetime Value (CLV): The net profit associated with a customer over a fixed period.
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Database Creation: Create a database, define schema, primary/foreign keys, and relationships, and apply normalization rules.
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Data Refinement: Make necessary schema modifications.
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Insights Generation: Analyze data using SQL to identify factors affecting CLV and churn.
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Data Visualization: Utilize Tableau for data exploration, dashboard creation, and storytelling.
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Python Integration: Connect Python to the database for advanced analysis.
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SQLite: Lightweight, portable, and easily integrated with Python and Tableau.
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Python: For running queries and complex calculations.
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Tableau: For data exploration, visualization, and storytelling.
The data used for the analysis can be accessed from Below links: