Intelligent Marketing Decision Model Based on Customer Behavior Using Integrated Possibility Theory and K-Means Algorithm

Abstract

E-commerce is referred as any transaction in which the sale and purchase of goods or services takes place via the Internet and leads to the import or export of goods or services. Supply always needs demand. We need marketing to expand the demand in order to sell more services or products. Organizations need to have a good understanding of their customers and their desires in order to become succeed in business, and to get this understanding, they must use tools and techniques to measure the customer's interest. With using of data mining techniques and with the discovery of hidden and valuable knowledge of data, organizations don`t miss the opportunity to sell more and provide better customer satisfaction. The customer segmentation is one of the methods of customer recognition. This method is used when we look for groups of similar data. Segmenting is one of the most important topics in reaching modern marketing and managing successful customer relationship management. The purpose of this paper is to design an electronic marketing model using the k-mean algorithm. First, customer`s data is collected and after preparing and pre-processing data, using the k-mean algorithm, segmentation customers and future marketing strategies and recommendations are discussed and eventually using the theory of the possibility, the possibility and requirement for the proposal to be considered, and each of the recommendations or strategies are given numbers with the name of the possibility and necessity of the system output, and a more favorable proposal is obtained.