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Identifying customers likely to churn
Conference paper   Open access

Identifying customers likely to churn

S. Zorn, W. Jarvis and S. Bellman
ANZMAC 2008: Marketing: Shifting the Focus from Mainstream to Offbeat (Olympic Park, Sydney, 01/12/2008–03/12/2008)
2008
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Abstract

As acquiring new customers is costly, it seems logical to keep and satisfy long-time customers rather than to acquire new customers. To reduce churn rates, firms should manage customers proactively to avoid losing churned customers. The study investigated how an Australian DVD rental firm can use customer data to derive indicators of satisfaction, attitude, and commitment to improve the prediction of customer churn in comparison to models calibrated on purchasing behaviour alone. The most significant predictor of churn in these data was a measure of uncertainty and commitment: the number of times a customer changed their subscription plan.

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