Google Analytics IQ Lessons Notes (2012) New Version 5 – Part 1

Taking the Google Analytics IQ Certification Test requires reviewing all the “Google Analytics IQ Lessons” – There are notes available online in other sources but they are not up to date. These notes were all captured and brought up to date so that new test takers would have the most current study notes available. without having to copy and paste from every tutorial. Notes captured on March 2012 – these also include the V5 new interface notes.

Introduction to Google Analytics

Google Analytics is a free, web analytics tool that is hosted by Google.

Google Analytics shows you how visitors actually find and use your site, so you’ll be able to

• make informed site design and content decisions

• improve your site to convert more visitors into customers

• track the performance of your keywords, banner ads, and other marketing campaigns.

• and track metrics such as revenue, average order value, and ecommerce conversion rates.


Google Analytics has been designed to meet the needs of novice users as well as web analytics experts.

Some of the features include:

• Map Overlay which can help you understand how to best target campaigns by geographic region

• AdWords Integration which makes it easy to track AdWords campaigns and allows you to use Google Analytics from your AdWords interface

• Internal Site Search which allows you to track how people use the search box on your site

• Benchmarking so that you can see whether your site usage metrics underperform or outperform those of your industry vertical.

• Funnel Visualization so that you can optimize your checkout and conversion click-paths

How GA Works?
Here’s how Google Analytics works.

When a visitor accesses a page on your site, a request is made to the webserver to display the page.

The page is served and the Google Analytics Tracking Code JavaScript is executed.

The Google Analytics Tracking Code, which is a snippet of code that you place on each page of your site, calls the trackPageView() method.

At this point, the Google Analytics first-party cookies are read and/or written.

The webpage then sends an invisible gif request containing all the data to the secure Google Analytics reporting server, where the data is captured and processed.

Data is processed regularly throughout the day and you can see the results in your reports.

What happens if?

Google Analytics uses only first-party cookies, which are considered safe and non-intrusive by most internet users today.

Although many people block third-party cookies from being set by their web browsers, this won’t affect Google Analytics.

Someone who blocks all cookies, however, won’t be tracked by Google Analytics since all the data is passed to the Google Analytics servers via the first-party cookies.

Someone who deletes their cookies will still be tracked, but they’ll be identified as a new visitor to the site and Google Analytics won’t be able to attribute their conversions to a prior referring campaign.

People delete cookies for many reasons, one of which is to prevent personal data from being captured or reported. But, note that Google Analytics does not report on personally identifiable information. You’ll learn more about cookies as they relate to Google Analytics in a later module.

A much less common scenario is that a visitor to your site has disabled JavaScript on his or her browser. A visitor who disables JavaScript won’t be tracked since the Google Analytics Tracking Code cannot be executed.

Cached pages are saved on a visitor’s local machine and so they’re not served by the webserver. Google Analytics will still track visits to cached pages as long as the visitor is connected to the internet.

JavaScript errors occur when an element of a web page’s script contains an error or fails to execute correctly. If an error occurs before the Google Analytics Tracking Code is executed, the visit to the page won’t be tracked. This is because the error will prevent the remainder of the JavaScript on the page from running. Since we recommend that in most cases you place your Google Analytics Tracking Code at the bottom of the page, JavaScript errors are always a possible cause for data not appearing in your reports.

Google Analytics can track visits from a mobile device as long as the device is capable of executing JavaScript and storing cookies. You can see which devices have been used to access your site by looking at the Browsers report in the Visitor section.

In general, no reporting tool can ever be 100% accurate. You’ll get the most out of web analytics if you focus on trends. Knowing that 20% more visitors converted following a marketing campaign is more powerful than knowing that exactly 10 people visited your site today.

Data Confidentiality

All data collected by Google Analytics is anonymous, including where visitors comes from, how the visitors navigate through the site, and other actions they may perform.

No personally identifiable information is collected.

Google does not share Analytics data with any 3rd parties.

Furthermore, Google optimization, support, and sales staff may only access a client’s data with the client’s permission. You can give permission verbally, over email or through a support ticket that asks for help with a problem or asks a question about your data.

You may elect to share your Google Analytics data “with other Google products”, and Google will use the data to improve the products and services we provide you. Electing to share your data “Anonymously with Google and others” allows you to use benchmarking.

To provide benchmarking, Google removes all identifiable information about your website, then combines the data with hundreds of other anonymous sites in comparable industries and reports them in an aggregate form.

If you select “do not share my Google Analytics data”, you will not be able to use benchmarking and may not have access to specific ads-related features such as Conversion Optimizer.

Again, regardless of your Data Sharing selections, Google does not share Analytics data with any 3rd parties.

Installing the Google Analytics Tracking Code


Google Analytics uses a combination of JavaScript and first party cookies to gather anonymous data about your visitors.

As you set up your Google Analytics account, you will be provided with a tracking code. You’ll need to install this tracking code across all pages of your site


If you need to access your tracking code later on, click the account administration icon at the top right of your screen.

On the Account Administration screen, you’ll see a table listing the accounts to which you have access. Click the account that contains the web property you’re interested in.

You’ll then see a table listing all the web properties for that account. Click the desired web property.

On the next page, click the Tracking Code tab.

This page gives you the asynchronous version of the Google Analytics Tracking Code. The asynchronous version of the tracking code allows your site to run at its fastest, so we recommend that you always use this version. Throughout this course, we use the asynchronous tracking code whenever we illustrate a tracking technique. Traditional ga.js tracking is still used on many sites. To see the traditional ga.js syntax, navigate to the URL shown on the slide.

Be sure to replace the “x”s in the code with your unique Google Analytics account number and property index, which will be explained in the next slide.


Let’s look at the tracking code. This section of the code tells Google Analytics which account this traffic belongs to. The number immediately following the “UA dash” is your unique Google Analytics account number, and the number following the last dash is the property index. Review the lesson on accounts and profiles to learn about the property index. This section of the tracking code automatically detects secure versus non-secure pages. So, you can use the same tracking code on both https and http pages.


The tracking code that is provided to you is designed to work with most site setups. In some cases, however, you’ll need to make small updates to the tracking code on each of your pages.

For example, if you need to:
• Track multiple domains in one profile,
• Track more than one subdomain per profile, or
• Track multiple domain aliases, you should review the module on tracking domains and subdomains — and customize your code before adding it to your pages.


To install the JavaScript, copy your tracking code–either the code provided during setup, or your customized snippet–and paste it into your page.

One of the main advantages of the asynchronous snippet is that you can position it at the top of the HTML document. This increases the likelihood that the tracking beacon will be sent before the user leaves the page. It is customary to place JavaScript code in thesection, and we recommend placing the snippet at the bottom of thesection for best performance.

Here’s a sample.
To maintain tracking consistency, it is important that the code is installed across all pages of your site.


If you buy keywords on Google AdWords, you can use Google Analytics to see how well your paid keywords perform in terms of conversion rates, revenue, and ROI. You can compare search result positions for each keyword and you can compare ad performance.

To do these things, you’ll need to link your AdWords account to your Analytics account. Review the module on Campaign Tracking and AdWords Integration for detailed instructions.

Urchin Software from Google is similar to Google Analytics, but Urchin runs on your own servers, whereas Google Analytics is a service hosted by Google.

If you’ve licensed Urchin, you can run both Urchin and Google Analytics together on your site. Running Urchin and Google Analytics together gives you a great deal of flexibility and analysis capability.

You’ll need to make modifications to your tracking code. While this isn’t covered in the course, you can learn how by following the link shown in the slide.


Once you’ve installed your tracking code, it usually takes about 24 hours for data to appear in your reports.

The best way to verify that you are receiving data is to simply look at your reports.


You can also view your webpage’s source code to verify that the tracking code is installed.

Navigate your browser to any page on your site. Right click within the browser window and select the “View Page Source” or “View Source” option in your browser.

This will open a new window that contains the source code for that page.


Now search for ga.js. (From the source code menu, select “Edit” and click the “Find” option.)

If you find the Google Analytics tracking code on your page, then it is likely that Google Analytics has been successfully installed on your site.

Repeat this process across several pages on your site to make sure that your installation is complete.



Use the Calendar to set your active date range – the time period for which you want to look at data.
Select date ranges by clicking on the day and month within the calendar or you can type dates in the “Date Range” boxes. Once you set a date range, it stays active until you change it, or log out.


You can use a comparison date range to see how your site is performing month over month, year over year or even from one day to another.The date range and comparison date ranges you select will apply to all your reports and graphs.


Most reports include an over-time graph at the top. You can make this graph display data by day, week, or month.


You can attach short notes or annotations to specific dates. Annotations are especially useful when you’re looking at historical data and wondering whether certain campaigns or outside events had some effect on your traffic.

To add an annotation, just click the date on the graph and select “Create new annotation”.
You can allow anyone with access to the profile to see the annotation, or make it private so that only you see it.


A metric is a measurement. Examples of metrics are “number of visits”, “pages viewed per visit”, and “average time on site”. Metrics appear in scorecards and as columns in tables.
Metrics can also be graphed.


You can graph any metric in a scorecard, simply by clicking it. Here, we’ve graphed Average Time on Site.


You can compare two metrics on the same graph to see how they are correlated. Click Compare Metric and select from the drop down.

In this example, we’re adding Average Time on Site to the graph.


Groups of metrics are organized into tabs.
The Site Usage tab shows metrics such as the number of pages viewed per visit, the average time on site, and the bounce rate. Goal Set tabs shows the conversion rates for each of your goals.
If you’ve enabled ecommerce, you’ll also see an Ecommerce tab.


The AdWords reports have an additional tab called Clicks. This tab contains AdWords related metrics such as clicks, cost, revenue per click and ROI.

The AdSense tab contains AdSense metrics such as revenue from AdSense and AdSense ads clicked.


Many reports contain tables. These tables usually break out your data by a single dimension.
Each row in the table shows the data for a different value of the dimension.
In this example, the dimension being shown is City. Each row contains the data for a different city.

Each row in this table corresponds to a kind of browser – Internet Explorer, Firefox, Chrome and so on.
So, this table is showing data for different values of the dimension “Browser”


The Viewing option above the table lets us change the dimension. If we click Operating System as the Viewing Option, the table shows data for each kind of operating system.


We can also add a secondary dimension. This lets us see data for each combination of two dimensions.
In this example, the table shows data for each operating system.
Let’s look at what happens if we select Browser as a secondary dimension.

Now we can see data for each Operating System and Browser combination.
So, we can see data for Windows and Firefox, Windows and Chrome, Macintosh and Safari, Macintosh and Chrome, and so on.


To filter the data that appears in a table, click the Search option above the table.
In this example, we’re excluding visits from London and New York and also excluding any visits in which there were fewer than 2 pages viewed.


The View option lets you visualize data in different ways.

The Data view organizes your report data into a table. This is the default view for many reports.

The Percentage view creates a pie-chart based on any one of the metrics in the report.

The Performance view shows a bar-graph based on any metric you select.

The Comparison view allows you to quickly see whether each entry in the table is performing above or below average.

Term Cloud helps you visualize your keywords.

Pivot creates a pivot table in which both rows and columns can break out dimension values.
In this example, we can see how many visits were referred by each combination of keyword and search engine.
Keywords are shown as rows and search engines are shown as columns.

You can select the metrics you want to display in the table and the dimensions.


Columns within tables can be sorted in both ascending and descending order simply by clicking on the column heading.
The arrows next to the heading title indicate the order in which the results are listed.
A down arrow indicates descending order and an upward arrow indicates ascending order.


By default, all reports with tables display ten rows.
To display more than ten rows, go to the bottom of your report and click the dropdown menu arrow next to “Show rows”.
You can display up to 500 rows per page.


An advanced segment is a subset of your data.

For example, by selecting Visits with Transactions, you can limit your analysis to just the visits during which a person bought something.

If you apply a single advanced segment, all your reports are limited to the data in that segment until you select a different segment.

You can always go back to seeing all your data by selecting the All Traffic segment.


You can select up to four segments at a time. This allows you to compare data for each segment side by side as you go through your reports.

In this case, we’ve selected three segments: Visits with Transactions, Search Traffic, and Paid Search Traffic.


The Advanced Segment pulldown shows two kinds of segments: Default Segments and Custom Segments.

Default Segments are predefined and available to anyone using Google Analytics.

Custom Segments are segments that you define. We’ll learn how to create custom segments in later lesson.



In Google Analytics, a pageview is counted every time a page on your website loads.

So, for example, if someone comes to your site and views page A, then page B, then Page A again, and then leaves your site — the total pageviews for the visit is 3.


A visit — or session — is a period of interaction between a web browser and a website. Closing the browser or staying inactive for more than 30 minutes ends the visit.

For example, let’s say that a visitor is browsing the Google Store, a site that uses Google Analytics. He gets to the second page, and then gets a phone call. He talks on the phone for 31 minutes, during which he does not click anywhere else on the site.

After his call, he continues where he left off. Google Analytics will count this as a second visit, or a new session.

Note that throughout these modules, the words “visit” and “session” may be used interchangeably.


A visitor is uniquely identified by a Google Analytics visitor cookie which assigns a random visitor ID to the user, and combines it with the timestamp of the visitor’s first visit.

The combination of the random visitor ID and the timestamp establish a Unique ID for that visitor.

You’ll learn more about the visitor cookie in a subsequent module.


Generally, the Visitors metric will be smaller than the Visits metric which in turn will be smaller than the Pageviews metric.

For example, 1 visitor could visit a site 2 times and generate a total of 5 pageviews


A pageview is defined as a view of a page that is tracked by the Google Analytics Tracking Code.

If a visitor hits reload after reaching the page, this will be counted as an additional pageview.

If a user navigates to a different page and then returns to the original page, an additional pageview will also be recorded.

A unique pageview represents the number of visits during which that page was viewed–whether one or more times. In other words, if a visitor views page A three times during one visit, Google Analytics will count this as three pageviews and one unique pageview.


“Total Visitors” counts each visitor during your selected date range only once. So, if visitor A comes to your site 5 times during the selected date range and visitor B comes to your site just once, you will have 2 Visitors. Remember, a visitor is uniquely identified by a Google Analytics visitor cookie.

The “New vs. Returning” report classifies each visit as coming from either a new visitor or a returning visitor. So when someone visits your site for the first time, the visit is categorized as “Visit from a new visitor.” If the person has browsed your website before, the visit is categorized as “Visit from a returning visitor.”

A high number of new visits suggests that you are successful at driving traffic to your site while a high number of return visits suggests that the site content is engaging enough for visitors to come back.

You can look at the Frequency and Recency report to see how recently visitors have visited. And you can look at the same report to see how frequently they return. The report is under Behavior in the Visitors section.


The Visitors metric — in other words the number of visitors who came to your site — is found in the Visitors section.

The Visits metric is found in the Visitors section and the Traffic Sources section.

The Pageviews metric can be found in the Visitors Overview and in the Content section reports. Most of the other reports show Pages Viewed per Visit instead of Pageviews.

Unique Pageviews is only found in the Content section.



To calculate Time on Page, Google Analytics compares the timestamps of the visited pages.

For example, in the slide, the visitor saw page A, then page B, and then left the site.

The Time on Page for page A is calculated by subtracting the page A timestamp from the page B timestamp.

So, the Time on Page for page A is 1 minute and 15 seconds.

In order for this calculation to take place, the Google Analytics Tracking Code must be executed on both pages.

The Time on Page for page B is 0 seconds, because there is no subsequent timestamp that Google Analytics can use to calculate the actual Time on Page.


Now, suppose the visitor continued on to a third page before exiting.

The second page now has a Time on Page of 1 minute 10 seconds.

The Time on Site is now calculated as 2 minutes and 25 seconds.


For Average Time on Page, bounces are excluded from the calculation. In other words, any Time on Page of 0 is excluded from the calculation.

For Average Time on Site, bounces remain a part of the calculation.

To calculate Average Time on Site, Google Analytics divides the total time for all visits by the number of visits.


Some sites make extensive use of Flash or other interactive technologies.

Often, these kinds of sites don’t load new pages frequently and all the user interaction takes place on a single page.

As a result, it’s common for sites like this to have high bounce rates and low average times on site.

If you have such a site, you may wish to set up your tracking so that virtual pageviews or events are generated as the user performs various activities.

You can learn how to do this in the module on EVENT TRACKING AND VIRTUAL PAGEVIEWS


Visit Duration categorizes visits according to the amount of time spent on the site during the visit.

The graph allows you to visualize the entire distribution of visits instead of simply the ‘Average Time on Site’ across all visits.

You can see whether a few visits are skewing your ‘Average Time on Site’ upward or downward.

Visit Duration can be found in the Engagement report under Behavior in the Visitors section.



The reports in the Traffic Sources section show you where your traffic is coming from on the internet.

You can compare your traffic sources against each other to find out which sources send you the highest quality traffic.


Direct Traffic represents visitors who clicked on a bookmark to arrive at your site, or who typed the URL directly into their browser.

Referring Sites include any sites that send traffic to you. These could be banner ads or links featured on blogs, affiliates, or any site that links to your site.

Search Engine traffic represents visitors who click on a search results link in Google, Yahoo, or any other search engine.

SEARCH ENGINE TRAFFIC can be organic — in other words, free search results — or paid.

PAID SEARCH ENGINE TRAFFIC is pay per click or cost per click traffic that you purchase from a search engine — for example on Google AdWords.

Understanding which search engines send you qualified traffic can help you select the search engines on which you want to advertise.


Looking at the highest traffic drivers is a start, but it doesn’t tell you whether the traffic was qualified.

In other words, did the traffic help you achieve the goals you’ve set for your site?

One easy indicator of quality is Bounce Rate — the percentage of visits in which the person left without viewing any other pages.

In the slide, although sent the most traffic, it has an 88% bounce rate. A bounce rate this high suggests that the site isn’t relevant to what the visitor is looking for

By clicking the “compare to site average” icon and selecting a comparison metric, you can see which sources outperform and underperform the site average.

So here, for example, if we select Bounce Rate as our comparison metric. we can see that the two most popular sources of traffic underperform the site average.

One note about bounce rate, if your site is a blog, bounce rate may not be relevant. With blogs, it’s common for people to look at a single page and then leave.


The All Traffic report lists all of the sources sending traffic to your site — including referrals, search engine traffic, and direct traffic

This report is particularly helpful because you can identify your top performing sources, regardless of whether they are search engines or sites.

For example, in the report, we see that referred more traffic than any other source. It has a medium of referral because it is a referral from a site.

The second most popular source of traffic was direct. Direct traffic always has a medium of (none).

Free Google search engine traffic was the fourth largest referrer.

The medium of organic tells us that this traffic came from clicks on unpaid search engine results.

The medium of cpc on this entry — for cost per click — tells us that this traffic came from paid search results.

You may sometimes see _referrals_ from These can come from Google Groups posts or static pages on other Google sites.


If you have goals or ecommerce set up on your site, you have a much wider range of metrics with which to assess performance.

Click on the Goal Set or Ecommerce tabs to view which sources are driving conversions and purchases.

In this case, we’re looking at metrics on the Ecommerce tab and comparing each traffic source’s revenue with the site average.


Looking at keywords is a very useful for understanding what visitors were expecting to find on your site.

Keywords with a high bounce rate tell you where you failed to meet that expectation.

For example.


This takes us to the Keyword report for ‘google games’.

To find out which landing page is being used for this keyword, we’ll click Other as the Viewing Option above the table, and select Landing Page.

We can now see which landing page is being used and evaluate it’s relevance to the keyword.

This report can be particularly helpful if multiple landing pages are being used.

You can find out which landing pages are responsible for the poor performance and send the keyword traffic to the most effective landing page.

Be sure to also check the bounce rates for organic, non-paid keywords. This information can offer insights into how to best focus your search engine optimization efforts.


By default, Google Analytics attributes a conversion or sale to the campaign that most recently preceded the conversion or sale.

For example, if a visitor clicks on an AdWords ad (Campaign 1 in the first session) and then later returns via a referral to purchase something (Referrer 1 in the second session), the referral will get credit for the sale.

However, if instead the visitor returns directly, then the AdWords ad (Campaign 1) will still get credit for the sale.

To prevent a specific referral or campaign from overriding a prior campaign, simply append “utm_nooverride=1” to all referring campaign links as shown in the slide. This ensures that the conversion is always attributed to the original referrer (or first campaign the user clicked on).

Therefore, in the example above, the original campaign will continue to get credit for the conversion.

If a visitor returns via a link without the utm_nooverride, as in the third example, that campaign will get credit for the sale since it overwrites all previous referring campaigns.



Two reports in the Content section focus on page traffic, but each report organizes it differently.

The Pages report lists each page that received traffic.

The Page Title viewing option on the Pages report groups your pages according to Title tag. You can click on a title to see the pages that share that title.

The Content Drilldown report groups pages according to directory. You can click on a directory to see the pages in the directory.


The Landing Pages report lists all of the pages through which people entered your site.

You can use this report to monitor the number of bounces and the bounce rate for each landing page.

Bounce rate is good indicator of landing page relevance and effectiveness.

You can lower bounce rates by tailoring each landing page to its associated ads and referral links.

The more relevant the page, the less likely a visitor will be to bounce.


The Navigation Summary can help you understand how people move through your site.
It shows how people arrived at a specific page and where they went afterwards.

The report is available from the Pages report.

Here’s the Navigation Summary report.

Percent Entrances shows how frequently the page was a landing page.

Percent Previous Pages shows how frequently visitors came to the page after viewing another page on the site.

Percent Exits shows how frequently visits ended on this page.

Percent Next Pages shows how frequently visitors continued on to another page on the site.

The list of pages that were viewed immediately before the page or pages is shown in the left column, under Previous Page Path.

The list of pages that were viewed immediately after the page or pages is shown in the right column, under Destination Page.


The Entrance Paths report is a powerful tool for analyzing navigation paths.

For example, let’s say that you want to find out whether people clicked the Purchase button on your landing page and actually completed the purchase.

To find out, go to the Landing Pages report and click Entrance Paths.


Select the landing page you want to analyze.

In the left column, you’ll see all the possible clicks people made on the page. Choose the link that represents the Purchase page.

In the right hand column, you’ll now see all the pages visitors went to after the Purchase page. By looking at this list, you’ll be able to see how many visits ended up on the Purchase Completion page.

This report can show you if the landing page is doing the job you designed it for.

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5 thoughts on “Google Analytics IQ Lessons Notes (2012) New Version 5 – Part 1”

  1. Michael,

    Thank you so much for your post, it is so helpful and clear – Very much appreciate that some people take the time and effort to write posts like this! It will surely help my revisions :)

    Have an awesome day,


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  3. Interesting read, although a lot more in depth than my poor brain can grasp right now. I am hoping you can tell me if the GA javascript can be placed on one line and still work? I have attempted this but GA still says Tracking Not Installed. I have waited 48 hours so far but no change. The main reason I am hoping the script will work without CRs is that I have over 700 pages for it to go on and adding to code manually is a big overhead.

  4. I am Currently doing G.A course and i am searching for notes for G.A, Please help me to find out from where i can get multiple choice question answers?

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