Predict customer churn with SQL

Predicting customer churn helps businesses retain at-risk customers by analyzing purchasing behavior and identifying patterns that indicate potential churn. This guide introduces the key concepts and steps required to implement a SQL-based logistic regression model for churn prediction.

Key topics covered

The main topics covered in the document are:

• Understanding customer churn and its business impact
• Preparing and structuring e-commerce data
• Building and evaluating a SQL-based logistic regression model
• Generating actionable insights for customer retention strategies

Next steps

To learn how to create and apply the churn prediction model, see the full guide.