I’ve said it before, but I’ll say it again — I like to #measure. Google Analytics has a great feature called Advanced Segments. Using this feature, you can easily show a subset of data.

Sharing advanced segments with other users

One of the ways I use advanced segments is to categorise traffic into user types. It works really well and the great thing is that any advanced segment you create, you can also share with other Google Analytics users.

The links below are examples of some advanced segments I created for the University of Nottingham. If they seem helpful to you, feel free to use them as part of your Google Analytics reporting activity. To use them, simply login to Google Analytics and then click on the links below.

• Visits from the University of Nottingham (Campus)
• Visits not from the University of Nottingham (the opposite of the previous one)
• Visits from the city of Nottingham
• Visits from China
• Visits from Malaysia

Tutorial

Here’s a nice tutorial video from GoogleBusiness on how to create and use your own custom advanced segments:

Last week I released Analytics Plugin for Confluence 1.2 on the Atlassian Plugin Exchange.

It’s been 6 months since the initial release which was only tested on Confluence 3.0. This time I’ve added a new dashboard section, full support for Confluence 3.1 & 3.2 and a pile of macro parameters as requested by Guy Fraser. The release notes are here. Confluence 3.3 is just around the corner, so I’ll add an update for that when it comes out.

Thank you

The Confluence community has shown a great deal of support and encouragement since the plugin was originally released. For example, Atlassian blogged about it before I got a chance to. So thanks to all for your support.

The plugin was name checked by Sherif Mansour – Atlassian’s Product Manager for Confluence in the Confluence State of the Union presentation at Atlassian Summit 2010 at the start of the month. Watch it all, but concentrate especially around 5:10!

This week Google approved the plugin for their Google Analytics Application Gallery — take a look here. The Apps Gallery has only been going for about a month so I’m really excited about being a part of it. The slight name change and new logo were done to fit in with the Application Gallery Policy.

In the future

The next release should support Confluence 3.3 and also complete tracking of all pages in a space — not just those with a URL starting /display/spaceKey/ — based on this hack :

// Add a page-level custom variable to record the space-key
if (typeof jQuery('meta[name=confluence-space-key]').attr("content") == 'string')
{
  pageTracker._setCustomVar(
    1, // This custom var is set to slot #1 of 5

    // The name acts as a kind of category for the user activity
    'confluence-space-key',    

    // This value of the custom variable
    jQuery('meta[name=confluence-space-key]').attr("content"), 

    3 // Sets the scope to page-level
  );
}

— If you want to use this hack now, try out this custom Google Analytics report which will allow you to take advantage of it now.

I’d also like to add full space specific tracking for attachments too.

A quick demo

And finally, this is what the new version looks like:

Related Posts

• Tracking Atlassian Confluence usage with Google Analytics
• 4 Useful Tips on Google Analytics Reporting for Confluence
• Announcing: Google Analytics plugin for Confluence – original release

I’ve previously written a number of posts about Confluence and Google Analytics (GA), including how to set up GA on Confluence and pointers for GA reports you should consider. Lastly, I wrote the Confluence Google Analytics Plugin (CGAP) which provides space specific GA reports from within Confluence.

However, I’ve not been entirely happy because there wasn’t a method to allow complete tracking of all space specific Confluence pages using CGAP or the reports that I’ve previously described.

This has been documented elsewhere, but briefly, the problem is with…

• pages with punctuation in the title e.g. This page is bad for Analytics, isn’t it? (hover on the link to see the URI)
• short URLs e.g. /x/2Bq9Ag
• space administration e.g. /spaces/spaceadmin.action?key=spaceKey
• page edits e.g./pages/editpage.action?pageId=XXXX
• page creation e.g. /pages/createpage.action?spaceKey=spaceKey&fromPageId=XXXX
• add/view attachments e.g. /pages/viewpageattachments.action?pageId=XXXX
• page history e.g. /pages/viewpreviousversions.action?pageId=XXXX
• view wiki markup e.g. /pages/viewpagesrc.action?pageId=XXXX

…and so on. I think you get the picture.

For any page where there is a real interaction with the wiki — such as page creation or page edits, attachment viewing or uploading — it is very difficult associate that interaction to the space where the interaction took place. Damn. That’s the main point really. Wikis are for collaboration — editing and creating content — not just passively reading.

It really bugs me that the URIs in Confluence aren’t built up so that they always provide a context of where you are. But what can we do?

This post suggests 2 possible solutions to this problem:

1. A Javascript only method
2. A Javascript and velocity templating method

Both have their drawbacks, but they do let you get a little closer to understanding what your users are doing within your Confluence spaces. Try them out and please report back on your preference or your own alternative solution.

The Javascript only method

In this method, we track a custom variable in GA where possible, so that we can attach a page view to the corresponding Confluence space.

Atlassian handily provide the following (example) meta tag on every page that has an associated space:

<meta id="confluence-space-key" name="confluence-space-key" content="~cczdas">

We can check for that meta tag and pass it into a custom variable in Google Analytics.

In Confluence, go to Dashboard | Administration | Look and Feel | Custom HTML

Click on the “Edit” button and add this javascript snippet (with your tracker code) to the “At end of the BODY” section:

<script type="text/javascript">
var gaJsHost = (("https:" == document.location.protocol) ? "https://ssl." : "http://www.");
document.write(unescape("%3Cscript src='" + gaJsHost + "google-analytics.com/ga.js' type='text/javascript'%3E%3C/script%3E"));
</script>
<script type="text/javascript">

	window.onload = function(){
		try
		{
			var pageTracker = _gat._getTracker("UA-XXXXX-XX");

			// Add a page-level custom variable to record the space-key
			if (typeof jQuery('meta[name=confluence-space-key]').attr("content") == 'string')
			{
				pageTracker._setCustomVar(
				     1,                         // This custom var is set to slot #1 of 5
				     'confluence-space-key',    // The name acts as a kind of category for the user activity
				     jQuery('meta[name=confluence-space-key]').attr("content"), // This value of the custom variable
				     3                          // Sets the scope to page-level
				);
			}
		}
		catch (err) {}
	}

</script>

This means for each page, we’ve added a custom variable which can later be check against. We can now therefore easily check which page belongs to which space.

In Google Analytics, the custom variables report looks like this:

This doesn’t really tell us much, other than the number of page views for a space and a little more. To get at the real power of custom variables, we need to create a custom segment for each space. This will allow us to see all the interactions for the space.

Here’s a short video guide to creating custom segments for Confluence spaces:

Pros

• It’s really simple. Anyone with Confluence administration rights can cut and paste this code.
• It’s pure. This should not be affected by upgrades to the platform.
• It’s easily to support. Lots of people know Javascript.

Cons

• You’re moving into slightly advanced Google Analytics territory here.
• You’ll need to set up a separate custom advanced segment for each space. This may be somewhat dull.

I really like this approach, but haven’t managed to successfully add it into CGAP yet whilst maintaining access to historical data.

Javascript and velocity templating method

In this method, we trick Google Analytics into reporting the URL in a the format that works with content drill-down e.g.

• /pages/viewpage.action?pageId=XXXX becomes /display/spaceKey/Page+Title
• /x/2Bq9Ag (short URL) becomes /display/spaceKey/Page+Title
• /pages/editpage.action?pageId=XXX becomes /display/spaceKey/Page+Title/edit
• /pages/viewpageattachments.action?pageId=XXX becomes /display/spaceKey/Page+Title/view-attachments

We do this by adding a custom meta tag named “analytics.url.fix” from which we read the “fixed” URL using a little Javascript.

Edits

page.vmd in your theme:

## Add Google Analytics support for page edits, attachment views etc.
## Called by $!sitemeshPage.getProperty("page.googleAnalyticsUrlFix") in main.vmd
<content tag="googleAnalyticsUrlFix">
	#if ($mode == "view")
		<meta name="analytics.url.fix" desc="$req.contextPath/display/$page.spaceKey/$page.title" />
	#else
		<meta name="analytics.url.fix" desc="$req.contextPath/display/$page.spaceKey/$page.title/$mode" />
	#end
</content>

main.vmd in your theme:
Add after the title node in /html/head/title

## Call the googleAnalyticsUrlFix content tag in page.vmd, fail silently:
$!sitemeshPage.getProperty("page.googleAnalyticsUrlFix")

In Confluence, go to Dashboard | Administration | Look and Feel | Custom HTML

Click on the “Edit” button and add this javascript snippet (with your tracker code) to the “At end of the BODY” section:

<script type="text/javascript">
var gaJsHost = (("https:" == document.location.protocol) ? "https://ssl." : "http://www.");
document.write(unescape("%3Cscript src='" + gaJsHost + "google-analytics.com/ga.js' type='text/javascript'%3E%3C/script%3E"));
</script>
<script type="text/javascript">
	window.onload = function(){
		try
		{
			var pageTracker = _gat._getTracker("UA-XXXXXX-X"); 

			// Test for the meta[name=analytics.url.fix] tag & fix the url
			if (typeof jQuery('meta[name=analytics.url.fix]').attr("content") == 'string')
			{
	 			// console.debug('corrected pageview');
	   			var pageUri = jQuery('meta[name=analytics.url.fix]').attr("content").replace(/s+/gi, '+');
				pageTracker._trackPageview(pageUri);
			}
			else
			{
				// console.debug('default pageview');
				pageTracker._trackPageview();
			}
		}
		catch (err) {}
	}
</script>

Pros

• You don’t have to do anything on the Google Analytics side at all
• This is just great for the content drilldown screen in Google Analytics.
  • It means that pages with punctuation in the title can now be seen within their correct space.
  • The space owners can now be sure of the stats for viewing and editing pages within their space.
• This is great for the Google Analytics plugin for Confluence (CGAP)
  • All the page edits should be shown in the analytics report
  • It’s easily supportable. Lots of people know Javascript

Cons

• It’s a bit messy.
• You’ll have to apply this to every theme you support.
• Editing velocity templates isn’t everyone’s cup of tea.
• I’ve no idea what will happen when you upgrade Confluence.
• It niggles me that we’re sending incorrect (though easily readable) pageview data to Google Analytics.
• It still doesn’t tie everything to the space, just the page interactions

To my mind, this is less elegant, but provides pretty much instant results.

Which one to choose?

I really like the simplicity of the first solution. Just a little bit of Javascript to read a meta tag that’s already there. It’s likely to easily survive an upgrade. But I’m disappointed that as yet, I can’t get it to work nicely with CGAP.

For ongoing support reasons, I’d always say don’t mess with the platform. Don’t do anything which makes it more difficult to upgrade to the latest and greatest version. If you agree, then steer well clear of the latter option. If however, you absolutely have to start complete space specific tracking right now, no matter what, then the latter is then choice for you.

At work, we use Sungard HE‘s Luminis portal (v3.3) — It’s been good to us over the years, but there’s a lack of usage information regarding users’ roles and their interactions with Luminis.

In the past, we’ve added Google Analytics to Luminis to track the interactions, but never managed to fully segment user roles. Until now.

Out of the box, Luminis has roles such as staff, student, faculty, ProspectiveStudent etc. Users can have one or more of these roles and other custom roles too. If we could capture all the roles and pass them onto Google Analytics, then we’d be able to fully segment the user types and gain a better understanding of how each segment uses Luminis.

This post aims to show how this is possible in just 3 steps:

1. XSL: Edit nested-tables.xsl to add a custom meta tag for the luminis roles
2. Javascript/jQuery: Read the custom meta tag and set a custom variable in Google Analytics
3. Google Analytics: Create custom segments to view traffic for specific Luminis roles

Edit nested-tables.xsl and add a custom meta tag to the header

We’ve seriously hacked at nested-tables.xsl over the years, so our version of the file is likely to be different to most. The main aim here is to find the html > head section and add a custom meta tag:

<!-- Dump all roles into a single meta tag as a comma separated value -->
<meta name="luminis.role">
   	<xsl:attribute name="content">
		<xsl:for-each select="//layout/cp:cpInfo/cp:cpProperty[@name='pdsRole']/child::*">
			<xsl:value-of select="concat(., ',')" />
   		</xsl:for-each>
   	</xsl:attribute>
</meta>

Read the custom meta tag and set a custom variable in Google Analytics

Our implementation of Google Analytics is a little complex, but this example I’ve based on the standard Google Analytics example code.

Using Javascript (infused with jQuery in our case), we can read the custom meta tag and set a custom variable.

<script type="text/javascript">
var gaJsHost = (("https:" == document.location.protocol) ? "https://ssl." : "http://www.");
document.write(unescape("%3Cscript src='" + gaJsHost + "google-analytics.com/ga.js' type='text/javascript'%3E%3C/script%3E"));
</script>
<script type="text/javascript">

	window.onload = function(){
		try
		{
			var pageTracker = _gat._getTracker("UA-XXXXX-XX");

			if (typeof $('meta[name=luminis.role]').attr("content") == 'string')
			{
				pageTracker._setCustomVar(
				     1,                                                // This custom var is set to slot #1 of the 5 available in GA
				     "luminis.role",                                   // The name acts as a kind of category for the user activity
				     ','+$('meta[name=luminis.role]').attr("content"), // The value of the custom variable (starting with a comma)
				     2                                                 // Sets the scope to session-level
				);
			}
			pageTracker._trackPageview();
		}
		catch (err) {}
	}

</script>

According to the documentation, it’s important to set the custom variable before tracking the page view.

Create custom segments to view traffic for specific Luminis roles

Sign in to Google Analytics and view your normal website reports.
Click on Advanced segments | Create a new advanced segment

Create a new segment where…
Custom variable (Value 1) contains ,staff,
AND
Custom variable (Value 1) contains ,faculty,

Note the surrounding commas – we’re using them as role delimiters.

Give the segment a name e.g. “Luminis roles: staff AND faculty”"

All done, but have patience

Your custom segment is now available from the advanced segment drop-down:

Custom variables seem to take longer to filter through to Google Analytics than normal data such as page views. So come back in a couple of days and try out your new advanced segment.

Update (12 April 2010):
Shortly after I published this post, the Google Analytics blog posted their webinar on Google Analytics custom variables.

Also, if you’re interested in creating advanced segments from custom variables, I’ve posted ayoutube video that steps through the process.

I recently started building Confluence plugins. The first one being my Google Analytics plugin for Confluence. This post outlines my “journey” into Confluence plugin development. It documents a beginner’s pitfalls when developing with the Atlassian Plugin SDK. Hopefully others can learn from, or at least laugh at my mistakes.

Where I was starting from:

• No experience of maven
• No understanding of how Confluence plugins work or how they are written
• Some experience of Java – Mainly uPortal/Luminis portal development for the University of Nottingham and some consultancy work e.g. for Astra Zeneca, Documentum and 3Com
• No experience of unit testing or integration testing in Java – oh dear
• I prefer UI work to real programming

Initial failure

I tried to setup a development environment for plugin development using Atlassian’s documentation a little before the beta release of version 3 of the Atlassian Plugin SDK. It was a pain. This was no fault of the documentation — it was really just to do with my schedules and available time to experiment.

The problem was two-fold:

1. I’d not done this before, so was clueless to what was involved
2. The setup was a complete ball-ache considering the time restraints

I was well aware of point 1 and the pain it was likely to cause. Point 2 seemed to be the old chestnut – install and configure the exact correct versions of the software you need in the correct sequence, then start.

Wait. I don’t know what that means, see point 1. Yes, I’ve got maven installed on my MacBook! Woo! Let’s go. Hang on, it’s not the correct version. Where do I get that from?

In many ways, it reminded me of my initial experience of building and installing Apache 1.x on Solaris SPARC boxes back in the day:

cd /path/to/apache/source; make; make install;
Oh. Wrong version of make. Where do I get that from? Hmmm.
Install correct version of make. Damn, make needs the correct version of gcc. Where do I get that from?
And so on. Moving further and further away from the problem you’re trying to solve.

So, I stopped there. No shiny Confluence plugins for me. I’ve got plenty of other things to do anyway thank you very much.

Reboot

Then Atlassian released the Plugin SDK beta and all this nastiness was removed. Everything you need to build an Atlassian plugin was bundled in one place. Refreshing. All commands have been wrapped and so are prefixed with atlas- to prevent conflict with whatever else you’ve got installed.

For the impatient, this really drives down the barriers to entry for plugin development.

Following the documentation for installing the Plugin SDK was a piece of cake. It just worked.

• Download
• Unzip
• Add some environment settings. Edit ~/.profile and add:

  PATH=$PATH:.
  PATH=$PATH:$HOME/
  PATH=$PATH:$HOME/bin
  PATH=$PATH:$HOME/atlassian-plugin-sdk/atlassian-plugin-sdk-3.0-beta3
  PATH=$PATH:$HOME/atlassian-plugin-sdk/atlassian-plugin-sdk-3.0-beta3/bin
  export PATH
  

• Start building a plugin

Starting out to build your Atlassian plugin is documented here. It’s a fairly straightforward set of instructions.

You start by doing something like this:

mkdir ~/projects/davidsimpson.me/
mkdir ~/projects/davidsimpson.me/confluence
cd  ~/projects/davidsimpson.me/confluence

atlas-create-confluence-plugin
...
...
...
When prompted
Define value for groupId: : me.davdsimpson.confluence.plugins
Define value for artifactId: : googleanalytics
Define value for version:  1.0-SNAPSHOT: :
Define value for package:  me.davdsimpson.confluence.plugins: :
Confirm properties configuration:
groupId: me.davdsimpson.confluence.plugins
artifactId: googleanalytics
version: 1.0-SNAPSHOT
package: me.davdsimpson.confluence.plugins

Then type…

cd googleanalytics
atlas-run

…and sit back. If maven doesn’t fall over for lack of memory at this point, you’re laughing. Go away, have a beer or two. This may take some time.

On your return, maven will hopefully have finished dragging all manner of nonsense from Australia and installed a working copy of Confluence, together with an empty plugin onto your computer. Nice. Next, write some code.

I like to run before I can walk. It seems like much more fun to attempt something that’s harder. You do fall over a lot more often though. So rather than some kind of silly little hello world or equivalent plugin, my first plugin was an integration of Google Analytics with Confluence using the Google Analytics API to fetch data from Google. It requires some additional JARs from Google.

Google doesn’t have a public maven repository to my knowledge and I’d no idea how to get these JARs added into maven. Luckily, people had already written about parts of this, so I put 2 and 2 together.

Add Google Analytics JARs to maven:

atlas-mvn install:install-file -DgroupId=com.google.gdata
    -DartifactId=gdata-core
    -Dversion=1.0
    -Dpackaging=jar
    -Dfile=/path/to/gdata-core-1.0.jar
    -DgeneratePom=true

atlas-mvn install:install-file -DgroupId=com.google.gdata
    -DartifactId=gdata-analytics
    -Dversion=2.0
    -Dpackaging=jar
    -Dfile=/path/to/gdata-analytics-2.0.jar
    -DgeneratePom=true

atlas-mvn install:install-file -DgroupId=com.google.collect
    -DartifactId=google-collect
    -Dversion=1.0
    -Dpackaging=jar
    -Dfile=/path/to/google-collect-1.0-rc3.jar

Edit the Project Object Model (POM) to add the dependencies

Edit the pom:

vi ~/projects/davidsimpson.me/confluence/googleanalytics/pom.xml

Add this bit to the end of the dependencies node:

<!-- Add Google Analytics dependencies: -->

       com.google.gdata
       gdata-core
       1.0

       com.google.gdata
       gdata-analytics
       2.0

	com.google.collect
	google-collect
	1.0

Next, fire up your IDE

My chosen IDE is IntelliJ IDEA.

• Open the pom.xml in IntelliJ IDEA (File | Open project)
• Override/set the maven home directory:

  /Users/davidsimpson/atlassian-plugin-sdk-3.0-beta3/apache-maven

• Set the JDK for build as 1.5 or 1.6
• Start editing the plugin

Hiccups

It’s not all straightforward. Here’s some of the annoyances that I came across.

Maven needs more memory

I needed more memory for maven. Not really a problem – append to ~/.profile:

MAVEN_OPTS=-Xmx512m
export MAVEN_OPTS

Annoying warnings on atlas-run

I noticed this on running atlas-run – it probably shouldn’t be there:

[WARNING] Using platform encoding (MacRoman actually) to copy filtered resources, i.e. build is platform dependent!

Of course, someone has already blogged about it — Red Leopard — and it’s easily fixed by editing the POM to add the correct encoding.

3.0.2
    3.0

    <!-- Fix for MacRoman warnings on build -->
    UTF-8
    UTF-8

Now, we have no nasty warnings.

The macro browser icon

I love the Macro Browser in Confluence. It’s a nice step forward in the evolution of the UI. So as a result, I wanted my macro to have a shiny icon in the macro browser. That damn Macro Browser icon ate up several hours of my life. Looking at the comments on the documentation page, several other people have had a whole load of fun getting their pretty icon to show up too.

The macro browser icon: What we

Could I get the Macro Browser to show my plugin’s icon. No. I followed the documentation. It did not work. I looked again. This time I really paid attention. Was it my fat fingers? Was I just being stupid? (Probably.) I ignored this for a while — maybe it would be better after a night’s sleep.

Everything seemed to work a whole lot better when I dropped the beta and moved to version 3.0.2 of the Plugin SDK.
Note: I had to update my ~/.profile to point to the new version of the SDK and update the references to maven in Intelli-J at this point.

I also followed a different tack on getting the macro browser icon to work

• Find a macro that has a custom icon in the macro browser
• Go to the Atlassian public subversion repository and browse to the source for that macro plugin.
• Copy the exact syntax from the atlassian-plugin.xml and paste into your macro’s own atlassian-plugin.xml
• Name the icon exactly the same as in the atlassian-plugin.xml and put it in the correct place in the directory structure

I’m not entirely sure whether it was the copy and paste approach that helped or moving away from the beta. It works now, so I’m not going to loose sleep on why.

Adding a configuring UI to the plugin

My plugin needed to store Google account credentials and display a list of Google Analytics sites, so you can choose the correct profile. How do you do that? Hmmm. Go back to the documentation. It wasn’t nearly detailed enough for my liking, so time to vent a little.

Again, it seemed the best way to learn was to find a plugin that has a similar kind of configuration to that you’re hoping for and start appropriating the code.

Unit testing and integration testing

This is a good idea. Period. Did I have a clue how to do it for Confluence? Of course not.

Again, the community helped out. Atlassian partners at Adaptavist, Comala Technology and Customware have written about this:

• Integration Testing of Confluence Plugins by Bo Wang
• Unit testing a Confluence Action by Edward Robertshaw
• Unit testing a Confluence Macro by Edward Robertshaw
• Confluence plugin integration testing by Roberto Dominguez

Browsing around the Atlassian public subversion repository was also a help. I’ve got to say that I’m an easy convert to testing. It just makes sense.

Update (2010-05-04): A nice feature of the SDK is running or testing your plugin against different versions of the product. This is straightforward:

# Integration tests for different versions
atlas-integration-test -v 3.0
atlas-integration-test -v 3.1
atlas-integration-test -v 3.2
# Run different versions of Confluence
atlas-run -v 3.0
atlas-run -v 3.1
atlas-run -v 3.2

Wrapping up

After a good deal of stumbling around, it turns out that I can write a Confluence plugin after all. Everything started working a lot better after I updated from the beta version, but that could just be coincidence. The documentation could be a little better to help the uninitiated but it was equally my fault for not learning to walk first. There is a lot of good information, but it is spread over a few different spaces.

My next step was to get the plugin added to Atlassian Plugin Exchange. It took a little while to get this done — maybe that’s best saved for a follow up post. The plugin is now available on Atlassian Plugin Exchange. I hope other people get some use out of it.

I’m pleased to announce the release of my first Confluence plugin — Google Analytics plugin for Confluence.

It lists Google Analytics reports for a particular Confluence space – from within that space. The current version has 10 reports and shows the first 20 results for each report.

• Top Content
• Depth of Visit
• Internal Search
• Browser and OS
• Browser Version
• Screen Resolution
• Network
• City
• All Traffic Sources
• Search Engine Keywords

Just before Christmas, Atlassian quietly approved the plugin on their Plugin Exchange website. Since then, Matt Hodges posted a great write up about it on the Atlassian website — Report Confluence Activity Using Google Analytics in the Wiki.

Screencasts and live demonstrations

I’ve done a couple of screencast demos on usage and configuration:

But better than that, it’s now out in the wild and you can try it for yourself on other people’s sites:

• Atlassian have installed it on their Confluence Sandbox
• Arne Schirmacher has posted a live demo on his Confluence site
• Another live demo on my personal Confluence space (using 1.2-SNAPSHOT)

What next?

• Download Google Analytics plugin for Confluence
• Setup Google Analytics on your Confluence site

If you’re using this plugin or have tried it out, I’d really like to know what you think of it.

• What improvements would you like made?
• What reports are missing?
• Where could the UI could be improved?

Please post a comment if you’ve got it installed.

Thanks

I’d like to thank the Confluence community for their help mainly via Atlassian Forums and some Atlassians for helping me out when I got stuck – particularly Shaun Hare, Keith Brophy, Jonathan Nolen and David Peterson.

Image credit: Google Analytics icon

Here’s a quick screencast I made to show how easy it is to add custom segments – e.g. based on country/territory – to Google Analytics. There’s no audio. Sorry.

Adding custom segments to Google Analytics from David Simpson on Vimeo.

Having installed Google Analytics on Confluence, you need to ensure that you’re not lost in a world of pretty metrics.

Make sure that your new analytics toy produces something solid and actionable. Anything less is just a shiny curiosity that your organisation will soon fail to engage with.

This article presents 4 useful tips that really show the power of the analytics data available. Each one can help improve the success of your Confluence installation.

1. Use the Content Drilldown report to segment traffic by site

Want to know which sites are generating the most traffic? The Content Drilldown report is for you. This allows you to view page reads by Site.

The gallery below shows you how to access the correct report – In Google Analytics (GA), click on the highlighted links to get to the next page.

Content Drilldown - Shows pages within the DOC site

Missing Page Views

The Content Drilldown report does not however show everything that happens within the site, but rather only pages that are descendent of /display/DOC/

Examples of missing pages

• Pages with punctuation marks in the title.
  A page with a title of What’s this? would have a URI similar to /pages/viewpage.action?pageId=26181760
  As a workaround, only use alphanumerics and spaces in page titles.
• Page edits.
  A page edit would have a URI similar to /pages/editpage.action?pageId=26181733
• Attachment views.
  These do not call the Google Analytics JavaScript, so are not caught by the tracking code

The first 2 of these are tracked, but not on a site by site basis within the Content Drilldown, so they are a little more difficult to understand.

Each of these could be tracked within the Content Drilldown by using a little jQuery magic to rewrite the URL before it is sent to Google Analytics.

I’ve not done this yet, but it should be fairly simple to change the reported URLs to e.g.

• /display/DOC/What’s This?
• /display/DOC/Test+Page/Edit Page
• /display/DOC/Test+Page/attachment/screenshot.png

2. Enable Site Search & Search Categories in GA

Google Analytics will allow you to categorize site searches. With this option enabled, you can see searches within individual sites.

In GA, go to Analytics Settings > Profile Settings > Edit Profile Information

* Select Do Track Site Search
* Add queryString,searchQuery.queryString to Query Parameter (required):
* Select Yes from Do you use categories for site search?
* Add key,searchQuery.spaceKey,where to Category Parameter:

A screenshot of the Site Search Setting section

Example – Searching for “David Simpson” on Atlassian’s own installation of Confluence

The table below shows the various different situations and query parameters that I’ve used to Categorize the Site Search:

3. Use “Site Search Categories” to show search terms from within individual sites

With site specific search information you can see

• What people are looking for
• Whether they’ve found it

Some screenshots of how to view the Site Specific search terms:

Site Search - List of categories

Site Search Results - DOC category only

This is powerful. If they’re searching and finding stuff – great!

If they’re failing to find the content they desire, then there’s a real problem that needs fixing. The top search terms that return no result should be tackled.

With a little consideration, the user experience can be improved considerably, saving the organisation time and money.

Ask yourself a few questions:

• Why are my visitors searching for search-term-x?
• Is this search term relevent to my site?
  • If so, add the content you the site.
• Is the search term related to different terminology that I’m using?
  • If so, include the various terminologies in pages, so that people with different language styles can find the content
• Should the top result be easier to find?
  • Consider moving the top search term to be visible on the site home page or higher up in the site hierarchy

4. Use the “Site Search Start Pages” report to find out where visitors turn to search

This report exposes the page a visitor is on when they abandon the navigation system in the site and jump to the search box. This could give some insight into what’s missing in your navigation system.

Site Search Start Pages Report

To view the search start pages on a site by site basis, filter this report by using the URI of each site.

Filter by site URI

Ask some more questions…

• Are my visitors browsing or just searching?
  • When I’m on the eBay homepage, I generally just start searching and ignore all the content on the page. Are your visits doing this?
• Do visitors search from particular pages?
  • If so, what are the search terms? Should these be included on, or linked to from these pages?

To Conclude

Using just these 4 simple tips highlights the combined power of Google Analytics and the internal search engine within Confluence. Answering some of the questions posed should provide the insight you need to improve the usability for all your visitors.

These tips are really only the a small part of what analytics has to offer. I’d encourage you to learn more and let me know how you get on.

Further reading/viewing

• Google Analytics Conversion University
• Internal Site Search Analysis and Visitor Intent – video by Avinash Kaushik (@avinashkaushik)
• Search Analytics book by Louis Rosenfeld (@louisrosenfeld) and Marko Hurst
• Web Analytics ToolKit and Internal Search
• Kick Butt With Internal Site Search Analytics – Avinash Kaushik

Please note: We’ve not had GA tracking Confluence for very long, so there are some empty results for the start of the month.
I’ve used Firebug to pretend we’re looking at the analytics reports for Atlassian’s own installation of Confluence

Updated 2011-06-30: Changed to asynchronous Google Analytics tracking
You’ve chosen Confluence as your Enterprise wiki and got it installed. People are using it. But how many people?

You could have a look at the Global Activity page on Confluence, but this might confuse matters.

You’ll get to see graphs, but what do they really mean? The Global Activity statistics are at best very basic.

Better still, install Google Analytics and you’ll have a much more accurate idea of what’s going on. Best of all, it’s really easy to install.

How to install Google Analytics on Confluence

I’m assuming (for my sake) that you already know your way around Google Analytics.

In Google Analytics

Login to Google Analytics and add a new website profile

The settings will roughly mirror those in the screenshot below

Make sure that you check “Do Track Site Search” against Site Search. Add queryString as the Query Parameter. This will allow you to monitor who is searching for what.

Update (2009-11-12)
Edit the Search Settings configuration like in the image to see search terms grouped by spaceKey in the internal search categories reports. Further details why can be seen here

A screenshot of the Site Search Setting section

The top search terms will suggest either content that’s missing from the site, or something that is not easily found in the current information architecture. Either way, tracking this and acting on the findings should improve the user experience.

In Confluence

Login to Confluence as an administrator and add the GA tracking javascript code to the end of the page body…

Navigate to:

Dashboard | Administration | Look and Feel | Custom HTML

Click on the “Edit” button and add the javascript sample (with your tracker code) to the “At end of the HEAD” section:

<script type="text/javascript">
  // See: http://davidsimpson.me/2009/03/18/tracking-atlassian-confluence-usage-with-google-analytics/
  // Put this in Confluence Administration | Look and Feel | Custom HTML -- "At end of the HEAD"

  var _gaq = _gaq || [];
  _gaq.push(['_setAccount', 'UA-XXXX-XX']); // Your GA code here
  _gaq.push(['_trackPageview']);

  // Add a page-level custom variable to record the space-key
  if (typeof jQuery('meta[name=confluence-space-key]').attr("content") == 'string') {
    _gaq.push(['_setCustomVar',
      1,                        // This custom var is set to slot #1 of 5
      'confluence-space-key',   // The name acts as a kind of category for the user activity
      jQuery('meta[name=confluence-space-key]').attr("content"),  // This value of the custom variable
      3                         // Sets the scope to page-level
    ]);
  }

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

</script>

Results

This works nicely, particularly as the custom variable allows us to easily track all space related content separately, and thus facilitate the use of the (Google) Analytics reporting plugin for Confluence.

Screenshot of Content by Title report:

Screenshot of Site Search Terms report:

Related Posts (Updated)

• 4 Useful Tips on Google Analytics Reporting for Confluence
• Announcing: Google Analytics plugin for Confluence
• How to track Confluence usage with Google Analytics by Remo Siegwart

If someone using a desktop Twitter client (such as TweetDeck or Twirl) clicks on a link I’ve posted to my blog, the Google Analytics referer information will be blank. It registers as direct traffic to the website.

This is fine when linking to other people’s websites — I’m not worried about them — but I’d like to know where that traffic to my websites comes from.

I generally shorten URLs with a service like bit.ly (which does provide basic statistics on click throughs). The trouble here is that you still miss the referrer information on your Google Analytics account.

How can we capture that the source of the link was a Twitter post?

The Analytics Talk blog post — Twitter and Google Analytics: What to Track — gives a good solution to this problem.

Put simply, before you shorten the URL, add the following GA campaign request parameters to the end:
?utm_campaign=blog&utm_source=twitter&utm_medium=micro-blog

e.g.
http://example.com/
becomes
http://example.com/?utm_campaign=blog&utm_source=twitter&utm_medium=micro-blog

Now you can track referrers from Twitter clients within Google Analytics using
Traffic Sources | Campaigns. Nice.

Check out Twitter and Google Analytics: What to Track by Justin Cutroni for the details.

Aside: Justin’s Google Analytics Short Cut PDF book ($10 from O’Reilly) is a great read, but it was written in 2007 before the last GA update. I hope Justin gets the time to release an updated version soon.