Targeted Online Marketing using Social Networking

Mohamed K. Watfa, Nima Najafi and Mahmoud Numan Bakkar
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Mohamed K. Watfa: Faculty of Engineering & Information Sciences, University of Wollongong in Dubai, Dubai, UAE
Nima Najafi: Faculty of Engineering & Information Sciences, University of Wollongong in Dubai, Dubai, UAE
Mahmoud Numan Bakkar: Al Dar University, UAE

International Journal of Online Marketing (IJOM), 2013, vol. 3, issue 3, 37-50

Abstract: For the past century, companies have had the luxury of deciding what they will produce and sell, what their brand message will be and how they will deliver it to their audience. Planning how best to allocate marketing dollars is arguably the most annoying challenge marketers face. The social web and more specifically, Web 2.0 have changed the original marketing strategy and have done so by giving rise to a new way of marketing where people belong to different social groups and markets have become conversations or recommendations. Social networking sites such as Facebook have reported exponential growth rates and have attracted millions of registered users, and they are interesting from a marketing point of view because they store large amounts of sensitive personal user data. In this paper, the authors introduce a targeted Marketing strategy that exploits group membership information that is available on social networking sites. More precisely, the authors show that information about the group memberships of a user can lead to a more efficient target marketing campaign. To determine the group membership of a user, the authors leverage well-known web browser history recording attacks and other available crawling services. The authors’ proposed algorithm is designed to use the captured customers' details and generate target marketing campaigns by relating each customer with certain rank of products. The authors demonstrate an Experiment by sending a SPAM Email to more than one thousand Facebook users and relate them with certain product pages. To measure the efficiency of the proposed techniques, the authors analyzed how many people have consequently accessed those pages and clicked on the products links inside those pages to get a promising success factor of 82%.

Date: 2013
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International Journal of Online Marketing (IJOM) is currently edited by Hatem El-Gohary

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