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.

References

• Official Docs – https://help.salesforce.com/s/articleView?id=sf.custom_ai_prediction_builder_lm.htm&type=5
• Einstein Prediction Builder: A Deep Dive – https://www.salesforce.com/video/7790708/
• Trailhead – https://trailhead.salesforce.com/content/learn/projects/prediction_builder