The 10/90 rule is about how a company should invest into the web analytics department in order to obtain the maximum output and costumer satisfaction. As the law states a company should invest 10% on the web analytical tools and the other 90% on the skilled persons and experts to do the analysis by using the analytical tools. Basically, it says that the budget should be divided as 10% for the analytics tool, and 90% for the actual, thinking analysts. People and brain power trumps data gathering, and immensely important in making sense of all the gibberish. The point is that data interpretation should be the focus, because it is important to read the numbers and a skilled analyst is the only source to extract out the desired information from …show more content…
the analytical reports. The common trend in the market to perform the web analytic of any company’s website is to give the contract or projects to any consultancy company or analytical firms. These analytical firms charges a handsome amount of money, while today a number of free analytical tools are available and these tools are highly powerful to perform almost all sort of analytical operations. The rule works in simple manner and states the simple concept of investing the budget wisely on the analytical software and the employees to understand and operate that toll and able to provide the accurate data to the company. For example if a company is having a budget of around $300,000 for the analytical department, in that case what usually companies do they give the contract to the other analytical firms which claims to do the analytics of everything whether it is relevant to the requirement of the company or not. So as per the rule a company should invest $30,000 to buy the analytical software from the various vendors like Omniture, WebTrends, Coremetrics, HBX etc. and should invest rest $270000 to appoint the people to extract the required information and value from the data as per the company’s need. Today the websites are not simple, they are very complex structure providing a lot of information and data to interpret and know the behavior of the costumers and the tools those are available can capture every data but are unable to extract the desired information by their own.
The web analytic has evolved in massive way in recent past, because of which the companies have to deal with quantitative data, qualitative data, competitive intelligence marketing trends costumer behavior and many more, and to deal with these issues a company need a proper skilled analyst with the correct power of analytical tool. Now consider a situation that a company has invested a huge amount of money acquiring the most advance analytical tool and hired a very expensive web analytical contractor to set up the tackling strategy and utilized the ability of an in-house developer to implement the tool. But due to some reason the contractor has left and the in-house developer has been moved to some other project and the company is left with huge undefined numbers unanswered business queries and with one or two analysts. This is the best situation to use the 10/90 rule, according to which the company should have invested 10% on a web analytical tool (Omniture, Coremetrices etc.) and rest 90% should be spending on the people to analyse the numbers and on a team of web analysts to analyze and gain valuable
insights. The 10/90 rule is also a reproach to companies who tend to spend too much on their web analytics service, sometimes amounting to tens of thousands of dollars, when the same metrics can be had with free tools such as Google Analytics and the company’s professionally trained analyst will be capable to extract out the same information from the free tool. But perhaps the most important reason why the 10/90 is even more relevant now is that the web is even more complex now, customer experience and content consumption is ever more complex and companies are required to invest in the actual person to interpret the data and extract out the information from the tool. In other words we can easily conclude that though today there is huge advancement in the technology and data driven aspects but still as the tools are getting powerful, there is high need of the individual to access the required information from the dataset by using the powerful tools. 10/90 rule does not states to completely depend upon the tools neither it says to leave the person alone, but it says that a proper ratio has to be maintain between the tool and the skilled person to handle and use the tool.
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 ...
Well today many businesses are turning to "Enterprise-wide Analytic Technology" to help streamline the processes and steps that an organization goes through when conducting business. Enterprise analytics is quite simply put a way for enterprise sized companies to capture business-critical information and make it visible across the entire organization. Informatica (2001)
Companies have transformed technology from a supporting tool into a strategic weapon.”(Davenport, 2006) In business research, technology has become an essential means that many organizations use in their daily operations. According to the article, Analytics is a major technological tool used. It is described as “the extensive use of data, statistical and quantitative analysis, explanatory and predictive models, and fact-based management to drive decisions and actions."(Davenport, 2006) Data is compiled to enhance business practices. When samples are taken, they are used to examine research and understand how to solve problems or why situations are as they are. Furthermore, in this article, Thomas Davenport discusses analytics from a business standpoint. He refers to organizations that have been successful in their usage of data and statistical analysis. In addition, he also discusses how data and statistics can be vital in the efforts to improve the operations of businesses.
First, you will need to familiarize yourself with the concept of the 80/20 rule. In order to use the rule to become more successful, you must know what the principle is and
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In today’s world there are many rules and laws. There are laws against smoking in public places, there are laws against playing ball hockey on the street, and there are even laws about standing in front of a store or an establishment for too long. These laws are severely enforced. Breaking any of these laws can result in fines of up to $2000. Said laws have not been around nearly as long as the Golden Rule has, but in today’s society they seem to be more important than the number one rule most religions believe in. “Do to others as you would have them do unto you” is a well-known rule that was left on earth to assist people of every religion on their path to paradise (Luke 6:31- 10:27). Unfortunately, not many
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The golden ration can occur anywhere. The golden proportion is the ratio of the shorter length to the longer length which equals the ratio of the longer length to the sum of both lengths.