Improving complaints management system Using Support Vector Machine

Integrated complaints management system designed to give organizations the opportunity to learn from customer feedback information and use information to reduce weaknesses in business performance, efficient use of resources and maintain satisfactory capital base long term relationship with their customers. Therefore in this paper, a model is provided that could clear weak points first, in other words, discover and understand the Working patterns and factors affecting it. Second, it can provide solutions to the problem. As a case study customer relationship management data unit of Ayandeh private Bank is used. This data related to customer complaints in one of the call centers in Tehran. In order to provide a descriptive model, the data is clustered by using data mining tools, optimal clusters based on Davis– Bouldin Indicator is determined and based on the analysis obtained, the architecture of response system is designed. Next, in order to provide a prediction model, support vector machine is used. The result is validated and suggestions to improve complaints management system are presented