Using The Wrong Tracking Code Can Cost You $500k a Year

This is a guest post from Tom Critchlow who is an excel ninja, data geek, analytics nerd and head of search for Distilled, a London & Seattle based search agency. Tom provides a cautionary tale on the importance of keeping your site up to date.

This blog post title may appear sensational but I assure you that it's not (much...). I recently spotted an issue with a client's e-commerce website which was costing them £100,000 / month in revenue (~$150,000). The fix took 5 minutes. Even more surprisingly, since I've been on the lookout for this issue I've spotted it on quite a significant number of websites. Hence why I got in touch with the Google guys and asked if I could talk about this in front of as many people as possible to try and spread awareness!

1) Graph of Win

Firstly, let's take a quick look at a pretty graph. This is comparing revenue month on month before and after the fix was made:

Note the increased revenue! :-) Everyone loves increased revenue. For those with beady eyes you will have spotted that this isn't total revenue on the site but it's just IE8 users. What's going on here?

2) The Issue

Before I delve into the issue, let me first give you a little background. When you enter private information online, such as your credit card details, you want to be sure that you're transmitting the information over a secure connection. You can usually tell you're on a secure connection to a website if the page URL begins with https:// instead of http://

Making webpages secure, however, is more resource intensive and so most websites only make their most important pages secure (though Gmail now always uses https:// by default). This means that when you browse a website, for example http://www.amazon.com you will browse around product pages which are all located on http:// URLs. When you want to actually purchase something from the site however you transition over to secure URLs such as https://www.amazon.co.uk/gp/cart/view.html

This is standard practice for e-commerce websites and when you move through the buying funnel you should inevitably transition at some point from a non-secure page (http://) to a secure page (https://).

Now, the issue I'm talking about in this post is with the client's site. The site uses Google Analytics however unfortunately they were using the old version of the code and were using the same piece of code across all pages of their site. The code they were using looked a little like this:

Unfortunately, this means that their secure checkout pages such as https://www.example.com/checkout/payment contained non-secure elements - namely the URL call to "http://www.google-analytics.com/urchin.js". Browsers like Chrome and Firefox don't display a warning but Internet Explorer 8 produced the following security warning when users transitioned from the non-secure (http://) pages to the secure (https://) pages. This error looks like this:

Pretty scary huh! Unsurprisingly this was causing almost all users browsing in Internet Explorer 8 to abandon the shopping process. Since Internet Explorer 8 is one of the most popular browsers on the web this was a huge amount of revenue they were missing out on!

3) How To Fix It

This issue arose because of a non-secure HTTP call within a very old version of the Google Analytics tracking code. The fix for this is very simple - just install the new code! The new code is more versatile than the old code and works both on http:// pages and https:// pages so you don't need to worry about using a different code on secure and non-secure pages. The new code looks a little like this:

There's a complete run-through here on using this new code here and specific migration advice.

And that's it! It's a simple fix but one that can have significant impact on your bottom line. I repeat what I said at the top of the post - I've seen plenty of sites that suffer from this issue so it's really not as rare as you might think!

I should point out here that the Google Analytics code has been able to handle HTTPS and HTTP pages properly since well before the asynchronous code was released, but plenty of sites are still using very old legacy code, which is why this is still an issue for some sites. Also, it's not just the Google Analytics code which can cause problems! Any non-secure elements on a page can cause a security warning so double check your code carefully.

4) How to Diagnose This Issue (simple)

If you're wondering if your site suffers from this problem there's a quite easy way of checking by looking at your conversion rate segmented by browser:

Setting up these custom segments is really easy, but to make it even easier I've set them up for you and all you need to do is click these links to add both these segments directly into your Google Analytics account:

Internet Explorer 8 Users

Non-Internet Explorer 8 Users

Then browse to your conversion rate report and select the segments from your custom segments:

5) How to Diagnose This Issue (advanced)

Of course, the issue I'm talking about in this post is only a specific issue and plenty of other issues may well exist like it. The underlying principle is that segmenting your funnel is a useful thing to do so that you can see if a specific visitor type are not converting or there is a specific drop-off point for them. Unfortunately there isn't a way of segmenting your funnel within Google Analytics at the moment but there are a few advanced ways of getting around this. For example:

• ROI Revolution have a method for segmenting on the fly. Unfortunately this method doesn't let you check custom date ranges.
• LunaMetrics have a way of segmenting the funnel using goals. Unfortunately this method won't let you capture historical data.
• Analytics Ninja has a way of segmenting using advanced segments. Unfortunately this method only let's you track up to a maximum of 3 funnel steps at a time.

None of these methods quite does what I want it to so I'm presenting a 4th option here:

Step 1 - Identify your funnel steps

This is fairly straightforward, all you need to do is understand what the URLs look like for your funnel. For example, let's say our funnel looks like this:

1. http://www.example.com/cart/availability
2. http://www.example.com/cart/details
3. http://www.example.com/cart/extras/
4. http://www.example.com/book/check/
5. https://www.example.com/book/payment/
6. https://www.example.com/book/confirm/

Step 2 - Create some regex

This is getting slightly more complex, however, assuming that all your URLs are exact match (rather than head match or something more complicated) the regex to create is this:

^/cart/availability$|^/cart/details$|^/cart/extras/$|^/book/check/$|^/book/payment/$|^/book/confirm/$

Where we generate this string as follows:

• ^/url1/$ - this matches the exact URL contained between ^ and $
• | - separate each URL with a pipe, this OR matches any of the statements in the string

For a more complete (and very pretty) guide to using regex in Google Analytics download this PDF.

Step 3 - Enter this regex in the top content report

In the top content report copy and paste this regex into the filter box:

This will then filter the top content report to only show you visits to one of the above pages in your funnel. Now we can see the drop off between steps like we can in the regular funnel.

Step 4 - Add custom segments & export to Excel

Now, we add whichever custom segments we want (for example IE8 users like above). This gives us each step of the funnel and the visits to each step broken down by segments:

Unfortunately this data is a little bit difficult to analyse as it doesn't give us the drop off percentage. So, to make this data easier to process and analyse export it to Excel. This will allow us to create a nice little table like this (very minimal excel magic required!):

This is an improvement over the simple diagnosis above because it not only shows us that IE8 users are not converting as well as users from other browsers, but it even tells us the exact step where it's a problem (the cell highlighted in red in the image). Looking back at the URLs we've identified we see that this drop off percentage is the same step where a user transitions from HTTP to HTTPS.

Note: The super-observant among you may have noticed that there is a potential discrepancy here. The warning message that IE8 throws up allows the user to select the option to only view secure elements on the HTTPS page. If the user selects this option then theoretically the user could still carry on through the site and complete the purchase. This visit and the revenue from this purchase wouldn't be tracked in Google Analytics since the HTTP Google Analytics call is blocked by the browser. So the extra £100,000 / month could in theory only be a reported increase in revenue. In reality however we found that the true bottom line still increased by over £30,000 per month as a result of this change. This implies that displaying the pop-up still has a drastic effect on conversion rates.

6) Conclusion

So what have we learned? The key lessons here are as follows:

• Keep your GA code up to date
• Use advanced segments to monitor conversion rate between browsers
• Always perform browser testing to ensure your website functions for all browsers

Remember, the HTTP/HTTPS issue applies equally to all URL calls so even if you use the up-to-date Google Analytics tracking code some other non-secure element on the page might be costing you revenue so always make sure that your website is functioning perfectly across all browsers. If you don't, you might end up losing £360,000 ($500,000) a year or more!

Thanks Tom for a thorough look at how to avoid this problem. And to echo Tom's advice, we encourage everyone to move to the newest version of the GA tracking code. You can follow more analytics insights and online marketing tips at the Distilled Blog or follow Tom on Twitter.

Posted by Trevor Claiborne, Google Analytics Team

Advanced: E-Commerce Roll Up Reporting For Websites With Different Languages

If you're a business owner of any size, you've at some point considered expanding. And as the web makes the world smaller, one way to expand is to offer your website in different languages and take your business across borders or to different segments. By entering other markets with your website, you can gauge new markets and find ways to grow and generate revenue.

Getting set up to offer your products and services in a different country can have a number of steps including localization and legal processes. Another thing to keep in mind is how you will set up your web analytics for the different languages and countries your site now serves.

We're highlighting a series of posts on the topic, called "Google Analytics reporting for multilingual e-commerce stores" by Gavin Doolan, a Googler based in Dublin specializing on Google Analytics for Europe. The posts are all from our Analytics blog in Europe, the Conversion Room. This is obviously a topic very close to the European businessperson's heart.

The great thing about the posts is that Gavin presents solutions for different structures of sites, since not everyone is doing the same thing when they sell products internationally or in different languages.

Part #1: Multiple languages on a single domain

Part #2: Multiple profiles, multiple domains and a single payment gateway

Part #3: Roll up reporting, multiple domains and a single payment gateway

We hope you'll find this information helpful as you think about expanding your business and your website.

Posted by Trevor Claiborne, Google Analytics Team

Custom variables webinar available for your viewing pleasure

Custom variables is one of the most powerful features in Google Analytics. With them you can segment traffic by almost any attribute. We recently hosted a webinar on how to make the most effective use of custom variables. If you missed it, you can now watch this highly informative webinar on the Google Analytics YouTube channel.

If you’re interested in learning how to use this powerful feature in Google Analytics, sit yourself down with some popcorn this Friday night and get analyzing.

Posted by Trevor Claiborne, Google Analytics Team

Upcoming Webinar: Google Analytics Custom Variables

Custom variables are one of the most powerful features in Google Analytics. With them you can segment traffic by almost any attribute. For example, you could compare traffic from first-time customers versus repeat buyers. Or, if you run a content-oriented site, you could see which authors produce the most traffic..

While powerful, setting up custom variables can be a bit tricky, so we’re holding a webinar so you can learn how to make the most of them.

We'll start with Phil Mui, Senior Product Manager for Google Analytics, who'll share with you the features and capabilities of custom variables. Next, we'll hear from Nick Mihailovski, Google Analytics Developer Evangelist. Nick will show you how to implement custom variables on your website and share best practices.

We'll also be joined by Jim Snyder and Peter Howley from Empirical Path, a Google Analytics Authorized Consultant. They'll share how they implemented custom variables for the Business Insider and the insights they've gained as a result. We'll close with a Q&A session with all the speakers.

We’ve set up a Google Moderator to take your questions in advance and so you can vote on the questions you’d most like to see answered. Ask your questions

Date: Wednesday, March 24th

Time: 10:00 AM Pacific

Register for the webinar

If you can't make the live webinar, we'll post a recording on the Google Analytics YouTube Channel a week or two afterwards.

Posted by Trevor Claiborne, Google Analytics Team

Advanced: Structure Your Account With Roll Up Reporting And More

Guest post by the team at E-Nor, a Google Analytics Authorized Consultant

For the analytics ninjas out there, you know that data accuracy is probably one of the most challenging aspects of analytics across all solutions and platforms, and you learn to apply best practices and establish processes to improve data collection and reporting.

But for the rest of us, how do we help marketers, business owners, and webmasters have confidence in their data? Analytics is all about clarity. It should help you see actionable statistics clearly and quickly. However, when you have a website structure with multiple domains and subdomains - which is often the case - sometimes things can get jumbled.

For instance, you are a CMO or a Director of Marketing at the enterprise and you are responsible for the performance and ROI of a large number of web proprieties. You look at your analytics reports and you can't find your ecommerce data from site A, site B is referring traffic to itself (definitely not a good thing!), and conversion data from your marketing campaign microsite is no where to be found.

This image sums up the feeling.

No need to panic. This post aims to offer an approach to help you plan your Google Analytics accounts setup in a structured fashion to help with clarity. I hope that by following the approach and the technical steps, you will be able to collect and manage all your data, make more sense of it, and most importantly, ensure what you are reporting on, trending, dashboarding and analyzing is based on accurate data.

There are two distinct sections of this post:

• The Strategy (non-technical)
• The How (technical)
  
  

The Strategy

There are many ways to structure your Google Analytics profiles when you have multiple domains and subdomains. But in this post I will limit myself to the one that I like the most and I believe is the least confusing.

Before I go into details of the solution, and for simplification, let us assume we are dealing with a project that has the following requirements:

• A business with 3 domains (www.a.com, www.b.com, and www.c.com)
  
  
• 1 domain (a.com) links to a 3rd party shopping cart (www.mystore.com)
  
  
• 2 domains (a.com and b.com) have multiple sub-domains

Here is a graphical representation of the structure:

Measurement Requirements

• Track each domain and sub-domain separately (e.g. www.a.com, news.a.com, and blog.b.com)
  


• Track the rollup/overall traffic for all domains and sub-domains
  


• Track full e-commerce transactions
  
  

Solution

• Create a Google Analytics account for each domain (www.a.com, www.b.com, and www.c.com)
  


• Customize the tracking code to link the multiple sub-domains with their main domains
  


• Link the third party shopping cart with the main domain and install Google Analytics tracking code in all shopping pages
  


• Create a rollup Google Analytics account and add its code to all domains and sub-domains

Graphical example of a well-planned Analytics Account Structure:

Now on to the technical stuff. If you don't enjoy javascript and regular expressions, you may stop here and ask your webmaster or technical analyst to read further :-)

The How:

I will try to illustrate the technical implementation in 10 simple steps:

1- Create a unique Google Analytics account for each domain www.a.com, www.b.com, and www.c.com and then use the account number UA-AAAAAAAA-1 in the code in step 3 and use the accounts UA-BBBBBBBB-1 for www.b.com and UA-CCCCCCCC-1 for www.c.com in the code in step 8.

2- Create a Google Analytics account for the a rollup account that will oversee all domains and sub-domains (use the GA account number UA-XXXXXXXX-1 in the code used in step 3 and 8)

3- Add the following Google Analytics tracking code to the main site (www.a.com) and its sub-domains (blog.a.com, news.a.com, images.a.com, and media.a.com)

About the following code: We have a regular pageTracker object to track activity on each particular subdomain and a rollupTracker to track activity across all subdomains and the third party checkout site. (Click here to learn more about the customizations we made to the standard Google Analytics tracking code)

<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">
try {
var pageTracker = _gat._getTracker("UA-AAAAAAAA-1");
pageTracker._setAllowHash(false);
pageTracker._setDomainName(".a.com");
pageTracker._setAllowLinker(true);
pageTracker._trackPageview();
var rollupTracker = _gat._getTracker("UA-XXXXXXXX-1");
rollupTracker._setAllowHash(false);
rollupTracker._setDomainName(".a.com");
rollupTracker._setAllowLinker(true);
rollupTracker._trackPageview();
}
catch(err) {}

</script>

4- Enable E-Commerce Reporting

Analytics Settings > Profile Settings > Edit Profile Information

5- Add the following code* to all shopping cart pages on the store site (www.mystore.com)

*Make sure to add this code to the top of the pages.

<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">
try {
var pageTracker = _gat._getTracker("UA-AAAAAAAA-1");
pageTracker._setDomainName("none");
pageTracker._setAllowLinker(true);
pageTracker._trackPageview();
var rollupTracker = _gat._getTracker("UA-XXXXXXXX-1");
rollupTracker._setDomainName("none");
rollupTracker._setAllowLinker(true);
rollupTracker._trackPageview();
}
catch(err) {}

</script>

6- Add the e-commerce tracking code to the confirmation page after the GATC.

Read more about "How to track e-commerce transactions?"

7- Change the links to the store site (www.mystore.com) on the main site (www.a.com) to use _link as following:

If the current link looks like:

<a href="https://www.mystore.com">Buy Now</a>

Change it to:

<a href="https://www.mystore.com" onclick="pageTracker._link(this.href); return false;">Buy Now</a>

8- Repeat step number 3 for domains www.b.com and www.c.com after updating the Google Analytics account number UA-AAAAAAAA-1 and the setDomainName value.

• To view the entire code for www.b.com and its sub-domains (click here)
  


• To view the entire code for www.c.com (click here)

9- Create a profile for each sub-domain (only if needed)

In order to track a sub-domain (ex. blog.b.com) in its own profile, follow the following three steps:

a- Create a filter that include only traffic from Hostname=blog.b.com

b- Create a profile and name it "Blog"

c- Apply the sub-domain filter to the new profile

10- As you might have noticed from the codes that we added so far to all pages, we added an extra Google Analytics account to track all pageviews across domains and sub-domains to one Google Analytics account. We call this account “rollup account”.

var rollupTracker = _gat._getTracker("UA-XXXXXXXX-1");
rollupTracker._trackPageview();

Since in the rollup account, we will track pages from different sites and many of these pages might share the same naming convention, I suggest that you create an advanced filter that adds the hostname to the page name to differentiate between pages with same URI.

Once you apply the filter, the upcoming data will appear as following:

Note, in the example above if we didn’t apply the “Add Hostnames” filter, all home.aspx pages will appear as one page with 2685 pageviews.

If you have been with us so far, you are now ready to conduct your analysis based on clean and much more accurate data :)

• To review each domain by itself and for deep-dive analysis, use the domain profiles
  


• To get an overview and to see how the business is doing across all sites, use the “Rollup Account”

Related Posts

• Google Analytics - Accounts and Profiles
  


• Account Rollup in Google Analytics
  


• Google Analytics for the Enterprise

Posted by Allaedin Ezzeidin, Analytics Specialist @ E-Nor, a Google Analytics Authorized Consultant

Public Broadcasting Service (PBS) - Teach People to Fish

What works better, a centralized web analytics team with deep technical knowledge, or non-expert users spread throughout an organization? This was the question faced by Amy Sample when she joined PBS Interactive as web analytics director in the fall of 2007. Amy shared her story with us in response to our call to share your web analytics story.

Implementation

PBS Interactive helps individual PBS producers and local PBS stations create and promote microsites for programming like NOVA, American Masters, and Sid the Science Kid. Amy had the difficult task of helping these managers make educated decisions about how to improve their online show sites.

When Sample came on board, she learned that PBS had standardized on a single analytics tool. This was a good first step, but few at the company were familiar with the tool and the reports it generated were not being used to take action. Producers wanted to know more about how people interacted with microsites for their programs, but they weren't sure what to focus on. At the same time, the analytics group had a hard time keeping up with demands from so many stakeholders. According to Sample "The producers wanted to dig deeper into their site data than a monthly report could provide."

Amy's response was two-fold. First, after consulting with a pilot group of producers and other members of the interactive group, she decided to deploy an installation of Google Analytics. In Sample's words "We chose Google Analytics because we had to deal with a diverse group of needs and very limited resources. We wanted a system where a user with very little training could get insights right away."

Second, Sample worked with LunaMetrics, a Google Analytics Authorized Consultant, to manage the complex issues PBS faced with cross-domain tracking and a complicated account structure. LunaMetrics also created training materials, hosted an on-site training for PBS staff, and conducted a series of training webinars for producers and local stations.

Applying the Data

As it turns out, despite challenges around getting resources assigned to tag pages and working out the right account structure, deploying Analytics was actually the easy part. In Sample's experience, the more challenging problem came in spreading knowledge and awareness of Analytics through the organization in a way that lets people take action on the data. "My approach has been to teach people how to fish," Sample explains, "It's been about doing training classes and one-on-one work with key practitioners, creating specific training decks by job function and getting other groups to use Analytics data in their daily activities."

Google Analytics has been a key facilitator in the transformation of PBS online. Stakeholders are no longer focused on monthly reports. Increasingly, they are using Analytics to inform actual business decisions. Here are some examples highlighted by the PBS team:

• Site Search Tracking - The PBSKIDS.org site has implemented changes as a result of insights gleaned from site search tracking that have increased traffic to the site 30% in the last year.
  
  
  
• Funnel Optimization - The PBSKIDS Island team used funnels to optimize their registration path resulting in a 3x improvement in conversion rate.
• Content Optimization - An analysis of users’ video consumption behavior on PBS.org and PBSKIDS.org led to the development of the PBS Video and PBSKIDS GO! Broadband portals. PBS went even further, basing a full 2008 PBS.org redesign on the data that indicated which content visitors access.
• Advertising Optimization - PBS' marketing group also looks at post-click behavior for their display ad campaigns to zero-in on referring sites that send high-quality traffic. They use this information to optimize successive campaigns.

Long-Term Vision

Sample's long term vision is to extend Analytics to measure engagement with PBS content both on-site and off-site. She also hopes to gauge the impact of online content on TV tune-in and track online donations, while expanding her training efforts to teach producer colleagues how to segment traffic and drill deeper into visitor behavior on their microsites.

The lesson learned is that no matter what analytics tool you're using, a well-planned deployment is only a first step. The hard part is "teaching people to fish," and making analytics data a key component in your organization's everyday business decisions.

Posted by Sebastian Tonkin, Google Analytics Team

Segment your Traffic with the User Defined Report

Have you ever been in the Visitors section of your favorite Google Analytics profile and wondered what the heck “User-Defined” was? Well today it's time to find out.

So, what is “User-Defined?"

The user defined variable allows you to "label" a visitor if they complete a certain action on your site, such as making a purchase or visiting a key page. These labels are useful because they last across multiple visits to your site.

These labels are often called Custom Segments (or Custom Segmentation). You can see the data from these Custom Segments in the User Defined report, which is the last report of the Visitors section in Google Analytics.

How do I add these “labels” to my website visitors?

Making use of the User-Defined report in Google Analytics requires a bit of extra coding help from your IT department or webmaster, but it’s often well worth the effort.

For example, let’s say that I want to add a label of “customers” to any visitor who reaches my shopping cart’s receipt page. In order to do this, I would add an additional line of code to the Google Analytics Tracking Code (GATC) on my receipt page. It would then look something like this:

<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"> try { var pageTracker = _gat._getTracker("UA-XXXXXXX-1"); pageTracker._trackPageview(); pageTracker._setVar(”customers”); } catch(err) {}</script>

Notice the line in bold that includes _setVar. When this is present on a page within the Google Analytics Tracking Code, an additional cookie (called the __utmv cookie) gets set on a visitor’s computer, with its sole purpose being to identify the visitor by the label (or value) that you used in the code. If you take a look at the code example above, you will see that I used the term “customers,“ the label that I want to appear in the User Defined report.

Now, on their next visit to the site, they will be identified as a part of the “customers” segment in the User Defined report, allowing you to perform analysis on all visitors who have purchased something from your online store. Neat, huh?

Can I use _setVar when someone clicks on a link instead of visiting a page?

Yes - you can also use the pageTracker._setVar function when someone clicks on an important link on your site, or makes a key selection on an important form that you want visitors to fill out. For example, if you wanted to add a custom label to any visitor who clicks on your “Live Help” applet, you can ask your IT department or webmaster to add an “onClick” event, and give them the following line of code:

onClick="pageTracker._setVar('Needs Help');"

What will this look like in the end?

When all of your coding is complete, check the User Defined report after about a day or so and you should see something like this:

After the data has been collected by Google Analytics, you can interact with it just like you would with any other report. Click on the “Goal Conversion” tab directly above the table to see how many customers have reached key pages of your site, or use the dimensioning feature to see what sources of traffic were responsible for bringing these special visitors to your website!

Are there any other ways to use _setVar?

One neat usage of the _setVar function is to use it to exclude your own traffic from reports when using a dynamic IP address. For example, let’s say that you wanted to exclude your entire company’s traffic from appearing in reports, and your company uses dynamic IP addresses.

Because it would be nearly impossible to write a filter to exclude traffic from a dynamic IP address, you can create an HTML page that is not a part of your website and add Google Analytics Tracking Code with the call to _setVar and a label of “employees” (or something similar).

Next, you can ask each employee to visit that page from their browser of choice – this will drop a cookie on their computer, identifying them as “employees.” Finally, you can then apply a filter with the following specifications to your profile, and your internal traffic will be excluded:

• Filter Type: Custom Filter >> Exclude
• Filter Field: User Defined
• Filter Pattern: employees
• Case Sensitive: No

Some technical notes about Custom Segmentation:

1. As we just talked about, when a person visits a page calling the _setVar function, the __utmv cookie is set on their computer. This is a persistent, first-party cookie that has a lifetime of two years. This means that every time a user with a __utmv cookie returns to your site, the label assigned to the user will continue to identify them as such until they either delete the cookie or visit another page with another call to _setVar with a different label.
   
   
2. The purpose behind something like a User-Defined report - and Custom Segmentation in general - is that it is not designed to be updated very often. This label, for the most part, should be a permanent one for a visitor. You should only use _setVar on pages like a receipt page of a shopping cart, or an account registration “success” page for a visitor who becomes a member of your site. You shouldn’t use _setVar on your homepage, or use several different _setVar’s with different labels scattered across many pages of your website.
   
   
3. Google Analytics - at this time - only has the capacity to store one custom segment at any one time for one website. So if you are using multiple calls to _setVar on your site, Google Analytics can only store the latest value that a visitor runs into in the __utmv cookie. John Henson at LunaMetrics – a fellow Google Analytics Authorized Consultant - has created a custom version of the Google Analytics Tracking Code that can support multiple custom segment labels at any one time.
   
   
4. On the other hand, Google Analytics uses what they call the “first association” of the session for visitor session calculations. If you are using multiple calls to _setVar on your site, be aware that if a user runs into the first one, and then runs into the second one in the same visit, their Goal Conversion and Pages per Visit metrics would be attributed to the label of the first encounter with _setVar.
   
   
5. For page view calculations, Google Analytics uses the most recently defined value. So if a person runs into the second instance of _setVar on your site, all of their pageviews afterwards - including the current pageview - will be attributed to the second _setVar’s label, even though as we just learned in #4 above, visitor session information is attributed to the first encounter of _setVar.

A full, technical explanation of _setVar and the User-Defined Report can be found here.

Summary

The User Defined report in Google Analytics is a great place to start segmenting your traffic. With a little bit of help from your IT department, you can not only begin to collect awesome data, but you can also begin to gain advanced knowledge about what makes your VIP website visitors register, sign-up for your newsletter, or purchase something from your online store. This will definitely help you become that Analysis Ninja that Avinash Kaushik loves to talk about!

Written by Joe Teixeira of MoreVisibility, a Google Analytics Authorized Consultant.

Twittering with Google Analytics and Google Website Optimizer

Our good friend John Marshall just posted this Facebook status update: "cycling to work this morning I hear the birds twittering. Instinctively I wonder if they should be doing something more productive."

Lol, John. He's referring to twitter.com and the fact that with it, your opportunities to waste time have increased. Anyone following Ashton Kutcher? Consider this recent tweet:

you are the man @tonyhawk skates the halls of the white house http://twitpic.com/7sx4j

Actually, that is kinda cool. Definitely a good way to waste time if you want to. =) And we appreciate how Twitter has been a powerful force in the current Iranian election. It's a novel and intimate way to broadcast - and even moreso to listen - many to many.

If you work with and love web analytics like John does and we do, then following some tweets from thought leaders in the industry will keep you on the forefront of what's going with your favorite products. It's an energizing and quick way to connect and engage, in 140 characters or less. Here are a few Google Analytics and Google Website Optimizer-related tweets from last week along with some of their latest and greatest posts.

Brett Crosby
twitter.com/brettc(@brettc)
Google Analytics Group Product Marketing Manager
Twitter bio: "One man brand"

• New Aberdeen report, Google Analytics wins enterprise: http://bit.ly/HK3RY
  9:13 AM Jun 22nd from web
  
  
• New Google Analytics website launched, what do you think? http://www.google.com/analytics (retweet all you want)
  about 15 hours ago from web

• Google Analytics cost data issue fixed, no longer in "direct": http://bit.ly/18eGbk
  about 20 hours ago from web
  
  
• Now use Conversion Optimizer with Google Analytics goals: http://analytics.blogspot.com/2009/06/import-your-google-analytics-goals-into.html
  10:45 PM Jun 17th from web
  
  
• RT @avinashkaushik 2 say the downside of free tools is U have 2 invest in people is wrong. Paid tools with Analysts? Free tools=more $ 4 U.
  11:01 AM Jun 17th from web
  
  
• How to visually explain analytics to the world: http://bit.ly/1p1U0J
  10:26 PM Jun 15th from web
  
  
• @DennisMortensen sounds like it is going to be extremely entertaining... esp'ly if you end up having to do it in your underwear.
  9:30 PM Jun 15th from web in reply to DennisMortensen
  
  

Avinash Kaushik
twitter.com/avinashkaushik (@avinashkaushik)

Analytics Evangelist, Google
Twitter bio: "Author - Web Analytics: An Hour A Day | Analytics Evangelist - Google | Co-Founder - Market Motive Inc"

• Want to improve conversion rates? Consider following Seth Godin's specific advice for ecommerce: http://tr.im/p4SL
  about 3 hours ago from web
  
  
• Hurray! Auto-tagged Google paid search campaigns move back fm Direct 2 the Search report: http://tr.im/p4vp Thanks Phil!
  about 3 hours ago from web
  
  
• [And this is in NYC!] What is a Browser? Video, 3 mins http://tr.im/oYTe
  about 14 hours ago from web
  
  
• "Simplicity good. But simple it is not." - Yoda.
  about 21 hours ago from web
  
  
• @links4legends You could set them up as separate sources http://tr.im/oYPH and then segment them as normal. Pls try it.
  about 22 hours ago from web in reply to links4legends
  
  
• Just look at it... http://tr.im/oYc0 Its the most perfect gorgeous day in San Francisco. I love this city!
  about 24 hours ago from web
  
  
• The best free e-book on Web Analytics+Testing+Usability, 30 pages: http://tr.im/oT6x So simple ur grandma will love it!
  9:18 AM Jun 18th from web
  
  
• This is cool web analytics: The 50 most frequently looked-up words on nytimes.com in 2009: http://tr.im/oSQf
  11:38 PM Jun 17th from web
  
  

Trevor Claiborne
twitter.com/tclaiborne (@tclaiborne)

Google Website Optimizer Product Marketing Manager
Twitter bio: "Product Marketing Manager for Google Website Optimizer and a nice guy too"

• Free new AdWords interface webinar today at 11 AM PDT. Register here: http://bit.ly/1kePS
  about 6 hours ago from web
  
  
• Holy crap - RT @MotivityCMS: Google Website Optimizer Increases Conversion 591% http://ow.ly/eH8e. I love #gwo
  10:02 PM Jun 17th from TweetDeck
  
  
• @oggy Sure it can. Are you doing an A/B or an MVT test? Happy to walk you through it if you DM an email address.
  4:15 PM Jun 16th from web in reply to oggy
  
  
• @waynepelletier What issue are you seeing? And have you read this: http://bit.ly/VBYWL? GA and GWO should play nicely together.
  10:06 AM Jun 11th from web in reply to waynepelletier
  
  
• RT @josh_baker Interpreting Google Website Optimizer’s Page Sections Report http://tinyurl.com/quasvf #GWO #optimization - Nice post!
  10:17 AM Jun 4th from web
  
  
• In Seattle for #SMX. Come to my session Deep Dive into the New AdWords Interface tomorrow at 11.Also at the Google booth for #GWO
  1:11 PM Jun 1st from web
  
  

Justin Cutroni
twitter.com/justincutroni (@justincutroni)

Google Analytics Authorized Consultant with Epikone and author of Google Analytics Shortcut
Twitter bio: "Dad, husband, skiier, hiker, cook, data nerd, author."

• Are you an @avinashkaushik fan? Are you a Timbuk2 fan? Check out their new bag: http://tr.im/nTO8 How about a discount Avinash? :)
  6:21 AM Jun 9th from tr.im
  
  
• @BrainsOnFire Try creating an INCLUDE filter to only include traffic from your home country.
  1:49 PM Jun 3rd from TweetDeck in reply to BrainsOnFire
  
  
• What it's like to be the Comcast's Twitter guru. Could you handle 6,000 email a month + 30,000 tweets? http://tr.im/njlb
  11:17 AM Jun 3rd from tr.im

• Ok, I'm a fan of using new media (Utube) 2 drive innovative marketing ideas.But I think this might be going a bit too far! http://tr.im/niXp
  10:01 AM Jun 3rd from tr.im
  
  
• RT @jonathanpb: Podcast catchup #1: my interview with @justincutroni is now posted online #btv http://bit.ly/3iSL Thanks Jonathan!
  5:43 AM Jun 3rd from TweetDeck
  
  
• #GA ToTD:Advanced Segment data sampling sucks.To avoid create different profiles for the segments that you need to measure accurately.
  5:42 AM Jun 3rd from TweetDeck
  
  
• Has anyone used SeeWhy abandonment tracking? Looks like a simple way to follow up on abandoned carts. http://tr.im/ncly
  11:56 AM Jun 2nd from web
  
  
• Went a whole week without any social media. Quiet, but very refreshing. Surprisingly the world has not changed that much :)
  11:33 AM Jun 2nd from web
  
  

Bryan Eisenberg
twitter.com/TheGrok (@TheGrok)

Google Website Optimizer Authorized Consultant with FutureNow.
Twitter bio: "Website Conversion, Persuasion Architecture expert and best selling author of Waiting for Your Cat to Bark, Call to Action, and Always Be Testing."

• Web Analytics and Yellow Lobsters http://tinyurl.com/mr5lt2
  about 8 hours ago from twitterfeed
  
  
• Conversion Rate Exercise: Why Should I Do Business With You? http://tinyurl.com/m6rok7
  4:25 AM Jun 18th from twitterfeed
  
  
• Import web analytics data from Google Analytics in to an Excel spreadsheet http://tr.im/oTQi #wa
  2:15 AM Jun 18th from TweetDeck
  
  
• Bagging the Conversion Elephant: Google Analytics Blog http://tr.im/oQZC
  3:36 PM Jun 17th from TweetDeck
  
  
• Are Your Analytics Causing You to Lose 30% of Your Sales? http://tinyurl.com/lha4sq
  12:24 PM Jun 17th from twitterfeed
  
  
• RT @minethatdata: #IRCE Top 500 Internet Retailers represent 65pct of e-commerce sales. Mercy.
  6:45 AM Jun 17th from TweetDeck
  
  
• RT @Mike_Stelzner: Interesting stats on how much video people watch online: http://bit.ly/srS6L
  6:16 AM Jun 17th from TweetDeck
  
  
• Do you think Twitter will become obsolete?- iMedia connection's Jason Clark does - http://tr.im/owWI
  5:37 AM Jun 15th from TweetDeck
  
  
• The Day the Media Died http://bit.ly/12Le0c
  4:17 AM Jun 14th from TweetDeck
  

Posted by Jeff Gillis, Google Analytics Team

Bagging the Conversion Elephant

In reading an Occam’s Razor blog post from earlier this year, “Aggregation of Marginal Gains: Recession Busting Analytics!," I noted that Avinash is discussing exactly the same experience we at FutureNow underwent. Ten years ago, low hanging fruit in the conversion improvement space meant high traffic, high impact changes from fixing obviously-wrong calls to action: bad linking, non-obvious next steps, poor UI (user interface).

In fact, for several years conversion improvement was all about UI. Remember that? The theory was (mostly from the UI people, of course), that if you just improved the UI then conversion would follow. What we found out was that if you had a weak UI then of course fixing it would help... but only so far. When it worked you got big fireworks-busting improvements, but only at a singular point in the sales process.

A few years after that it was analytics. If you simply measure everything, then (wave hands here, sprinkle magical pixie dust) you’ll “just know” what to do to improve. If you want to improve more well then just “measure more” — get more analytics apps installed. Or buy more expensive ones.

In the last year or so, the buzz word technique seems to be testing. If you just test everything then somewhere, somehow you’ll know what helps conversion. And when I say “everything”, I mean “EVERYTHING.” Testing is great — in fact, I wrote a best-selling book on this very topic, "Always Be Testing", centered specifically on Google Website Optimizer — but if there’s a bee on your grandmother’s nose, do you honestly have to do a test to determine whether to swat it away? Yet, some companies out there imply to clients they should freeze like a deer caught in the headlights unless and until they have a test to back up every decision made. And if you don’t have enough traffic for the test to be valid just drive more traffic, any traffic, even if precision comes at the cost of accuracy. It's lunacy. No thanks, m’am, that bee on Granny gets swatted and I don’t need 95% statistical confidence to make that decision.

Each time the industry thinks it’s got the elephant in its sights, that five-ton peanut-eater slips away. I think it’s because everyone keeps chasing technology as the solution to pachyderm-sized conversion improvement. If you install the right mix of digital toys, then whamo you’re sure to be the next market leader in your space. Again with the pixie dust.

But it just doesn’t work that way. What we’ve learned is that the big wins come from a long series of small wins, accumulated over time. And small wins come from experienced insight and hard work. And it has to be the type of hard work that a company is willing and able to perform. Not pie-in-the-sky goals without any mechanism for implementing.

I'd recommend focusing less on "big projects" and more on iteration. At FutureNow we did just that, re-tooling our entire business model around this "OnTarget" concept, letting clients decide how many resources they have to devote to improvement in a current cycle, and delivering experienced recommendations specifically for that cycle, and using analytics tools to measure the improvement and testing tools to back up any conclusions. "Rinse and repeat". How do you eat the conversion elephant? One small bite at a time. Exactly what Avinash was speaking about.

Posted by John Quarto-vonTivadar of FutureNow, a Google Analytics Authorized Consultant

Event Tracking Now Available in All Accounts

Event Tracking is a feature of Google Analytics that allows you to track visitor actions that don't correspond directly to pageviews. It's a great fit for tracking things like:

• Downloads of a PDF or file
  
• Interaction with dynamic, AJAX sites
  
• Interaction with Adobe Flash objects, embedded videos and other media
  

Unlike virtual pageviews, Event Tracking will not alter your pageview count. This makes it the preferred method for tracking a variety of visitor actions.

We're happy to announce that earlier today Event Tracking became available by default in all Google Analytics accounts. To access the new reports, just navigate to the Content Section of the Google Analytics interface and select the option labeled "Event Tracking."

Screenshot of Event Tracking reports

In future posts, we'll explain more about some of the ways you can put Event Tracking to good use. For now, here are some great resources to get you started:

• How to send Events to Google Analytics (Code site)
• Event Tracking Overview/Tutorial (Analytics Talk)
• Tracking Flash Videos with Event Tracking (Inside RIA)
  

Note, your reports will not show data until you start sending events. You can use the above resources to find about more about how to send events to Google Analytics.

We hope you enjoy the feature. Leave a comment and let us know what you think!

Posted by Nick Mihailovski, Google Analytics Team

Top Ten Myths About Google Analytics

We've noticed some misconceptions about Google Analytics floating around, and we thought we'd take a shot at correcting the most common ones. Without further ado, here they are, the top ten myths about Google Analytics debunked.

MYTH 1: "You get what you pay for." Google Analytics is free, which means the system is down a lot.

Google Analytics makes use of the same network of secure and reliable data centers used to power Google.com, making downtime an extremely rare occurrence. We have a large team focused exclusively on keeping your data safe and accessible, and benefit from multiple redundancies in our infrastructure around the globe (this makes us fast as well).

We even rely on Google Analytics for our own mission-critical products such as AdWords, which see huge volumes of traffic every day. If you're still having doubts, we'd encourage you to talk to some users and ask them how their experience has been with uptime.

MYTH 2: Google Analytics is basic and doesn't have any "advanced" features or metrics

Ack, this one is a tough one to swallow! A more frequent complaint is actually that Google Analytics has too much data. The product includes over 90 standard reports with more than 125 metrics and dimensions covering everything from visits to internal site search queries.

Custom reports and user-defined variables allow you to create your own metrics and reports where the standard ones don't meet your needs. With Pivoting, Advanced Segmentation, Secondary Dimensions, Event Tracking and the ability to share customizations, Google Analytics reports are more powerful than ever.

Google Analytics may look "basic," on the surface, but it can do a lot more than you think! If you have complex needs try talking to a Google Analytics Authorized Consultant or diving into the documentation on the Google Code Site.

More Info (Feature List, Custom Reports, Advanced Segmentation, Analytics API)

MYTH 3: Google Analytics only supports third-party cookies

False! Google Analytics has always used first-party, not third-party cookies. First-party cookies are important because they allow Google Analytics to track repeat visitors, so you can see which keyword, referring site, etc is responsible for bringing buyers even when it takes multiple visits for them to convert.

MYTH 4: Google Analytics is not really accurate

If you've spent time doing web analytics work, you'll know the sinking feeling that comes when two sets of numbers don't match. If you're experiencing a data discrepancy, don't panic. There are many others in the same boat.

Google Analytics uses JavaScript tags to collect data. This industry-standard method yields reliable trends and a high degree of precision, but it's not perfect. Most of the time, if you are noticing data discrepancies greater than 10%, it's due to an installation issue. Common problems include JavaScript errors, redirects, untagged pages and slow client-side load times.

For tips on how to sensibly approach data reconciliation, check out this post by Avinash Kaushik, Google's Analytics Evangelist, or this whitepaper on accuracy in Google Analytics. You can also talk to an expert.

All web analytics tools face the same technical limitations posed by JavaScript tags, so if another vendor claims their tool is more accurate, ask for some evidence.

More Info (Web Analytics Data Reconciliation Checklist, Whitepaper)

MYTH 5: It's not possible to export your data from Google Analytics

Not true! You have two options for exporting data. Use the "export" button at the top of each report to export the current view in PDF or XML (up to 500 rows). Or, use the new Analytics Export API to extract large amounts of data in any format you like. Also, if you want to share data with a colleague, you can schedule reports to be delivered directly to their email inbox, or even send regular updates to your own email address.

More Info (How to Export your Data, Analytics API)

MYTH 6: With Google Analytics you can't control your data

You have three options for data sharing in Google Analytics. You can change these options at any time from inside your Analytics account.

• do not share your data
  
• share your data with Google to improve its products
  
• share your data anonymously for benchmarking

No matter which option you choose, your data is protected by several layers of defense:

1. Dedicated security and infrastructure teams
   
2. Multiple redundancies to prevent data loss
3. Network redundancies to keep data accessible
4. Advanced security, firewalling and routing to keep data secure
5. Restricted access and principle of least privilege for personnel
   

If you opt-out of data sharing, your data will remain within Google Analytics and will not be shared with other products or services. If you decide to share your data with Google, it will be used to improve those products and services. Lastly, if you decide to share your data anonymously with others, it will be blended with other data to support the Google Analytics benchmarking feature. For more information on these options and what they mean, refer to the Google Analytics data sharing FAQ.

If you're still concerned, Google also offers a software product called Urchin (www.urchin.com) that you can run locally.

More Info (Data Sharing FAQ, Google Privacy Policy)

MYTH 7: There is no professional support for Google Analytics

Contrar! We flipped the model. Instead of providing an expensive analytics product with a one-size-fits-all professional services plan, we provide a free product and let you purchase the professional services that fit your needs.

There are several ways to get support: email support, help forums, the help center, and a network of Authorized Consultants. Authorized Consultants speak your language, accept your currency and often share your timezone. More than 80 companies across the globe provide a full range of installation and analysis support for Google Analytics. Some examples of things they can help you with are:

• Validate and troubleshoot your installation
• Integrate your analytics data with other data sources or CRM
• Optimize your marketing efforts
• Train your staff on how to use Analytics
• Respond to support tickets, phone calls and provide on-site consulting
  

To find out more, give one or two of them a call. Our Authorized Consultants are hand-picked and are the best in the business.

More Info (Google Analytics Authorized Consultants)

MYTH 8: Google Analytics does not support A/B or multivariate testing and isn't well-integrated with other tools

Google offers a full range of marketing products including a free testing tool called Google Website Optimizer. You can use it to test different page elements and find out which ones yield the highest conversion rate and ROI. You can also use Google Analytics in conjunction with Website Optimizer to create an optimization plan for your site.

Google Analytics is also integrated with many of Google's other business products including AdWords, AdSense, and AdPlanner. It is also widely supported by third party tools ranging from content management systems, to email suites, to call center applications. In addition, you'll find many products that are complementary to Google Analytics including DoubleClick, TVAds, Webmaster Tools, Google Trends, Insights for Search, Feedburner, and more.

More Info (Google Website Optimizer, GWO Blog)

MYTH 9: You can't segment data in Google Analytics

In the fall of 2008, Google Analytics released three new Enterprise Features: Advanced Segmentation, Custom Reports and Motion Charts. Advanced Segmentation lets you segment visits by dozens of metrics and dimensions such as geographic location, time on site, referral site and much much more. You can create segments on the fly and apply them to virtually all the standard reports in Google Analytics as well as custom reports.

More Info (In Depth Look at Advanced Segments, Video)

MYTH 10: You have to spend a lot of money to get "real" web analytics

Getting a return from your Analytics data does take an investment. The most important investment to start with is making sure you or someone at your organization has the expertise and time to put your data to use. If at that point you still feel you need to pay more for a more complicated tool, that's OK, but remember that every dollar you spend on a tool takes away from money you could be spending on actually getting results, i.e. hiring or contracting a talented analyst (see the 90/10 Rule).

The question sometimes comes up, "if Google Analytics is free, what's in it for Google?" Google benefits from Google Analytics in two ways. First, if webmasters build better sites, it helps us connect searchers with the information they need faster. Second, if advertisers use Google Analytics, they are able to see their advertising ROI, which helps us demonstrate the value of Google AdWords. Both aspects have helped create a strong business case for Google Analytics over the years.

Google Analytics is getting more powerful with each new update, and you may be surprised by what it can do. Find out more by attending an Analytics Seminar for Success or talking to an Authorized Consultant in your area. If you're an AdWords advertiser, you can also speak with your Customer Service Representative.

More Info (90/10 Rule, Google Analytics Authorized Consultants, Seminars for Success)

Leave a comment

That's it for the top 10 myths. Still not convinced? Leave a comment and let us know!

Posted by Sebastian Tonkin, Google Analytics Team