Tag Archives: Search Engine Optimization

Google Launches New Algorithm Update to Target Link Farms

No More SpamOver the past few weeks Google has taken some serious measures to eliminate web spam from its organic search results. Early February, JC Penny was hit with a manual and algorithmic penalty for “buying” links with very specific targeted keywords. More recently Overstock and Forbes have been penalized for participating in both “buying” and “selling” links respectively.

We knew it was not going to be long before Google released a major algorithm update to combat the very prevalent web spam and link farms we have seen growing over the past couple of years. Well the time has come; today Google’s Matt Cutts & Amit Singhal unveiled an algorithmic change that claims to impact 11.8% of search queries.

According to Singhal, this update is targeted to “reduce the rankings for low quality sites while increasing the ranking for high quality sites.”

What exactly is Google’s definition of “low” quality and “high” quality? The official definitions from Google are:

“Low-quality sites – sites which are low-value add for users, copy content from other websites or sites that are just not very useful.”

“High-quality sites—sites with original content and information such as research, in-depth reports, thoughtful analysis and so on.”

Google is also claiming that the update does not rely on the feedback that it receives from the “Personal Blocklist Chrome Extension”. They do however claim to have compared it to the Block List Data they have gathered to date and show a staggering 84% match with the algorithm update. Coincidence?

Finally this update is currently only being rolled out in the United States Only, other countries will follow over time.

You can read the Offical Blog Post from Google here.

Experiment – How Twitter Links Effect Search Engine Ranking

Last week both Google and Microsoft confirmed that they do in fact take in to consideration social media links (links within Facebook and Twitter) in their ranking algorithms.

I thought it would be interesting to try a little albeit slightly selfish experiment to see if I can gather some data to support what both search engines have confirmed.  This is an informal experiment that will both help start to answer the questions these changes have brought and at the same time promote my wonderful wife’s website.

Below is a pre-crafted tweet with Keywords built in to the structure of the tweet, simply click the share button below to participate in the experiment.

I will be tracking the results with topsy.com and will publish a findings post once the experiment has concluded and I have had time to correlate the date.

I need your help!

If tweeting or linking is not your thing what are you doing reading an SEO blog? ;)

Full Disclosure / Disclaimer – Participating in this experiment will promote a site that is owned by my wife, I do not want to hear from people that I was performing a selfish experiment. Though I fully believe the results will be useful to all SEO’s out there.

Tracking Google Instant Partial Queries in Google Analytics

My previous post describes Google Instant and the new search results user interface. Now that folks have had several hours to play certain realizations begin to set in. What does this mean for Search Engine Optimization? What does this mean for my traffic?

All good questions in this post I will address the first question which came to my mind. What about Analytics? How do I track Google Instant partial queries? Now that Google is presenting real time or instant results, there is a high chance that the query string that gets passed to Google Analytics is incomplete or rather partial because the link was displayed before the user even completed typing the query!

For example an instant query result for “weather” may only be passing along “w” as the query parameter to Analytics since Google displays the link to weather after just typing “w”. To understand what a user needed to type to find the result they were looking for an additional parameter is being used in the result set. The parameter is “oq=” which will give you the information you are looking for.

To track Partial Queries, and their position in Google Instant, you will need to create a new profile along with a new filter in your Google Analytics Report. It is pretty straight forward; below is a sample filter you can use to start tracking.

  1. Create a new Filter name: “New Instant Ranking Filter”
  2. Set Filter type: “Custom filter – Advanced”
  3. Field A -> Extract A: Referral, ^https?://www\.google\.(co.uk|com)/(?!custom|m/).*[?#&]cd=([^&]+).*&q=([^&]+).*&oq=([^&]+)
  4. Field B -> Extract B: Medium:^organic$
  5. Output To -> User Defined: $A5 (position: $A3)

You may have to play a little with the filter for you specific requirement but this should give you a good start.

Let me know if you have any other suggestion or comments.

Google Instant – New Search Enhancement

Google LogoThe big anticipated announcement from Google this morning is “Google Instant”.

Google is moving away from the traditional HTML based results to a more robust AJAX based application for delivering ‘real’ time search results. Marissa Mayer noted that Google has already made approximately 500 changes to search ranking and user interface (UI) in 2010.

It takes a user on average 9 seconds to enter a search query followed by a few hundred milliseconds on Google’s Servers to render a search result. The user then averages about 15 seconds looking at the results. Google Instant claims to save user 2-5 seconds per query, which in turn will save 11 aggregate hours per second.

Google will display characters in black that they have typed followed by shifting grey predicted characters as the user continues to type. Why even keep the search button at this point? Well it forces Google to search for exactly what you’ve typed, without predicting how you’ll finish that search.

Instant will begin rolling out to Google domains in the US, UK, France, Germany, Italy, Spain and Russia who use the following browsers: Chrome v5/6, Firefox v3, Safari v5 for Mac and Internet Explorer v8.

For more information from Google you can visit their brief description over at:

 http://www.google.com/instant

Web Browser Statistics – 2010

Over the past couple of years it appears that the demise of Internet Explorer 6 has finally reached some momentum. I do concede this may not be true in larger organizations where simple changes like upgrading a Web Browser to a newer release can be a very large undertaking.

However: Looking back at my 2010 analytic stats I can see the increase in Internet Explorer 8 adoption amongst the general home user (my target demographic). What I do find interesting is that IE7 seems to have had a very small adoption rate. This may be in part due to the commercials Microsoft has released promoting the “Enhanced Security” features of IE8.

Below are two images showing the different browser distribution of my visitors and more importantly drastic trend to move away from Internet Explorer 6.
type of browser Internet Explorer Version Chart