New GA tracking code to track social interactions of Facebook, +1, etc. (screenshots)

This slipped under my radar a bit, but coming soon Google have a new bit of tracking code to add to your website to have social interactions (including not just +1 but Facebook, Delicious etc) in Google Analytics.

As the Google +1 webinar says:

The recording of the webinar to the Google Business Channel on YouTube (goo.gl/GhlqZ) and copy of the presentation online (goo.gl/YQn0u). Implementation guide for the +1 button at the following link: goo.gl/4te65

Screenshots are below of the implementation from the webinar – like the tracking of pagespeed line added earlier this year, this will only appear in the new GAv5 interface.  It involves adding:

_trackSocial(network, action, target_url)

...to the GA tracking code.  Be great to add soon as its availble. 

Also in the webinar is talk of paying for your social action to appear in listings (??) and the demographics of users appearing in the reports, which will be hyper useful, as well as the use of the canononical link element to make all +1 votes credit one page.

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Filed under  //  GAv5   analytics   google   screenshots   social  
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New Google image search proves Penguins use the Force

Screenclip

 

Hehe.  It seems Google is associating "star" from this picture (which I got from Windows7 demo examples) to posts where a user has used it in his avatar:

http://hawkcentral.com/2011/05/10/matt-gaten-bryce-cartwright-to-join-all-sta...

Work to do, but a little insight on how Google Image recognistion works - looking at text on pages around where it finds that image across the web.  Does still show text is still an important driver in image SEO.

Filed under  //  google   image   seo  
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Every day this marching band marches past my window [video]

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It was kinda cute the first time - after the 50th time....not so much ;ø)  "luckily" they are only drumming in this vid, usually they have the full band playing as well.

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Example of how sitespeed increased crawling by Googlebot

Here is a great example of how sitespeed makes a difference in crawling a site – the server had an upgrade end of October.

 

Cross posted on Search Engine War

 

Image001
 

 

 

 

Filed under  //  crawling   google   sitespeed  
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New Google Webmaster Tool data - changes from last month [screenshot]

Gwt_new_data

Nice new feature in Google Webmaster Tools, this shows how your impressions and average epositions have changed over the last period. Should be very useful to see how SEO changes are affecting keywords.  Here is a screenshot for this blog.


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Virtual Page Views with Asynchronous Google Analytics [example]

I got a bit miffed that Google haven't updated thier help files for asynchronous GA tracking yet for virtual page views, so here is one if you're checking your code like I was today.

<a href="javascript:addBasket('773')" 
OnClick="javascript:_gaq.push(['_trackPageview', '/vpv/basket/']);" 
class="linkOpacity"> 
<img src="images/button_enrol.gif" alt="Enrol" width="202" height="42" /></a>


When someone clicks on the button to enrol, a page will appear on the GA report called /vpv/basket

Another thing to note is you do not need to code in a delay for the script to fire now, as was recommended for the previous version.

Thanks to ericmatisoff for confirming in a GA forum thread around virtual page views for the new asynchronous Google Analytic code.

Filed under  //  analytics   code   example   google  
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A question that could be solved by SEO science? Find C(k) to predict how to become a WWW hub.

Came across this reference to something that may be a good experiment for an SEO scientist to do, comments in extract below:

From Statistical mechanics of complex networks

p62

3.6 Discussion and outlook

The identified hierarchical architecture offers a new perspective on the topology of complex networks.  Indeed, the fact that many large networks are scale-free is now well established.  It is also clear that most networks have a modular topology, quantified by the high clustering coefficient they display.  Such modules have been proposed to be a fundamental feature of biological systems, but has been discussed in the context of the WWW, and social networks as well.  The hierarchical topology offers a new avenue for bringing under a single roof these two concepts, giving a precise and quantitative meaning for the network's modularity. (MarkeD - modularity could be interpreted as a set of websites in a niche?)  It indicates that we should not think of modularity as the coexistence of relatively independent groups of nodes.  Instead, we have many small clusters, that are densely interconnected.  These combine to form larger, but less cohesive groups, which combine again to form even larger and even less connected clusters.  This self-similar nesting of different groups or modules into each other forces a strict fine structure on real networks. (MarkeD - demonstrating long tail theory giving websites that are more and more specialised)

For biological systems hierarchical modularity is consistent with the notion that evolution may act at many organizational levels simulaneously: the accumulation of many local changes, that affect the small, highly integrated modules, could slowly impact the properties of the larger, less integrated modules.

[cut out a bit about how this applies to genes]

Most interesting is, however, the fact that the hierarchical nature of these networks is well captured by a simple quantity, the C(k) curve, offering us a relatively straightfoward method to identify the presense of hierarchy in real networks.  The law indicates that the number and the size of the groups of different cohesiveness is not random, but following strict scaling laws. (MarkeD - so could use this to predict how connected with the rest of the niche a particular website is in - the more connected, the more likely search engines will rank them?) 

The presence of such hierarchical architecture reinterprets the role of the hubs in complex networks.  Hubs, the highly connected nodes at the tail of the power law degree distribution, (MarkeD - "winners" of the web = big internet brands such as Twitter, Google, Amazon, Yahoo, MSN and Facebook) are known to play a key role in keeping complex networks together, playing a cruical role from the robustness of the network to the spread of viruses in scale-free networks.  Our measurements indicate that the clustering coefficient characterizing the hubs decreases linearly with the degree.  This implies that while the small nodes are part of a highly cohesive, densely interlinked clusters, the hubs are not, as their neighbours have a small chance of linking to each other.  (MarkeD - competitors do not link to one another?)  Therefore, the hubs play the important role of bridging the many small communities of clusters into a single, integrated network. (MarkeD - so if you want to be a hub, bear this in mind)

In many ways our study offers only a starting point for the understanding the interplay between scale-free, hierarchical and modular nature of real networks.  While the C(k) curves offer a tool to unearth the presence of a hierarchy, it is unclear what are the minimal ingredients at the model level for such a hierarchy to emerge.  Finally, the role of the geometrical factor, which appears to remove the hierarchy, needs to be elucidated.  Further modeling and empirical studies should allow us to address these questions. (MarkeD - Google may already know the answer)

 

Filed under  //  book   networks   science   seo  
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Search Engine War: Organic Click Through Rate - Brand vs Intent vs Research keyphrases

Organic Click Through Rate - Brand vs Intent vs Research keyphrases

Tuesday, 01 June 2010

The recent updates to the Google Webmaster Tools Top Searches report have offered new data to SEOs on clickthrough rates from natural search positions.

There have been various posts recently looking at the accuracy of the data and on click through rates which I'd like to add to with a look at how different types of searchers interact with the SERPs.

The types of keyphrases I have chosen to look at are Brand, Intent and Research keyphrases.

Three Different Types of Searches

Brand are all those phrases looking for a specific website, including navigational phrases (like ACME and www.acme.com )

Intent I classed as those phrases that signalled intent to purchase - these are phrases that usually include "cheapest", "deals" or "compare" (like "compare blue widgets")

Research I classed as those phrases that were more general information queries with no intent to buy seen (like "what are blue widgets")

The data found that these queries do exhibit different click through rates and user behaviour.

Summary of Results

  • Brand queries had a high click through at number 1, as expected, with number 1 taking 46% of clicks.
  • Intent queries were lower, showing 31% clicking through to number one.
  • Research queries showed an even higher clickthrough rate at number 1, getting 51% of click throughs, but also showing a higher clickthrough rate overall throughout the SERP


Organic Click Through Rate (CTR) Charts

Data was gathered from 630 keyphrases that had CTRs included within the Google Top Search reports.  Websites were a mix of ecommerce based websites varying in size and sectors.  Data and trendlines compiled in Excel2007.

A chart detailing the trend lines is shown below - Blue for Brand, Green for Research and Red for Intent.

(Click on charts for bigger version)

Ctr-brand-intent-research
Log trendlines were used as they give the best R2 values:

  • Research - 0.55
  • Intent -  0.75
  • Brand - 0.76

I made a post on Search Engine War about Click Through Rates in Google organic search, check it out the full post on the blog ->>> search-engine-war.co.uk

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Google Webmaster Tool Search Reports - a few factoids

A quick record on features of the new Google Webmaster Tool Search Report features:

sq-avg-position.png

Search Queries now available with bookmark stars and average organic positions

Local map impressions do not register as an impression, but will register a click (vi@neyne)

Image search shows a lot more people clicking through past the front page

Search query data is available for last 35 days only

Export of data not available for per keyword per ranking (can only take screenshots to show how many times a keyword was at #3, #2 etc)

Export of data not Unicode compliant

A message "hm something isn't right" is usually temporary


Filed under  //  google   webmaster tools  
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Helsingør, Denmark - Kronborg Castle

Famous for the setting for Hamlet.

 

edit - woops, this should have been posted to my photo blog, Things Mark Saw, but I'll leave it up here anyway :)

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