Segmentation is a technique that is used to help get to more detailed information on your site’s performance, which is done by slicing and dicing your existing data until you get only the information that’s relevant to your cause. A simple example is the conversion rate. You’ve established that your site’s conversion rate is 3%. Great, but that gives you very little information. By using segmentation you can determine the individual conversion rates for separate streams of traffic, which gives you a clearer direction as to which parts of your online marketing efforts need to be stepped up.

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Most of us know how well Google AdWords PPC ads can work for online businesses. With not all too much tweaking you can get targeted traffic to your site at a fairly low cost (depending on the niche you operate in). A lot of businesses know that visitors from certain geographical regions are much more valuable in that they convert more easily and thus result in higher ROI (Bigger Bang for Buck). By being able to invest only in these more valuable visitors you can get much better results from your PPC campaigns.

AdWords offers a feature called Geo targeting, which enables you to have your AdWords ads show up only for people from specific geographical regions, and with the help of Google Analytics you can find out where your best converting visitors live. This post will give you a guide on how you can get the info you need and make the changes in AdWords.

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The latest script version for Google Analytics enables you to track clicks on outbound links. By manually tagging each link to other sites using a javascript function, data on these clicks will be gathered in the content reports.

Before trying out this technique, please be sure you’re using the latest ga.js script and not the legacy urchin.js version of the script. The updated Google Analytics code can be found by editing the targeted website’s profile in the welcome screen and by clicking ‘Check Status’ at the top right corner of your website profile. Both urchin.js as well as ga.js based code is provided here.

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Disclaimer: This post is NOT intended to put large web analytics vendors in bad light and to endorse the use of Google Analytics instead.

In my daily work I rely on one of the larger web analytics solution vendors, which over the past two years has provided me with rich data, custom and on the fly reporting and one the whole things were alright. Until we needed better reporting, which we thought would be relatively easy to get since we chose one of the leaders in the market. Little did we know.

I’ve noticed that over the past couple of years it’s become increasingly difficult to work with these guys. It was already quite a feat to get through implementation, which was almost completely unguided and parts of which had to be corrected later on. Bit by bit we learned more about how the solution works and once we deciphered most of the ingeniously chosen terms used solely by this vendor we started to uncover what went wrong during implementation and we obviously needed to correct these issues to get everything sorted.

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Google Analytics added a few nifty new features in beta recently, which includes the ability to map out multiple metrics in one graph at once. All Google Analytics users should have this functionality enabled already (the new features were introduced on December 13, 2007) so here’s a little appetizer to get you going.

New Google Analytics graphing tools

The new graphing tools enable you to view multiple metrics in one graph and see how they correlate. This enables you to see, for example, how your pay-per-click traffic compares to organic search engine traffic, but also how one conversion goal compares to another in a set date range.

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Whereas many web analytics practitioners let go of page views quite a while ago, some people on the receiving end of online advertising still hold on to it and assign great value to what has become a hollow metric.

There are few standard metrics that have value when considered on their own, but page view is what “hit” still was two years ago – practically redundant but over-used. A page view itself is not a proper measure for traffic volume and is merely a secondary metric that adds dimension to unique visitors. Examples are the use of newer standardized metrics, which set out page views vs visits to create “bounce (or exit) rate” and “pages per visit” – two metrics both used by Google Analytics (amongst other providers of web analytics solutions) that provide much more meaning to analytics efforts.

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The use of Goals comes forward from the main motivator behind web analytics for most of us: Analyzing and optimizing how many people are doing what we want them to do and (perhaps more importantly) why others don’t.

In its simplest form, a Goal is a page marker that can be set in Google Analytics, which tells you the amount of times a certain page is reached and its most common use is recording product purchases or registration completions.  Without tracking Goals, trying to get more business in and out of your website would be like driving blind. There’d be no way of telling what performance is today, nor what it will be tomorrow so it’s impossible to know which of your online marketing efforts are paying off and which aren’t.

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Using filters is a basic tool that can help you ignore data that is of no use to you, or that will cause inaccuracies in your data. It’s important that before you start working with filters you know which reports and which data matter to you or your organization, so as to avoid future complications or worse: gaps in your data.

Another tool that helps you organize your data better is segmentation.

Available filters in Google Analytics

Google Analytics provides a powerful set of filters which can easily be set through the Account Settings dashboard. By clicking the option Filter Manager, at the bottom of the Website Profiles table, you’ll be able to access the Filters dashboard. The top right hand option Add Filter allows you to create new filters, based on the following pre-set options:

• Exclude all clicks from a domain: Using this filter you can exclude tracking of visitors to your site that come from specific referring sites
• Exclude all clicks from an IP address: This filter option will allow you to filter out any visits made to your site from a specific IP address or IP range
• Include only traffic from a specific subdirectory: This filter is particularly handy when creating separate website profiles to track certain parts of sites, based on subdirectories in your site’s page structure
• Custom filter

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Access Management is another option you’ll find in most web analytics tools. It’s the ability to enable others (colleagues, manager, administrator or simply partner) to look into and control (optional) Google Analytics reports.

Sharing a single account might not be something one would naturally do and it might be something that makes many people nervous (accidental changes or mistakes made by others can be extremely frustrating), but thankfully the GA Access Manager lets you control who has access and to what degree they can manipulate settings.

Something to be careful with is user access when you track multiple websites within the same account. Should you enable other users to access your account with administrator privileges, they will be able to view reports for your other sites as well. Should you want to avoid other users from seeing reports for sites that they do not need to look into you can choose to grant access only to a single website profile (rather than providing them with access to the whole account), but only for “Read only” users, not administrator enabled users. This can be done within the Access Manager, but also by editing Website Profile settings.

You can find the Access Manager option at the bottom of the Analytics Settings page, and this will take you to the Access Management settings dashboard. Here you can add users and manage user access.

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In order to use advanced settings for Google Analytics, log in to your account and you’ll land on the settings dashboard straight away.

Website Profiles

GA offers the option to track multiple websites within the same account, which is a handy feature that most web analytics tools offer these days. Besides completely separate sites, you can create profiles to track subdomains or parts of a single website separately. On the settings dashboard you’ll notice a table of Website profiles, which gives you an overview of sites currently tracked and their tracking status.

Adding a profile

1. In the Website Profiles table, click Website Profile
2. An information page appears, which offers you the option to add a profile for a new domain or an existing domain (in case you’d like to track part of one of your sites or a subdomain).
3. In case you’re adding a profile for a new domain, select whether the site is an HTTP or HTTPS site, provide the website URL which you’d like to track and select your country from the drop-down list, and click Continue. In case you’d like to add a profile for an existing domain, select the domain in question, enter a new profile name, select your country from the drop-down list, and click Finish.
4. If you’re creating a profile for a new domain, the Tracking Status screen will show up, providing you with the script you’ll need to place on all pages of your sites (or in your site’s templates).

Once you’ve added the code to your website, Google Analytics will change the tracking status of the new profile to Pending and to Receiving Data when enough data has been gathered to start reporting. Keep in mind, however, that to make sense of your reporting data you’ll need at least a couple of months’ worth of data!
So why would you set up separate profiles for parts/subdomains of your sites? The main benefit is that you can adjust specific settings for each part. This can be particularly handy in case you’d like to use customized segmentation more than once on the same site. (Customized segmentation can generally be used for one specific purpose in Google Analytics.)

Should conversion paths go through other parts/subdomains, you can adjust the Google Analytics code and track a single page in multiple accounts.

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