Which Types Of Changes Are Saved

This is a significant improvement to Google Analytics Administrators, but it is important to understand which changes are saved and which are not. The changes saved are those made through the interface: changes to accounts, properties, profiles, filters, goals, users and AdWords linking.

It does not include changes made to the code in the website, to external marketing campaigns or to private assets (e.g., Advanced Segments, Custom Reports, Dashboards, email, etc.). Therefore, it is still important to have a centralized place to save changes made to the Google Analytics Tracking Code. Here is a method I created to track code changes using Google Docs.

To find the “Change History” section, click on the “Admin” button on the right side of the orange top navigation (after logging into Google Analytics). Then, just below the orange bar you will see bread crumbs, click on the left-most link with your account name (right after the link “Account list”). You will see a tab named “Change History.”

Below is a screenshot of what the Change History table looks like.

It’s important to note that all the fields below are searchable, i.e., I can search for all the filters that were created or all the changes made by a specific user. As we can see in the table above, here is the structure of the table:

1. Date: the date and hour of the change.
2. Email: the user that performed the change.
3. Change: what changed and in which profile/user/goal/filter.

Concluding Thoughts

As I previously wrote, I believe that everything is about context. In the past, Google Analytics released the Annotations feature, which is a great way to add context to charts when it comes to marketing and sometimes technical changes.

The “Change History” feature brings context to another level by enabling us to understand settings changes (which often affect the data) even if they were not documented, which can bring significant context to changes in data.

One improvement I would love to see is a checkbox that says “Add this change as an annotation.”

New Top Navigation And Sidebar – Less Tabs, More Coherent

The most prominent change is the top navigation (orange bar) and sidebar. Previously the reports were divided between the profiles list, “Home”, “Standard Reporting” and “Custom Reporting.” Now we can see the following:

Basically, all the report tabs that were listed under a main tab called “Home” (Dashboards, Shortcuts, Intelligence Events and Real Time) are now listed under “Reporting”, which is really where they belong. In addition, Real Time is considered an integral part of the standard reports, with the other three mentioned reports being considered “My Stuff”

Another interesting change when it comes to the reports placement is that the AdWords section is now part of the Traffic Sources drop-down. This has always been like that, and that’s where AdWords belongs, as it is traffic source; but last year, in a major update called Google Analytics V5, the AdWords reports were given a section of their own, which is now no more.

Ah! And now the top navigation floats as we scroll down the page.

New Customizations To Dashboards

The dashboards also got a big change in design, now with white widgets over a light grey background. But, more importantly, it is now possible to create different layout to your dashboards as seen in the screenshot below. This comes as a great improvement, as it allows, for example, more rooms to tables which are more data-rich.

In addition, we now have two more Widget options: GEO maps and Bars. GEO maps will add a widget that contain a world (or country, states, etc) and color it based on a metric you choose, a very quick way to analyze metrics based on a location. Bars are a very advanced way to graph data. Below are the options offered in this widget:

Needless to say that all the additions mentioned will enable the creation of more powerful visualization and dashboards. This, together with the fact that dashboards are “emailable”, exportable, “segmentable” and shareable, makes it even more useful. Here are some tips on how to make the most out of dashboards.

The In-Page Analytics reports provide, in a page basis, the percentage of clicks from page to page in a website. The reports are a great way to analyze patterns of behavior, and can provide important insights to web designers and UX professionals. For example, they can be used to understand if specific links on a page are used or not and by which segments of visitors. A great case would be to check how often mobile users click on specific links as opposed to non-mobile users. As we can see below, by using Advanced segments we would see for each link the percentage of mobile vs. non-mobile clicks (learn more about advanced segments and how to create them).

However, as we can see in the screenshot below, two separate links that send visitors to the same page are aggregated in this report, meaning that we wouldn’t be able to measure the success of two different links in driving visitors to another page. In addition, JavaScript buttons and actions could not be tracked using In-App Analytics up till now.

According to the launch post:

Before now, In-Page Analytics was limited to showing clickthrough information by URL and not by the actual link on the page, and was limited to showing information only on links, and not on other elements like buttons. The most common complaint about In-Page Analytics is that if a page has two or more links to the same destination page, we show the same statistics for both links, since there was no telling which link the user actually clicked.

Therefore, Google has worked to improve this feature in a way that three important aspects are now possible:

1. See separate information for multiple links on a page that all have the same destination.
2. See when one page element has multiple destinations (e.g. searches performed on a page).
3. Track buttons, menus, and actions driven by javascript.

It is important to note that this feature requires additional code, which can be found in this help center article.

Google Tag Manager allows you to conveniently manage tags (such as tracking and marketing optimization tags) on your site. You can add and update AdWords, Google Analytics, Floodlight and non-Google tags from the Google Tag Manager user interface instead of editing site code. This reduces errors, frees you from having to involve a webmaster, and allows you to quickly deploy tags on your site.

Basically, according to Phillip Klien, a tag management system is a solution that controls the deployment of externally hosted JavaScript “page tags”, very similar to what a Content Management System does for content. It helps optimizing website performance and lets webmasters focus on other important tasks.

Below we discuss some of the capabilities and tags supported by the Google Tag Manager.

Which Tags Does Google Tag Manager Support?

The Google Tag Manager offers different tag templates for AdWords, DoubleClick, Analytics and Remarketing to minimize errors, but it also allows custom tags. Below is a list of the tags supported, for an explanation about each of them, check this help center article:

• AdWords Conversion Tracking
• DoubleClick Floodlight Counter
• DoubleClick Floodlight Sales
• Google Analytics
• GDN Remarketing
• Custom Image Tags
• Custom HTML Tags

Google Tag Manager Functionality

As shown above, Google supports various tags out-of-box and custom tags. But some of the tags, such as the AdWords Conversion Tracking, have “special needs,” they must appear in a limited number of pages when a conversion is completed. As we can see in the screenshot above, we have four main functionalities in the tool:

1. Create a new Tag: any number of tags can be added to a container. A container is the code you should create for each website you own. And if you own multiple websites, you can create multiple containers for your account.
2. Create a new Rule: this tells Google when to fire each of the tags (i.e. fire a tag just in a specific page).
3. Create a new Macro: name-value pairs for which the value is populated during runtime. These are the conditions that will be used to create tags and rules.
4. Create a Version: when a new tag or rule is added to a container, they do not take effect until you publish the container. Whenever a change is made the change must be published and a new version will be added to the Container Versions page

For a more in-depth overview of how to use the Google Tag Manager, check this step-by-step guide. Here is a product tour created by the Google team:

Last week Google announced 3 upgrades that will make testing with the tool significantly easier and more powerful. Below I discuss each of the upgrades and how they can enhance testing with Google Analytics

1. Ability To Copy Experiments

This new functionality is valuable as it allows marketers to perform additional tests to the same page without modifying the codes, which makes the process much shorter. In order to copy an experiment, go to your experiment results page and click on “View settings” as shown below:

On the settings page, on the bottom-right corner you will find the “Copy experiment” button, as seen below:

After clicking the button, you will get the following message: “Copying an experiment will copy the current settings into a new experiment—where you can adjust as you desire. It will not affect the current experiment. There is no need to reinstall the experiment code on your test page in order to run the copy.”

2. Support For Relative URLs For Variation Pages

This upgrade is extremely important as it allows website owners to test different page versions without having to create multiple URLs, they can simply create a version that has a different URL parameter (either using a “?” or a “#”). This is critical, for example, for ecommerce websites that want to test different versions for a product template page. Using relative URLs they will now be able to to that.

In addition, it is important for websites using multiple domains (such as Top Level Domains) where the URL is the same with the exception of the domain. According to the help article:

Relative URLs offer more flexibility in defining the location of the variations. Content Experiments takes the concept of relative URLs as used in hyperlinks since the early days of HTML and applies it to the definition of variations. This means the variations may inherit parts of the original URL (e.g. the domain, the domain and path, etc.). Using relative URLs doesn’t conflict with parameter propagation. This means that any parameter not specified in the variation will be copied over from the original page at runtime.

3. Improvements To The Experiments Report

Google added standard report capabilities to the experiment reports, such as: Site Usage (Pages/Visit, Time on Page, Bounce Rate and % of New Visits), Goal Sets (includes all goals), Ecommerce, and Adsense. This means that from now users will be able to compare the page variations based on all the metrics, not only the goals defined while setting the experiment.

Closing Thoughts

As expected, Google will improve the tool in fast pace. On my launch post I wrote the following list of missing features. Google started solving it from last to first:

1. Multivariate Testing not be available anymore.
2. E-commerce transactions as the goal not be available
3. Maximum of 5 variations per test.
4. Maximum of 12 active tests per profile.
5. Implement the control snippet code once and leave it on the page for future tests.

Also check this step-by-step guide on how to create A/B Tests using Google Analytics Content Experiemnts.

Remarketing is a feature that lets you reach people who have previously visited your site, and show them relevant ads when they visit other sites on the Google Display Network. When people leave your site without buying anything, for example, remarketing helps you connect with these potential customers while they browse other websites. You can even show them a compelling message or offer that will encourage them to return to your site and complete a purchase.

The feature will be rolled out in waves by the end of the summer to all Google Analytics users who are account administrators with at least one linked Google AdWords account. Below is a screenshot on where you will find it once you have access to it:

Requirements For Using Remarketing With Google Analytics

• Agree to the Google Analytics Terms of Service (please make sure to review them fully as they may have changed since you last viewed them).
• Agree to the Google Analytics for Display Advertisers Policy.
• Update your privacy policy and include an appropriate description of your use of remarketing in online advertising.
• Update your Analytics tracking code by adding a single line.
• Have at least one active Google AdWords account that is linked to your Analytics account, and be an Admin on that Google Analytics account.

When you create a remarketing list, you can share it with a single AdWords account. If you want to use the list in more than one AdWords account, then you need to recreate the list for each account.

Change To Code Snippet And Privacy Policy Required

According to a help article, only one line of code needs to be changed on the standard Google Analytics tracking code in order to make it work. According to them, after the change Google Analytics will also collect information from the DoubleClick cookie when that cookie is present; the DoubleClick cookie enables remarketing for products like AdWords on the Google Display Network.

Important to note that it is recommended that websites update their privacy policy following these guidelines once the change is made.

In terms of code, look for the following line

ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + 'google-analytics.com/ga.js';

And replaced it with

ga.src = ('https:' == document.location.protocol ? 'https://' : 'http://') + 'stats.g.doubleclick.net/dc.js';

Closing Thoughts

This is great news for Adwords users as it provides a simplified way to use the Remarketing feature, without the hassle of code updates. It is also great news to Analytics users as Google is pushing the use of Analytics even stronger than before. We can see a pattern where Google is trying to use the Google Analytics code (which is found in over 10 million websites) to enable additional products (just like they did with Content Experiments). This is a very interesting trend.

In the new functionality Google adapted its whole mobile solution to the App experience, providing additional reports and metrics for App owners and developers. In addition, they adjusted the registration flow to make it more streamlined for App developers. “Our goal with the new Mobile App Analytics reports is to help marketers and developers measure the end-to-end value of their mobile app, to ultimately help them build richer, more engaging experiences for their users.” Said JiaJing Wang, Product Manager at Google, explaining the reasoning behind the new functionality.

According to a recent article, mobile search traffic is on the rise, showing increases across different industries and website types. Google Analytics confirmed this trend with the following statement: “mobile now accounts for 8% of all conversions that we’re seeing in Google Analytics, and mobile conversions have grown by about 180% in just the last year.” All the above, and other mobile launches by Google, reinforce the company’s drive to improve the Mobile experience across the web.

Google will open the App Analytics beta to whitelisted users in waves, so if you are interested complete this beta signup form. According to the launch post, the reports will be available to all Google Analytics users by the end of the summer.

Mobile App Analytics

According to Google, the new Mobile App Analytics functionality is “designed to measure the entire mobile customer journey – from discovery to download to engagement. This enables the creation of app experiences that are more useful and engaging through data-driven decisions at each stage of the app lifecycle:

The following reports will be available through the new reports, but note that the new reports will be available to Apps using the new SDK v2.0.

New and active users: shows the number of new and active users who launch the app everyday.

Google Play traffic sources: shows where visitors come from to the Google Play. This supports Google Analytics campaign tags. This means that if you send traffic to Google Play and tag your links, you will see this information in this report. If you are using Admob, Ad information will be automatically populated.

App versions: shows the distribution of active users over the older and newer versions of apps (similar to screenshot below on App crashes). This report gives an overview of which App versions are still being used and how frequently.

Device overview: shows the top mobile devices and OS versions that apps runs on. Important to understand which mobile devices should be prioritized for QA and future development.

User behavior: shows how loyal your users are, how frequently they use the app, and the engagement level of each loyalty group. This new visualization is very interesting and useful, it shows in a glance how loyal are your visitors and how they engage with the App.

Engagement flow: shows the screens and paths users take to move throughout apps. This feature has being upgraded for the App Analytics. As Google Analytics users will note, there are additional colors; the colors represent different types of interactions. As an example, a screen view would be different than a click of a button. Very similar to how we see Page Views and Events on the Web.

App crashes: shows trends in crashes and exceptions that will help developers troubleshoot problems on certain devices, operating systems, and App versions.

Goal conversions: shows conversion events defines as goals for apps.

In-App purchases: shows the number of purchases and the revenue generated for in-app purchases. Unfortunately, even though Admob is currently integrated for Advertisers (i.e. they can see traffic coming as a result of their ads), it is still not integrated for publishers (i.e. a website showing ads on their mobile App cannot know when an ad was clicked and set them as goals).

New Registration Flow

As we can see in the screenshot below, the new signup page for Google Analytics has a clear differentiation between users who need the tool for Apps and users who need them for mobile applications.

Closing Thoughts

Mr. Wang defined the objective of this new feature as follows: “in order for marketers to truly measure their app effectively, they need to examine the entire lifecycle of the app, from acquisition (like new and active users or acquisition channels) to engagement (like top screens and user loyalty) to outcomes (like in-app purchases or goal conversions). More importantly, it’s crucial to see these areas in concert with one another, like how certain acquisition channels lead to better user engagement and ultimately more goal conversions.”

In summary, this a major change in the Google Analytics offering. Basically, what Google is saying is that the Web is as important as mobile for them. This is another step following Webmaster Tools official recommendation for mobile SEO and Google’s Mobile Planet: Global Smartphone Users research. Now marketers will have a more complete tool set to optimize mobile experiences which, hopefully, will improve the current state of mobile.

Bounce Rates are calculated as visits where no request was sent to Google Analytics besides the initial request when the visitor landed on the website, i.e. it is relevant only to visits where the visitors landed on a specific page. So without knowing in how many of the sessions a page was also the landing page, analysts might overreact to Bounce Rates, giving too much emphasis to it. For more on why most people misinterpret Bounce Rates also see Yehoshua Coren post on Demystifying Bounce Rates.

According to Jordan Louis on his Web Analytics Primer: “It is important to know the bounce rate because it can help to indicate which pages are the most ‘repulsive’ to your visitors, or which repel the most visitors off of your site when viewed alone.“

“In line with Yahoo!’s focus on more quickly innovating with our core products and properties, over the coming quarters we are shutting down or transitioning a number of products that did not meaningfully drive revenue or engagement. After carefully reviewing our portfolio, Yahoo! has decided to discontinue Yahoo! Web Analytics services for analytics-only customers as well as the Yahoo! Web Analytics Consultant Network on October 31, to help us speed time-to-market in other areas. External YWA support will remain for Yahoo! Store customers and those using the Audience Definition feature. We will continue to share details of further changes in the months ahead.”

If you are a Yahoo! Web Analytics client, here is what you need to know:

Starting August 31, 2012, existing Yahoo Web Analytics projects will become “read-only,” with access to view historical data for two months. We recommend removing YWA tags from your website(s) at this stage, as those tags will no longer populate data to your YWA account. Also, if you wish to retain any historical data from your account, please utilize the data export functionality through your account. On October 31, 2012, all Yahoo! Web Analytics projects scheduled for discontinuation will be shut down for use, including the discontinuation of the Yahoo! Web Analytics Consultant Network for all users.

In May 9th 2008 Yahoo! bought IndexTools, a high-end product that was considered as a powerful tool by industry leaders. It was a very welcomed acquisition as it was believed that Yahoo would offer it for free, like Google Analytics did after acquiring Urchin. However, Yahoo did not make it a free-for-all product, as we can still see in the homepage of their website (screenshot below), you had to be a Yahoo client in order to get an account.

In a recent research by Stephane Hamel he found that 3% of the Top 500 US retailers were using Yahoo! Web Analytics. While this is not a large market share, Google Analytics Premium will happily welcome them.

If you are an existing Google Website Optimizer, you will automatically be in the first round of whitelists, but Google is not manually whitelisting users after the public roll-out begins. Also, it is important to note that Google will not offer a migration option for Google Website Optimizer users, if you have tests running you can run them up to August and then you will have to re-create the tests on the new Content Experiments.

Content Experiments Advantages (over Website Optimizer)

1. Only the control script will be necessary to run tests, the script that redirects the traffic from the original page to the variations. The standard Google Analytics tracking code will be used to measure goals and variations, including existing goals.
2. Google Analytics advanced segments and page metrics will be available along with optimizing goal conversions based on your test pages. That means we will now be able to segment our results based on any advanced segment, which can help understand for which visitors the winning pages works best.
3. Improved statistical engine for analyzing experiments, which will help making decisions faster about the winning/loosing pages.
4. Tests results will not appear for at least 2 weeks. According to Google this is a mechanism to encourage statistical significance and avoid fluctuations in traffic patterns. Post Script: The Google Analytics team clarified that “While we won’t declare a winner for the first 2 weeks, we will be sharing test results from the very first days. It’s a small distinction, but an important one.”
5. Tests will automatically expire after 3 months to prevent leaving tests running if they are unlikely to have a statistically significant winner.
6. “Dynamic Traffic Allocation” functionality: traffic will be shifted away from low-performing variations, over to higher performing ones. This feature can’t be turned off. This is to prevent poor-performing variations from doing extensive damage)

It is interesting to analyze the new features and the ones being left behind for now. By removing (almost all) tag implementations, forcing users to test 2 weeks (to take care of statistics), and allocating traffic dynamically, Google is clearly focusing on the beginners, making it simple for companies starting their testing efforts.

Another interesting change is that tests will be limited to 3 months. For experienced testers, it is clear that a test that runs more than 3 months will suffer from several statistical problems, as the data will be very scarce. But this will also stop websites that use Website Optimizer as a cloaking tool, where your original page is optimized for search engines and receives a small percentage of traffic and the variations are showed to users.

Content Experiments Features Not Available Or Missing

1. Multivariate Testing will not be available anymore. Google will rebuild this functionality at some point in the future (read this testing framework for more on the differences between A/B and multivariate testing).
2. E-commerce transactions as the goal will not be available
3. Maximum of 5 variations per test: this is a very big disadvantage and will limit tests significantly.
4. Maximum of 12 tests per profile at this time: another big disadvantage for companies doing many tests. Post Script: The Google Analytics team clarified that ”the maximum is 12 active/draft tests per profile. People can create more than 12 tests per profile over time, just not run them all at once.”
5. Implement the control snippet code once and leave it on the page for future tests. As of now, each test will have its own code.

Again, we can notice that features that would be extremely important for advanced users have not been added to the Content Experiments. Limitations such as variations limits, test limits per profile, one code per test, and a lack of multivariate testing are extremely problematic for advanced users. Hopefully Google will lift some of those barriers quickly.

Content Experiments Help Articles

Below are the official help articles from Google. In addition, also check this step-by-step guide on how to create A/B Tests using Google Analytics Content Experiemnts.

Overview Topic

• The Benefits
• Requirements & Sign In
• The Experiments Interface
• Elements of an Experiment

Run an Experiment Topic

• Life of a Typical Experiment
• Prepare
• Configure & Modify
• Track Progress
• Stop
• Respond to Results
• Metric Calculations
• Page Does Not Appear Correctly

Notifications and Errors Topic

• Code-Checking Errors