Financial services such as banking and insurance use applications of predictive analytics for churn modeling, because customer retention is an essential part of most financial services' business models. Other sectors have also discovered the power of predictive analytics, including retailing, telecommunications and pay-TV operators. One of the main objectives of modeling customer churn is to determine the causal factors, so that the company can try to prevent the attrition from happening in the future. Some companies want to prevent their good customers from deteriorating (e.g., by falling behind in their payments) and becoming less profitable customers, so they introduced the notion of partial customer churn.
Customer attrition merits special attention by mobile telecom service providers worldwide. This is due to the low barriers to switching to a competing service provider especially with the advent of Mobile Number Portability (MNP) in several countries. This allows customers to switch to another provider while preserving their phone numbers. While mature markets with high teledensity (phone market penetration) have churn rates ranging from 1% to 2% per month, high growth developing markets such as India and China are experiencing churn rates between 3% to 4% per month. By deploying new technologies such churn prediction models coupled with effective retention programs, customer attrition could be better managed to stem the significant revenue loss from defecting customers.
Customer attrition is a major concern for US and Canadian banks, because they have much higher churn rates than banks in Western Europe. US and Canadian banks with the lowest churn rates have achieved customer turnover rates as low as 12% per year, by using tactics such as free checking accounts, online banking and bill payment, and improved customer service. However, once banks can improve their churn rates by improving customer service, they can reach a point beyond which further customer service will not improve retention; other tactics or approaches need to be explored.
Read more about this topic: Customer Attrition
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