Analytics - 3/6 - Digital Marketing Agency

Google Analytics – Social Reports

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With Social Media sending more traffic to sites, Google Analytics now has more reports to analyse that traffic. Check them out in your interface now, you can find them under the Traffic Sources section;

Google Analytics Measuring Social Media


One of the best graphs available in here is the Social Shares graph, which is available in the Overview report. Because Social Media is more of a branding and communication tool, rather than a direct sales tool, it is sometimes hard to justify the investment of time and money into it. If you have goals set up in your analytics account, the Social Shares graph will be able to show you how often social media was seen by the customers who converted on your site, and how often it was the most recent campaign for a converting customer.

Social Share Report - Google Analytics

The other reports are pretty self explanatory, but two are quite new.


The Social Plugins report shows how often there was interaction with any social media plugins on your site – this report will require some extra set up to help it run if you want to see results for plugins other than Google Plus.


The Social Visitors flow shows how customers from social media channels move through your site – and should be compared to your other channels. For example, do social media users want different things from your site?



Google Analytics – How To Use Custom Variables

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Having learned a lot at Google Engage’s Advanced Analytics seminar last week, we’re keen to write it all down, to make sure that others can discover these underutilised features of Google Analytics. First stop, Custom Variables.


So, what are Custom Variables?


Custom variables help you with that very important aspect of data analysis – segmentation. Using custom variables, you can segment the behaviour of users on your site depending on a range of characteristics. Just a few examples might be;

– Visitors who viewed video.

– Visitors who are logged in

– Visitors interested in certain content (e.g. cooking category of pages)


You can make custom variables at 3 levels;

  1.  Visitors – e.g. what country are they from? Are they a subscriber?
  2. Visits – e.g. visits including a blog view, or visits including a video view
  3. Pages – e.g. when they saw a particular page of the blog, or content category.


The only thing you need to remember is that custom variables either have to be things about the page they visit (e.g. the content category or a subscriber page) or something they tell you (e.g. their location, gender, or language). Custom Variables aren’t some magic Google Analytics feature which can give you additional information about your visitors – YOU have to assign custom variables to visitors, so you need to know those things about them already.


How Do Custom Variables Work?


To make these custom variables work, Google Analytics puts a cookie on a visitors browser to allocate a custom variable to them. However, there are limits to how many custom variables you can use in a single request.


The sum of all your custom variables cannot exceed 5 in any given request

– A Visitor level metric occupies a whole slot for 2 years
–  A visit level metric occupies a slot for just one whole visit
– A pageview only uses more than one slot if you want to do more than one custom variable on one page


The code will look like this




Index = Slot and has to be a number between 1 and 5

Name is a string, e.g. “gender” or “video view”

Value is also a string, e.g. “male”, “yes” or “no

Opt_scope is the level of the variable (where visitor =1, visit =2, page =3).


If the viewing of the page itself results in the custom variable being assigned then the code needs to be put between _setAccount and _trackPageview.


If the visitor has to do something on the page to have a custom variable attributed (e.g. choose a language), then you must attach the code to visitor action, like onClick events.


For more information on how to use the code, visit the Google Developers page.


Tips for Custom Variables


– Before implementing custom variables, check for old ones.


– If you have complex tracking requirements, where you have a mix of page- and session-level variables that might collide, you should build a slot matrix to ensure that session-level variables do not inadvertently over-ride page-level variables.


– Similar to when you use Google Analytics event tracking or URL building – name things sensibly, so that in the future it is a system which is easy for other people to understand, and you also need to make sure there is no duplication of any of the names.


Tracking Subdomains in Google Analytics

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Although information similar to this is available in the Google Help Centre – in my opinion the help is not that great because it fractures the two steps in tracking subdomains in Google – the code change and the setting up of a filter. Even now, with the new help centre at Google Developers they don’t give you all the advice you need in one place.


So – here we will outline the very easy steps to identifying subdomain traffic in your analytics account.


You might notice that in the normal Google Analytics set up, your content reports show your pages from the trailing / after the domain.


So, pageviews of

will show up as



This is no good if we have subdomains. For example, say I had an English subdomain and a Chinese subdomain, and both had the same subfolder


Google Analytics would put that traffic for both these pages together under



To be able to separate them out you need to take 2 steps

1. Change your site-wide analytics code snippet

2. Set up a filter


Change to Analytics Code

If you are using the new asynchronous code (not so new anymore), then you need to insert the part in red


<script type=”text/javascript”>
var _gaq = _gaq || [];
_gaq.push([‘_setAccount’, ‘UA-XXXXXX-1’]);
_gaq.push([‘_setDomainName’, ‘’]);

(function() {
var ga = document.createElement(‘script’); ga.type = ‘text/javascript’; ga.async = true;
ga.src = (‘https:’ == document.location.protocol ? ‘https://ssl’ : ‘http://www’) + ‘’;
var s = document.getElementsByTagName(‘script’)[0]; s.parentNode.insertBefore(ga, s);


If you are using the old code


<script type=”text/javascript”>
var gaJsHost = ((“https:” == document.location.protocol) ? “https://ssl.” : “http://www.”);
document.write(unescape(“%3Cscript src='” + gaJsHost + “’ type=’text/javascript’%3E%3C/script%3E”));
<script type=”text/javascript”>
try {
var pageTracker = _gat._getTracker(“UA-XXXXXXX-X”);



Create a Filter


Then what you need to do is create the filter. I recommend creating a new profile  (and then using it in all subsequent profiles you create), just because I like to create new profiles when ever I use a new filter.


The new filter should look like this;


Filter Type: Custom filter -> Advanced
Field A -> Extract A: Hostname -> (.*)
Field B -> Extract B: Request URI -> (.*)
Output To -> Constructor: Request URI    /$A1$B1
Field A Required: Yes
Field B Required: No
Override Output Field: Yes
Case Sensitive: No



This will mean the URLs will now show up in Google Analytics as the complete URLs ;


If you wanted to isolate the traffic to each subdomain, and make them show in separate profiles, you should make multiple profiles using the above filter and then you can use custom filters on each one of those profiles, to include or exclude the subdomain traffic as you need;


Filter Type: Custom filter -> Include
FIlter Field: Hostname
Filter  Pattern:  ^en\.moomumedia\$
Case Sensitive: No

9.29% of Organic Search Terms now ‘Not Provided’ in Google Analytics

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In late 2011, Google announced that it would start encrypting search results of logged in Google users, to help protect users’ privacy. This initially sent some search marketers into a spin, as they were scared they would lose their precious Keyword Data in Google Analytics.


(Note that this protection of privacy did not extend to users of Google Adwords, where your searches will still get passed on to advertisers).


Anyway, I thought I would do a quick recap to see what kind of effect this was having on our analytics data so far this year.  Below is a graph showing – very basically – the results by geographical area of what percentage of search terms are now “Not provided” by Google in our Google analytics accounts.


Not Provided Organic Search Terms in Google Analytics


Note that although I am presenting a scienc-ey graph, the results should not be assumed to be too accurately sciencey, they are just demonstrating what we are seeing as a pattern among our own sites, and those of other analytics accounts we manage.


Note also that the ‘geographical’ areas I am using are where the site is targeted, not where the users are actually located (which may arguably be more useful, but which would also take a significantly longer time to organise – I might do that in the future).


Note that ‘Not Provided’ search terms are only an issue when users have been logged in to Google. You can see that this is happening almost 12% of the time in the USA. I was surprised to see that the Asian sites were so highly represented in this table, insinuating many Asian users are also logged in to Google accounts. Strange.


Australia and Europe were the lowest, insinuating we are less frequent users of Google properties like Gmail, etc.


It is expected (by me), that sites which have a higher volume of ‘savvy’ internet users, like technology sites, would have higher rates of Google account usage, and therefore “not provided” keywords. This proved true with 13.51% of keywords to our technology sites not providing search terms.


The actual results of our survey of websites showed that ‘not provided’ keywords contributed from around 2% to 14% of organic searches this year, depending on the site.


The weighted average of all sites surveyed was 9.29%.

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