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Predicting Customer Churn with Einstein Prediction Builder

Real-world Application: Customer Churn Prediction Use Case (Binary Example)

Predictive Model: An innovative predictive model has been crafted using Einstein Prediction Builder. This model is designed to provide probability scores for customer churn based on historical data.

Key Factors: The model meticulously considers various elements, including:

  • Customer service usage
  • Past behavior
  • Other relevant information

Personalised Predictions: By leveraging these factors, the system generates tailored predictions, empowering organisations to make data-driven decisions.

Demonstration Video: This video not only showcases the system in action but also reveals its potential to manage churn-risk customers effectively.


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