The 10/90 rule, its method of application & implementation:
Numerous studies have pointed out that while almost all Fortune 500 companies have great investment in web analytics they still struggle to make any meaningful business decisions. Most people complain that there are terabytes of data and gigabytes of reports and megabytes of excel and power point files. Yet no actionable insights, no innate awareness is present on what is really going on through the clutter of the clickstream data.
In order to fix the issue, the 10/90 rule was implemented. The rule says the following:
Goal: Highest value from web analytics implementation.
Cost of analytics tool & vendor professional services: $10
Required investment in intelligent resources/analysts: $90
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Bottom line for the magnificent success: It’s the people The rule works quite simply.
If we are paying our web analytics vendor (Omniture, Web Trends, Click tracks, Core Metrics, HBX etc.) $25,000 for an annual contract we need to invest $225,000 in people to extract value from the data. The reason behind this rule is as follows:
a. If our website has more than 100 pages and we get more than 10k visitors per month, we can imagine the complexity of interaction that will happen in our website.
b. It is given, if we open most web analytics tool, they show the exact same metrics, almost all of them measured and computed differently. So we have to sort this issue.
c. Finally, actionable web insights do not come from clickstream so we have to have people who are smart and have business acumen to tie clickstream behavior to other sources of data, information and company happenings.
So in order to apply the 10/90 rule we have to consider the following:
a. We have to apply for a free google analytics account at google analytics sign up
page. b. Once we get the code, implement Google Analytics on our website in parallel with our favorite expensive analytics tool, we need to get a comfort level of delta between the two sets of key numbers (visitors, page views, conversion etc.) and create a multiplier (the tool will show visitor 10% higher and page views 10% lower than google). We can use this multiplier in future to compare year over year trends. c. We can test this by cancelling the contract with the expensive analytics vendor and instead hire a smart analyst between $50k. In this way we can save a lot of money. d. The smart analyst will be able to extract more value from Google Analytics than the old tool. e. As the level of savvy of our organization grows, as the level of sophistication of supporting processes increased, perhaps in two years we might be ready to plunge down $200k on a web analytics tool and then be ready to extract a corresponding amount of value from it. Often companies are not aware of, or forget the above, leaving the analysts to spend between 50-70 percent of the time on reporting and just 30 percent for analyzing, optimizing and seeking out new opportunities. So for the actual implementation of the rule, company should keep in mind that people matter more than the tool. The most important thing to remember when making a decision is that while choosing the right tool is important, of far greater importance are the people who will be deriving the key insights from the tools. Analytics guru Avinash Kaushik has identified a useful rule of thumb for companies looking to make a decision about what analytics tool to acquire which is discussed above. Only a team of 4-5 top quality analyst working full time is enough to analyze the reports, create test and really make use of the service. Thus, we can say that implementing the 10/90 rule organization can get more insights from the data and can save lot of money. Overall we can say this system can dollarize any project.
If the organization is unable to spend huge amounts on this web analytics tools and the corresponding resources it is better to spend some money on the
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 ...
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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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