Blackhat Search Engine Optimization Essay

Introduction

Blackhat SEO is the process of increasing the website or the webpage rank trough violating the search engine terms and conditions. The primary intents of the people who practice the Black hut SEO is to gain popularity (Lu, Perdisci, & Lee, 2011). The more the popular the website page is; the more income it makes. Hence, people practicing this act are after increasing their revenue. To deter website from using the black hut, Google ignores all the links involved with the website and also high staple penalties from websites that are included in the activities. This act discourages other websites from engaging in such activities. The primary tactics of the people using black hut SEO are the hidden texts and buying links (Malaga, 2008).

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Search engine technologies that impact business

The leading business technologies that bring an impact to businesses include the yahoo and MSN. The yahoo has the website named "Yahoo finance." The website has the details on the stock exchange market hence it helps one to invest wisely one their shares (Pasquale, 2008). On the other hand, the MSN has the MSN money website that updates people on the world economic conditions of the countries in the world. These updates are significant for the international investments.

Matrices PPC

The two commonly used matrices PPCs are the Click through rate, CTR, and the quality score matrices. The click-through rate Matric measures how often websites ads are shown about how often they are clicked (Patil Swati, Pawar, & Patil Ajay, 2013). The CTR is considered throughout the day, week or Month. It is considered to be one of the leading online marketing strategies. Quality score is another important metric. This matric is commonly used by Google when determining the positioning of the websites' ads (Mangani, 2004). The quality score is based on the amount of CTR that the website has, the quality of page as well as the keyword relevancy (Richardson, Dominowska,, & Ragno, 2007)

References

Mangani, A. (2004). Online advertising: Pay-per-view versus pay-per-click. Journal of Revenue and Pricing Management, 2(4), 295-302.

Lu, L., Perdisci, R., & Lee, W. (2011, October). Surf: detecting and measuring search poisoning. In Proceedings of the 18th ACM conference on Computer and communications security(pp. 467-476). ACM.

Malaga, R. A. (2008). Worst practices in search engine optimization. Communications of the ACM, 51(12), 147-150.

Pasquale, F. (2008). Internet nondiscrimination principles: commercial ethics for carriers and search engines. U. Chi. Legal F., 263.

Patil Swati, P., Pawar, B. V., & Patil Ajay, S. (2013). Search Engine Optimization: A Study. Research Journal of Computer and Information Technology Sciences, 1(1), 10-13.

Richardson, M., Dominowska, E., & Ragno, R. (2007, May). Predicting clicks: estimating the click-through rate for new ads. In Proceedings of the 16th international conference on World Wide Web (pp. 521-530). ACM.