2.) HEADLINE ARTICLE
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Does Keyword Density Affect Ranking?
by Jon Ricerca
http://www.SearchEngineGeek.com

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Once upon a time, it was thought that keyword density
was the most important factor that search engines used
for ranking. Perhaps it was. We weren't performing
these studies prior to a couple of years ago so we just
don't know. In any case, it seemed that it would be a
simple study to statistically reverse engineer the
leading search engine for this particular factor.

We found that it was not. The amount of data required to
reliably study this particular factor to a 1/10th of a
percent accuracy was far beyond the amount of data we
normally gather (the actual searches for 4 researches for
one month). We decided to lump data together at the 1%
accuracy level so that we could provide valid (although a
magnitude less fine) results. Still we found that we were
not able to gather sufficient data beyond the 4% keyword
density range. However, the resulting graph showing only
1%-4% turned out to be startlingly conclusive.

The methodology: I gathered the results of the queries
that were naturally performed last month by myself and
three associates using the leading search engine and
analyzed them. I had to visit each page and calculate a
keyword density between the body and /body tags. Those
keyword densities were then rounded to the nearest 1% and
tabulated for the first 10 rankings and finally converted
into a normalized "ranking correlation".

The keyword density was calculated by number of
characters. The number of letters in the keyword under
study are represented by l in the following formula. The
number of letters between the body and /body tag are
represented by b in the following formula. The number of
times the keyword was found between the body and /body
tags are represented by c in the following formula. The
keyword density is the resulting d in the following
formula:

d = (c * l) / b

The resulting number shows each group of keyword densities
(grouped at the 1% rounding level to reduce the amount of
data required for a valid statistical analysis) normalized
into a number between ~100 and +100 showing the likelihood
of being ranked higher/lower. A value of +100 shows that
all 10 rankings were in the proper order to show that
pages of the studied value ALWAYS rank HIGHER than pages
of another value. A value of ~100 shows that all 10
rankings were in the proper order to show that pages of
the studied value ALWAYS rank LOWER than pages of another
value. Numbers in between show the varying likelihood of
rankings proportionally between ~100 and +100.

That is the number you see on the Y-axis. On the X-axis,
we have groups of keyword densities varying from 1% to 4%.
I stopped at 4% because the number of sites found with
keyword densities higher than 4% were too few to consider
statistically valid. Here is the graph:

http://www.SearchEngineGeek.com/graphs/dbg01.jpg

(Note to webmasters: Feel free to hot link to the above
graph, text link to it, or even copy it to your own site)

The result is vary conclusive. The leading search engine
ranks sites having a keyword density between 1.5% and
2.49% higher than pages having any other keyword density.
The correlation was a staggering +92 on a scale of -100 to
+100. Rarely in our studies have we seen such a clear and
positive correlation.

Notes:

1. Over 1,000 queries and over 10,000 sites were examined
for this study.

2. There was no exercise to attempt to isolate different
keywords. I merely took a random sampling of the queries
performed by myself and three associates during the month.

Conclusion:

Pages with a keyword density of 1.5%-2.49% between the
body and /body tag rank higher than pages of other keyword
densities on the leading search engine.

This is merely a correlation study, so it cannot be
determined from this study whether the leading search
engine purposefully entertains this factor or not. The
actual factors used may be far distant from the factor we
studied, but the end result is that this search engine
does, in fact, rank pages with the above keyword densities
higher than pages with other keyword densities used in the
study.

Jon Ricerca is one of the leading researchers and authors
of the Search Engine Ranking Factor (SERF) reports at
SearchEngineGeek.com. For access to the other SERF
reports, please visit:
http://www.SearchEngineGeek.com