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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