Churn Case Study

Problem Statement

Understanding the factors contributing to customer churn is crucial for improving retention strategies and enhancing customer satisfaction. This case study aims to analyze churn rates and identify key reasons behind customer attrition.

Methodology

We applied a comprehensive data analysis approach using Power BI to examine various aspects of customer churn. The methodology included:

• Data Collection: Gathering data on customer demographics, contract types, payment methods, service usage, and churn reasons.

• Data Modeling: Structuring the data to facilitate analysis, including categorizing churn reasons and segmenting customers by age, contract type, and data plan.

• Visualization: Creating interactive dashboards to visualize churn rates, customer service calls, and other key metrics.

Key Insights

• Overall Churn Rate: 26.86%

• Churn Rate by Contract Category and Gender:Monthly: 46.29%
  Yearly: 6.62%
  Gender Breakdown: Female, Male, Prefer not to say
  

• Churn Reasons: Competitor offers, service dissatisfaction, pricing issues, product dissatisfaction, network reliability, and more.

• Churn Rate Analysis:By Age: Analysis across different age groups.
  By Contract Type: Month-to-Month (51.01%), Two Year (26.87%), One Year (22.12%).
  By Payment Method: Direct Debit (55.36%), Credit Card (39.09%), Paper Check (5.55%).
  By Data Plan: Unlimited Data Plan (32.11%), No Unlimited Data Plan (16.10%).
  By Consumption: Less than 5 GB, Between 5 and 10 GB, 10 or more GB.
  By Account Length: Analysis based on the length of the account in months.
  

• Customer Service Calls: Average number of customer service calls and their impact on churn rate.

• Churn Rate by State: Analysis of churn rate across different states.

Best Solutions

Based on the analysis, the following solutions are recommended to reduce churn:

• Enhance Customer Support: Improve the attitude and expertise of support staff to address customer concerns effectively.

• Competitive Pricing: Offer competitive pricing and affordable plans to attract and retain customers.

• Service Quality: Focus on improving network reliability and overall service satisfaction.

• Self-Service Options: Provide more self-service options to empower customers and reduce dependency on support staff.

• Targeted Marketing: Use insights from data analysis to plan targeted marketing activities and improve customer engagement.

Conclusion

The Churn Case Study highlights the importance of understanding customer behavior and the factors leading to churn. By addressing the identified issues and implementing the recommended solutions, businesses can significantly improve customer retention and foster long-term loyalty. This comprehensive analysis serves as a valuable tool for developing effective strategies to reduce churn and enhance overall customer satisfaction.