Random Forests for Uplift Modeling: An Insurance Customer Retention Case
Models of customer churn are based on historical data and are used to predict the probability that a client switches to another company. We address customer retention in insurance. Rather than concentrating on those customers with high probability of leaving, we propose a new procedure that can be used to identify the target customers who are likely to respond positively to a retention activity. Our approach is based on random forests and can be useful to anticipate the success of marketing actions aimed at reducing customer attrition. We also discuss the type of insurance portfolio database that can be used for this purpose.
KeywordsRandom Forest Switching Cost Customer Loyalty Insurance Industry Loyalty Strategy
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