The Usage of Search Engines
A recent article by Aybuke, Jafarazdeh, Babak and John indicates the use of search engines like Google within the business world has advanced greatly with ever changing technology. At all times, there are improvements in search engine aimed at keeping up with the increasing demands of different businesses. The article states innovation of Search Engine Advertising (SEA) is now serving as an outstanding revenue source for majority of the search engine companies. Additionally, the idea has also proven significant solution for businesses in the promotion of Web visibility (Jafarazdeh, Aybuke and John & Babak).
The article, however claims no proper investigation on underlying factors that contribute to the decision of SEA adoption by the businesses exists. Based on unknown theories on behavior, the article seeks to conceptualize and it builds a context specific model meant for understanding the issue that influences the decision of majority of businesses in the use of SEA. According to conceptual model of the article, there are 4 direct factors that influence the decision. These are the attitude towards SEA, perceived control over SEA, subjective norms and perceived SEA benefits. Additionally, there are 10 indirect factors that influence the decision. These include trust in the search engines, perceived SEA risk, advertising expertise, ability manage keywords as well as bids, ability to analyze and monitor outcomes, ability to detect fraud and usage of third party tools, external experts use, perceived SEA tools complexity and SEA commitment.
When information regarding advertising gets mined adequately, it can be applied in improving marketing results of the business. The information can be mined through use of different kinds of data mining tools. During the data mining process, some of the information that is important is considered in the searches, product links, user inputs, user profiles, purchase history, page browsing among others (Gupta, 280). There are different techniques used in analysis of the data like decision trees, data visualization, rule induction, genetic algorithms among other techniques. However, it is easy for the information to be misused in the event it is not analyzed correctly. For instance, in the case of premature conclusions that are drawn from data mined, they can result to bad mistakes.
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Gupta, G. K. Introduction to data mining: with case studies. New Delhi: Prentice-Hall of India, 2013. Print.
Jafarazdeh, Hamed, Aybüke Aurum, John D’Amba, and Babak Abedin. “Determinant of Intention to Use Search Engine Advertising: a Conceptual Model.” International Journal of Enterprise Information Systems (ijeis). 9.3 (2013): 22-38. Print.