“Customer retention” is an important real-world problem in many sales and services related industries today. This work illustrates how we can integrate the various techniques of data-mining, such as decision-tree induction, deviation analysis and multiple concept-level association rules to form an intuitive and novel approach to gauging customer’s loyalty and predicting their likelihood of defection. Immediate action taken against these “early-warnings” is often the key to the eventual retention or loss of the customers involved.