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KC is the CEO of the leading social networking site in the world. His company, Connect Inc., stands out because of it’s excellent computer programming, impressive Internet entrepreneurship, and KC’s incredible, visionary altruism. As a result of these qualities, Connect Inc. has web users from all over the world, and companies worldwide are contacting Connect Inc. to help them generate revenue and sales from Internet advertising. Internationally, there are more than two billion web users implementing Connect Inc. KC and his employees were extremely excited that they generated revenue from Internet advertising, because almost everyone in the world was using their networking site Connect, Inc. Also, The Economist, US Business News, Vanity Fair, and Time featured Connect, Inc. as the most likely company to succeed in the 21st century. The next step was for Connect Inc. to go public and, for the past two years, Connect’s price per share has been dropping consistently. Web users are not clicking the online banner ads that are displayed by Connect Inc., and the company is not generating income/revenue/sales from Internet advertising as predicted. KC and his employees realized that the mathematical models they developed for ad personalization have been helpful, but unfortunately, the mathematical models alone cannot solve the problems and challenges Connect Inc. is currently facing. All the more unfortunate is that Connect Inc. does not have a clear strategy on how to generate revenue from mobile applications in the future.
Studying cognitive factors that enhance click-through rates is of vast importance, because it provides insight for social media and online firms. Options are presented for generating revenue from Internet advertising and an explanation is provided as to why the click-through rates of online banner ads have been decreasing continuously for the past two decades. Also, our study provides important insights for social media firms and banner ad designers on how to evaluate and design effective and efficient online ads.
Online banner ads are stationary or moving figures, images, graphics, or photos that are displayed on the monitors of computers and cell phones to advertise products and services (Idemudia 2010, 2012, 2014; Idemudia et al. 2007; Li et al. 2012). The design of online banner ads for online target marketing places consists of three sequential components and steps: (1) input: the data is collected from cookies, keyboards, web logs, or the log files for an ecommerce website, (2) process: mathematical modeling, such as linear programming, data mining, or pricing models that generate personalized and customized banner ads and (3) output- where banner ads are displayed to users (Idemudia et al. 2007; Idemudia 2009, 2010, 2014; Li et al. 2012). There is a current focus in the information systems and computer science disciplines, to concerned with addressing the issue of how to improve click-through rates, and there has been a great deal of research on the process component of target online banner ad design (Idemudia et al. 2007; Idemudia 2009, 2010, 2014; Kazienko and Adamski 2007; Li et al. 2012). The process component involves the development of algorithms, techniques, programs, data mining, text mining, codes, and mathematical models to accurately display the right target online banner ads to web users and online visitors at the right time and with the appropriate content (Amiri and Menon 2001; Attardi et al. 2004; Feng et al. 2006; Hoffman et al. 1997; Idemudia 2009, 2010, 2014; Kazienko and Adamski 2007; Lacerda et al. 2006; Langheinrich et al. 1999; Li et al. 2012). Of all the target online banner ad design components, output has received the least attention from information systems researchers and scholars (Idemudia 2009, 2010, 2012, 2014). Thus, the limited research on factors that influence the output component of online banner ads might have led to the constant decline in click-through rates. This issue is most adequately addressed using the Visual Perception Theory.