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

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

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

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

This new release includes:

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

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

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

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

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

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

Google Analytics Version 3.0 is a post from: Analytics Talk by Justin Cutroni

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

Click to enlarge the image.

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

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

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

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

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

click to enlarge.

This is where things get really juicy!

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

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

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

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

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

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

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

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

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

Getting to Know the New Google Analytics Admin Interface is a post from: Analytics Talk by Justin Cutroni

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

Google Analytics Compliance with WAA Standard Metrics is a post from: Analytics Talk by Justin Cutroni

But I believe that many of us, myself included, are really missing the point when it comes to Google Analytics. I don’t think that we fully embrace the paradigm shift that Google is pushing with GA. Let me explain…

By releasing Google Analytics for free, Google has thrust web analytics into the mainstream. This is great for our industry, but it places a heavy burden on Google. They must provide a product that makes analytics easy.

But is web analytics easy? That’s debatable, but the simple truth is that there are millions of people out there getting into web analytics via GA and Google needs to help them understand their data.

Paradigm Shift #1: use GA to do more analysis.

Google Analytics is designed to facilitate the understanding of click stream data. How? By providing an interface that helps people explore their data by providing lots of context. All of the time spent redesigning GA was for one reason: to create a product that makes analysis easy for everyone. That’s a rather lofty goal but it is analysis most critical part of being a web analyst. If GA can help us understand what’s happening with our website then we can take action.

Have people embraced this idea? To some extent, yes. Many users I talk to like the features in GA and feel that it is an effective tool for analysis. But there is a huge number of users that still do not understand or know about many of the features in GA. Believe it or not, people still don’t know that you can track different types of online advertising, not just AdWords. A large segment of people use GA to track “hits” to their site.

Let me caveat this by saying that there are some analysis tasks that are just not possible in GA. However, these tasks are usually more advanced analysis techniques, like applying a control limit or doing a long tail analysis. Perhaps the GA team will ad advanced features as the product matures with the market.

Paradigm shift #2: less formal reporting, more pestering!

Just as important as understanding the data is the distribution and access to the data. Google has tried to facilitate this need in two ways.

First, access to Google Analytics is pretty easy. Anyone with a Google Account can get access to a GA account. Three fields and two clicks and you can add someone to your analytics account. It’s that easy. And, to the best of my knowledge, there is no limit to the number of users. Now Joe in IT can access the data along with Kathy in marketing.

Second, the new GA redesign included email reports. While this does not seem like a revolutionary feature, the ability to distribute actionable data, to anyone, at any time, helps drive change. Why export data, create a report and then email it when you can email it right from GA? You can pester your co-workers and contractors (who are the ones that usually need to take action on the data) with the information they need to make change.

I don’t think that many people have really embraced GA’s email reports feature. Multiple people a week ask me how to get data out of GA so they can create elaborate dashboards or other reports. They try to force GA into their current reporting framework rather than trying to change. I’m not saying this is wrong, but I think we need to give GA’s features a chance.

Parting Thoughts

While Google Analytics is not the end-all be-all web analytics application, it is a solid foundation that will continue to evolve and meet the needs of a growing and maturing user base. The big question is, will we embrace the change that many of GA’s features support, or will we continue with analytics as usual?

Think I’m off the mark? Have I consumed too much of the Google Analytics Kool-Aid? Leave a comment below!

Do we really “get” Google Analytics? is a post from: Analytics Talk by Justin Cutroni

You can find the TOS, in all its glory, here: http://www.google.com/analytics/tos.html

The first part of the TOS is actually very interesting. It defines certain GA terms including:

• Page View: “Page View” is the unit of measurement for usage of the Service. A Page View is used when the UTM is executed on a web page accessed by a visitor, and processed as part of a Profile. A Page View will be incurred for each instance of the UTM on the web page, and for each Profile receiving information from the UTM for such web page.
• Profile: “Profile” means the collection of settings that together determine the information to be included in, or excluded from, a particular Report. For example, a Profile could be established to view a small portion of a web site as a unique Report. There can be multiple Profiles established under a single Site.
• UTM: “UTM” means the proprietary Google Analytics Tracking Code, which is installed on a web page for the purpose of collecting Customer Data, together with any fixes, updates and upgrades provided to you (collectively, the “UTM”).

I especially like the definition of a profile. Many people have trouble understanding that a profile is more than just a website. It’s business rules (filters) applied to a set of data.

But my favorite part is section 7, the PRIVACY section:

7. PRIVACY . You will not (and will not allow any third party to) use the Service to track or collect personally identifiable information of Internet users, nor will You (or will You allow any third party to) associate any data gathered from Your website(s) (or such third parties’ website(s)) with any personally identifying information from any source as part of Your use (or such third parties’ use) of the Service. You will have and abide by an appropriate privacy policy and will comply with all applicable laws relating to the collection of information from visitors to Your websites. You must post a privacy policy and that policy must provide notice of your use of a cookie that collects anonymous traffic data.

I think there are two very interesting things to note about section 7:

First, you can not use GA to collect any personally identifiable information (PII). This means no names, email addresses, IP addresses, etc. One mistake that many people make, inadvertently, is collecting PII in the URL. If you have a form that collects visitor data, and that form passes data via query string parameter, then you may be collecting PII. If you’re unsure if you are collecting PII, just check the top content report. Look for any records that include an email address, name, etc. It’s easy to resolve this issue, just exclude the appropriate query string parameters in the profile settings.

Also, if you’re using any third party solutions make sure that they do not violate the GA TOS.

Second, you must post a privacy policy on your website that informs visitors that you are using a cookie to collect clickstream data. This was a surprise to me. I’m 99% sure that this blog has no posted privacy policy. Doh!

What are the consequences of violating this policy? Honestly, I don’t know. I’ve always advised clients to adhere to this policy as it is in the best interest of their customers. And happy customers are usually a good thing. There are options to integrate GA data with other information… but that’s a completely different blog post.

Understanding The Google Analytics Terms of Service 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

One of the Google Analytics goals for my site is to get RSS subscriptions. You’ll notice that I have a number of feed reader subscription links in the right hand navigation of my site. When someone clicks on one of the subscription links I record a page hit in Google Analytics. Each subscription link generates a different page hit. Here’s what the page hits look like:

/blog/outbound/rss/rss
/blog/outbound/rss/google
/blog/outbound/rss/yahoo
/blog/outbound/rss/bloglines
/blog/outbound/rss/newsgator

So my goal is to get someone to reach one of those ‘pages’. Most people would create a goal for each of the above so they can track exactly which subscription type was requested. But that would be messy. There are 5 subscription types, I would need to use two profiles to track all of the goals.

Rather than create a goal for each of the above, I can use a regular expression to match then all. Then I only need to create a single goal. The regular expression that I use for the goal looks like this:

/blog/outbound/rss/

Here is the neat part. Google Analytics has a special report that will explain which of the links were hit. Remember, I’m using a regular expression that can match all of the subscription links (5 different links). While it is valuable to see the overall number of times the goal is reached, it is even more useful to understand which of the 5 links actually contributed to the goal.

The report is called the ‘Goal Verification‘ report and it is located in the Content Optimization > Goals & Funnel Process reports. Here’s the report for my site (don’t laugh at my data :) ):

You can see from the image that there were three different matches for my goal regular expression. There were three matches for the Google Reader, three matches for the pure RSS feed and 2 matches for the Yahoo! feed reader. This is a great way to ‘drill down’ into your goal, especially if it can be achieved a number of different ways.

Just for some comparison, if I look at the Goal Tracking Report I see the total Number of goals achieved:

This is fun, let’s keep digging into this data! In our example, a visitor can reach my goal from any page on the site. It would be interesting to see which page they were on prior to hitting the goal. Google Analytics has a ‘Revers Goal Path‘ report. This report, found in the Content Optimization > Goals & Funnel Process section, shows the path that the user took to reach a goal.

Looking at the report we can see that two people landed on my homepage and subscribed to the Google RSS feed. This report is great because it can show the ‘high value’ pages that people need to see on the way to your goal page.

I hope this post was useful. Many people fixate on goal conversion rate and don’t dig into the more useful functionality.

I’m off for a vacation, I’ll be back in two weeks :)

Getting More out of Google Analytics Goals is a post from: Analytics Talk by Justin Cutroni