For a discrete manufacturing industry, customer churn is an important factor to be considered for business improvement. However, customer churn as a factor is often neglected, which leads to direct as well as indirect losses in business revenue. In this paper, variables affecting customer churn are considered and a model is developed for identifying and curbing customer churn so as to improve the aftermarket functions. Advanced analytical solutions (models) and visual patterns study is developed to address the issues contributing to the customer churn. The solution effectively identifies customer churn and supports the aftermarket sales team for improved decision making.