Google Analytics is a fantastic tool from the moment you arrange to have the tracking code installed and you experience the thrill or anxst of your first reports appearing showing how real people are interacting with your business.
Every business now needs a Google Analytics customisation strategy
You can certainly get a lot of value from reporting and analysis using the standard setup, but to really drive results for your business, you're better off spending some time on customisation.
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With each passing month there are more customisation options available in Google Analytics, so I believe you really need a strategy of what to customise, particularly if there are several team members using the account. This post gives my ideas on a customisation strategy based on consulting work I have done and typical usage of Google Analytics by attendees on Econsultancy training Site Optimization with Google Analytics - the length of the post shows that there are lots of customisation options available.
I've published it as the pre-read for marketers attending the training course and hope it's useful for others who pass this way. I plan to update it as the need for new customisations appear.
If you're on my next course, "Hi and I look forward to meeting". Don't worry if you don't have time to go through all the links(!), it's just intended to give you a flavour of some of the main concepts we cover so you can 'hit the ground running'. It will also provide a reference after the course.
We'll cover each of these concepts on the course, but we spend most time on using analysis of reports to get better results rather than configuration and setup - that's what I find interests people most!
Customisation options for Google Analytics
From several years experience of using GA, I recommend reviewing these six types of setup or configuration for Google Analytics to customise the reports you view. Some may need some tech assistance, but most can be completed by any business user, if you know where to look!
A recently published companion to this post is Brian Clifton's Book Advanced Web Metrics with Google Analytics which explains how to implement the setup in more detail than possible here
So, from easiest to hardest, the six customisation options are:
1. Working with reports in a smarter way
2. Segmenting your audience by setting up advanced segments
3. Creating custom reports and dashboards within Google Analytics
4. Setting up marketing campaign tracking
5. Modifying profile setup within "Google Analytics Settings"
6. Customisations that require server modifications
Resources for finding out more about Google Analytics customisation
Most Google Analytics users will have used the Google Analytics Help System which is functional, but I find that many don't know about the excellent "Google Conversion University" which as the name suggests is a much better way to learn.
The Google Conversion University is designed to help analytics specialists take the Google Analytics Individual Qualification. I worked my way through the GAIQ back in September 2009 and I can recommend it if analytics is a big part of what you do. But even if they're not, I can recommend some of these lessons as a great way to learn about Google Analytics. I've highlighted the most useful ones here. Here's an example:
I've also linked to relevant posts within Avinash Kaushik's Occam's Razor blog. Avinash is analytics evangelist for Google and thinks deeply about how GA can be best applied to benefit businesses. As well as his recommendations, suggestions of other users about customisations make this an excellent place to learn.
There will naturally be future updates as Google enhances it's Analytics services. To help here, I've created a Google Analytics update wiki where I add a short note on the latest, most significant, changes as they happen.
1. Working with reports in a smarter way
The most basic customisation you can do is to change the way default reports are displayed. For example, changing or comparing time periods or variables or the number of results displayed. Most readers will be doing this already because the system is intuitive and you have to use it for basic analysis.
But it's worth checking out this lesson on Interface Navigation in the Conversion University since it also shows how to compare different metrics to review correlation and how to do a quick segmentation within a report to drill down to the detail.
There are also some newer features in Google Analytics to help with report analysis which aren't included yet in the Conversion University, so here's the low-down on these:
Google Analytics Intelligence
What is it?
The Intelligence feature of Google Analytics currently gives you automated or custom alerts of changes in visitors from different sources like an individual country, search engine or another site.
Ideal for overlaying a reminder of the start of new marketing activities to jog your memory or to share with colleagues. Annotations are overlaid on the graph on each report. For instance, you can show new campaigns, new content or new publicity and relate it to changes in traffic or conversion.
- Read more about Annotations (GA Blog).
2. Setting up advanced segments
Using Advanced segments is one of the most powerful features of Google Analytics which is used routinely by analytics ninjas. But when training, I find that many marketers haven't tried clicking the magic "Advanced Segments" button you will see at the top of right of the Google Analytics screens or in the section on the left.
Using Advanced Segments is essential if you want to find how different groups of visitors behave and then work out how well your content, messaging, offers and navigation is appealing to them.
The most useful standard segments to apply are:
- Paid and natural search traffic
- First time visitors or returning visitors
I'll write more about custom segments in a later post, but for me, the most useful are:
- Visits from brand and non-brand searches
- Visits from social media
- Visits from key markets or country
- Visits involving different conversion types
- Engaged visits, etc
Read more Advanced segments:
- Advanced Segment lesson from Conversion University
- Advanced segments from Google Analytics help
- Introduction to Advanced Segments from Avinash Kaushik
3. Creating dashboards and custom reports within Google Analytics
When you first log-in to Google Analytics, you start with the dashboard screen for your selected profile. This is arguably less easy to configure than dashboards in other analytics systems. You can move, add or subtract reports. You add additional standard report widgets through using the "Add to Dashboard" option.
With the addition of custom reports, these can now also be incorporated in the dashboard through clicking the "Add to Dashboard option" button at the top of the screen.
Motion charts can be customsied in reports where the "€œVisualisation"€ option is available at the top of the screen.
Tip: Add additional standard or custom reports to your dashboard and then add then schedule a daily, weekly or monthly email.
Read more on custom reports:
- Quick Start Guide to Custom Reports from Google Analytics Help
- Avinash Kaushik ideas on custom reports
Read more about Bubble charts and motion charts
4. Setting up marketing campaign tracking
These changes are different to the other setup changes mentioned in this post in that changes aren"€™t made within Google Analytics, rather they are made through Google AdWords or when placing advertising or sponsorship on third-party sites.
Many companies will track AdWords because of it's automated integration enabled from Google AdWords, but they may not track other codes or have a standard notation which needs to be defined and then added to all links involving media placements.
Google Analytics uses 5 standard dimensions for a campaign which need to be incorporated into the query string of the URL for each ad placement as this example shows:
The campaigns report in Google Analytics will then enable you to compare media.
The table explains each of these 5 dimensions which refers to this example:
|The name of the marketing campaign, e.g. Spring Campaign.|
|Media channel (i.e. email, banner, CPC, etc).
What is the 'distribution method' that is used to get our message out to our clients?
|Who are you partnering with to push your message. A publisher such as handbag.com, or for paid search, Google, Yahoo, Live Search, etc|
|The version of the ad (used for A/B testing) or in AdWords. You can identify two versions of the same ad using this variable. This is not always used and is NOT included in the above example.|
|The search term purchased (if the link refers to keywords).
This is not always used and is NOT included in the above example.
The Google URL builder can help with creating these links.
Note that in the major Fall 2008 upgrade to Google Analytics, Advanced segmentation provides some standard source codes for campaign types such as paid search.
Tip: Defining a standard set of online marketing source codes is essential to determining the value of different referral sources such as ad campaigns or email campaigns.
Tracking offline campaign referrals
Many companies will reference promotional URLs or so-called vanity URLs (we hate that term) in offline Print ad, Direct Mail and TV campaigns to make it easy for the customers to fulfil the offer.
Of course, they also want to track the effectiveness of different promotions.
Best practice in such offline or multichannel tracking has been explained well by Avinash in his post: Multichannel Analytics: Tracking Online Impact Of Offline Campaigns.
The core technique is to use a 301 redirect which appends a campaign code. He gives the example of http://www.dell.com/tv which redirects and appends a (non Google Analytics) tracking code referencing TV:
As with digital campaign tracking, offline campaign tracking should use standard codes for medium, source and campaign name.
5. Modifying profile setup within "Google Analytics Settings".
The Google Analytics settings section is more likely to be used by analytics specialists who have experience of previous setup, but some of the changes are quite straightforward. We we will cover the 4 main types of settings changes most businesses will need to make:
A. Setting up conversion goals.
Visitors to a site do not have equal value to a company, they engage to different degrees as indicated by the types of pages they visit.
A visitor who has visited a product page, registered for an e-newsletter, bought a product or visited the contact page is clearly more engaged - in web analytics we call these "value events".
Tip: Setting up value goals to report $Index Value and Goal Value per Visit
This is another really powerful option I find isn't used much eventhough you can apply it to the many non-Ecommerce sites (this post by Brian Clifton author of Advanced Web Metrics with Google Analytics explains how. But the approach of assigning value to goals is incredibly useful since you can compare how successful different pages, referrers and journeys are in influencing conversion goals and generating value.
In Ecommerce sites, value from sales transactions are used to automatically populate $Index values and you can also report on Revenue per Visit.
Even for non-transactional sites, you should set a nominal value on each value event such as a newsletter signup or lead-generation form since you can then see which traffic sources or pages influence success.
Many non-transactional sites which use the web for brand or relationship-building struggle to identify relevant goals beyond email signups or leads. With engagement goals you can now set thresholds for time on site and number of pages viewed.
The Breeze Learning example has been updated for the October 2009 introduction of site engagement goals which are here called Threshold Goals: http://services.google.com/analytics/breeze/en/goals/index.html
Arguably the best use for this is to exclude visitors who are not engaged at all i.e. poor quality traffic which isn't well targeted. I suggest greater than 10 seconds and greater than one or two pages per visit.
Avinash Kaushik has a great post on the rationale and examples of conversion goals.
B. Setting up conversion funnels
Funnels representing the different steps in a checkout process are an essential piece of configuration for retailers. After these have been setup up you can then visualise the drop-off or attrition at each stage. But you can set up funnels for most types of site.
Tip: Setup Higher-level conversion funnels. They can also be setup for sites showing how many people engage with different parts of the site such as browsing or searching for products, viewing product content which then contribute to a lead or a sale.
C. Setting up on-site search
On site search is not setup as often as you would expect in my experience, but is usually easy - you simply specify the search parameter which is a text string used to tell the search engine what the query term is. For example, my sites use the Google custom search engine which like Google.com uses the search parameter 'q'.
Analysing the volume and types of searches completed by site visitors can pay dividends to find the type of content visitors are looking for and whether they can actually find it or leave the site frustrated!
These types of insights are available:
If you are using a Google appliance for search or Google custom search for providing on-site search configuration is straightforward. But other search engines can be integrated through specifying the query string parameters to Google Analytics.
D. Setting up Filters and profiles
The granularity with which you collect and report data should be consistent with the way the organisation is structured since different people in the organisation will likely NOT want to review the results for the entire site, but instead you will want to separate out data for part of the company or a particular product, service or audience they are responsible for. Common options which you should consider to report separately on include:
- Distinct domains - Many larger companies will use different domains for different services or audiences, for example using a different Country code top-level domain (ccTLD) such as .nl or .de as well as .com or .co.uk.
- Sub-domains - For example, you may have a blog on a subdomain, for example fashion retailer ASOS has http://blog.asos.com.
- Sub-folders - Alternately you may want to report separately on content in a subfolder, for example if your blog is configured this way,http://www.domain.com/blog.
To report separately on domains, sub-domains or sub-folders you need to apply the concepts of profiles and filters within Google Analytics. You may even want to have different accounts with different unique tracking codes for different countries, particularly if they operate as separate entities and you want to apply different currency and time zones to the report. Each account will use a different unique tracking code, but you will need to remember to include an aggregrate tracking code to report all the sites together.
A Google Analytics profile will typically be used to produce reports for different sites , subdomains or subfolders. Google Analytics Help on Profiles.
So, on my site I have a master profile that is unmodified for the entire site other than a filter for excluding my IP address together with other profiles for particular types of content such as blog content or visitor segments such as returning visitors. You should specify your default page for the profile, e.g. index.html.
A Google Analytics filter is applied to modify data from a particular profile so that it shows a subset of data within the profile. A filter will often be used to show visitor interactions with product information stored in a sub-domain or subfolder. Google Analytics Help on Filters.
In this example I have a filter which is applied to my Right Touching blog which only includes visitors who go to that sub-folder.
For example, a filter could restrict results to first time time visitors or returning visitors. With the Advanced Segmentation feature in Google Analytics you are effectively provided with several default filters, such as all visitors from
So you can see this is complex! You need to get this right from the outset of collecting data since profiles and filters cannot be applied retrospectively, applying filters incorrectly will introduece errors and introducing new profiles will lead to employee confusion.
- Google Help on Domains and Sub-domains
- Google help on tracking across/links between separate domains
Excluding employees from report.
This configuration is relatively simple! You don't want visitors from a company skewing the results, so these should be excluded unless you want to artificially boost your visitor numbers and have difficultly understanding visitor behaviour.
A filter should be created to exclude a range of IP addresses for company employees and contractors working in different offices.
Alternatively, if staff have a range of IP addressses or dynamic IP addresses then using the _setVar function call on a page used by staff only (e.g. Intranet home page) to update a cookie to filter staff out. Both strategies are explained below:
6. Customisations that require server modifications
There are 5 main types of customisation that may be required which involve changes to the tracking code that will need to be configured or coded within the content management or Ecommerce system.
A. Ecommerce Tracking
E-retailers will need to enable E-commerce tracking for their Profiles since this isn't enabled by default. Ticking the tick-box will be straightforward.
The reports summarising E-commerce transactions and revenue within require inclusion of additional tracking code on the checkout completion page specifying order and product information.
Including the transaction information about the order and product(s) will be less straightforward, but many popular E-commerce systems will support this.
pageTracker._addTrans( "1234", // Order ID "Mountain View", // Affiliation "11.99", // Total "1.29", // Tax "5", // Shipping "San Jose", // City "California", // State "USA" // Country);
pageTracker._addItem( "1234", // Order ID "DD44", // SKU "T-Shirt", // Product Name "Green Medium", // Category "11.99", // Price "1" // Quantity ); pageTracker._trackTrans();
B. Event Tracking
In Google Analytics, Events apply to interactions with content made by visitors, so if they are setup, they are found within the Content reports section of Google Analytics.
Event tracking allows you to track additional types of events other than page views. The most important are:
- Video or rich media interactions
- PDF downloads or emails from mailto: links on pages
- Outbound or external links.
Usually an additional script is required for tracking downloads and outbound links. This was originally implemented through generating additional or "virtual" page views, but care has to be taken that these don't contribute to the overall event title.
This is a good example of a link/downloading tracking script:
For video tracking an additional script isn't required, see Google announcement of final rollout of Event tracking June 2009:
- http://analytics.blogspot.com/2009/06/event-tracking-now-available-in-all.html and this technical description from Google code: http://code.google.com/apis/analytics/docs/tracking/eventTrackerGuide.html
This shows that Event Tracking can be specified with these parameters to the _trackEvent() method values of which then appear in the Analytics Reports interface under content:
- implicit count
This is an example from Google help:
- <a href="#" onClick="pageTracker._trackEvent('Videos', 'Play', 'Baby\'s First Birthday');">Play</a>
In this scenario, the reports for Events would display Videos as the Category, Play as the Action, and Baby's First Birthday as the Label. The rest of this document describes these components in detail. Bear in mind that when you implement Event Tracking, you can use this data model as a guide, or you can simply use the _trackEvent() method to segment user interaction in any way that works for your data.
C. Custom variables for visitor segmentation.
Custom variables apply to Visitors, so they are found within the Visitor reports section if specified.
Custom variables were originally specified through a call to _setVar, but are set through _setCustomVar. They are most often used for defining specific segments based on the profile detail identified through a form or consuming particular content.
Options for setting custom variables including:
- Customer vs non-customer
- Different customer segment (or demographic profile variables like male or female). For example, Econsultancy has Bronze, Silver, Gold and Platinum member segments
- Segmenting visitors according to landing page
- Recording referral source attribution
- Categorising different content types
Read more: http://code.google.com/apis/analytics/docs/tracking/gaTrackingCustomVariables.html - this example shows how different content groups can be reported on through the example of an online newspaper and explains the difference between Visitor, Session and Page based custom-segments.