We’ve been putting on these training events for almost a year now, and, to be honest, I think they are an amazing value. The cost is $249 US per day and our goal is to dump everything we know into your brain. Seriously.

Day 1 focuses on the data in GA and how to find actionable information. We cover almost every report and the insights you can draw from each. Also during day 1 we’ll cover many of the new GA analysis tools including Advanced Segmentation, Custom Reports and Motion Charts. Here’s a taste of day 1 topics:

• Introduction to Web Analytics
• Website testing with the Google Website Optimizer
• Google Analytics Reporting Features
• Sharing GA Data
• Custom Dashboards
• Understanding Site Visitors
• Tracking online marketing campaigns
• Evaluating site content and user navigation
• Understanding Goals and Conversion Funnels

On day 2 we really dig into how GA works and how to get it configured correctly. Ever wonder how all that great day gets into GA? We cover that in the morning. Have you been curious about how to use filters and profiles? Yup, we cover that too. We even cover event tracking in the hopes that it will be released from beta soon! :) Treats for day 2 include:

• GA architecture overview
• Learning about Regular Expressions
• Improving your data with filters
• Setting up Goals and Funnels
• Implementing E-Commerce Tracking
• Configuring Custom Segmentation
• Introduction to Event Tracking
• Tracking websites with multiple domains/subdomains
• Code customization

But I think the best part of Seminars for Success is the interaction. We usually have groups of 60 which is big, but we’re able to have lively discussions about data and its uses.

You can learn more and sign up for Seminars for Success here. Got questions? Leave a comment below.

And don’t worry if you can’t make it to Montreal, we’ll be doing more of these next year in different cities around the US and hopefully Canada.

In the past few weeks I’ve gotten a lot of questions about how to track email with Google Analytics. While I did cover the broad topic of online ad tracking in a previous series of posts, email tracking has certain nuances that I think should be addressed.

The Concept

Tracking email campaigns in Google Analytics is done using a process called link tagging. This process is the manipulation of the links in your emails. Here’s a sample link that might appear in an email:

http://www.mysite.com/page.php

To track it with Google Analytics it would be modified like this:

http://www.mysite.com/page.php?utm_campaign=fall-sale&utm_medium=email&utm_source=female-list

And another email link that looks like this:

http://www.mysite.com/page.php?prodid=100

Should be modified like this:

http://www.mysite.com/page.php?prodid=100&utm_campaign=fall-sale&utm_medium=email&utm_source=female-list

When someone lands on your site after clicking on a tagged link, GA removes the information from the URL and stores it in a cookie. Because the info now resides on your machine (in the cookie) GA can associate all visitor actions (like conversions and transactions) with the email. Pretty slick, huh?

How Link Tagging Works

What is all that info I added to the URL? They’re called link tagging parameters. The name of the parameter is on the left side of the equal sign and the value of the parameter is on the right side.

Each parameter represents a different attribute of your email. Looking at the example above we can identifiy the following parameters and their values:

utm_campaign=fall-sale
utm_medium=email
utm_source=female-list

Each one is identified by the Google Analytics tracking code and helps GA understand that the visitor arrived on your site via an email.

You must use the parameters that Google provides. However, you can specify any value for each parameter. This is where the real power lies. By using your own values for each parameter you can add markting information, that is specific to your business, to GA. We’ll get to where that information appears in a second.

[ NOTE: All you advanced user may be calling my bluff here. You can rename the link tagging parameters that GA uses, but it is an advanced technique that requires a change to the GA tracking code. I'm not going to cover it in this post but you can learn more in the GA help section. ]

Let’s look at each link tagging parameters and some of the logical values for each.

utm_campaign

This parameter identifies the marketing campaign that the email belongs to. It may be that this email is just one part of a bigger online marketing strategy. For example, you may be using paid search, some display advertising and this email to reach new prospects. You can group this email with other marketing activities by using a common value of utm_campaign.

As for suggested values, use something that represents the campaign that your running.

utm_medium

The medium parameter describes how the message got the to visitor. In the case of email I recommend that you always use the same value. I like to use ‘email’. It’s short and pretty darn descriptive.

Using a single value consolidates all email generated traffic into a single line item in the reports.

utm_source

This is where things get interesting. Traditionally, in link tagging, the source is the ‘who’ attribute. It describes who you’re working with to push a message out. But how does the concept of ‘who’ map to an email?

When it comes to email I like to think of the ‘who’ as the list of recipients that you’re sending the message to. This may be a segment of your email list (like a specific gender segment, age segment of purchase history segment) or your entire email list. For example, some potential utm_source values might be:

utm_source=gender:female
utm_source=gender:all
utm_source=purchase:last-30-days
utm_source=purchase:last-60-days
utm_source=purchase:free-shipping-offer

The key here is that by identifying the segment in the utm_source parameter you’ll be able to measure the performance of that segment in GA. You are segmenting your email list, right?

utm_content

The final parameter is named utm_content and helps us test emails. The content parameter identifies the actual content of the email. So if you’re producing different versions of the email for an A/B test you can mesaure the performance of each by varying the value of utm_content. For example:

utm_content=free-shipping-offer
utm_content=20-off-offer
utm_content=product-creative
utm_content=value-creative

Some folks like to use utm_content to describe not only the version of the email that the recipient received, but also the actual location of the link in the email.

utm_content=top-nav
utm_content=call-to-action
utm_content=image-link

Sometimes this can be overkill as it leads to a lot of very granular data. Normally we just use this to measure which email variation performed better.

Think about how powerful this can be. Using utm_content and utm_source you can measure the performance of a specific message to a specific segment of your customer base (i.e. email list). This is a great way to measure if you’re sending the right message to the right person!

How to Tag Your Links

So now that we know what paramters we can use to track our email, how do we actually tag the links? It starts by assigning a value to each parameters. You could use the Google Analytics URL builder: a free tool in the GA help center. Just enter a value for each parameter, along with the URL from your email, and the tool will automatically generate a tagged URL that you can place in your email.

But I find the URL builder can be cumbersome when tagging a large number of links. Just think of all the links that you might have in a single email!

Instead I use a small Google Spreadsheet that has a built in formula. Just enter your campaign values in the columns, along with the URLs from your email, and drag a pre-programmed formula to automatically created your tagged URLs. Then place the URLs in your email.

You may have noticed that a tagged URL is pretty ugly. If you’re sending an HTML email to you can hide the long URL using an anchor tag, but if you’re using a text based email the recipient will see the entire crappy URL. Try using a service like Tiny URL to hide the query string parameters.

I should note that some email platforms (the cool ones!) have begun to integrate GA link tagging into their tools. Check with your email provider to see if they offer this service.

The Reporting

As I mentioned before, the values used in your link tags get pulled directly into Google Analytics. Each parameter becomes the foundation for a report. Let’s start with the Traffic Sources > Campaigns report:

This report lists all the values of your utm_campaign parameters. You can measure the performance of your email campaigns by finding the values you use for utm_campaign. But be aware, this report will also contain the titles of your AdWords ad campaigns. They’re automatically imported from AdWords. Also remember that you might use the same value of utm_campaign in activities other than email.

Remember utm_source and utm_medium? We can drill into a campaign to determine how the email medium, for a specific source, performed in the campaign. Select a campaign by clicking on the name. Then use the dimension drop down to view all the sources within the campaign.

The above report shows just one source within this campaign, but that’s all that was used. The important thing to understand is how you can see certain sources, specifically email segments, contributed to the success of a campaign.

But what about evaluating a source across multiple campaigns? Try using the Traffic Sources > All Traffic Sources report:

The first column shows all sources and mediums, so in our case we can see how a segment of the email list performed cross all campaigns. We can quickly filter this report by ‘email’, the medium, to identify how well a segment performed. Remember how

What about the utm_content parameter? Where can we find that data? It’s in the Traffic Sources > Ad Versions report.

Here’s where we can evaluate the performance of our different email variations. The Ad Versions report not only contains the values from utm_content, but also the titles from your AdWords campaigns. This is another piece of data that GA automatically pulls in.

And let’s not forget that all of these reports have three tabs full of metrics: site usage, goal conversions and ecommerce (if you choose to use ecommerce tracking). All of these metrics provide insight into the sales or conversion process.

Bounce rate provides insight into the begining of the process. A high bounce rate probably indicates a disconnect between the message in the email and the content on the landing page.

You can quickly switch to the goal conversions tab to measure the other end of the process by looking at the conversion rate for your email. And if you’re using the ecommerce tab you can look at a metric like revenue to qualify the conversion rate.

Don’t Forget the Pre Click Data

While all this data is great, don’t forget that your email provider has a number of metrics that give insight into what happened before the visitor arrived on your site. Such metrics include # emails sent, # emails received, # bounces, # emails opened and click throughs.

I know that metrics like open rate are inherently flawed due to the tracking technology, but you can’t evaluate things like subject line effectiveness using the data in GA. Don’t be afraid to look at metrics like # of bounces when evaluating the performance of email.

Create your Advanced Segment

With GA’s new Advanced Segments we can really drill into the email traffic segment. At the very least, you should create one advanced segment to evaluate email traffic.

To create the advanced segment use the ‘medium’ dimension and enter a value of ‘email’. Remember, ‘email’ is the value we used for utm_medium in the link tagging. Talk about coming full circle!

Using an advanced segment helps you easily identify what content the email segment found interesting, if they converted, how well the progressed through various processes, etc.

Common Problems

The most common problem we see with link tagging is that people forget to tag their links. Link tagging is usually a process related issue, not a tech related issue. Before your organization sends any email communication make sure the links are tagged.

A simple way to test your links is to send the email to a few coworkers and ask them to click on some links. In a few hours you should see the data in your GA reports.

The second most common problem has to do with redirects. Many times a site may have a redirect that strips off the campaign tracking parameters. The simple test mentioned above should tell you if you have a redirect issue. Remember, when you click on a tagged link you should see your link tagging parameters in the URL of your site.

A Note on Privacy

A few people have mentioned that it is possible to add a visitor’s email address to your GA data using link tagging. While this is possible, keep in mind the GA terms of service specifically forbids the collection of personally identifiable information with Google Analytics.

If you’re still reading, and you’re trying to understand how to track other types of online ads, then you may be interested in these posts:

• Google Analytics Campaign Tracking Pt. 1: Link Tagging
• Part 2: EpikOne Link Tagging Tool
• Part 3: Reports and Analysis

I know the past week has been full of Google Analytics news, but I’m excited to tell you about something one of our team members created: Google Analytics Notes.

For a long time we’ve wanted to add business data to GA to help keep track of marketing activities, industry news and GA configuration changes. These things are critical to know when analyzing data as they add more context and help us understand what’s affecting website performance.

We tried using Google Spreadsheets to store business info but it never worked. People did not take the time to open up a spreadsheet and add information. We figured that adding some type of ‘note’ functionality to GA would be the easiest way to change this behavior. That’s how GA Notes was born.

GA Notes is a Firefox extension that lets you add business data to a profile. Notes appear in a concealable table at the top of every report.

Any GA user who views a profile, and has the Firefox extension, will see the notes entered for the profile. You can add notes, edit notes and delete notes. Notes can also be exported in XML format for archival purposes.

Installation

Installing GA Notes is easy. Just download the following file to your computer:

https://ga-notes.appspot.com/ganotes.xpi

Once downloaded double click on the file. Firefox should open and ask if you want to install the extension. Click install and that’s it. You’re ready to start adding notes to your GA data.

Usage

The extension adds a ‘Show Notes’ button in the GA menu bar. Click on the button to view notes for this profile or to add a note or edit/delete an existing note. It’s not that complicated. :) We wanted to keep this easy and flexible.

How it Works

For those of you that are interested, GA Notes runs on Google’s App Engine. No data is stored on your machine or our servers. It’s stored on Google’s servers. The Firefox extension provides the interface to enter and display data. But all of the processing and data storage happens on App Engine. All data sent to App Engine is encrypted prior to transmission.

In a perfect world we would have added notes to the data-over-time graph at the top of each report. However, we can’t get inside that part of GA using a Firefox extensions (or Greasemonkey script). We thought this was a good compromise. If anyone out there knows how to dig into Flash let us know! :)

Road Map

This is obviously a beta version of the software. We have a number of features that we’re working on and hope to have done soon. These include:

• Sorting and searching notes by date
• Excel friendly export
• An admin flag for notes to separate admin changes to your GA account
• Some type of alert to show you how many new notes have been added since your last login
• A more graphical visualization of note

If you have any suggestions or ideas please let us know!

Credit

I don’t have the smarts to build these types of things, I just know enough to be dangerous. Chris, a new member of our team, built GA Notes from the ground up. Thanks Chris for all the hard work.

Today Google is releasing a significant update to Google Analytics. I’m not sure if it is officially version 3.0, but the amount of new functionality is extraordinary. Not to mention some nice changes to the interface to clean things up.

This new release includes:

* Motion Charts (a data visualization tool)
* Advanced Segmentation
* Custom Reporting
* AdSense Integration
* A data API
* A new administrative interface

Not all of these features are public. The API and AdSense reports (I believe) are in private beta meaning your account must be authorized to use them. All other features are public! Woo Hoo!

These new features cover 90% of the requests we get from all users, both big and small. In my opinion this release is game changer, especially for the enterprise market.

For example, our ability to manage massive GA implementations (1,000 + sites) is now much easier with the new administrative interface. And the data API let’s companies integrate their click stream data with other data sources. Did I mention that Advanced Segmentation let’s you segment historical data?

I’ll slowly be rolling out some posts and to cover all new features as well as a few posts to discuss how this changes the way we work with GA.

A big congratulations to the Google Analytics team. The amount of new functionality is really amazing.

When you firs log in the new admin area will display a list of all accounts that you have access to.

Click to enlarge the image.

This tabular layout of accounts is new, and very helpful. If you’re an agency, or a large company, you probably have access to multiple GA accounts. This layout makes it easy to identify performance at the account level.

Key to the new layout is the addition of metrics. Available metrics in are:

* Visits
* Time on Site
* Bounce Rate
* Completed Goals

One column actually does a date comparison. Choose one of the above metrics using the drop down at the top of the column and a simple date range using the buttons at the top right corner of the screen to determine how said metric has changed over the past day, week, month or year.

Looking a bit closer, you’ll notice that each account name is a link. Clicking on the link will display all profiles within that account:

click to enlarge.

This is where things get really juicy!

GA is now grouping the profiles that have been created for each tracking code in an account. I’ve talked a lot about creating multiple profiles for a single site, and this is a great way to see all those properties in one place.

As an analyst I like the fact that I can view basic information in the admin area and do a quick performance evaluation. Would I like to see more metrics? Sure, but this is a great start. This literally turns the admin area into a basic dashboard for large groups of websites.

Another feature that I really like is the Favorites. Anyone that uses other Google products (like GMail or GDocs) will recognize this.

You can ’star’ certain profiles and then display only those that you starred. This makes it very easy to zoom through all profiles and find the ones you regularly use. Unfortunately starring is not available in the account view, just the profile view.

Try changing the number of rows displayed using the drop down at the bottom of the table… Notice anything interesting? The new interface uses AJAX to dynamically pull back the data. Pretty slick.

Another interesting AJAX feature is the ability to rename accounts and profiles right from the table. Just click on the little pen icon next to an account name or profile name. Is this totally necessary? I’ll let you decide. But given the new interface I bet a lot of people are going to rename their accounts and profiles.

With the new layout of accounts and profiles we can eliminate the website domain name from the profile and account name and use a functional description that everyone can understand.

One thing that is missing from the new admin screen is a summary row. I think it’s critical to have a scorecard, similar to the scorecard in the reporting interface, that displays summary information for the profiles and accounts displayed.

Overall, this is a fantastic change that goes a long way to helping us manage and analyze large GA deployments.

In the old days (i.e. last week) we needed to use filters and duplicate profiles to segment data. This approach worked, but it was a lot of work and had many pitfalls.

Feel like segmenting by time on site? No problem. How about average order value? We can do that two. Remember my post about segmenting time on site in Google Analytics? This technique is now dead. Rest in peace.

By the way, advanced segments are RETROACTIVE! This means that there is no need to reprocess historical data in Google Analytics. Well, there is no reason unless you mess up the implementation. You’re still out of luck if you do that.

For those of you that don’t feel like reading, here’s a quick video tour of advanced segments.

Creating an advanced segment is pretty easy. Google added a cool interface where you drag and drop dimensions and metrics you want to use in your segment.

Dimensions are the attributes of site visitors or the visits that they create. Think keyword, campaign, medium, new vs returning, etc. Metrics are basic counts of things that occur on the website. Think pageviews, visits, revenue, transactions, etc.

The concept here is that you choose a dimension or metric that you want to segment by, specify a value for that dimension or metric, and then create a relationship between the two.

Let’s start with an example. Let’s create an advanced segment to view all visits that last at least 10 seconds. Why? Because those people are leaving aweful fast and I want to understand why.

We start by choosing the Time on Site metric and dragging it to the correct location. HINT: If you don’t know whether you’re looking for a metric or dimension try the search!

Once we place our metric we specify a condition that it must meet and a value. In this case we want the time on site metric to be ‘greater than’ 10 seconds.

I want to call your attention to the Value field. This is no simple text field. This is a dynamic field that updates with all potential values while you type. The interface is reaching back into the data to show you which values have been collected for the metric or dimension used in the segment. Pretty slick, huh?

If we really wanted to get sophisticated we could add more dimensions and metrics to our advanced segment. Say we wanted to see all segments longer than 10 seconds from Google paid search. No problem, we can add ‘and’ and ‘or’ logic to link mulitple dimensions and metrics. Then we just keep dragging and dropping dimensions and metrics into the interface and adding values and conditions for each.

Once we’ve created our segment we can apply it to a profile. Once applied all the data in the profile will be segmented. Again, this includes historical data as well!

All Advanced Segments can be accessed via the Advanced Segment button in the top right corner of the screen. Click the button and you’ll see a nice big drop down with all your defined segments.

Advanced Segment area grouped in two categories: default segments (created by google) and custom segments (created by you). Notice how you choose a segment using a check box? This means that you can display multiple segments at the same time.

After you apply your segments the reporting interface will update and all reports will be segmented based on your criteria. We’ll see the results in a number of locations.

First, notice that the data over time chart will update to include all of the segments that you chose. (Note that you can only display 4 segments in the data over time graph even if you choose more than 4 segments).

Click to Enlarge.

Now you can trend multiple segments of traffic on one graph. This is really great for visualizing how multiple campaigns, mediums or geographic segments perform over time. How cool is that!

When you create an advanced segment it is tied to your specific user name. This means that you can use your advanced segment in all accounts and profiles that you have access to, which is pretty cool. Think of your advanced segments as a library that you can apply to different sets of data.

I’ll be writing a lot more about Advanced Segments in the future, especially some really cool segments that help analysis. But this should be enough to get you going. :)

Below is a list of all standards defined in the WAA metrics definitions document and GA compliance with each definition. GA is compliant with 19 of the 26 metrics. Most of the non-compliance is due to the fact that GA does not offer all the metrics that the WAA defined.

One thing I’ve noticed is the amount of promotion done with Twitter. Whether it be self promotion, like me promoting a blog post, or corporate promotion, like a sale, people are driving traffic to websites using tweets (posts on Twitter). Check out how CNN is driving traffic to their Political Ticker blog using Twitter.

Here’s another great example that was mentioned on the GokDotCom blog. Bryan Eisenberg found a t-shirt coupon posted as a tweet and passed the information on to his coworkers. Here’s the original tweet that Bryan read and sent on via email (I assume he used email):

Who wants a FREE $50 gift code? Here it is: TLTW7897 First come, first serve - and all tees are ON SALE FOR $12!! http://tinyurl.com/yqe9f

This got me thinking, how are people tracking Twitter as a marketing activity using Google Analytics?

Default Tracking Method

By default, traffic from Twitter will be tracked as referral traffic in Google Analytics. if someone clicks on a link to your site from a tweet you will see ‘www.twitter.com’ in the Referrals report.

This data will give you a basic idea of how much traffic your tweets are generating. It’s good, but there is an issue.

What happens if your tweet gets passed along to others, as it did in Bryan’s case? Bryan’s co-workers never clicked on a link at twitter.com, they received a link in an email. How can we identify these visitors as coming from Twitter and not an email?

Preferred Tracking Method

A better way to track a Twitter campaign would be to use GA’s campaign tracking feature. This method will track anyone visiting the site as a result of your tweet, regardless of where they clicked on the URL. It doesn’t matter if it’s in an email client, hosted email app. etc.

Here’s how to make it happen.

Most tweets that include a URL use some type of URL shortening service, like Tinyurl.com. This service shortens a URL by creating a redirect that is hosted on www.tinyurl.com.

The cool thing about Tiny URL is you can add GA’s campaign tracking parameters to your Tiny URL, thus encoding campaign info into the URL you use in your tweet. When someone forwards your tweet using email the tiny URL will contain campaign info identifying the visitor’s source as your Twitter campaign.

This is the secret to tracking tweets with GA: adding campaign information to your tiny URL.

Here’s an example. Here’s a tweet that I posted with a link to this blog:

Help me test tracking Twitter with Google Analytics: Please click on this link http://tinyurl.com/5eyfjo

I added GA campaign parameters to the Tiny URL in the tweet above. If you click the tiny URL in my tweet you get this URL:

http://www.epikone.com/blog/?utm_campaign=blog& utm_source=twitter&utm_medium=micro-blog

The campaign information in the URL will bucket the visitor as part of the blog campaign and as someone who was reached by the ‘micro-blogging’ medium. Here’s how the data looks in the All Traffic Sources report:

There it is in all its glory. But let’s dig deeper. I’m really interested in knowing how people are using Twitter. Are they on their mobile (like me) or PC? This can have a big impact on how they interact with my tweet. Let’s segment the tweet by OS:

7 of 25 users are on the iPhone, interesting. I know that I’m an iPhone user and it’s one of the only reasons I twitter. It’s just easy on the iPhone! :)

So if you’re using Twitter to drive traffic to a site:

1. Always use a Tiny URL
2. Always add Google Analytics campaign tracking information to your Tiny URL

If you’re unfamiliar with campaign tracking you may want to check out these posts:

Google Analytics Campaign Tracking Pt. 0: An Overview
Google Analytics Campaign Tracking Pt. 1: Link Tagging
Google Analytics Campaign Tracking Pt. 2: The EpikOne Link Tagging Tool

Update: You can use a number of URL shortening services such as TwwetBurner and SnipURL. Both of these services also provide some basic reports on the number of clicks your shortened URLs generate.

Good luck!

But over the past few weeks Google has rolled out a few other subtle changes to GA that may indicate changes and future enhancements.

1. Easier Login

There’s a new button to log into GA! Awesome, a new BUTTON! Woo Hoo!

Just kidding, while there is a new button, the real benefit is some added functionality that makes it easier for all of us that are in and out of GA on an hourly basis to access into GA.

You will now remain logged into GA even if you navigate away from GA or close your browser, just like you do when using GMail.

This is not a major deal, but I think it ties GA closer to other Google services. Combined with the layout and access changes to Website Optimizer (which is now organized more like GA), I think it moves us one step closer to the Google Business Platform. The same functionality already exists for Google AdPlanner, Google Insight for Search, etc. How long before all these tools are linked together?

2. Revamped Profile List

Google recently added website domain to the list of profiles that appears when you first log in:

While this change may not seem like a big deal, I think it signals a shift in the way that we think about profiles. For a long time I’ve been stressing that profiles are not websites, they are segments of traffic. That’s why we can, and should, create lots of profiles for a single website. This change facilitates that line of thought.

Changing the profile list to include the website URL makes it easier for us to name profiles something more descriptive, like ‘Segment: New Visitors’ or ‘Segment: CPC’. The addition of the domain simplifies profile naming and promotes the use of profiles as segments.

Could this have something to do with segmentation of data or might profiles fundamentally change? I’m not sure, but I know that it’s now a lot easier to organize all of the various profiles that we create for clients.

3. Bye, Bye Segments, Hello Dimensions!

This one came as a complete surprise to me. Google changed the ‘Segment’ drop down to a ‘Dimension’ drop down. The options in the drop down have not changed, and the functionality remains the same.

Does this mean we’ll be doing ‘di-mentation’ rather than ’seg-mentation’? HA!

Not only did they change the name from Segment to Dimension, but they also changed the location of the drop down. It moved from above the data table to within the data table. This reinforces that we need to start thinking in terms of Dimensions rather than Segments.

Now the important question, why this change?

I’m not sure. But I think this is a pretty big deal. I think this has something to do with the way that we segment data in GA. Given the change to the profile list, maybe segmentation will change into some type of ‘profile mashup’ tool, where you can mix data from different profiles into a single profile in order to do segmentation.

Who knows what will happen, but it’s Friday and I’m having fun with this.

What do you think these changes indicate?

In my opinion, it depends. It depends on your analytics needs.

We’ve worked with plenty of “enterprise” class organizations that were new to web analytics. They had very simple needs and GA met most of them easily. We’ve also told companies that GA is not right for them because it did not fit their core needs.

Your organization may be different. You may need a tool that integrates with ODBC data sources, something that GA doesn’t do very well. If that’s the case then you might need to go with a different tool. But again, it all depends.

But the point of this post is not to debate GA’s “enterpise-y-ness”, but to address some of the common issues that we usually see during an enterprise installation.

Issue #1. Tracking All Sites Logically

Large organizations tend to have more sites, and more sites mean more data. Collecting the data in an organized fashion, that allows room for growth and appropriate access for users, takes time and planing.

During an enterprise implementation we usually create a series of accounts and profiles that segments the data based on business logic and access needs. We create a data hierarchy that provides high level aggregate tracking across the entire online experience (i.e. roll-up reporting) and detailed tracking for each individual property.

Let’s consider the websites for Major League Baseball. Each team has their own site located on a subdomain. There is also an MLB store and different micro sites dedicated to things like the All Star Game and the World Series.

Lots of content on many different sites. While the exact implementation solution will depend on their specific needs, it probably involves collecting all the data in a single profile for roll-up reporting and then creating profiles for each team and micros site for detailed reporting.

Issue #2. Unique Visitors

Tracking lots of domains usually leads to an issue with unique visitor tracking. GA uses a first party cookie to identify each visitor. This means that if a visitor visits 3 different domains they will receive 3 different cookies and appear as three different unique visitors.

Now, I know GA has a cross domain tracking feature. But what happens if an enterprise wants to know the unique visitor count across 50 web properties? Installing cross domain tracking on that scale is a huge task. In fact, it’s a pain in the ass.

Many of the clients that I’ve worked with have compromised and ignored unique visitor tracking.

You may be different. Unique visitors may the one critical metric that you can’t live without. Could you use GA? Maybe, but you should carefully weigh the implementation needs vs. your analysis needs.

Issue #3: Page Tagging

When I first started working with GA I never thought that tagging pages would be an issue, but it is. It’s not so much a technical issue as it is an organizational issue. Big companies can have so many sites with some many nooks and crannies. It can take a lot of work to identify every site, find an owner and then get the tags placed in the appropriate place.

And let’s not forget non-HTML pages. Tracking non-HTML content with Google Analytics can be a huge challenge. You can’t slap a JavaScript Tag on a PDF. When we work with large organizations we usually help then develop an automated click tracking script. This takes more time and more effort and doesn’t always work (usually due to page rendering delays).

Issue #4. URL Structure

This is probably one of the most difficult challenges we face when working with large sites that have hundreds of thousands of pages. GA will only track 50,000 unique URLs per day. While this is completely adequate for most sites “enterprise” sites can exceed this limit, especially if the site is content based (think about a some of today’s largest community sites, they have forums, blogs, and tons of user generated content).

What happens when you fill GA with 50k unique URLs in a day? You start to see ‘(other)’ in your content reports and you can no longer identify which pages visitors are viewing on your site.

To resolve this issue we usually need to create some type of bucketing strategy to ‘roll up’ pageview data into different content categories. This is normally done by matching requested URL patterns at the server level, and then generating a ‘virtual’ pageview in GA.

Sometimes we segment the data into different profiles, thus giving us more ‘buckets’ to store the data.

Again, the exact solution depends on many different factors, but this issue can be mitigated with some effort.

Issue #5. Campaign Tracking

This is a problem for everyone! I find very few clients whoa are diligent about tracking their marketing campaigns using link tagging. A general rule of thumb, the bigger the client the more challenging it is to track all online campaigns. Why?

Big organizations have different people running different campaigns. Many times they’re using one or more agencies to help run their campaigns. Getting everyone to use a cohesive link tagging strategy is a lot of work due to the sheer number of people that are involved. This is more of a training/process issue rather than a technical issue.

Wrapping Up

If you’re an enterprise organization, or consider yourself an enterprise organization, don’t discount GA without taking a hard look at your real analytics experience and your needs. GA might just work for you.

If you do decide to use GA don’t expect to slap the tags on your site and finish the configuration in a week. Like every tool out there, it takes time and planning to get things right.

Do you have experience with GA in a large, “enterprise” environment? Leave a comment and share your thoughts.