The 10/90 Rule
Many years ago, Avinash Kaushik created a general rule for the implementation of web analytics called the 10/90 rule. This rule stated that for every 10 dollars you are paying your web analytics vendor (WebTrends, Omniture, CoreMetrics, etc), you need to be investing an additional 90 dollars in analysts/intelligent resources to extract value from that data. As you can probably imagine, most people saw this rule as either a massive exaggeration or simply unrealistic. But the logic behind the 10/90 rule is really very sound which is most likely the reason why it has been implemented in countless real world businesses in recent years. First of all, web analytics tools, like WebTrends or Google Analytics, are incredible at providing you with
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massive amounts of real-time data telling you “what.” For example, these tools can tell you what happened on your site today or what was your most effective marketing channel in the previous month with regards to revenue.
But they cannot tell you the “why.” The “why” is made up of the insights that drive successful business decisions that can set your business apart from your competitors. This “why” can only be determined for you by your expert team of analysts that you chose so wisely to invest your money in. As Gibson (2013) puts it, “your Web analytics tool is only as powerful as the person using it.” Additionally, with the introduction of free web analytic software, such as google analytics, we have entered a world where data, and massive amounts of it, is essentially free. But what is still not free, is using this data to identify specific business decisions and actions business leaders can act on based on rigorous and detailed analysis. Which is why Kaushik’s 10/90 rule makes a lot of sense when you realize that it is actionable insights and not data that your company should really be paying for. Chaffey (2015) provides a personal example in his article on the 10/90 rule where he illustrates this point: “In every company, every leader wants a dashboard. “Get me a summary of the business performance. Decisions shall be made!” Analysts scurry around and an intense burst of data, manifested as tables and charts, is presented on a vanilla-scented piece of
paper. Happiness? Job promotions? Sadly, no.” The incredibly advanced web analytic tools nowadays could easily provide these dashboards that these company leaders so eagerly desire, but Chaffey goes on to note that the higher you go up the chain of command at a company, the more analytical skills decrease, and the more there is a need for context to make sense of what these table and charts actually mean. The point Chaffey is making, is that all of this data and these charts and tables are great, but simply handing them up the chain of command in a company only results in confusion and a lack of decisive action. A much more effective method, would be to have capable analysts perform rigorous analysis on this data and then write out, in plain english, the recommended actions and insights that have been determined from the data and hand those up the chain of command. This way, the company is actually getting the most of the data that it is paying for and is acquiring the actionable insights that make it all worth it. Of course, as with all rules, there are going to be some caveats along the way that might make the rule difficult to follow in some cases. One area where Kaushik might have overestimated the simplicity of this rule is the ability to find qualified analysts with the money you are saving by possibly downgrading your web analytics software. Kaushik (n.d.) says that the analysts in question must be “smart and have business acumen who can tie clickstream behavior to other sources of data / information / company happenings.” The bottomline is people with these abilities, obviously not people straight out of college, are going to be very difficult to come by and therefore might make his 10/90 rule slightly more difficult to follow that he makes it seem. However, all in all, Kaushik’s 10/90 rule for web analytics has served as a excellent guideline for companies seeking to incorporate web analytics into their decision making process and will continue to do so.
massive amounts of real-time data telling you “what.” For example, these tools can tell you what happened on your site today or what was your most effective marketing channel in the previous month with regards to revenue.
But they cannot tell you the “why.” The “why” is made up of the insights that drive successful business decisions that can set your business apart from your competitors. This “why” can only be determined for you by your expert team of analysts that you chose so wisely to invest your money in. As Gibson (2013) puts it, “your Web analytics tool is only as powerful as the person using it.” Additionally, with the introduction of free web analytic software, such as google analytics, we have entered a world where data, and massive amounts of it, is essentially free. But what is still not free, is using this data to identify specific business decisions and actions business leaders can act on based on rigorous and detailed analysis. Which is why Kaushik’s 10/90 rule makes a lot of sense when you realize that it is actionable insights and not data that your company should really be paying for. Chaffey (2015) provides a personal example in his article on the 10/90 rule where he illustrates this point: “In every company, every leader wants a dashboard. “Get me a summary of the business performance. Decisions shall be made!” Analysts scurry around and an intense burst of data, manifested as tables and charts, is presented on a vanilla-scented piece of
paper. Happiness? Job promotions? Sadly, no.” The incredibly advanced web analytic tools nowadays could easily provide these dashboards that these company leaders so eagerly desire, but Chaffey goes on to note that the higher you go up the chain of command at a company, the more analytical skills decrease, and the more there is a need for context to make sense of what these table and charts actually mean. The point Chaffey is making, is that all of this data and these charts and tables are great, but simply handing them up the chain of command in a company only results in confusion and a lack of decisive action. A much more effective method, would be to have capable analysts perform rigorous analysis on this data and then write out, in plain english, the recommended actions and insights that have been determined from the data and hand those up the chain of command. This way, the company is actually getting the most of the data that it is paying for and is acquiring the actionable insights that make it all worth it. Of course, as with all rules, there are going to be some caveats along the way that might make the rule difficult to follow in some cases. One area where Kaushik might have overestimated the simplicity of this rule is the ability to find qualified analysts with the money you are saving by possibly downgrading your web analytics software. Kaushik (n.d.) says that the analysts in question must be “smart and have business acumen who can tie clickstream behavior to other sources of data / information / company happenings.” The bottomline is people with these abilities, obviously not people straight out of college, are going to be very difficult to come by and therefore might make his 10/90 rule slightly more difficult to follow that he makes it seem. However, all in all, Kaushik’s 10/90 rule for web analytics has served as a excellent guideline for companies seeking to incorporate web analytics into their decision making process and will continue to do so.