Specific things that Brett talked about:

The rebranding of Google Analytics consultants as Google Analytics authorized partners.

This was announced on the AdWords blog and on the Analytics blog. Google is unifying their partner programs. The GAAC is gone, now partners are Google Analytics Certified partners. This should help differentiate partner companies from individual passing the GAIQ exam.

The formal launch of the new Async tracking code.

It’s been out for a while but this was the official coming out for the new version of the tracking code. I wrote a about how the async code works and if you should switch. The async code will now be the default for tracking. Check out the blog post for more information about how it works.

The introduction of the Google Analytics Apps Gallery.

Google is creating a place to showcase apps built on the API. I’ve long felt that the marketplace can innovate more than any Analytics company. GA has more or less become a giant data collector. The gallery should help push more development of analytics tools.

The addition of the AdWords ID to the GA API.

It is now possible to pull actual ad and search query information via the API. This is huge, I think it’s going to lead to a lot of innovation in the search tool marketplace. Vendors like ClickEquations can now connect what happened on a visitors site directly back to the AdWords search query and ad variation. Pretty cool.

New AdWords reports.

Google also announced the addition of new AdWords reports to Google Analytics. I think we all agree that the previous reprots were less than good. The new reports offer additional data, like the actual search term, that was not previous available in Analytics.

Brett also spoke about the recently introduced AdWords Search Funnels. This is Google’s crack at AdWords campaign attribution. My buddy Nick dove a little deeper over on the WebShare blog.

While some might look at this list and shrug that there’s not much new I think these changes hint at things to come. Specifically I think the AdWords API announcement is huge. This tells us Google is pulling more and more data into Analytics. How long before we get DoubleClick data and other types of data in Analytics? Or when will they let us import data into Analytics, like cost data?

Overall, a nice little treat for us analytics users. Thanks to the Analytics team and great job.

As always, I welcome your comments!

Google Analytics Launches new AdWords Reports & Other Goodies is a post from: Analytics Talk by Justin Cutroni

Related posts:

1. Google Tackles Campaign Attribution with AdWords Search Funnels
2. Google Analytics Campaign Tracking Pt. 3: Reports and Analysis
3. Segmenting Visitor Loyalty Reports in GA

fewer than 1% of search queries are affected by the site speed signal in our implementation and the signal for site speed only applies for visitors searching in English on Google.com at this point.”

This may be the beginning of Google’s use of site speed. It’s probably a good idea to think about speed when designing your site.

How GA can Slow Your Site

One thing that can potentially slow your site down is the Google Analytics tracking code. Specifically, the ga.js library and how the browser loads the file.

When a browser renders a page it literally starts starts to display the HTML from the top of the page and moves to the botton. When it hits a JavaScript file, like ga.js, it requests the file from the remote server.

Then it waits.

And waits.

And waits.

Once the file has been pulled into the browser it continues to process the HTML.

You can see the issue here, the browser could wait a long time for the JavaScript file depending on the visitors proximity to the server, the visitor’s bandwidth, and a bunch of other factors most of which you can’t control. Waiting for a page to render is a bad user experience. I know I don’t like to wait!

There’s a great example of how a remote file can make the browser slow down on the High Performance website blog.

Google tries to mitigate load-time issues by geo-loadbalancing ga.js, so the visitor’s browser will automatically contact the closest data center to load the ga.js faster.

It’s also best to place the ga.js at the bottom of your pages just in case there is an issue with the communication between the data center and the visitor’s browser. By placing the ga.js at the bottom of the page all of the content has already rendered, so the visitor won’t experience a blank or partially loaded pags.

While placing the GATC at the bottom of the page can mitigate some issues it can cause others.

First, it is possible for visitors to navigate away from the site before data is sent to Google Analytics. This leads to missing data.

Second, if you need to do any advanced tracking, like ecommerce or events, you may need to move the ga.js to the top of the page thus negating the benefit from putting it at the bottom of the page. This can also complicate your implementaiton because some pages may have the code at the top of the page and some might have the code at the bottom of the page which is a maintenance nightmare.

Using the new async code can help mitigate both of these problems.

How the Async Code Helps

First, The asyncronous version of the tracking code utilizes HTML 5 and the modern browser’s ability to load files asyncronously. This means that the browser can load files like ga.js while it continues to render the page for the visitor.

Second, the async code let’s us send data to Google Analytics before the ga.js has loaded in the browser. Technically we’re not sending the data to Google, but we are executing the commands that generate the data. The broser just holds the commands until the ga.js has completely loaded. Then the commands are executed (in the order in which they were added) and the data is sent to Google.

In the old days (like last year) we had to wait for ga.js to load before we could call any GA code. Not any more.

So the Async code is a good thing.

The big question is, should you use the async tracking code?

Well, if you’re concerned that Google Analytics is slowing down your site, and that it may be impacting your search rankings, then yes, use the async code. There are a number of free tools that you can use to test how long it takes ga.js to load on your site. (YSlow, Page Speed, etc.) Use them to determine if GA is slowing down your site.

If you decide to use the async version of the code there are a few things you should know.

Using the async code is slightly different than using the standard tracking code. Let’s look:

< script>
//
// This section creates the queue
//
var _gaq = _gaq || [];
_gaq.push(['_setAccount', 'UA-XXXXX-X']);
_gaq.push(['_trackPageview']);

//
// This section calls the ga.js
//
(function() {
var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true;
ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s);
})();
</ script>


The async code can appear anywhere in a page. But it’s best to place it at the immediately after the opening BODY tag. This let’s you add commands to the queue as soon as the page starts to render.

Some of the GA documentaion states that you can place the code in the HEAD tag. But this can cause some JavaScript issues with IE6. If you have a lot of visitors that use IE6 don’t put the code in the HEAD tag.

If you’re still leary about putting the code at the top of the page you can split the tracking code into two sections. You can place the first part of the code at the top of the page and the second part, the calls the ga.js, at the bottom of the page.

While this let’s you add commands to the queue immediately it is still possible to miss some GA data becayse the ga.js will be the last thing the browser requests. But the choice is up to you.

How the Code Works

Digging into the code a bit more, the first thing you’ll notice is the call for the ga.js is the second part of the code. This is the opposite of the standard tracking code. The async tracking code begins by creating the queue to store commands. Then the tracking code calls Google’s servers for the ga.js file.

The great thing about the queue of commands is you can add things to the queue whenever you want, even if the ga.js has not finished loading. This is what makes it possible to add GA commands at the top of a page.

The second section of code is the request to Google’s servers for the ga.js. It’s the exact same ga.js that’s used in the standard tracking code, it’s just pulled into the browser in a different way. Notice the ga.async=true part of the code? That’s the part that tells the browser it should load the code asyncronously. The browser not execute any commands in the queue until after the ga.js has loaded.

If you’ve got a basic site then all you need to do is add the async code to your pages and you’re good to go. You don’t need to worry about adding items to the que, etc.

But if you’re doing any advanced tracking, like virtual pageviews, events or ecommerce you need to know how to add items to the queue.

How to Add Items to the Queue

Adding items to the queue can be done a number of different ways. The easiest way is to “push” things onto the queue. This is done with the push command, as shown below.

_gaq.push(['_setAccount', 'UA-XXXXX-X']);
_gaq.push(['_trackPageview']);

If you wanted to add an event to the click of a link you would push the command on to the queue like this:

< a href="onClick='_gaq.push('cat','act','label');'">go red sox< /a>

Or, to create a virtual pageview you could push the command onto the queue like this:

< a href="onClick='_gaq.push('_trackPageview','/virtual/go-red-sox');'">go red sox< /a>

You can also add mulitple commands to the queue at a time. But this is where things start to get technical, and I’m not going to go there :)

How you implement the code depends on your site, the commands you want to add and how much JS you know. To learn more about how to add commands check out the GA Code site.

Switching to the Async Code

The complexity of migrating to the async tracking code depends on your site. If you’re not using any of the advanced GA features then migration can be as simple as swapping the tags.

But, if you are using advanced features, you’ll need to update all of the GA code on your site. Remeber, all the standard Google Analytics functionality in the ga.js exists in the async code. You just need to replicate your existing code in the async format. You can find an overview of the async code (written in nerd) as well as code examples, on the Google Code site.

Obviously the migration effort depends on the complexity of your implementation. But if you take your time and document your existing GA code and test your implementaiton thoroughly everything should go smoothly.

Have you tried the new async code? Got an experience you want to share? Leave a comment!

Faster, Better, Stronger. The GA Async Tracking Code is a post from: Analytics Talk by Justin Cutroni

Related posts:

1. GA.JS: New Google Analytics Tracking Code
2. Updated GA.JS Tracking Code
3. Tracking Clicks with GA Pt. 1: About urchinTracker()

In their own words:

We help businesses get in front of an online audience, convert visitors into customers, and use accurate measurement and intelligent analysis to drive decisions.

They manage paid search, they do usability and design work, they do website testing and they’ve been developing tools that utilize the GA and AdWords API.

The common theme through all of their services is analytics. Everyone at WebShare is completely analytics driven. And it’s not just Google Analytics. WebShare will use whatever tool you throw at them. And then they’ll suck the data out and use JMP or SPSS to really dig in. It’s this transition from standard web analytics to web intelligence that is exciting. While it’s not for everyone I’ve seen more and more organizations start to apply BI techniques to their web analytics efforts.

Don’t get me wrong, they’re a pretty big force in the world of Google Analytics and have have helped some major brands make the jump to GA. I’ll still get my GA fix but am excited to learn some more advanced things. :)

I’ll be doing a little bit of everything at WebShare. I’m going to help with all things analytics, from guiding implementation projects, to doing data analysis, to providing feedback on software development efforts. I’m also looking forward to advancing how many of our clients look at web analytics by speaking at more events.

With whatever time I have left over, I’ll continue to hit the road and teach Google Analytics & Website Optimizer Seminars for Success. In fact, I’ll be in Dallas next week with my new co-worker Julie doing a GA and WO event .

I’d like to personally thank everyone who took the time to send me an email, tweet, comment, telegram, carrier pigeon and smoke signal wishing me well. :) I really appreciate it, and it’s one of the things I love about the web analytics community. This is a pretty tight group that really supports one another.

Be well.

Now Batting for WebShare, Justin Cutroni is a post from: Analytics Talk by Justin Cutroni

Related posts:

1. Big Changes for Justin

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

Related posts:

1. Tracking Zero Result Searches in Google Analytics
2. Measuring Internal Site Search with Google Analytics
3. Tracking Sub Domains with Google Analytics

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

Related posts:

1. Google Analytics Campaign Tracking Pt. 3: Reports and Analysis
2. Google Analytics Campaign Tracking Pt. 0: An Overview
3. GA On Site Search Pt. 2: Reporting & Usage

After five great years at EpikOne I’ve decided to move on and seek new challenges. I haven’t shared this news with a lot of people until now. Let me try to answer what I think will be the most asked questions :)

Why are you leaving?

Every year I take stock of where I am professionally and what I have planned for the next year or 18 months. At the end of 2009 I decided that I needed a new challenge. If I’m not challenged at work I get bored pretty fast. I decided to start looking and was pleased to find that there is a lot of opportunity in the web analytics industry :)

What are you going to do next? Are you going to keep doing web analytics?

I am absolutely going to keep doing web analytics! I love this field. I love the people and I love the close knit community. I’m currently looking for a job and hope to have something lined up in coming weeks.

Are you going to keep working with Google Analytics?

HELL YES. I still think that Google has a lot of gas left in the tank and will continue to revolutionize the web analytics industry. I’m going to continue to do GA Seminars for Success and am working on a new GA book with some friends. I’m even going to update my first book GA Shortcut (seriously!). I am absolutely going to remain a GA Fanboy.

But that doesn’t mean I’m not going to work with other tools. I’ve been playing with CoreMetrics and a few other and hope to use more tools in my next role.

Why don’t you start your own company?

I thought about this a lot. But I don’t want all the crap of running a company. I want to focus on doing web analytics, not sending invoices, tracking down payment, etc.

What will happen to Analytics Talk?

You’ve probably noticed that Analytics Talk has been moved to my personal domain. I’ll continue to blog, hopefully more often! I’m also going to clean out the backlog of comments and slap a new design on the blog.

So there you have it. If you’re trying to connect with me you you can always email me via the blog or feel free to connect with me on LinkedIn or follow me on Twitter.

I want to say thank you to everyone that I’ve worked with at EpikOne. It was incredible to see you all grow and develop new skills during our time together. I’ll miss working with you all.

And a big thank you to all of the clients that I’ve worked with over the years. Thanks for pushing me to learn and grow.

Here’s to the unknown and new challenges!

Big Changes for Justin is a post from: Analytics Talk by Justin Cutroni

Related posts:

1. Headed to EMetrics

You can now create up to 20 goals per profile in Google Analytics. I can literally hear the applause at eMetrics :)

In addition to expanding the number of goals Google has expanded the types of goals to include ‘threshold’ goals for pageviews per visit and time on site.

I think we all know the importance of tracking goals, so I’m not going to get too deep into why you should use goals. If you’re not using goals you should start NOW!

Let’s talk about this new feature.

Goal Sets

Goals are now organized into four sets. Each set of goals can contain up to five different goals.

Sets have been introduced as a way to accommodate all the new data in GA. In the report tabs, rather than one goal tab there can be up to four goal tabs in a GA reports.

When creating a goal you can place it in any set as long as there is room. Once you place a goal in a set it’s best to NOT MOVE IT. Google Analytics sees this as a NEW goal and does not move the previously captured conversions to the new goal.

TIP: I like to organize goals by business function i.e. put goals that are related together. For example, if you’re a content site, you might create goals for spending a certain amount of time on site (1 minute, 2 minutes, etc.). I would group these goals in a set all related to time.

Goal Types

In the old days a goal was a pageview that represented the completion of some high value process, like a thank you page. Now goals can be based on actions that have nothing to do with viewing a page. Conversions can be based on how much time a visitor spends on the site or how many pages the visitor views.

Time Based Goals

Time based conversions are triggered after a visitor has spent a certain amount of time on the site. To configure a time based goal enter the hours, minutes and seconds that a visitor must spend on the site before a conversion is counted. Once the visitor reaches that amount of time on the site then a conversion is triggered.

What’s interesting here is that you can create a time based goal if a visit does NOT reach a certain amount of time. If you choose ‘Less Than’ Google Analytics will trigger a goal if a visit does NOT reach a certain length.

Why on earth would you measure this? I like to think of ‘Less Than’ goals as ‘Failure’ metrics. We often define success metrics, like Conversion Rate, but rarely define metrics to measure our failures!

Using failure based metrics really packs a punch when you’re talking to co workers or clients. For example, when you configure a failure goal you can easily measure and say, “Did you know that 97% of our traffic does not spend at least 2 minutes on our site? We suck!”

Abandonment rate is another well know failure metrics.

Time based goals can also be very useful if you’re trying to MINIMIZE the amount of time people spend on your site. For example, if you have a support section on your site you may want to understand what percentage of traffic spends a certain amount of time on your site. Long term you can try to reduce the number of visits that are too long.

How about setting up a goal set for various time intervals and then try to move visitors from one “goal” bucket to the next. 10 minutes, to 7 minutes, to 5 mintues… You guys are bright, you get the idea :)

Remember, time based goals can be affected by creating virtual pageviews and events. Both of these activities send data to Google Analytics and can change how visit length is calculated.

Pageview Based Goals

Another new goal type is pageviews per visit. Like time on site goals this this type of conversion is triggered when a visit exceeds a certain number of pages. I can literally hear all the advertisers clapping out there!

Pageviews goals are set up in the same manner as time based conversions. Just specify a condition (greater than or less than) and the number of pageviews in a visit.

Like time goals, pageview goals can also be affected by virtual pageviews. If you’re creating a lot of data using _trackPageview() you need to understand that this can change your overall goal calculation.

URL Destination Goals

The old standby! ‘Traditional’ goals are now called URL Destination Goals. You can still use a regular expression, head match or exact match to identify a page that represents a goal. This functionality has not changed (you can learn more about goals in this old post.)

Now that we have 20 goals we can easily measure all of those micro conversions (RSS subscription, email signup, reaching product page, downloading white paper… etc, etc, etc).

And yes, you can still use a virtual pageview as a URL Destination goal.

Funnels

Google did spend some time tweaking the interface. The old interface always showed 10 steps in the funnel. Now you can choose the number of fields the funnel form displays. You’re still limited to 10 steps in total. This isn’t such a big deal.

But think about the bigger picture. Do we really need funnels if we have so many goals? With 20 goals we can use a goal to represent each stage in a process, rather than a funnel step? So do we still need funnels?

Yes. Funnels provide a nice visualization of critical processes, so I think they are still relevant. Plus, you need to configure a funnel if you want to measure Abandonment rate, a very nice failure metric that can make people squirm :)

Odds and Ends

A few random thoughts re: new goals:

If you’ve been creating lots of profiles for goals you may want to consider consolidating all goals to a single profile. The benefit is you can have all your conversions in one interface. No more messing with multiple browser tabs and adjusting the date range.

If you need to control the access to certain goals, you may need to create a profile for certain goals and then give only the people who need access to those goals access to the profile.

A visitor can only convert at each goal once per visit. This is the way it’s always been.

And finally, creating new goals will not modify your historical data, only future data. So all those new goals you’re going to create this week will only track from the day your create them onward.

New Google Analytics Goals is a post from: Analytics Talk by Justin Cutroni

Related posts:

1. Time-On-Page Goals in Google Analytics & Website Optimizer
2. All About Google Analytics Goals
3. Getting More out of Google Analytics Goals

Unique visitors is a critical metric especially in the advertising industry. But it’s also a really hard metric to measure because it take a lot of data processing power. Why? Because of the way unique visitors are identified and measured.

Google Analytics defines a unique visitor as a cookie. For all you nerds it’s the __utma cookie.

Every time a visitor visits a site GA checks for the cookie. If the cookie exists then GA knows the visitor has been to the site before. If the cookie does not exist GA sets the cookie and increases the unique visitor count.

The challenge is that every time you want to view a report that contains unique visitors GA has to literally count all of those cookies collected to find how many are unique. That’s why there was only one GA report with Unique Visitors (Visitors > Visitor Trending >Absolute Unique Visitors report).

But Google figured out some way to effectively count all of the cookies in real time. Now the unique visitors metric that can be added to any custom report.

If you need to segment unique visitors you can simple create a custom report and include this metric.

Here’s an example. Let’s say you’re running a branding campaign for an upcoming movie. You want to measure how many actual people visit your website. You can create a custom report with the campaign dimension and the Unique Visitor metric.

There is one technical limitation. Google Analytics will sample data when a date range for the custom report contains more than 200,000 visits.

Still, I’m completely amazed that they figured out how to make this happen.

Segmenting Unique Visitors in Google Analytics is a post from: Analytics Talk by Justin Cutroni

Related posts:

1. Segmenting Visitor Loyalty Reports in GA
2. Segmenting Members from Non-Members
3. Google Analytics Compliance with WAA Standard Metrics

Like Custom Segmentation, custom variables are a flexible way to add more information to Google Analytics. The big difference is that you can create LOTS of custom variables. How many? In theory you can set an infinite number of custom variables. But GA has some internal limits that keep you to 50,000.

What can we use custom variables for? The possibilities are endless:

• Segmenting members from non-members
• Segmenting customers from non-customers
• Tracking all the campaigns a visitor sees prior to converting
• Content categorization
• Segmenting visitors based on landing page
• Visitor segmentation based on demographic info
• Customer segmentation based on order history

As my friend Phil likes to say, custom variables are decorations that you hang on your data. Almost like holiday decorations hanging on a tree! This is a really good analogy that I’ll continue in this post.

There are four critical attributes of a custom variable that we must understand in order to use them.

Name and Value

The easiest attributes to understand are Name and Value. The Name of a custom variable is literally the name you give to the variable. Each variable can have many, many values. For example, you could define a variable named ‘Baseball Team’ and then add the values:

• Red Sox
• Yankees
• Phillies
• Giants
• Angels

This is totally different than the old Custom Segmentation feature. With Custom Segmentation you were limited to one variable (ie one Name) that could contain multiple values. Now you can create multiple variables each of which can have multiple values.

You can view all of your variable names in the new Custom Variables report.

It’s important to note that the name of a variable, plus the value for a variable must be less than 64 characters. Why? The data is sent to Google via a request for an image file. The actual length of the request is limited and Google wants to insure that all of the data makes it to the server.

Scope

The real power of custom variables comes with something called the Scope. Think of scope as the different ‘levels’ of visitor data. When a visitor visits a website Google Analytics collects data at three levels:

• Pageview level: This is data associated with each page viewed during a visits. Page level data can change from one page to the next.
• Visit level: This is data associated with the visitor’s entire visit. This data can change from one visit to the next. But visit level data is applied to every page within a visit. This data only exists for the CURRENT visits.
• Visitor Level: This data is applied to the visitor and every visit and every pageview that the visitor generates. This data persists across all visits that a person creates. How does it persist? Via a cookie.

This means we can set information, ie custom variables, at the page level, the visit level and the visitor level. If we think of custom variables as decorations “hanging” on our data then we could use the following graphic:

So scope is the same as level. Anyone drooling out there?

The ability to control the scope of a custom variable makes this feature extremely flexible. For example, if you want to group all of the content on your site you can add a page level custom variable to every page that identifies the groups that a page belongs to.

If you want to segment visitors by their purchase history you can add visitor level custom variable. The possibilities are truly endless.

Let’s take a look at some of the reporting so you can get a feel for some of the data.

Here’s the Custom Variables report. You’ll notice it looks a lot like the user defined report. This report contains all of the variables that you defined. If you click on a variable you’ll see all of the VALUES for that variable.

So why has google added a scope if we can’t see it in the reports? I’m just going to let you guys speculate. But it’s obviously a critical part of CVs and we should see that data.

Index

The last attribute that we need to discuss is something called the Index. To be honest, it’s really hard to define the index. Basically the index is a technical attribute that helps GA organize all the custom variables on a page.

It’s only used during the implementation, so we’re not going to dig any further in this post.

Speaking of the implementation, you’ve probably noticed that I haven’t talked much about the implementation. To be honest, we’re still playing with CVs. Obviously this data comes from JavaScript. So you have to do some coding to get this data.

But I’m going to hold off on the implementation talk until later. Implementation involves another concept called the Index which is, to be honest, vague and confusing.

Google Analytics Custom Variables Overview is a post from: Analytics Talk by Justin Cutroni

Related posts:

1. Google Analytics Configuration Mistake #2: Query String Variables
2. Event Tracking Pt. 1: Overview & Data Model
3. Custom Segmentation with Google Analytics

Included in this new release is:

• New and Improved Goals (20 goals per profile and new ‘threshold’ goals based on pageviews and time on site)
• New mobile tracking
• Table Filtering (a way to quickly filter data in a report)
• Unique Visitor Segmentation (Unique Visitors is now a metric and can be added to custom reports)
• Multiple custom variables (an evolution of Custom Segmentation, wicked awesome!)
• Analytics Intelligence (automatic data analysis. And yes, it is as cool as it sounds!)
• Analytics Alerts (customizable alerts based on your data rules)

NOTE: Links above are to individual posts.

There are also a couple previously announced features that have FINALLY made it into the product, including:

• Sharing custom reports and advanced custom segments
• Pivoting data and segmenting with a secondary dimensions

I must say, this release is very cool. Google has listened to users and included some of the most requested features. 20 goals, automatic alerts, more custom variables… We’ve been hearing/making these requests for years!

One thing I think people will ignore is that many of these features represents dramatic improvements in the GA system. While these features have a definite ‘wow’ factor they provide a solid foundation for future enhancements.

If you’ve been reading this blog for a while you know that I usually blast out as many posts as possible to explain the new features. Today is no different.

Because there are some many people blogging about GA, I’m going to be a bit selective and cover the topics that I don’t think will get much attention or that I just really like :)

So click away! Let’s all explore these cool new features together!

Introducing Google Analytics v4 is a post from: Analytics Talk by Justin Cutroni

Related posts:

1. Introducing Urchin 6
2. Introducing SiteScan
3. Google Analytics Version 3.0