What is churn propensity score in SAP CEC-MKT-ML - Machine Learning?

SAP Term: churn propensity score

• Component: CEC-MKT-ML

• Component Name: Machine Learning

• Description: Formula that calculates a point value in view of the question how likely it is that a customer will churn. The formula can be based on a predictive model, on manually defined rules and conditions or on machine learning.

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• Key Concepts: 
  Churn propensity score is a metric used in customer relationship management (CRM) to measure the likelihood of a customer leaving or “churning” from a company. It is calculated using machine learning algorithms in the SAP CEC-MKT-ML component. The score is based on customer data such as past purchases, interactions with customer service, and other factors. 
  
  How to use it: 
  The churn propensity score can be used to identify customers who are at risk of leaving and target them with special offers or incentives to retain them. Companies can also use the score to prioritize customer service interactions and allocate resources more efficiently. 
  
  Tips & Tricks: 
  It is important to keep the churn propensity score up-to-date by regularly updating customer data. This will ensure that the score accurately reflects the current state of the customer relationship. Additionally, companies should use the score in combination with other metrics such as customer lifetime value (CLV) to get a more complete picture of their customers. 
  
  Related Information: 
  The churn propensity score is just one of many metrics used in CRM. Other metrics include customer segmentation, customer lifetime value, and customer satisfaction scores. Companies should use a combination of these metrics to get a comprehensive view of their customers and make informed decisions about how to best serve them.