The top 10 searched for terms last month on Google were: myspace, myspace.com, ebay, www.myspace.com, youtube, craigslist, mapquest, yahoo, facebook and myspace layouts.
Despite those terms being the most searched for, a few months ago, Google’s VP of Engineering - Udi Manber gave a presentation at Supernova where he said 20 - 25% of the queries typed into Google on a daily basis have never seen before.
I wasn’t able to find any totally accurate and current figures, but based on some reports over the last few months from Nielsen/Netratings, it suggests that roughly 515,000,000 searches are performed globally each day… which works-out to be approximately 6000 searches done every second.
Now imagine that one in every four (or five) of those searches is totally unique and has never been typed into Google before - that’s a staggering 103,000,000 - 128,750,000 unique searches every single day.
So how does Google and the other search engines rank sites when they don’t know what a quarter of their users are going to search for? It’s a tricky problem that Bill Slawski discusses in his article: Predictive Queries versus Unique Searches
As a website owner, these types of statistics are fantastic. A lot of sites tend to focus on highly competitive terms (and there’s nothing wrong with that as Hamlet Batista points-out) but there are still a lot of non-competitive terms that you can focus on knowing that statistically, someone is likely to search for at some stage.
So how can you ensure that you’re targeting as many appropriate terms through-out your site? Three simple words - Content, Content and Content.
The more relevant content you have on your site, the more chances you have of attracting long-tail search patterns.
So what are you waiting for - stop searching for ‘myspace’ and start writing some additional articles and other relevant content for your website!
If you're new here, you may want to subscribe to my RSS feed. Thanks for visiting!
Great insights, Pete.
You forgot a post by Identity@Seomoz that talks about using patterns for predicting “invisible long tail searches”. Check it out.
Keep up the great content!
Thanks Hamlet - I was aware of Identity’s post and made reference to it in my post about long-tail :
http://blog.sitemost.com.au/2007/07/04/a-short-story-about-a-long-tail/
But to save everyone else from having to read that post, here’s a direct link to Identity’s post on SEOmoz :
http://www.seomoz.org/blog/identifying-long-tail-patterns
Not to mention Hamlet has a good write-up on long-tail as well on SEOmoz:
http://www.seomoz.org/ugc/uncovering-the-invisible-long-tail
Thanks
Great insights, Pete.
You forgot a post by Identity@Seomoz that talks about using patterns for predicting “invisible long tail searches”. Check it out.
Keep up the great content!