Companies should track how people react to these campaigns and which ones are most successful. But what’s the best way to do this with Google Analytics?

Some people use the standard campaign tracking to track internal campaigns. THIS IS INCORRECT AND SHOULD NEVER BE DONE. Using the standard campaign tracking for internal campaigns will cause problems with your source data. So don’t do it!

There are a few correct ways to track internal campaigns. You could use Event Tracking, Custom Variables or Virtual Pageviews. But I like to use GA’s internal campaign tracking tool.

What? You’ve never seen or used the GA’s internal campaign tracker? It’s in the profile settings and it’s called Site Search tracking! Did I fool you ;)

Site Search can easily be configured to track internal campaigns. Let’s walk through the steps to set it up and then the data and analysis.

Step 1: Create a New Profile

Because we’re using Site Search for an unintended purpose it’s best to configure these settings on a new profile. It’s not possible to use Site Search for both tracking internal campaigns and internal site search within the same profile. You need to have a separate profile to track internal campaigns.

Step 2: Tag your Internal Campaigns

Once you’ve created your new profile it’s time to tag your internal campaigns. Internal campaigns need to be tagged in a similar manner to external campaigns: you need to add query string parameterrs to your internal ad.

However, unlike external campaigns you do not use the standard link tagging parameters (utm_campaign, utm_medium, etc.). You get to make up your own parameters!

You can use one or two parameters for internal campaign tracking and you can name then anything you want. The reason you can use one or two parameters is that GA’s site search configuration uses two parameters, one for the search phrase and one for the search category.

Whatever you choose, make sure the parameters are not used for anything else.

TIP: Check your Top Content report for a complete list of your site’s query string parameters. Verify that the parameters you create are NOT in this list.

For the sake of this post I’ll use the parameter icn (shor for internal campaign name). This parameter will holds the name of the internal campaign. I’m going to use the following format for the value of the campaign name parameter

icn=[internal-campaign-name]

I mentioned that you can use two paramters. You don’t need to use two, but GA’s site search can be confiugured to track the internal site search phrase and a site search category. We’ll use the category paramter to track the internal campaign name.

I’m going to name the second paraeter ici (short for internal campaign info). Again make sure the parameter you’re using does not already exist. This second parameter let’s me collect details about the ad the visitor clicked on and the location of the ad.

Here’s a basic format:

ici=[ad-creative]_[location-on-the-page]

You can see that I’m stuffing a lot of information into the parameter. You can put whatever you want and GA will gladly suck it in. By adding more information we’ll get a granluar view of how the internal campaigns perform and which locations and variations lead to tbe most conversions.

If you don’t have different types of internal ads, or just don’t care about this level of detail, then you can ignore the add internal campaign info parameter. It blank, it’s up to you!

Now you need to define the values for all the ads. Thic can get messy if you’re running a lot of internal campaign. But you can do it, just be organized! Use a spreadsheet to keep track of all the values you use.

Once you’ve got al your parameters it’s time to tag your links. The exact process depends on your site. You may need to change static links, like this:

< a href=”/internal-page.php?icn=2010-spring-sale&ici=stubs_home-roller >

Or if you have complicate flash ads you may need to get inside the Flash code. It depends on your site.

The bottom line is when somone clicks on an internal ad you want to see your internal campaign parameter on the next page. If you don’t see the parameter in the URL then you did something wrong.

You can use the sample spread sheet below to track the different parameters you use for your internal campaigns. The spread sheet also has a formula in column D to automatically add the parameters to your URLs.

NOTE: There is an iFrame in this post. If you can not see it, you can view the original post here or view the Google Spreadsheet here.

Once youe’ve got the parameters added to your links it’s itme to configure the Site Search settings.

Step 3: Configure Site Search Settings

Remeber, we’re configuring these settings on a new profile so we don’t break the site search in our main reporting profile.

Site search has three settings. First, turn site search on.

Next, tell GA the name of the paramter that holds the site search phrase (in this case it’s out internal campaign name) by adding the parameter to the ‘Query Parameter’ filed.

Next, choose Strip Query String Parameters. This setting will remove the parameter from the URL after GA processes the data. This is a good idea because it reduces duplicate pages in your top content reports.

TIP: You probably want to exclude your internal campaign name parameter, and internal campaign information parameter, from your other profiles. It can really mess up your pageview data.

If you’re using an internal campaign information parameter configure the Site Search Category settings the same way. Just make sure you use your internal campaign info parameter in the ‘Category Parameter’ setting.

Here’s how the settings look using the parameters from my example:

That’s it! Let’s look at the data.

The Reports

Let’s start by answering a simple question: do people who respond to internal camapigns convert more or less than those that do not respond to internal camapigns? To answer this question use the Content > Site Search > Usage report. Here we can see that there were only eight visits that clicked an internal campaign. Sad! But it’s just test data.

Now let’s drill deeper ad identify which inernal camapigns are most effective. Use the Content > Site Search > Search Terms report. Rather than search phrases this report contains the names of all internal campaigns. Again, what was the response to the campaign? Was it worth the effort? Don’t forget to check the Goals tab and the Ecommerce tabs (if applicable) to measure outcomes!

But let’s drill deeper to understand which ads within those campaigns are working. Click on a campaign name and choose Category from the Analyze drop down.

Now we’re looking at all of the information that we put into the ici query string parameter for this particular campaign name. If we had multiple internal ads we’d be able to differentiate ad placements and creative variations.

Don’t forget to use the Goals and Ecommerce tabs to measure outcomes! This is what most people want to know: did internal campaigns, and specifically which internal campaigns, generated revenue and conversions?

But we can do more. Now change to the Content > Site Search > Start Pages report. Now you can see which page people were on when they click on an internal ad. Again, more insight into where visitors responded to an internal campaign.

And for all those marketing folks that are so concerned with internal campaigns, how about creating a nice custom report and automating the delivery or, better yet, use the Custom Report Sharing feature to share this report with others. People will love this because you can change the wording so it does not say Site Search it says Internal Campaigns Report.

But wait, there’s more! What about using a secondary dimension to view the external marketing campaigns (or sources, or mediums) that drive visitor to react to internal campaigns. Perhaps the extrnal creative has some influence over how visitors react to the internal campaign creative. The data isn’t so hot in the image below, but you get the idea.

And finally, the ultimate in analysis, internal campaign attribution. We can use the Search Term Refinement feature if visitors click on multiple internal campaigns. Google Analytics will track all subsequent site searches, but in our case follow up site searches are actually additional internal campaigns that the visitor responded to. Honestly, I have never found any insights from this type of analysis, but you can do it if you want!

Ok, I’ve officially entered nerdville.

I think you get the idea. By adding all this data you can do many different kinds of segmentation and analysis. More than enough to understand the behavior of your site visitors and how your internal campaigns perform.

Last but not least, I’ll mention that you can track internal campaigns using events and custom variables. But both of those solutions require coding. And that requires working with IT. Using Site Search, in most cases, will not require any code changes to your site.

Tracking Internal Campaigns with Google Analytics is a post from: Analytics Talk by Justin Cutroni

Throughout the discussion it has become clear that the classic first click and last click attribution models that many web analytics tools use are flawed. The problem is no one has come forward with a better solution to the attribution issue… until now.

Google has taken a very low-risk move by tackling campaign attribution for AdWords only. The new AdWords Search Funnel reports help marketers understand which cpc ads people see and click on prior to converting.

If you’re looking for details about the reports and how to use them check out the video below from Google. The new Search Funnel reports have not been rolled out yet so no one has had a chance to play with them. Hence no real description here :)

We’ve long known that people see a lot of different cpc ads during a sales cycle. Avinash Kaushik calls these keywords “upper funnel” keywords. They are used by people that are early in the buying cycle. While many of these keywords don’t always lead to a conversion they help educate a potential customer and move then closer to purchasing a product or service.

Even though they do not directly generate revenue there is some value in bidding on upper funnel keywords.

Up until now we haven’t had many ways to help us understand the true value of upper funnel keywords. Sure, we can use time on site or pageviews per visit to measure “engagement”, but that was a bit of a hack. We can also create all sorts of custom JavaScript to store the first click and last click in a Custom Variable. But again, these are just hacks.

The Search Funnel reports are a well thought out way to understand how people interact with AdWords ads prior to conversion and thus help us understand the ROI of our AdWords spend. The reorts provide insight into which keywords

I think this is a good first step by Google. They took reliable set of data that was just sitting around a data center and created some reports that will help marketers understand the real value of different types of keywords. This is all very low risk for Google with very high potential (read: more AdWords revenue).

But these new reports are also a good test of how users, and the overall analytics market, will respond to Google’s version campaign attribution reporting. Real attribution models are very complicated to create. They involve a lot of data about different types of campaigns (banners, cpc, email, etc.).

[Side note: Why is it that we haven't seen any DoubleClick data in Google Analytics yet? Pulling that data into GA will be critical for real attribution measurement.]

In addition to the data complexities, every business will have their own way to weight certain marketing activities in an attribution equation. For example, some companies may value email more than paid search. This business logic will be difficult to implement. Not impossible, but difficult.

At the end of the day the new AdWords Funnel reports are exciting. But I’m excited to see how Google takes information about how these reports are used and tackles the bigger challenge of true campaign attribution!

Google Tackles Campaign Attribution with AdWords Search Funnels is a post from: Analytics Talk by Justin Cutroni

Simply put, Google Analytics will attribute a ‘bookmark’ visit to the information in the Google Analytics campaign cookie.

Many people believe that GA tracks bookmark visits as (direct) traffic. Google Analytics does not track bookmark traffic as (direct) traffic unless (direct) is the value in the cookie. Whatever is stored in the campaign cookie becomes the source of the ‘bookmark’ visit.

The cookie is named __utmz, I’ve talked about a few times, in my series on Campaign Tracking and my post on GA – CRM integration. __utmz always stores where the visitor came from (organic search, campaign referral, etc.)

How about a quick video to walk through an example and save me some typing.

How Google Analytics Tracks ‘Bookmark’ Visits is a post from: Analytics Talk by Justin Cutroni

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

Tracking Email with Google Analytics is a post from: Analytics Talk by Justin Cutroni

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.cutroni.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!

Twitter and Google Analytics: What to Track is a post from: Analytics Talk by Justin Cutroni

But what about YouTube videos that are embedded in a site? What’s the best way to measure interactions with these videos? You could use some basic metrics like Avg. Time on Page and Avg. Time on Site, but they’re averages and, well, averages suck. Fear not, there is a better way.

We can track almost every aspect of an embedded YouTube video using Event Tracking, a Google Analytics beta feature.

There is one catch. In order to track an embedded YouTube video you must use the ‘chromeless’ YouTube player. A chromeless video player has no controls which means you must create all of the controls yourself. This results in a fair amount of coding.

Why do we have to use the chromeless player? The chromeless player let’s us add JavaScript code (i.e. GA Event tracking code) to user actions, thus giving us the ability to capture visitor actions as events. I’ll do my best to walk you through all of the code.

You can read more about the chromeless YouTube player on the YouTube developer site.

Let’s get started.

Event Data Model

Before we look at any code let’s talk about data and analysis. One of the keys to any successful event tracking implementation is a clear definition of the data we want to collect. Remember, event tracking is really a flexible data collection tool. We need to explicitly define the data we want to collect.

I want to track three primary things related to the embedded video:

1. Which video does the visitor choose to watch?
2. How do they interact with the video player (i.e how do they use the controls)?
3. How much time do they spend watching each video?

Now let’s translate these needs into the Google Analytics Event model which consists of Objects, Actions, Labels and Values.

Objects

The object is the part of the page that we want to track. Defining the object in this case is pretty simple: we want to track the YouTube video player, so we’ll create one object and call it “YouTube Video Player”. The object will literally be created in the code and I’ll explain how later.

Actions

Actions are the interactions that the visitor exerts on the object. What we want to track, and what we can track, really depend on what interactions we can capture. In this example, the actions we can capture are directly related to the chromeless YouTube player and what it ‘bubbles up’ for visitor interactions.

Based on the chromeless player, and the data needs we have defined, here are the actions that we are going to track:

• Player Loaded: Indicates the YouTube player has loaded. No video has been loaded into the player, but the player is ready for a video.
• Video Started: Indicates the user has chosen a video and it has started playing in the player.
• Play: User has restart the video after it has been paused.
• Pause: Video has been paused.
• Mute: Video has been muted.
• Unmute: Video has been unmuted.
• Error: An error has occurred.
• Ended: Selected video has ended, either intentionally or on purpose by the visitor.
• Get Embed Code: Request HTML code to embed the video in a site.
• Get Video URL: Request YouTube URL for the current video.

Like the object, actions are actually created in the code and we’ll see how later.

There are other things that we can track, but I’ve decided to limit it to the above list. Why? I don’t think there is a lot of insight that can be gained from some of the other information that is available to us. Plus the above actions will cover the data needs we’ve defined.

Labels

Labels are the content of the object. In the case of most video player object, the label will be the name of the video playing. In this example you can choose three potential videos from a drop down box. The name of the video will become the label that is tracked in Google Analytics.

• Apollo 11 Launch
• About the YouTube API
• Phish – Weekapaug Groove
• Authors@Google: Avinash Kaushik

Values

This is where things can get a bit unique. The value collected by GA’s Event tracking is just a plain integer. All values associated with actions are summed and averaged. So we can’t mix different types of data, like monetary values (which may be in dollars) and time (which may be in seconds). For this example, we’re going to track time, so the values will be in seconds and will represent the total time that each video played.

I’m only going to associate a value with a single actions: Ended. When a video ends we’re going to record the total number of seconds played for that video.

The Example

Now that we’ve created the data model for tracking a YouTube player, we need to create a YouTube player to track. :) Remember we can only access visitor actions when we use the chromeless YouTube player.

Here’s a simple page that I created using the chromeless player and Google Analytics Event Tracking.

If the above iFrame is not visible, you can view the entire code here.

For those interested, this test page is actually a modification of the YouTube API example.

To start the tracking, select a video from the drop down and it will start playing. Then experiment with some of the controls. All actions that we defined in our event model will be tracked.

If you want to change videos just choose a new video from the drop down box.

I don’t want to go over too much of the code, but here’s the JavaScript behind the tracking.

If the above iFrame is not visible, you can view the entire code here.

A majority of the code is not Google Analytics code, but rather YouTube player code. What I’ve done is added the Event Tracking code in the appropriate places to capture the visitor interactions. Setting up the event tracking code is really pretty simple.

The first thing I did was create the Object, which is called ‘YouTube Video Player’. I created the object in the main GA page tag.

<script type='text/javascript'>
var pageTracker = _gat._getTracker("UA-XXXXXXX-X");
pageTracker._initData();
pageTracker._trackPageview();

// Create the event tracking object
var ytpEventTracker =
pageTracker._createEventTracker("YouTube Video Player");
var eventLabel;
</script>

After creating the object I added the _trackEvent() method wherever I want to capture a visitor action, like Play or Pause. Here’s how I capture the Play action:

function play() {
  if (ytplayer) {
    ytplayer.playVideo();
    ytpEventTracker._trackEvent("Play",eventLabel);
  }
}

Most of the Play code is actually YouTube code. The only GA specific code is ytpEventTracker._trackEvent("Play",eventLabel);.

We pass three values to _trackEvent(). The first is the name of the action and this value will appear in the GA Actions report. The second value is the lable value which will appear in the Labels report. I should note that eventLabel is the name of the video (per the data model) that is currently playing when the visitor clicks on Play.

The final value, which is not shown above, is the value value. In this example, the value is the total number of seconds played. This is only recorded for the Ended action.

If you look at the example code, all I really did was add ytpEventTracker._trackEvent() to all the actions that I wanted to track.

The Results

Enough with all the techno-mumbo-jumbo. Let’s look at some of the data starting at the top of our hierarchy: the Object report.

Noting too exciting here. We’re only tracking a single object here, hence the one line of data. The data can be a little confusing. The total number of events is really the total number of actions that occurred. The number of unique events is the number of visits that included an event.

But let’s dig a bit deeper. Let’s see which video was most popular by viewing the labels associated with the YouTube Video Player object. All I need to do is click on the Object name to view the associate labels and actions, and then choose ‘Labels’ using the Detail Level link above the table tabs.

Here we can see that ‘Phish-Weekapaug Groove’ was the most popular video, when based on time. It had a higher total value than the other videos. Sorry Avinash. :)

One thing to notice is that measuring the popularity of each video based on Events is not correct. Just because a label has the most actions does not mean that it is the most popular.

Remember, an action can occur ever time a visitor interacts with the player. In this example it would be more accurate to judge popularity based on time.

Now let’s see how people interacted with the most popular video. What actions did visitors perform when ‘Phish-Weekapaug Groove’ was playing?

All I need to do is click on the label name to see the actions associated with the label.

Cool, here we can see that the video was started 32 times, but only completed 12 times. It was viewed a total of 1775 seconds but only an average of 143 seconds.

What does it all mean? I know that the Phish video is 179 seconds long. So, on average, visitors viewed 80% of it. I can also tell, by the number of unique events, that the Phish video was viewed multiple times in the same visit. It must be pretty popular.

I also want to point out that we can view the data in other ways. We can navigate directly to the Actions report to see a list of all the actions, regardless of the object or label they are associated with. This is a great way to get a feel for the most commonly used features of our YouTube player.

Conclusion

So was this really worth it? Sure, I think so. I wanted to create a real life example that demonstrates some of the ways to use Event Tracking. I also wanted to use YouTube as an example because so may people use it as a platform to distribute video.

While it may seem like a lot of work to track video and other web 2.0 technologies it is vital. If you’re spending money producing videos, or if you’re selling video ad space, you need to know how people interact with your player and content. It’s the perfect use for Event Tracking.

Tracking YouTube Videos with Google Analytics is a post from: Analytics Talk by Justin Cutroni

To manage our link tagging effort we’ve created a tool in Google Spreadsheets that automatically generates tagged destination URLs. All you need to do is fill in the values for the Google Analytics tracking variables and a built in formula does the rest. Here’s a link to the file. Please help yourself :)

http://spreadsheets.google.com/ccc?key=p7c_HKcmspSUfEYSO0gskKw&hl=en

How to Use The Tool

1. Click on the above link to open the Google Spreadsheet. Once open, use the menu in the top left corner (File > Export >xls) to export the file to your hard drive.

2. Once you have the file on your machine, open it using MS Excel.

3. Delete all the demo data in the file EXCEPT the equation in cell G8. Cell G8 contains the equation that does all the work.

4. Enter your campaign information into the corresponding columns. Enter a dash (-) for all variables that you are not using. You should always use the campaign, medium and source variables.

5. Add the destination URL to the destination URL cell. Don’t worry if your destination URL already contains query string variables, the tool is smart enough to handle them.

6. Cell G8 will automatically build your destination URL.

7. Continue entering your campaign data in new rows.

8. Copy the formula in cell G8 to other rows. The tagged destination URL will be created automatically.

After you have your destination URLs you can paste them into your on-line ads.

Let me know if you find this tool useful or a complete pain in the as*. Got a better tool and feel like sharing? Post a comment below!

*** Note: EpikOne assumes no liability for those that choose to use this file. ***

Google Analytics Campaign Tracking Pt. 2: The EpikOne Link Tagging Tool is a post from: Analytics Talk by Justin Cutroni

To track your marketing campaigns Google Analytics uses a technology called link tagging. This provides a fine level of detail about marketing efforts. The data we gather from link tagging helps us make informed business decisions about our marketing spend.

With link tagging, we add additional information to the destination URL used in an ad. The technical name for this additional information is the query string. Here’s an example:
http://www.cutroni.com/landing_page.php?utm_campaign=fall-sale
&utm_medium=banner&utm_source=boston.com&utm_content=text-only

*** NOTE: I moved some text to a second line for readability ***

Everything after the question mark is called the query string. Within the query string we have a number of parameters. Each parameter is separated by an ampersand (&). Pulling apart the above query string we find the following parameters:

utm_campaign=fall-sale
utm_medium=banner
utm_source=boston.com
utm_content=text-only

Each parameter can be further divided into two parts; a variable (the text on the left side of the equals sign) and a value (the text on the right side of the equal sign). Let’s break the above parameters into variable – value pairs:

Ok, stick with me. We’ve gone from a query string, to parameters, to variables and values. Now, let’s start to explain what all of this means. What are the variables and values? I’ll start by explaining the variables:

It’s important to note that you do not always need to use every variable. The core variables are utm_campaign, utm_source and utm_medium. You should always use those three. With Campaign, Medium and Source you’ll reap the most benefit from Google Analytics.

Just to recap, link tagging is the process of adding additional information to the destination URLs we use in our ads. This additional information consists of variables and values.

Here’s the really cool part, the values. The value for each variable is a piece of business information that will end up in Google Analytics. Let me clarify that, you’re actually taking information that is specific to your business, like the name of a marketing campaign, and placing it in Google Analytics. GA will display it, exactly as it is typed, in a series of reports called the Marketing Campaign Results (see Part 3 of this series). This is extremely powerful because you can look at your analytics data through the lens of your business.

So now we know everything about what link tagging is, but what happens after we tag our links?

When someone clicks on a tagged link Google Analytics, using the urchin.js JavaScript, stores all the values in a cookie on the visitor’s machine. That way we can track the traffic generated by each marketing campaign. When a visitor completes one of our goals we can view the marketing activity that drove them to the site.

It’s important to understand that the cookie will persist until 2038. It’s also important to understand that the cookie will be updated with other information. For details about how Google Analytics stores various referral information please see the following post: How Does Google Analytics Track Conversion Referrals?

How to Tag Your Links

The process of Link Tagging is simple. Start by identifying the information that you need to place in the variables. You need to identify the campaigns, mediums and sources that you use in your marketing activities and place it in your destination URLs. Then modify your destination URLs to include the new variables and values.
How do you do that? You can use any text editor, the Google Analytics URL Builder or the special tool I discuss in Part 2 of this series. I’m partial to the special tool :)

Remember, if you’re placing links to your site in cyber-space, you should be tagging them.

Google Analytics Campaign Tracking Pt. 1: Link Tagging is a post from: Analytics Talk by Justin Cutroni

With that said, I’ve put together a series of posts that will dive into Google Analytics Campaign Tracking. I wanted to preface the series with a ‘summary’ post so people know where I’m going.

Part 1: Link Tagging

I explain the technology behind Google Analytics link tagging. Don’t worry, this isn’t too technical and it is really important stuff to know.

Part 2: EpikOne Link Tagging Tool

I’ll give you guys access to an internal tool that we use to manage our link tagging effort. Hopefully this tool will save everyone some time.

Part 3: Reports and Analysis

We put our knowledge to work and start looking at some reports.

Part 4: Tips & Best Practices

This is a brain dump. Everything I’ve learned in the past 2 years about tracking online campaigns with Google Analytics.
So sit back, relax and get ready.

Google Analytics Campaign Tracking Pt. 0: An Overview is a post from: Analytics Talk by Justin Cutroni

Each time a visitor visits your site the Google Analytics Tracking code updates this cookie with the appropriate campaign information. When the cookie is updated GA discards the previous campaign information. As a result GA only tracks the current campaign information, not previous campaign information.

With that said, there is a ‘pecking order’ regarding which activities will overwrite the the data in the campaign tracking cookie. Let’s review how GA buckets your traffic in terms of referral information:

• Campaigns: links that you have tagged with campaign information
• Referrals: untagged links on other web page
• Direct: people who type your URL into a browser
• Organic: organic search engine traffic

Here is how GA updates the campaign tracking cookie based on referrer:

• Direct traffic is always overwritten by referrals, organic and tagged campaigns
• New campaign, referral or organic link that brings a visitor to the site always overrides the existing campaign cookie

Here’s an example. A visitor visits your site from a newsletter with tagged links. They look around and decide to leave. When they leave your site the campaign tracking cookie will persist and indicate that they originated from the newsletter.

The same visitor decides to come back the next day and types your URL into the browser. The campaign cookie will still indicate that the visitor arrived via your newsletter because the second visit was a direct visit, and direct traffic does not overwrite existing campaign information.

With that all said, you can configure GA to NOT overwrite the campaign data that is stored in the tracking cookies. This let’s you identify the first campaign that brought the visitor to your site. Here is the link:

http://www.google.com/support/analytics/bin/answer.py?answer=27247

However, this technique does NOT prevent the Google Analytics Tracking Code from updating the campaign cookie if a visitor arrives by organic search or untagged referral link. This technique can only be used to prevent tagged campaign links from overwriting previous referral information from a tagged campaign link.

So how do you get around this? Well we’ve come up with a hack that we’re using with a few of our clients. The goal is to store all referral information about a specific visitor across all of their visits so we get a better understanding of the sales cycle.

The Google Analytics Tracking Code re-writes the data in the campaign tracking cookie every time the visitor hits the site. We need a mechanism that can store data across multiple sessions and would only update the referral data and not overwrite it. To do this we wrote some JavaScript that uses the custom segment functionality to track the visitor’s referral information.

Here’s a brief outline for what the JavaScript does:

• When visitor lands on the site check the previous referral information.
• If there is no previous referral info then gather the referral info and store it in a custom segment using utmSetVar()
• If there is previous referral info, then UPDATE the custom segment to include the current referral information

While this isn’t an ideal situation it does help. Using the User-defined report we can identify conversion rates for the various combinations of referral information that drove the visitor to your site during the sales cycle.

Obviously this takes some technical know-how. But if you’re working with a client, and the client wants to know EVERY step in the process then this is a hack that can help.

So there you have. Some information about how Google Analytics tracks referral information. I think there are two key things to remember.

1. Not all referral information is created equal
2. You can configure GA to let your campaign information persist

You may also be interested in the series I wrote about Campaign Tracking with Google Analytics:
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
Google Analytics Campaign Tracking Pt. 3: Reports and Analysis

Thoughts? Questions? Leave a comment.

How Does Google Analytics Track Conversion Referrals? is a post from: Analytics Talk by Justin Cutroni