Applying data mining method for marketing purpose in social networks: case of Tebyan

Abstract

Within a very short period of time, social networking sites are developed among different users all around the world. Social networks have high value to business intelligence. In these networks, there are so many advantages and demands on addressees and their interest recognition. How do we increase our social network users, posts, and effectiveness? How many consumers can be segmented with respect to their reactions to social network? The creation of a target market strategy is integral to developing an effective business strategy. The purpose of this article is market segmentation and correctly identifying the target groups for social network using data mining techniques. As users in each segment have their own and specific interests, social networks can define them by their demographic profiles, they can also change their development strategies according to users and interests they want to engage in. In this research, we deploy data mining methods for segmenting Tebyan social network users to see how this method could contribute toward marketing strategies and purposes. According to K-mean algorithm, we demonstrate five different customer categories based on their characteristics and behaviour that deploying appropriate strategy for each category can help the marketing performance.