Please use this identifier to cite or link to this item: http://hdl.handle.net/11189/8075
Title: Spending on PPC search engine marketing and its influence on return on investment
Authors: Sabwa, Jean-Marie 
Weideman, Melius 
Keywords: PPC;search engine;marketing;influence;return on investment
Issue Date: 2010
Source: Sabwa, J.M. & Weideman, M. 2010. Spending on PPC search engine marketing and its influence on return on investment. 13th World Wide Web, Johannesburg, South Africa, 14-16 September. [https://www.researchgate.net/publication/321359009]
Conference: 13th World Wide Web 
Abstract: The primary objective of this research project is to investigate and determine the most important characteristics that influence the traffic to a website generated by a Pay Per Click (PPC) campaign. The literature has shown that spending on a PPC campaign does attract traffic to the website, but the return on investment (ROI) does not follow the same trend as the marketing expenditure. Components of the PPC campaign need to be investigated, evaluated, modeled and applied toward maximising of traffic and return for online business. The chosen methodology consists of collecting information, developing of a dynamic model and setting up a multi optimisation strategy. These analytical methods are useful for changing attributes (inputs) and also to observe the change that affect the outputs of a PPC campaign. In summary, a quasi-experimental quantitative research approach is to be followed. Surveys will be conducted and a real-life experiment will be done on conducting and managing website traffic using a PPC campaign. The management of the website helps to observe the differences in the attributes when applying a PPC campaign. Graphical representations is the preferred method of displaying results, but in these studies both analytical and graphical presentations are used in order to convey only essential information. It is expected that the proposed model will assist in optimising ROI. The understanding of dynamism of the PPC campaign will help advisers in focusing on the correct attributes at the right time.
URI: https://www.researchgate.net/publication/32135900
http://hdl.handle.net/11189/8075
Appears in Collections:FID - Conference Papers

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