Automated automobile prediction system

In the past decade the rise of the automobile industry/dealers in Sri Lanka is significant. This trend emerged the requirements to build efficient ways of analyzing the customer behavior to identify their need have strengthened the customer relationships. This paper is reveals a novel solution to automobile customers to match the desired vehicle model based on customer value classification. To achieve this goal need to classify the vailable customer data with available vehicle models then predict new customer based on classified model. Data mining techniques are employed to obtain the loyalty measure of a past customer details. As the result of this study, new customer’s contribution is estimated instantly and the most suitable customer model will suggest the preferred automobiles. The architecture of customer analysis model for marketing themes, which is based on the data of automobile enterprise’s/dealer’s customers and management information systems, is designed by integrating the basic data through some data mining models. The benefit goes to both customers and vehicle dealers from this approach. This solution is based on customer value classification based on previous customer attributes such as Age, Occupation, Income, Area, Vehicle Usage Type, Fuel Type and their personal interest