Using Social Network Data to Identify Key Influencers for Social CRM Activities

Using Social Network Data to Identify Key Influencers for Social CRM Activities

Goetz Greve (HSBA Hamburg School of Business Administration, Germany)
DOI: 10.4018/978-1-4666-4026-9.ch013
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Abstract

Social network data can be used to identify key influencers within a company’s customer database. Key influencers are consumers that are equipped with a large and strong network of connected neighbors. Within such a strong network, marketing messages can be passed on easily via the key influencers. The purpose of the chapter is to elaborate on the social effects of customer networks and the possibility to use data from these networks for Social CRM. First, the foundations of social contagion in networks and the relationship between social effects and Social CRM performance measures are explained. Second, possible ways of data acquisition and data integration are discussed and an overview of analytical software solutions is given. Fourth, the implementation process and its challenges are elaborated. The chapter closes with an outline of further research directions.
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Background

Social networks have been studied fairly extensively over two decades in the general context of analyzing interactions between people, and determining the important structural patterns in such interactions. In recent years research has focussed on online social networks. Online social networks have rapidly grown in popularity, because they are no longer constrained by the geographical limitations of a conventional social network in which interactions are mainly bound to face-to-face meetings or personal friendships. In addition, social networks are extremely rich, in that they contain a huge amount of content such as text, images or video for further analysis. Generally, social networking sites are just online equivalents of offline social networks. A social network is defined as a network of interactions or relationships, where the nodes consist of actors, and the edges consist of the relationships or interactions between these actors.

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