Why the Keyword Efficiency Index (KEI) Doesn't Work Properly
The Keyword Efficiency Index is a concept developed by Sumantra Roy and used by thousands of webmasters and search engine optimization experts to try to choose more effective or efficient keywords for targeting in search results.
The basis is that a keyword (let’s say pink elephants) is searched for X times per month, let’s say 1000 times. The same keyword is targetted by Y number of websites (let’s say 25) and the maths looks like this. KEI is X*X/Y. The formula is X times itself and divided by Y.
So in the above example Pink Elephants is searched for 1000 times a month. 1000 times 1000 is a million, divided by 25 leaves 40000 as the answer. The answer is the KEI of the keyword.
In another fictional illustration, the keyword Yellow Elephant is only searched for 9 times a month but 100 websites are competing for that keyword. The maths says that 9X9=81 divided by 100 = 0.81.
So the first keyword (pink elephants) has a KEI of 40000
The second keyword (yellow elephants) has a KEI of 0.8
The higher the number the more likely the keyword is to bring success to the one doing the research. With this model you would focus on targetting pink elephants and ignore the yellow elephants.
Or at least that is the theory.
What this model neglects to mention is that not all competition is equal. If your website is competing against Facebook or Youtube for position you might not be likely to win… because they are too big. But if your competition is the Country Women’s Club with its 3 old ladies… you have a better chance.
Google has used a system of Ranking Pages to work out which websites are more valuable than others in terms of their power to rank. This system scores every website page on the internet out of ten. Ten is the ultimate score and only a few websites have that. Zero is nothing, and a score of 1 is the median webpage score. It goes from Zero to Ten in a hyperbolic curve where each increment is essentially something like ten times more valuable than the preceding number.
So back to the keywords.. If pink elephants has a KEI of 40000, but all its competition has page ranks of high numbers like 8, 9 or 10, what is the chance of succeeding with that keyword. Not much chance.
But if the yellow elephants has competition which is non existent in terms of page rank and it all has ranks of 0, what is the chance of succeeding with that keyword. The Likelihood is almost certain.
So another factor should be included… the quality of the competition. For this purpose we can take Google Pagerank to be that factor.
So the revised formula could work something like this.
The Keyword is Pink Elephants (using real statistics now)
This keyword is searched for 14800 times per month. It has 462000 entries competing for this keyword.
Now we find out the page rank for the first ten competing websites (because you want to be on the first page) and average them. The average page rank on the first page of Pink Elephants is 3.9 (comprised of 5 pageranks of 4, 2 pageranks of 5 and 3 pageranks of 3)
My proposed new formula works like this
X is still the number of searches per month
Y is still the competition
Z is the page rank
A is the inverse of the page rank (10 minues Z = A)
The formula is now X (Searchs) Times A (Inverse Pagerank) Divided by Y (Competition) equals AKEI (Adjusted Keyword Efficiency Index)
So for Pink Elephants the KEI with old formula is 474
However the AKEI for Pink Elephants taking into account the fairly stiff competition is 14800 times 6.1 divided by 462000 is 0.19 – a LOT lower.
Part of this is that we don’t multiply by itself and we only multiply by the amount left over after competition. So if there is less competition we get to multiply by a higher amount giving an increased number to divide by.
This new AKEI formula is more accurate.
Author: David Alley – Freelance Web Designer