Project

Project Steps:

1. Database Creation:
   • Create a new database for the project, e.g., “CustomerChurnDB.”
2. Data Import:
   • Import sample data into your database. You can use a tool like MySQL Workbench or command-line tools to load data from CSV files. Sample data should include customer information, transaction history, and relevant attributes.
3. Exploratory Data Analysis (EDA):
   • Write SQL queries to explore the dataset, examining the distribution of variables, identifying missing data, and gaining initial insights into customer behavior.
4. Churn Analysis:
   • Identify criteria for defining “churn.” Churn might be defined as customers who haven’t made a purchase in the last 30 days, for example.
   • Write SQL queries to identify and count churned customers based on your criteria.
5. Customer Segmentation:
   • Define criteria for customer segmentation. You can use demographics, purchase history, or other factors.
   • Write SQL queries to segment customers into groups, such as “high-value customers,” “low-value customers,” or “frequent buyers.”
6. Analysis of Customer Behavior:
   • Write SQL queries to analyze customer behavior. Calculate metrics like customer lifetime value (CLV), average purchase value, or purchase frequency for each customer segment.
7. Visualization:
   • If possible, use SQL to generate summary tables or intermediate datasets and export them to visualization tools (e.g., Excel, Tableau) for creating charts and graphs to illustrate your findings.
8. Report and Recommendations:
   • Compile your findings into a report. Provide insights on customer churn and segmentation. Suggest strategies to retain high-value customers and engage with low-value customers.
9. Optimization:
   • Suggest possible strategies for customer retention and optimization based on your analysis.

Project Output:

• A SQL script or series of SQL files that document the steps you’ve taken to create the database, import data, and perform analysis.
• A report summarizing your findings, insights, and recommendations.
• Visualizations or charts, if applicable.
• A presentation, if needed, to explain your findings to others.

This project will help you gain practical experience in SQL data analysis, customer churn analysis, and segmentation. You’ll learn how to create and manage a database, analyze customer data, and draw actionable insights for businesses to improve customer relationships and business strategies.