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.
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