Efficient implementation of data mining: Improve customer´s behaviour

Evaluating the performance of any organization is an essential part for overcoming their weaknesses. Customer is always on prior for finding and assessing the company´s performance. They are always respectable for every organization. In this paper we first examine the Customer Relationship Management (CRM), especially customer behaviour and customer profiling. Then we describe the general overview of most common data mining techniques. The main purpose of this paper is how data mining techniques can extract respectable knowledge from the large customer´s database and how to analyze customer behaviour to improve business performance. Therefore, we proposed a model for CRM with the efficient implementation of data mining, for improving customer behaviour. For this, we evaluate and analyze the customer understanding by using rule induction process on clustered data from customer´s database with reference to the customer query.