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Advanced Web Analytics Using Google Analytics December 15, 2009

Posted by Joe Kamenar in web analytics.
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In the past, Google Analytics was seen as simply a quick “DIY” analytics tool that gave some useful reports. All you did was just add some code to each page, include a JavaScript file on your site, and you were finished. The tool costs nothing to use as far as license fees, and the learning curve was simple. However, no “real company” would use Google Analytics (GA), as it did not provide any real insight that would let management make any data-based decisions. Most mid to large size companies would use enterprise-level tools, such as Omniture’s Site Catalyst, WebTrends, CoreMetrics, or other subscription-based tools. However, the cost of using these tools can add up to some serious coin, making it hard to justify an ROI on the results you would get.

In the past year, GA has narrowed the gap in functionality between its older versions and paid services like Omniture and WebTrends. Now, more and more larger internet retailers and service providers are using Google Analytics, including Garmin.com, RitzCamera.com, FatBrainToys.com, several BCBS websites, UnitedRentals.com and many more. So, what kind of enterprise-level features does Google Analytics now provide that have caused companies to take a second look? In this article, I will show you some of the features that you can now get with Google Analytics.

Multiple Profiles

Within GA, you can set up multiple profiles for an account, and apply specific filtering to each profile to create specific views of visitor behavior. For example, you can have a profile that is only for paid search traffic, or for events, or for segments of the site that are for specific departments. It is recommended that you keep one unfiltered profile, to retain all non-filtered data, as once you filter the data, you can’t go back to the raw data. Specific filters can be done to create profiles that are for content groups, paid search, internal traffic, and so on. Within the unfiltered profile, advanced segmenting can be performed on historical data to drill down on specific types of visits or visitor behavior.

Conversion Funnels

A conversion funnel is simply the desired path you want a visitor to take to become either a customer, a lead, a registration, or whatever other goal you have in mind. It is a list of pages that represent the start of the path to the end. Within each stage, you can see what percent of visitors made it to the next step, and what percentage left the “funnel”. In the past, GA limited you to just 4 goal conversion funnels across your site. Now, you can have up to 5 goals in each of up to 4 profiles, for a total of 20 goals to analyze. Conversion funnels can help you pinpoint where your site is not delivering, as far as meeting your company goals.

Event Tracking

GA can now do event tracking, similar to SiteCatalyst. It is done a bit differently, but you can assign an event to any activity broken down to a category, action, label and value to any site interaction. An event can be used to track how videos and Flash objects are used on your site. You can see how many times an item is viewed, how far they get through it, and if your desired message is being viewed. Using events, you can see how specific actions impact conversions on your site. On a per-visit basis, a total of about 500 page views and event calls can be sent to GA by a visitor. Once you have these events captured, you can then segment on these events to look at things like conversion rate. For example, you can tag a “Get Quote” button, and then see what percent of those who clicked this button converted.  If you have a retail site, you can tag a “shipping cost” link, and then see what percentage of those who go to this link make the purchase. When used properly, events  can let you capture more than just page views and visits. It can truly let you see how visitors are using your site. Google is looking at creating event-based goal conversion funnels as well as page-based funnels. With an event-based funnel, you can track visitor actions to see how they get to your end goal. Just by using the event tracking properly on a site, you can now get more granular insight into visitor behavior.

There is no limit to the number of events as they are not assigned to a particular variable as in Omniture.. The total number of calls to GA on a per-visit basis is about 500. Also, with the event tracking, it gives you a total count of each item, and a unique, per-visit count.

As an example, suppose you run a truck rental site. You want to track specific events. The event tag looks like this:

_trackEvent (category, action, optional_label, optional_value)

Thinking along the lines of rental activities, you can set up the tagging like this:

  • Category: Itinerary, Pick-Up Location, Drop-Off Location, Contact Info, Trucks and Options, Quote and Payment, Review
  • Action: Get Quote, Search Pickup Locations, Search Dropoff Locations, Select Pickup Location, Select Dropoff Location, Add to Quote, Change Quote, Enter Payment Info

The label and value are optional. For the label field, if you are tracking Flash videos, you would do something like this:

  • Category – video
  • Action – press play (or reached a certain percentage of the file, or any other embedded action)
  • Label – [title of video]
  • Value – time to load, perceived dollar value, quality points, etc…)

When you think about the event method, you can use the optional label field to store something about the visitor as well. If you were to store a unique ID for the visitor, or segment type (see below), you can then do a query on the label field to see what actions were taken by a particular visitor or segment.


Segmenting is a powerful tool that lets you see how specific audiences act on your site. We often talk about analytics in terms of averages – average time on site, average pages per visit, average revenue per sale, and so on, but in reality, there is no “average” visitor. They can be segmented into specific groups, and the behavior of each group analyzed to gain insight into how they can be better served. Segments can be based on visitor type (new vs. return), visit method (direct, paid search, organic search, referral), key words (branded, unbranded), and even a custom defined segment (more on that later). Within each segment, you can apply filtering to extract visits that meet you desired criteria. Filtering an include queries like matches exactly, does not match exactly, contains, does not contain, starts with, ends with, equals, greater than, less than, and others.

GA also lets you set up a custom segment variable, and then set it as you wish. Suppose you have a health insurance site that caters to various audiences, such as non-registered users, subscribers, brokers, employers, providers (doctors and hospitals), and employees. Depending on how they identify themselves as in logging in, which type of login they use, and so on, you can segment these individuals into their respective groups. You can then see how users in the particular segments behave on your site, and to see if your site is meeting the desired goals.

You can also do your conversion analysis or other analysis based on the values stored in each segment. The user defined segment cookie lasts two years, and can be overwritten on subsequent visits. The biggest problem that I see with this variable is that it is read at the beginning of the session, and any changes that are made during the visit are not used until the visitor later returns to the site. Thus, if someone comes to the site an anonymous, then later registers, any activity will be attributed to the anonymous segment. Only when the visitor returns does this change to “logged in” or “member”. Thus, the next time the visitor returns, he or she is tagged as a “member” or “logged in”, even if they do not log in on the next visit. Thus, while having this user-defined segment can be useful, it can also give misleading segment information.

Google is planning on expanding the number of user-defined variables shortly. Right now, if you want to store multiple types of data, you would create a string that can be parsed or joined in JavaScript, then store the entire string in the user-variable cookie. To access the data, in the profile you would then create a custom segment that extracts out the portion of the string that contains the section of interest. You can then correlate that with other items in the string to create a more narrow segment. I have seen some JavaScript code available that creates mini-functions that either add an item to the string or remove an item from the string.

Essentially, you can store anything in this variable, including a login ID. Google, of course, prohibits storing any personally identifiable information, and this includes things like an email address, SSN, full name, drivers license number, address, phone number, credit card number, etc…

Google now gives you 5 custom variables that you can use to do segmenting and analysis. Within each variable, you can store data that is either permanent, session-based or page based. With each variable, you can set a name-value pair that lets you create a segment that can be visitor-based, visit-based (expires after 30 minutes or when a browser closes or visitor exits the site), or page-based, such as defining content groups for each page. This new feature give you much more power to create reports that have meaning.

Traffic Sources

One of the most misleading stats I see in web analytics is in the organic search area. Often, the top search terms are the website’s URL. If you know the URL, why search for it? The answer is in the sneaky way that browsers’ home pages are loaded. If you have Internet Explorer and your default start-up page is MSN.com, the curser drops right into the search field. On FireFox, often the default load page is the Google page. Instead of moving the curser to the URL bar, many users simply type the name of the site they wish to go to in the search box, then they click on the top result, which is the site’s home page. If the top result is also a “paid search” link, and the visitor click on it, the search engine makes money, as do the browser folks. Thus, the organic or paid search results can get skewed.

To keep your stats in line, GA lets  you change the traffic source from “search engine” to “direct” or “referral site” to “direct” by adding some lines of code to the GA code that goes on your pages. Thus, those who come to your site by entering the URL in the search field will not be classified as search visits.

Custom Reports

GA also lets you create custom reports, where you can select your dimensions and drag it to the report, then select which metrics you want to show for that dimension.  With the dimension section, you can add sub-dimensions to the list, such as “Keywords -> Search Engines -> etc…”. You can then add a series of metrics to the report, letting you drill-down on each dimension to get more refined data. This feature is seen in the paid analytics tools, and lets an experienced analyst create multiple views of visitor behavior.

Search Filtering

Within searches, such as keywords, instead of getting a massive list, you can apply filtering, to only look at keywords or other items (like page views) based on a metric range.  You can “nest” conditions to include or exclude specific terms or metrics to generate a more refined search.

Motion Charts

A new feature titled “Motion Charts” lets you create a 4-dimension view of specific metrics, such as keywords. It lets you assign x and y axis values, then show additional metrics in the form of the size and color of a dot. You can place the chart in motion to show how the performance of any keyword changed over time. You can see the dots move up and down or left and right across your grid to see changes in two of the dimensions, along with seeing the size and the color of the dots change to see changes in the other two dimensions.

Internal Site Search

Internal site search is a very useful tool that lets you see how easy it is for visitors to find what they want on your site. It is important to see what visitors do when they find or do not find what they are looking for.  Internal site search can also be tracked to show additional metrics, such as average pages per visit, time on the site and conversions for those who find site results and those who do not.


The API tool lets you export out a complete report, based on specific queries that you make. The GA API tool seems fairly robust, as you can send URL based queries via the API and receive an XML file in return. There are a variety of third-party tools that have already been developed using the API that integrate GA data with Excel data and display it within PowerPoint, desktop applications, email marketing platforms, and mobile platforms.


GA also provides analytics alerts that notify you when specific thresholds change, similar to the alerts that the paid tools provide. If your conversion rate drops below a specific threshold, or the number of orders you get exceeds a threshold, you can be notified right away, instead of waiting until you or your analyst does the report.


Google Analytics collect two types of e-commerce data: transaction data and item data. Transaction data describes the overall transaction (transaction ID, total sale, tax, shipping, etc.) while item data describes the items purchased in the transaction (sku, description, category, etc.). Here’s a complete list of the data:

Transaction Data

  • Transaction ID: your internal transaction ID [required]
  • Affiliate or store name
  • Total
  • Tax
  • Shipping
  • City
  • State or region
  • Country

Item Data

  • Transaction ID: same as in transaction data [required]
  • SKU
  • Product name
  • Product category or product variation
  • Unit price [required]
  • Quantity [required]

When the e-commerce reports are enabled, you get additional reports, such as number of visits until purchase and the time to purchase. The Visits to Purchase (VTP) report shows how many visits a visitor generated before they converted. The Time to Purchase (TTP) report shows how many days it took from the first visit to make a purchase. If the TTP is “0”, it means it was on the same day, but not necessarily on the first visit.

For lead-generation sites that are NOT e-commerce sites, the e-commerce code can still be used to apply segmenting information and value information to leads or registrations that are submitted. By doing this, the e-commerce functionality can be enabled, letting the user see the VTP and TTP for a visitor who submits a lead or completes a registration form.

Third Party Integration

While Google supports its own A/B test tool, Google Website Optimizer, it does not integrate with third party tools from other vendors. Such tools can provide more advanced testing and behavioral targeting tools, email clients, multi-platform PPC management and so on.


Google Analytics can provide small to mid-size companies with the tools they need to create an actionable analytics plan and increase the value of the website. However, just like using paid tools such as Omniture, WebTrends or other more advanced packages, the tool is only as good as the mechanic who uses it. Companies like Edgewater Technology can help you develop a road map that looks at your company’s goals and creates an analytics strategy that helps you meet these goals. Edgewater can help you define key business metrics, create profiles and reports, define tagging specifications, tag your site, set up site optimization using the Google Website Optimizer, and train your team how to use these reports and continue to enhance your site.

With all the new tagging capabilities within Google Analytics, there is a fair amount of analytics enhancement can be done for those who are using this free tool. It can be a lot more involved than just placing the GA code on each page and the ga.js file on your site. By creating the right tagging specifications based on business strategy, Edgewater can help you get a better look at how visitors are using your site, and how you can better serve them.

To learn more, visit http://Edgewater.com or contact Joe Kamenar, Manager of Web Analytics, at 215-480-2737.



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