Social Media Marketing: Web X.0 of Opportunities

Social Media Marketing: Web X.0 of Opportunities

Lemi Baruh (Kadir Has University, Turkey)
DOI: 10.4018/978-1-60566-368-5.ch004
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Abstract

In recent years social media applications, which enable consumers to contribute to the world of online content, have grown in popularity. However, this growth is yet to be transformed into a sustainable commercial model. Starting with a brief overview of existing online advertising models, this chapter discusses the opportunities available for advertisers trying to reach consumers through social media. The chapter focuses on viral marketing as a viable option for marketers, reviews recent viral marketing campaigns, and offers recommendations for a successful implementation of social media marketing. In conclusion, the author examines future trends regarding the utilization of the emerging Semantic Web in marketing online.
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Background

Online Advertising

In its most traditional sense, advertising is defined as a paid form of communication appearing in media, usually with the purpose of reaching a large number of potential customers. Since 1993, when CERN announced that the World Wide Web would be available to anyone free of charge, advertisers experimented with different methods of reaching consumers online. Unsurprisingly, the first reaction of advertisers was to treat the World Wide Web as a natural extension of traditional media, such as newspapers and television. And, just as in conventional mass media, early online advertising methods, such as banners, pop-ups and interstitials, were characterized by intrusiveness and adoption of a one-way stimulus-response model within which information flows from the advertiser to the customer (McCoy, Everard, Polak, & Galletta, 2007; Rappaport, 2007).

However, even in the early years of online advertising, signs of what was to come in interactive marketing were revealed. Shortly after banners became a popular online advertising method in 1994, keyword-activated “smart banners” were introduced. What set smart banners apart from their predecessors was that the contents of the banners were personalized in response to the search words entered by the users. As such, smart banners were one of the first examples of how content variability in new media (Manovich, 2001) can be utilized to customize information to consumers’ needs (Faber, Lee & Nana 2007).

Key Terms in this Chapter

Interactive Media: Interactive media is a catch-all term that is used to describe the two-way flow of information between the content user and the content producer. In addition to enabling consumers to actively participate in the production of content, interactive media also allow for the collection of real time data, which can later be used for content customization.

Social Network Sites: Social network sites are web-based systems that enable end-users to create online profiles, form associations with other users, and view other individuals’ profiles. Examples of social network sites include: Match.com, MySpace, Facebook, Orkut, Hi5, Bebo and LinkedIn.

Social Network Analysis: Social network analysis is a research methodology utilized in research to investigate the structure and patterns of the relationship between social agents. Examples of sources of relational data include: contacts, connections, and group ties which can be studied using quantitative methodologies.

Content Variability: Content variability refers to the notion that new media objects can exist in an infinite number of variations. This characteristic of new media is the result of the digital coding of content and consequently the modular nature of information.

Viral Marketing: Viral marketing refers to a form of word of mouth marketing that relies on consumers relaying product information, a marketing message or a personal endorsement to other potential buyers.

Data Mining: Data mining is a technologically driven process of using algorithms to analyze data from multiple perspectives and extract meaningful patterns that can be used to predict future users behavior The market basket analysis system that Amazon.com uses to recommend new products to its customers on the basis of their past purchases is a widely known example of how data mining can be utilized in marketing.

Web 2.0: Introduced in 2004, during a conference brainstorming session between O’Reilly Media and MediaLive International, Web 2.0 refers to the second generation of web-based content. Rather than merely pointing to technological changes in the infrastructure of the Internet, the concept of Web 2.0 underlines the notion that end-users can do much more than consume readily available content: The user of Web 2.0 also plays a key role in the creation and the dissemination of content. Popular examples include: video-sharing and photo-sharing sites, such as YouTube and Flickr; social network sites, such as Orkut, MySpace and Facebook; and Weblogs (blogs).

Semantic Web: The Semantic Web refers to a set of design principles, specifications, and web technologies that enable networked software agents to understand, interpret and communicate with each other to perform sophisticated tasks on behalf of users.

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