KEI - Keyword Effectiveness Index - The KEI - Keyword Effectiveness Index
was devised by Sumantra Roy. The index is a measure of the competitiveness of a Keyword.
It is defined generally as the square of the number of searches per month for a keyword (not specified in which
search engine) , divided by the number of
pages that are retrieved for that keyword. Roy multiplies the result by 1000 for convenience. If there are no pages
retrieved for a keyword, then the index is the number of searches squared times 1000. Roy used Alta Vista for the
source of number of pages retrieved. It would seem that for Google optimization, it is more appropriate to use th
number of pages and searches in Google.
An "effective" keyword is one for which there are many searches and few
competing Web pages. Suppose you discover that 5 million people a month are searching for [Sarah Palin] but there are
only 10 Web pages about Sarah Palin. Obviously, it would be easy to get a highly popular page or Web site if you write
about Sarah Palin.
On the other hand, suppose there are already 100 million Sarah Palin pages. It would take you many years to get a
page into a visible spot in the search engines (among the top results). By that time, nobody would remember who Sarah
Palin was, and there would be no searches for Sarah Palin. (If you are reading this in the year 2016, Sarah Palin was
the vice presidential candidate of the Republican party in the United States in 2008).
An index of keyword
effectiveness should reflect the number of searches in a given period for that word and the number of pages retrieved
for that word. But that is not enough. Suppose there are 10 searches a month for a keyword, and 10 pages about that
keyword. That gives a ratio of 1. Obviously, it is not worthwhile making a page that is built for a keyword that only 10
people are looking for each month. But if there are a thousand searches a month and a thousand pages, the ratio is still
one, but the keyword is much more desirable. Sumantra Roy therefore used the square of the number of searches divided by
the number of pages for a keyword for the KEI. Comparisons of KEI can be used to determine the Niche
of a Web page - that is, the optimal keyword for that page In the entry for Niche
There are also some data that use KEI as an illustration.
However, this index is arbitrary as Roy admits. One could use a different exponent for the number of pages searched,
such as 1.5, to give a different result. The psychological effect of this index is also different if "number of
searches" is taken from Google adwords, which shows many searches, or
from a service like
Wordtracker
which shows comparatively few searches. In both cases, the number of pages retrieved for
the keyword remain the same. [Prevent identity theft] (see
Niche) has an impressive KEI of 133,000 for its 9,900 Google searches
per month. But in Wordtracker, it only got 14 searches, so its KEI is a miserable 0.266304.
Apart from this "psychological effect" which can be solved by multiplying by a factor, there are other things to
consider. The number of pages is less important than their
Google PageRank
and their real relevance to a keyword. If you are really the only site talking about Identity theft and have a really
relevant page, it may not matter that Google has 35,000,000 or 54,500,000 pages retrieved for [identity theft] since
many of them may be irrelevant or off topic, or they may be at Websites that have 20 pages. The "Pages retrieved" number is also unreliable and may change as you click
on additional results. Try to see the "pages retrieved value for [identity theft]. Then do this. In the URL change
the start value to 900 like so:
http://www.google.com/search?hl=en&safe=off&q=identity+theft&start=900&sa=N
You will see that the number of pages retrieved is now different.
If your Website is large and strong, it makes sense for you to go after the more popular
keyword, whereas if it is small and has a low pagerank, you will do better with less popular keywords, which have a lower KEI and for which there is less competition.
Ami Isseroff
October 1, 2008
Note - Definitions of Search Engine
Optimization terms are based on inferences from common usage and definitions given by other sources. Conclusions about
search engine behavior are based on understanding of the behavior of the most popular search engines. Both are subject
to error or may change. Search engine company management may define or use a term or set or change any policy in any way
they see fit, and may make these definitions and specifications public or not. These decisions and definitions are
beyond our control. Notice: Copyright
All materials are copyright 2008 by Ami Isseroff. All rights reserved. These pages may not be reproduced in any
form in electronic or printed media without express written permission from the author.
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