The 10/90 rule explains a metrics between analytic tools and Web Analyst in order to fulfil …show more content…
There is yet no actionable insights, no innate awareness, of real thing that is going on through the clutter of site clickstream data. Most of the companies spend more than half of their budget on expensive tools, yet they end up with data that is not worth the tool cost. In order to get Returns on Investment, the cost of investment in analytics tool & vendor professional services should be reduced to 10 percent of the total investment cost and 90 percent on getting intelligent people who can better understand company’s business and analyze the data. As defined by Avinash Kaushik, the 10/90 rule explains strategic investment of a company for $100 in a website, the company should invest $90 for intelligent resources/analyst and $10 on the analytical tools. (Kaushik …show more content…
At the end of the day tools are just ways to get data. The Web is very complex and it will remain so for now. All of this essentially over emphasizes measuring clickstream data and attempts to figure out the effect of the website on the bottom line. Stellar success is achieved after hacking clickstream data. Companies that underestimate the value of business acumen & common sense are hugely underrated. The differentiator will be Web Analyst who can understand the use of tools. Reality is that companies invest millions of dollars to get tools and simply give it to admin which indeed doesn’t work, where they end up doing nothing. This is not the fault of the tool it is the fault of the company that does not investment in people. So, the basic principle of 10/90 rule is to invest smartly in intelligent people and make conversion to get the Returns on Investments. (Kaushik, Google