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Project report on web analytics
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Introduction
Web analytics can serve as a critical tool for assessing the success of a website and identifying opportunities for improvement. The use of web analytics technologies has proven useful to many businesses, organizations and websites in the tracking of web users visits and buying behaviors. There is more to what can actually be done to truly unlocking the full potential of web analytics. In this essay, the 10/90 rule, how it is used and how it can be fully implemented successfully in achieving results for an organization will be examined.
The 10/90 Rule
The 10/90 rule developed by Avinash Kaushik states that “for every $10 you spend on web analytics technology, you should spend $90 on people with brains to analyze that data.” [1]. Kaushik developed this rule so as to derive the highest value from web analytics implementation. Kaushik elaborated that there are lots of data but no insights in analyzing them. So emphasis should be placed on hiring top notch talent to analyze and interpret this data. Studies have shown that companies who have great investment in web analytic
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This shows that the ability to clearly analyze, report and understand customer’s on-site experience form the critical tasks an analyst must be able to perform. Kaushik in an article titled the 10/90 rule for magnificent web analytics success on Kaushik.net emphasized the importance of having skilled analysts by stating that “actionable web insights does not come simply from clickstream, you need to have people who are smart and have business acumen who can tie clickstream behavior to other sources of data/information/company happenings.”
10/90 rule states that for every 10$ of your expenditure on the web analytics tools you are spending for the analysis of data you need to spend 90$ on the highly competent business intelligent resources and analysts.
Avinash Kaushik in his blog proposed the 10/90 rule. [1] According to him, many large companies that have invested in web analytics tools still struggle to make any meaningful business decisions. Apparently, there is a no dearth of data that is collected via these web analytics tools for these companies. However, the caveat here is that there is no real useful information that is being analyzed from these data. In other words, there are not sufficient people with expertise in these areas working on these web analytics tools for these companies to make any meaningful suggestions from the data for the companies to implement and in return increase their profits or whatever they are trying to achieve/gain. The 10/90 rule suggests that for every $10 invested on web analytics tools, $90 should be invested on web analysts by the company to be able to expect positive results on their investment on web analytics tools. Primarily, the data collected from such web analytics tools is useless unless an expert is analyzing that data. It is the web analyst that is critical for the success from the ...
When implemented correctly a Web Analytics tool offers more than just data or information, it can offer knowledge and insights. One can analyze the effect of a new background color, the effectiveness of a marketing campaign, the emotional impact of positive vs negative news feeds (Vindu Goel, June 9th 2014), or the effects of dynamic pricing based on demographic and personal visitor data insights (Greg Petro, April 17th 2015). With the correct data and information we can make the insights needed not just to know what has happened, but to influence events. As Kaushik said, “We’ve evolved from hits to page view to visits. Now, we have Outcomes.” (Kaushik, 2010,
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However, given the limited scope of this paper, the primary focus was only on variables that were expected to have a positive impact on users. Yet, there may be negative influences of peripheral cues like negative customer reviews or delayed web page loading time, which exerts negative influence on user behaviour that were not covered in this paper.
Sallam, Rita L; Tapadinhas, Joao; Parenteau, Josh; Yuen, Daniel;Hostman, Bill (2014, February 20). Magic quadrant for business intelligence and analytics platforms. Retrieved from http://www.gartner.com/technology/reprints.do?id=1-1QLGACN&ct=140210&st=sb
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Google analytics can be applied in big as well as small businesses to support decision-making processes. In sense, each kind of business has its own
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There is a debate between the benefits and potential informational privacy issues in web-data mining. There are large amount of valuable data on the web, and those data can be retrieved easily by using search engine. When web-data mining techniques are applied on these data, we can get a large number of benefits. Web-data mining techniques are appealing to business companies for several reasons [1]. For example, if a company wants to expand its bu...
Analytics means using data and performing statistical analysis on it, applying quantitative and predictive models, in order to arrive at a certain decision. Analytics can be the first step in a process or can rather be an intermediate step as well. Analysis can be done using different set of tools that are available in the market or it can done manually using different concept and formulas. Business intelligence firms like Cognos, SAS and BusinessObjects have developed different tools that are readily available in market that assist in analysis and decision making. Analytics is used in order to find solutions to the problems and the solutions provided enables us to be successful and in the business world allow us to compete with our contenders.
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