Comments on: Keyword Analysis by Number of Terms (and the RegEx that helps) http://www.lunametrics.com/blog/2008/01/02/keyword-analysis-by-number-of-terms-and-the-regex-that-helps/ Traffic, Analysis, Action Sun, 12 Feb 2012 00:37:00 +0000 hourly 1 http://wordpress.org/?v=3.3.1 By: moncleroutlet http://www.lunametrics.com/blog/2008/01/02/keyword-analysis-by-number-of-terms-and-the-regex-that-helps/comment-page-1/#comment-499081 moncleroutlet Fri, 21 Oct 2011 18:40:20 +0000 http://www.lunametrics.com/blog/2008/01/02/keyword-analysis-by-number-of-terms-and-the-regex-that-helps/#comment-499081 yes.but they are invaluable in the pursuit of providing information that can be acted upon. yes.but they are invaluable in the pursuit of providing information that can be acted upon.

]]> By: monclernimei http://www.lunametrics.com/blog/2008/01/02/keyword-analysis-by-number-of-terms-and-the-regex-that-helps/comment-page-1/#comment-447068 monclernimei Sat, 17 Sep 2011 04:39:09 +0000 http://www.lunametrics.com/blog/2008/01/02/keyword-analysis-by-number-of-terms-and-the-regex-that-helps/#comment-447068 This works as the {3} … simply … acts like a multiplier. ie: ^([\b-"+',]*\w+\b)([\b-"+',]*\w+\b)([\b-"+',]*\w+\b) This works as the {3} … simply … acts like a multiplier. ie:
^([\b-"+',]*\w+\b)([\b-"+',]*\w+\b)([\b-"+',]*\w+\b)

]]> By: fpeiqin http://www.lunametrics.com/blog/2008/01/02/keyword-analysis-by-number-of-terms-and-the-regex-that-helps/comment-page-1/#comment-434574 fpeiqin Fri, 09 Sep 2011 02:22:31 +0000 http://www.lunametrics.com/blog/2008/01/02/keyword-analysis-by-number-of-terms-and-the-regex-that-helps/#comment-434574 there are also Lookbehinds … but GA does not support them as far as I can tell. there are also Lookbehinds … but GA does not support them as far as I can tell.

]]> By: Search Term Categorisation in Google Analytics | Web analytics consultancy and expert Google analytics | L3 Analytics http://www.lunametrics.com/blog/2008/01/02/keyword-analysis-by-number-of-terms-and-the-regex-that-helps/comment-page-1/#comment-257475 Search Term Categorisation in Google Analytics | Web analytics consultancy and expert Google analytics | L3 Analytics Thu, 19 May 2011 12:24:16 +0000 http://www.lunametrics.com/blog/2008/01/02/keyword-analysis-by-number-of-terms-and-the-regex-that-helps/#comment-257475 [...] number of keywords that they contain.  A bit of research and I found this post from LunaMetrics on Keyword Analysis by Number of Terms.  Just note though that the regular expression that I found to work [...]

[...] number of keywords that they contain.  A bit of research and I found this post from LunaMetrics on Keyword Analysis by Number of Terms.  Just note though that the regular expression that I found to work [...]

]]> By: Mike Plummer http://www.lunametrics.com/blog/2008/01/02/keyword-analysis-by-number-of-terms-and-the-regex-that-helps/comment-page-1/#comment-990 Mike Plummer Tue, 23 Sep 2008 23:45:19 +0000 http://www.lunametrics.com/blog/2008/01/02/keyword-analysis-by-number-of-terms-and-the-regex-that-helps/#comment-990 My 3rd grade English teacher would argue that in order for a string to contain 2 words, it must contain a space between the two words. In this case, it's as simple as: .+ .+ one word: change filter to exclude and hit the space bar or three words: .+ .+ .+ Sure, you'll get some funky outliers... but you'll also probably be able to memorize the regex. This would include numbers and other characters as well, but I would also argue that numbers are words in this context. If you don't think numbers are words, then just use John's example above to construct: \p{L}+ \p{L}+ Actually, this whole counting keywords thing seems a little numerology heavy. I think what really contributes to the higher conversion rates are the combination of a brand term with a relevant topic / item. For example, someone landing on this site having searched "luna metrics blue widgets philadelphia" is certainly going to convert higher, as they are measurably both brand aware and purchase intending for those fancy blue widgets and localized. You're gonna need some really fancy regex to measure that :) My 3rd grade English teacher would argue that in order for a string to contain 2 words, it must contain a space between the
two words. In this case, it’s as simple as:
.+ .+
one word:
change filter to exclude and hit the space bar
or three words:
.+ .+ .+
Sure, you’ll get some funky outliers… but you’ll also probably be able to memorize the regex. This would include numbers and other characters as well, but I would also argue that numbers are words in this context. If you don’t think numbers are words, then just use John’s example above to construct:
\p{L}+ \p{L}+

Actually, this whole counting keywords thing seems a little numerology heavy. I think what really contributes to the higher conversion rates are the combination of a brand term with a relevant topic / item. For example, someone landing on this site having searched “luna metrics blue widgets philadelphia” is certainly going to convert higher, as they are measurably both brand aware and purchase intending for those fancy blue widgets and localized. You’re gonna need some really fancy regex to measure that :)

]]> By: John http://www.lunametrics.com/blog/2008/01/02/keyword-analysis-by-number-of-terms-and-the-regex-that-helps/comment-page-1/#comment-989 John Sun, 09 Mar 2008 20:51:29 +0000 http://www.lunametrics.com/blog/2008/01/02/keyword-analysis-by-number-of-terms-and-the-regex-that-helps/#comment-989 Google Analytics supports the \p unicode character sets such as \p{L} any letter \p{N} any number \p{P} any punctuation \p{Z} any whitespace you can negate a character set with ^ inside the {} such as \p{^L} any non-letter So the equivalent to \w should be [\p{L}\p{N}] or any letter or any number So that lets us handle any part of the expression except the \b, the word break. I'm not sure what the equivalent is here. Note, I have no experience with the \p stuff myself, and I don't know how it would actually play out or how close you could come to getting it to work. This is just a starting point Google Analytics supports the \p unicode character sets such as

\p{L} any letter
\p{N} any number
\p{P} any punctuation
\p{Z} any whitespace

you can negate a character set with ^ inside the {} such as

\p{^L} any non-letter

So the equivalent to \w should be [\p{L}\p{N}] or any letter or any number

So that lets us handle any part of the expression except the \b, the word break. I’m not sure what the equivalent is here.

Note, I have no experience with the \p stuff myself, and I don’t know how it would actually play out or how close you could come to getting it to work. This is just a starting point

]]> By: Michael Dalmer http://www.lunametrics.com/blog/2008/01/02/keyword-analysis-by-number-of-terms-and-the-regex-that-helps/comment-page-1/#comment-988 Michael Dalmer Sun, 09 Mar 2008 17:55:31 +0000 http://www.lunametrics.com/blog/2008/01/02/keyword-analysis-by-number-of-terms-and-the-regex-that-helps/#comment-988 Hi, Thanks for this tip. Now for a Danish customer I need a regular expression that also include the Danish charaters æ, ø and å. And for this particular customer also the swedish character ö. If I use this one: ^([\+*"*\s*,*'*\-*]*\w+\b\s*[\+*"*\s*,*'*\-*]*){3}$ these characters are not included. If I use this one: ^(\W*\w+\b\W*){3}$ these characters are included, but they seem to count as spaces so that for example the word "hængelås" (Danish word for padlock) is listed as a three word phrase. Let me know if you have a solution for this - it will help me a lot! Thanks, Michael Dalmer Hi,

Thanks for this tip. Now for a Danish customer I need a regular expression that also include the Danish charaters æ, ø and å. And for this particular customer also the swedish character ö.

If I use this one: ^([\+*"*\s*,*'*\-*]*\w+\b\s*[\+*"*\s*,*'*\-*]*){3}$

these characters are not included.

If I use this one: ^(\W*\w+\b\W*){3}$

these characters are included, but they seem to count as spaces so that for example the word “hængelÃ¥s” (Danish word for padlock) is listed as a three word phrase.

Let me know if you have a solution for this – it will help me a lot!

Thanks,
Michael Dalmer

]]> By: Rethinking your strategy, and why the long tail converts better. http://www.lunametrics.com/blog/2008/01/02/keyword-analysis-by-number-of-terms-and-the-regex-that-helps/comment-page-1/#comment-987 Rethinking your strategy, and why the long tail converts better. Thu, 06 Mar 2008 19:10:43 +0000 http://www.lunametrics.com/blog/2008/01/02/keyword-analysis-by-number-of-terms-and-the-regex-that-helps/#comment-987 [...] it a good idea to go after it? Probably not. Theres a great post over at Lunametics that proves why longer keyword phrases convert better. For example if someone searches for a “Dell computer”, they are probably researching [...]

[...] it a good idea to go after it? Probably not. Theres a great post over at Lunametics that proves why longer keyword phrases convert better. For example if someone searches for a “Dell computer”, they are probably researching [...]

]]> By: Greg Moore http://www.lunametrics.com/blog/2008/01/02/keyword-analysis-by-number-of-terms-and-the-regex-that-helps/comment-page-1/#comment-986 Greg Moore Thu, 03 Jan 2008 20:14:12 +0000 http://www.lunametrics.com/blog/2008/01/02/keyword-analysis-by-number-of-terms-and-the-regex-that-helps/#comment-986 Another interesting take on this topic... http://www.isearchmedia.com/articles/Keyword_Length_and_Conversion_Rate.php Cheers! Another interesting take on this topic…
http://www.isearchmedia.com/articles/Keyword_Length_and_Conversion_Rate.php

Cheers!

]]> By: Loren Hadley http://www.lunametrics.com/blog/2008/01/02/keyword-analysis-by-number-of-terms-and-the-regex-that-helps/comment-page-1/#comment-985 Loren Hadley Thu, 03 Jan 2008 19:07:50 +0000 http://www.lunametrics.com/blog/2008/01/02/keyword-analysis-by-number-of-terms-and-the-regex-that-helps/#comment-985 Thanks John, Very interesting & useful. I did a quick run through our results for 2007 and discovered that roughly 87% of our traffic and 87% of our sales came in in 3 word phrases or less. with about 60% contributed by 2 word phrases, which is also where our conversion rate peaked. If I had guessed at the results before running this, my guesses would have been way off. I would have figured that our peak would have been at about 4 keyword phrases and more heavily weighted towards longer (brand and model specific) terms. Thanks, Loren Thanks John,
Very interesting & useful. I did a quick run through our results for 2007 and discovered that roughly 87% of our traffic and 87% of our sales came in in 3 word phrases or less. with about 60% contributed by 2 word phrases, which is also where our conversion rate peaked.

If I had guessed at the results before running this, my guesses would have been way off. I would have figured that our peak would have been at about 4 keyword phrases and more heavily weighted towards longer (brand and model specific) terms.

Thanks,
Loren

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