Abstract: Now days customer satisfaction has become crucial aspect of success of any product or organization as it directly impacts if customer would keep using same product or choose to an alternative. Most of service industries focus on providing best service and support for products and concentrates on time to answer customer concerns, having correct resources like domain experts. Considering customer support engineers its hard to sense nature of customer for avoiding dissatisfaction, its always needed to relay on static guidelines followed by organization like time to respond, keeping up with domain knowledge, communication skills. The goal of this project is to provide guidelines on each support case by understanding customer interaction using historical data. The historical data of customer would help to understand which things are important to customer, what he or she likes or dislikes, what kind of interaction is mostly preferred by customer, does he have problem with any specific product. By applying data mining techniques on historical data of customer interaction with customer support it would help to understand these trends which should help to improve customer satisfaction.

Keywords: Artificial Neural Network, Data Mining, Machine Learning.