关键词: 社交网络分析, 精准营销, 客户定位, 大数据

Abstract: Big data provides important support for enterprises doing precision marketing decision. It can significantly enhance marketing effectiveness and improve customer satisfaction. Customer identification and selection is fundamental for precision marketing. It helps companies target valuable customers and design marketing mix strategies. As a social structure analysis method, Social Network Analysis（SNA） method can effectively target the key customers by analyzing customer’s individual characteristics and group features. Firstly, through the social network centrality analysis, this paper studies the relationship between the node centrality in a network and the marketing effectiveness. Furthermore, by introducing a method called RMCL（Regularized Markov Clustering）, a solution is presented to partition social network into communities. More importantly, in order to detect communities in large-scale social networks, the RMCL method is implemented in Map Reduce Pattern, a parallel programming framework. This paper also explores the approaches to identify the core node within a social network community. Two indicators are proposed in term of customer influence degree and influence factor to measure the customer’s impact on purchasing. Lastly, combining with social network centrality metrics, CART method is used  to uncover the links between the social network and customer consuming response, and the order of variable importance is determined, which provides a feasible guidance for the enterprises adopting differentiated marketing strategies.

Key words: social network analysis, precision marketing, customer positioning, big data