111-2010: Creating a Customer Influence Factor to Decrease the Impact of Churn and to Enhance the Bundle Diffusion in Telecommunications Based on Social Network Analysis

Telecommunications’ industry evolves into a high competitive market which demands companies to put in place an effective customer relation approach. Social network analysis can be used to increase the knowledge related to the customers’ influence, arising relevant information to turns the customer experience better. SNA can be used to evaluate the customers’ links and therefore clarify distinguishes aspects about the virtual communities inside the networks, allowing companies to deploy a more effective action plan to better diffuse their products/services and avoid churn. THE INTERNAL SOCIAL NETWORKS BEHIND THE TELECOMMUNICATION’S ENVIRONMENTS The main feature of any community is the relationship events between their members. Any kind of community is established and maintained based on this kind of relation events. According these brand new technologies and communication devices available currently, this type of characteristic have been increasing in relevance and becoming more evident in telecommunications scenery. From distinguish possibilities of communication and relationship, with flexibility and mobility, those communities gained new boundaries, creating new means of relationships and social networks. Based on different ways to communicate, people are ready to create new types of virtual networks. Due the dynamism and cohesion of these communities, included in a context highly technological, the people’s influence can be significantly more strong and relevant to the companies. Additionally, some kind of events can be faced as a chain process, which means that some specific points of the network can trigger a sequence of similar events due its influence and weight. The linkages between the customers can describe the way that the events will run and the weight of the linkages can represent the impact of the chain process in the network. Understanding the way of these relationships occurs and recognizing the influences of some specific points inside the network could be a great competitive advantage, especially with respect to the event which could be performed in a chain process like churn or purchasing. Due the almost unique relationship between the telephones and the individuals, and the influence which some person could exert over the others members of the community, the recognition of the characteristics of the social network existing inside the customer base is completely relevant to the telecom companies [1] and [2]. Discovering the central and strong nodes of those social networks and understanding how they behavior could be one of the most effective way to establish a new customer value, and to predict the impact of the churn and product adoption, but in chain process overview. Realizing the customers connections and identifying the central nodes of each chain inside the social network might be the best way to prevent a massive event of churn and hence a huge leakage of revenue. Analogously, understanding the strength of the central nodes and the way they influence the other nodes mighty be a good way to improve the production adoption process and hence increase substantially the revenue and the effectiveness of marketing campaigns. USING SOCIAL NETWORK ANALYSIS TO CREATE A CUSTOMER INFLUENCE FACTOR Social network analysis can disclose the possible correlations among some particular business event, such as churn or purchasing, inside the community, proving the stronger impact when the event is triggered by a core node of the social network and the weaker influence when it is triggered by a boundary node. The influence means the number of customers which should follow the initial business event in a chain process. Monitoring and analyzing the social network, particularly those which are interconnected, can allow companies to assess the revenue impact assigned to the business events in a chain process [3]. Based on the likelihood assigned to the churn’s event and the level of influence related to the customer, companies can perform a more straight actions Customer Intelligence SAS Global Forum 2010