Primarily, a review on theoretical foundations and the history of Viral Marketing is shown. Based on this, different definitions were analysed to set up a practical definition for this study. Thereafter, possible targets of Viral Marketing are illustrated, followed by necessary elements of Viral Marketing campaigns and finally by an approach to measure the effectiveness. By means of an online questionnaire, a survey was conducted to collect empirical data. These data provide information about Viral Marketing within social networking sites and detect useful information for the practical use of Viral Marketing. The results of the analysis show the accelerating influence of social networking sites and other factors regarding the effectiveness of Viral Marketing. In addition, specific characteristics which make Viral Marketing messages appealing as well as the preferred types of Viral Marketing messages are illustrated. They help to understand how to create and design an effective Viral Marketing Campaign.

Sven Wilde wurde 1985 in Villingen-Schwenningen geboren. Sein Studium zum Wirtschaftsingenieur mit der Fachrichtung "Internationales Marketing&Technischer Vertrieb" an der DHBW Stuttgart/Horb am Neckar schloss er 2009 mit dem akademischen Grad des Bachelor of Engineering ab. Anschließend vertiefte der Autor seine wirtschaftswissenschaftlichen Kenntnisse im Rahmen des Masterstudiengangs "Management&Märkte" an der Universität Siegen und schloss sein Studium 2012 erfolgreich mit dem akademischen Grad des Master of Science ab.

Textprobe:Kapitel 2.3,Theoretical Foundations:This chapter briefly analyses the theoretical foundations to gain a general understanding of related topics prior to adequately define Viral Marketing in this study. As previously mentioned, word-of-mouth is strongly linked to VM (see also Cruz and Fill 2008, p. 746) and needs deeper insight. Furthermore, as the process of the spread of a message is elementary to Viral Marketing, theories and models related to its diffusion will be introduced: General Information about Epidemiology will be followed by "Memetics " - Dawkins model about cultural information transfer. Then, Rogers "Diffusion of Innovations Theory " as a model of growth with saturation and Gladwell's "The Tipping Point " as an utilisation of the previously named models to explain the spread of information will be introduced. The theoretical framework will be concluded with a chapter on social networks which form another important piece in the framework of Viral Marketing.2.3.1,Word-of-Mouth:The Oxford English Dictionary dates the first written occurrence of the term "word of mouth " back to 1533 by defining it simply as "oral communication " (Nyilasy 2006, p. 163f.). From a marketers point of view the information exchange is restricted and somehow related to a company, brand, product or service. Arndt (1967a, p. 3) defined it accordingly as:"Oral, person to person communication between receiver and a communicator whom the receiver perceives as noncommercial, concerning a brand, a product or a service ".A recent definition of the American Marketing Association (AMA 2012) defines word-of-mouth communication as:"[..] information imparted by a consumer or individual other than the sponsor. It is sharing information about a product, promotion, etc., between a consumer and a friend, colleague, or other acquaintance".As it was to be expected the understanding of word-of-mouth has not changed over time. Still today its main characteristics are the personal communication, the commercial regard to product, brand, or service, and non-commercial motivated communicators. Bruyn and Lilien (2008, p. 152) furthermore state influence not only on consumers' purchase decisions (Arndt 1967b, p. 295) but also on the consumer pre-consumption expectations (Anderson/Salisbury 2003, p. 122), pre-consumption product judgments (Herr et al. 1991, p. 456) and post-consumption product judgment (Bone 1995, p. 215f.).But, since not only positive information about products and services is passed on, WOM can be split into positive word-of-mouth (PWOM) and negative word-of-mouth (NWOM). Herr et al.'s (1991, p. 460) study showed that NWOM weights even heavier than PWOM. According to them, negative information about only one product attribute biases judgement stronger than many positive exhibited features. Regarding to East et al. (2008, p. 116) other studies support this fact. However, they also claim that the previous studies missed out the higher frequency of positive WOM. As a result, the position of most message-addressees is positive which gives negative WOM higher impact. With a new designed set-up, balancing out the disparate amount of PWOM and NWOM, their survey revealed a higher impact of PWOM. However, this illustrates the powerful impact WOM can have and the chances it offers to marketers to use this phenomenon for their purpose.The motivations why people forward WOM are also interesting. Canarella and Piccioni (2008, p.126f.) mention for example personal engagement, commitment towards others, personal improvement, altruism, loyalty and many more. East et al. (2008, p. 217) furthermore state satisfaction and dissatisfaction as catalysts of WOM but identify the main trigger as 'perceived need' and 'random occurrence during conversations'.Furthermore, WOM can be differentiated between amplified and organic word-of-mouth. Organic WOM refers to naturally appearing WOM while amplified WOM is artificially generate