Effective marketing communication activities require companies to identify and target the right customer segments. This dissertation explores the potential of social network analysis as a tool for online behaviour segmentation. To this end, the patterns of user interactions in the Facebook page of a Portuguese company, alongside clickstream data from its website, were cluster analysed. The cluster analysis of the interaction patterns yielded four clusters, mainly based on differences in content of the posts on Facebook. These clusters were the Photo-fans, Route-lovers, Promo-people and Video-viewers. The SNA metrics were able to provide concrete insights to characterize these segments. The analysis of clickstream data also yielded four clusters: Prospect, Info Seekers, Curious and Scanners. These consumer segments differ in terms of search detail, which could be attributed to their relative level in the purchase process. A field study on the Facebook page was conducted to link the interaction patterns to the browsing behaviour on the website. For the content of the posts during this field study, the clickstream data of the website did not show substantial differences. This dissertation concludes by noting that SNA tools can be useful and provide insights for marketers that attempt to segment social network audiences. Also, the link between the behaviour of social network audience and website visitors potentially leads to useful and actionable insights
Date of Award | 18 Jul 2016 |
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Original language | English |
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Awarding Institution | - Universidade Católica Portuguesa
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Supervisor | Ana Isabel de Almeida Costa (Supervisor) |
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- Mestrado em Gestão: Programa Internacional
Segmentation of online behaviour : the website & the social network
Slits, P. J. E. (Student). 18 Jul 2016
Student thesis: Master's Thesis