Temario 'completo' de Google Analytics IQ Lessons. First Steps, Interpreting Reports, Fundamentals e In-Depth Analysis

1. INTRO DE GOOGLE ANALYTICS IQ LESSONS

2. TEMARIO DE LAS DIAPOSITIVAS DE LAS IQ LESSONS
FIRST STEPS
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.
Features
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.

3. 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.

4. 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.
FIRST STEPS (SECTION 1)
Installing the Google Analytics Tracking Code
GOOGLE ANALYTICS TRACKING CODE (GATC)
Google Analytics uses a combination of JavaScript and first party cookies to
gather anonymous data about your visitors.

5. 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
FINDING YOUR TRACKING CODE
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.
UNDERSTANDING THE TRACKING CODE
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.
CUSTOM WEBSITE SETUPS
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.

6. INSTALLING THE JAVASCRIPT
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.
USING GA WITH ADWORDS AND OTHER PRODUCTS
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.
CHECKING REPORTS FOR DATA
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.
CHECKING SOURCE DATA
You can also view your webpage’s source code to verify that the tracking code
is installed.

7. 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.
CHECKING SOURCE CODE
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.
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FIRST STEPS (SECTION 1)
WORKING WITH REPORT DATA
SETTING THE ACTIVE DATE RANGE:
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.
SETTING A COMPARISON DATE RANGE
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.
GRAPHING BY DATE, WEEK AND MONTH
Most reports include an over-time graph at the top. You can make this graph
display data by day, week, or month.
ANNOTATIONS:
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.

8. WHATS A METRIC?
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.
GRAPHING METRICS
You can graph any metric in a scorecard, simply by clicking it. Here, we’ve
graphed Average Time on Site.
GRAPHING 2 METRICS
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.
SITE USUAGE, GOAL SET, AND ECCCOMERCE TABS
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.
CLICKS AND ADSENSE TABS
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.
WHATS A DIMENSION?
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”

9. DIMENSIONS AND REPORT TABLES
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.
SECONDARY DIMENSION
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.
FILTERING FOR TABLES
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.
REPORT VIEWS
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.

10. SORTING DATA:
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.
EXPANDING NUMBER OF RESULTS DISPLAYED
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.
ADVANCED SEGMENTS
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.
COMPARING SEGMENTS
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.
DEFAULT VS CUSTOM SEGMENTS
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.

11. NEXT MODULE: (SECTION 2)
INTERPRETING REPORTS
PAGEVIEWS, VISITS, AND VISITORs
PAGE VIEW:
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.
VISIT
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.
VISITOR
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.
PAGEVIEWS, VISITS AND VISTORS
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

12. PAGEVIEWS VS. UNIQUE 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 VS NEW VS RETURNING
“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.
PAGEVIEWS, VISITS AND VISITORS IN YOUR REPORTS
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.
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13. INTERPRETING REPORTS
•TIME METRICS
TIME ON PAGE
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.
TIME ON SITE
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.
AVERAGE TIME ON PAGE VS AVERAGE TIME ON SITE
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.
FLASH-BASES SITES
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.

14. 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 VS AVERAGE TIME ON SITE
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.
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INTERPRETING REPORTS
•TRAFFIC SOURCES
TRAFFIC SOURCES REPORT
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.
TRAFFIC SOURCES EXPLAINED
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.

15. Understanding which search engines send you qualified traffic can help you
select the search engines on which you want to advertise.
WHAT MAKES A GOOD SOURCE OF TRAFFIC?
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 blogger.com 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.
ALL TRAFFIC REPORT
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 blogger.com 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.

16. 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 google.com. These can come from
Google Groups posts or static pages on other Google sites.
REVENUE AND CONVERSION DRIVERS
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.
KEYWORDS
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.
KEYWORD LANDING PAGES
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.
CAMPAIGN ATTRIBUTION
By default, Google Analytics attributes a conversion or sale to the campaign
that most recently preceded the conversion or sale.

17. 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.
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INTERPRETING REPORTS
CONTENT REPORTS
PAGES, PAGE TITLE CONTENT DRILLDOWN
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.
LANDING PAGES
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.

18. The more relevant the page, the less likely a visitor will be to bounce.
NAVIGATION SUMMARY
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.
ENTRANCE PATH REPORT
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.
ANALYZING A LANDING PAGE USING 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.

19. FUNDAMENTALS (SECTION 3)
•Account Administration
ACCESSING ACCOUNT ADMINISTRATION
Click the Account Administration icon to manage your accounts, web properties,
profiles, and user access. (You can find the icon at the top right of any screen in
Google Analytics.)
You’ll be taken to the Account Administration screen which lists all of the
Analytics accounts to which you have access.
CREATING A NEW ACCOUNT
The ”Plus New Account” button is how you would create a new analytics
account under the login that you are currently using.
So, when should you create a new account? If you manage the analytics
services for several websites which belong to different organizations, you’ll
generally want to create a new account for each organization. We’ll discuss this
best practice in a few minutes.
You are permitted to create up to 25 analytics accounts per Google username.
However, you can be added as an administrator to an unlimited number of
accounts.
To administer an account, just click on it in the table.
THE USERS TAB
To give other users access to a Google Analytics account, click on the account
name in the Account Administration screen.
You’ll be taken to a screen similar to the one shown in the slide.
Click the User tab.
All of the users who currently have access to the account will be listed in the
table.
There is a settings link for each user in the table. Click this link to edit the user’s
name, email address, or to change their Role – either administrator or user.
ADMINISTRATORS AND USERS
There are two Roles. “Administrators” have access to all reports and they can
also modify settings.
So, Administrators can create profiles, filters, and goals, and they can add
users.
Users only have read access to your reports and they can’t modify analytics
settings. Also, “Users” can be restricted to viewing only specific profiles.

20. ADDING A NEW USER
To add a user, click the Plus New User button.
A screen that looks like this will appear. Enter the user information in the form.
In order for you to add a new user, they must have a Google Account.
If they don’t have a Google Account, ask them to create one at
google.com/accounts.
Select a Role for the new user.
You can either grant read-only access to certain reports or you can make them
an administrator. Remember that administrators can view all reports and modify
account settings.
GRANTING ACCESS TO A USER
If you select User as the role, the interface will show you a list of all profiles
associated with your account.
Select the profiles you would like this user to have access to and click the “Add”
button to apply your changes.
MODIFYING ACCESS
To modify access for an existing user, find the user on the Users tab and click
settings.
You can change the user’s role or change the profiles he or she can access.
Select the profiles you would like to remove report access to and click the
“Remove” button.
MANAGING ACCESS AND ACCOUNTS
Remember that an administrator has full administrative access to all profiles
within the account.
If you manage the analytics services for several websites which belong to
different organizations, the best practice is to create a separate Analytics
account for each organization. Otherwise, if you were to group all the websites
of all the different organizations into a single account, any Administrators you
created on the account would have access to all the reports for all the websites.
Not only would the administrators be able to see the reports of other
organizations, they’d also be able to change analytics settings on profiles that
don’t belong to them.
This raises the potential for an Administrator to accidentally edit — or even
delete — another organization’s settings and data.
CHANGING YOUR LOGIN EMAIL ADDRESS
If you want to change your e-mail login, create a new Google account. Add your
new login as an administrator to your Google Analytics account.

21. PROFILES
A profile is a set of rules that defines the data you see for a web property. For
example, you might have web property example.com for which you have three
profiles.
One of the profiles might show all the data for all the traffic that comes to
example.com.
Another profile might use filters to only show the data for traffic to a certain
subdirectory.
Still another profile might use a different set of filters to show only another
subset of data.
To see a list of the profiles that belong to a specific web property, navigate to
that web property from the Account Administration screen.
Once you are on the screen for the web property, click the Profiles tab. On the
Profiles tab, you’ll see a Profile selector menu that lists all the profiles.
Profiles are very flexible — they are basically just a set of rules that define what
data is to be included in the reports.
Here is a schematic showing an Analytics account with one web property and
two profiles.
Both profiles contain traffic data for the example.com web property.
One profile might contain all the traffic data. The other profile might be filtered
so that it contains only traffic from AdWords visitors.
In addition, you might want to give certain users access only to the filtered
profile. This has the effect of only allowing these users to see AdWords traffic to
example.com.
THE PROFILES TAB
Here is the Profiles tab for the “example.com test 1” profile.
If you are an administrator on the account, you’ll see the sub-tabs that list the
Assets, Goals, Users, Filters, and Profile Settings that are associated with the
profile.
You’ll also see the “Plus New Profile” button – which you can use to create a
new profile.
But, if you are not an administrator, you’ll only see the Assets tab.
That’s because you need to be an admnistrator to add new profiles or to edit a
profile’s goals, users, filters, and settings.
However, you don’t need to be an administrator to add or edit assets.
This includes advanced segments, annotations, and custom alerts.
PROFILE GOALS, FILTERS AND USERS

22. Each profile has its own goals, which you set on the goals sub-tab.
You control who has access to the profile via the Users sub-tab.
And, you can use the Filters sub-tab to control what data is included in the
profile.
PROFILE SETTINGS
The Profile Settings sub-tab is where you enable e-commerce and site search
reports, set your preferred time zone, and other settings.
REMOVING PROFILES
To remove a profile, you can simply click Delete this profile on the Profile
Settings sub-tab. You’ll need to be an Administrator to do this.
Be careful that you are deleting the correct profile, because you won’t be able to
recover the historical data for the profile once it’s been deleted.
_______________________________________________________________
__
FUNDAMENTALS (SECTION 3)
Campaign Tracking and AdWords Integration
ANALYZE ALL MARKETING CAMPAIGNS
Google Analytics allows you to track and analyze all of your marketing
campaigns — including paid search campaigns, banner ads, emails and other
programs.
HOW TO TRACK YOUR CAMPAIGNS?
There are two ways to track ad campaigns.
For AdWords campaigns, you should enable keyword autotagging. This allows
Google Analytics to automatically populate your reports with detailed AdWords
campaign information.
In order to enable autotagging, you’ll need to link your AdWords and Google
Analytics accounts; we’ll look at this in more detail in the next slide.
The second way to track campaigns is to manually tag links. So, for example,
you could tag the links in an email message with campaign-identifying
information. You may also choose to manually tag AdWords links if you do not
wish to enable autotagging.
The tags are campaign variables that you append to the end of your URLs.
LINKING ADWORDS TO ANALYTICS
By linking Google Analytics to your AdWords account, you can get advanced
reporting that measures performance and ROI for your AdWords campaigns.

23. Within AdWords, select Google Analytics under the Reporting tab to link your
accounts. The AdWords login that you’re using will need administrator privileges
in Analytics in order to link the accounts.
If you don’t already have an Analytics account, you’ll be able to create one.
When you link your accounts, you should enable “Destination URL
Autotagging”. This option allows you to differentiate your paid ads from organic
search listings and referrals and allows you to see detailed campaign
information in the AdWords section of your Traffic Sources reports.
Your cost data — the information about clicks and keyword spending — will be
applied once you link your accounts. If you don’t want cost data imported into a
particular profile, you can edit the profile settings and de-select the cost data
option — after you’ve completed the linking process.
WHY AUTOTAGGING?
Autotagging your links is important because it helps Analytics differentiate the
traffic coming from Google paid listings, outlined in green on the slide, and
traffic coming from Google organic listings, which are outlined in red.
If autotagging is not enabled, your Analytics reports will show that the clicks
from the sponsored listings and the organic listings are both coming from the
same source: google organic.
By default, Analytics considers them both to be from Google organic search
results.
So, enabling autotagging allows you to see which referrals to your site came
from your paid Google campaigns and which ones came from Google organic
search results.
HOW DOES AUTOTAGGING WORK?
Autotagging works by adding a unique id, or g-c-l-i-d, to the end of your
destination URLs.
This unique id allows Analytics to track and display click details in your reports.
It is important to note that 3rd party redirects and encoded URLs can prevent
autotagging from working properly.
You should test these cases by adding a unique parameter to the end of your
URL — for example you could add ?test=test.
Test to make sure that the parameter is carried through to your destination
page and that the link doesn’t break.
Notice that the first query parameter is always preceded with a question mark.
Subsequent values are separated using ampersands.

24. APPENDING GCLID TO THE DESTINATION URL
Here’s an example of a gclid appended to the end of a URL.
http://www.yoursite.com/microsite
HOW TO ENABLE AUTOTAGGING
To enable autotagging, select “Account Preferences” under “My Account”.
Make sure that the Tracking option reads “yes”. If it says “no”, click the edit link,
check the box for “Destination URL Autotagging”, and click “Save Changes”.
When linking your AdWords account to Analytics for the first time, you’ll be
prompted to automatically select “Destination URL Autotagging” and “Cost Data
Import”.
If you want to change your autotagging settings later, you can do so by editing
your AdWords account preferences.
IMPORTING COST DATA FROM ADWORDS
All AdWords cost data from an account will be imported into any profile in which
the Apply Cost Data checkbox is selected.
Make sure both your AdWords and Analytics accounts are set to the same
currency so that ROI data is accurately calculated.
Recall that when linking your AdWords account to your Analytics account, your
cost data will be applied to all of your profiles.
If you don’t want cost data imported into a particular profile, you can edit the
profile settings. Within the “Edit Profile Information” screen, find the “Apply Cost
Data” checkbox. De-select this checkbox.
And finally, note that Google Analytics is only able to import cost data from
AdWords, and not from other ad networks.
DATA DISCREPENCIES: EXPECTED BEHAVIOR
You may notice differences between the data in your Google Analytics and
AdWords reports. There are several reasons for these differences.
First, AdWords tracks clicks, while Analytics tracks visits. Second, some visitors
who click on your AdWords ads may have JavaScript, cookies, or images
turned off.
As a result, Analytics won’t report these visits, but AdWords will report the click.
You’ll also see differences between Analytics and AdWords if the Google
Analytics Tracking Code on your landing page doesn’t execute.
In this case, AdWords will report the click but Analytics will not record the visit.

25. Invalid clicks may also cause reporting differences because while Google
AdWords automatically filters invalid clicks from your reports, Google Analytics
will still report the visits.
Finally, keep in mind that AdWords data is uploaded once a day to Analytics so
the results for each may be temporarily out of sync.
DATA DISCREPENCIES: COMMON ISSUES
Make sure that your landing pages contain the Google Analytics Tracking Code.
If they don’t, campaign information will not be passed to Analytics, but clicks will
register in AdWords.
Make sure that you have autotagging enabled. Otherwise, visits will be marked
as Google Organic instead of Google CPC. While we strongly recommend that
you use autotagging instead of manual tagging, if you do manually tag your
destination URLs, you must make sure that all of them are tagged, otherwise
data discrepancies will occur.
Be aware that campaign data can be lost if your site uses redirects. As a result,
Analytics won’t show the visits as coming from AdWords, but your AdWords
report will still report the clicks.
TRACKING ONLINE MARKETING
Google Analytics automatically tracks all of the referrals and search queries that
send traffic to your website.
However, if you are running paid advertising campaigns, you should add tags to
the destination URLs of your ads.
Adding a tag allows you to attach information about the campaign that will show
up in your Analytics reports.
WHAT ABOUT ADWORDS?
Although it’s possible to manually tag your AdWords ads, you should enable
auto-tagging instead.
If you manually tag your AdWords ads, the AdWords reports will only show you
information by Campaign and Keyword.
If you enable auto-tagging, you’ll be able to see much more detail. The
AdWords reports will show you results by ad group, matched search query,
placement domain and many other AdWords attributes.
URL TAGGING
There are five variables you can use when tagging URLs. To tag a URL, you
add a question mark to the end of the URL, followed by your tag, as shown in
the slide.

26. The variables and values are listed as pairs separated by an equals sign. Each
variable-value pair is separated by an ampersand.
Let’s look at each variable.
You should use utm_source to identify the specific website or publication that is
sending the traffic.
Use utm_medium to identify the kind of advertising medium — for example, cpc
for cost per click, or email for an email newsletter.
Use utm_campaign to identify the name of the campaign — for example, this
could be the product name or it might be a slogan.
You should always use these three variables when tagging a link. You can use
them in any order you want.
If you’re tagging paid CPC campaigns, you should also use utm_term to specify
the keyword.
And, you can differentiate versions of a link — for example, if you have two call-
to-action links within the same email message, you can use utm_content to
differentiate them so that you can tell which version is most effective.
EXAMPLE: TAG VS NO TAG
To illustrate, let’s look at a two versions of a link to mysite.com, both placed on
yoursite.com.
The first link in the slide does not have a tag. Traffic from this link will show up
in your reports as a referral from yoursite.com. There won’t be any campaign
information.
The second link has a tag. Traffic from this link will show up with a source of
yoursite, and it will show as a banner, instead of a referral.
Also, you’ll see this traffic reflected under summerpromo in your Campaigns
report.
EXAMPLE 2: PAID KEYWORDS (COST PER CLICK)
Let’s look at a destination URL from an AdWords ad.
In the first example, no tag has been provided and autotagging is disabled. In
this case, you won’t see this traffic in your AdWords reports.
The second example shows how to manually tag an AdWords link. This traffic
will show up in your AdWords reports, but information will be limited to
campaign and keyword.
You must specify cpc as your medium and google as your source in order to
see this traffic in your AdWords reports. You should also specify cpc as your
medium when tagging paid search campaigns from other search engines.

27. The third example shows what an AdWords autotagged URL might look like
once AdWords has appended the g-c-l-i-d variable to the end of the URL.
This traffic will show up in your AdWords reports and you’ll see complete
AdWords information.
WHERE IS THE CAMPAIGN INFORMATION REFLECTED?
You can select any of these variables as a dimension in most reports.
For example, to see all of the sources in California from which you received
traffic, you could go to the Map Overlay report, drill down to California, and
select Source as a dimension.
THE URL BUILDER
You can use the URL Builder in the Google Analytics Help Center to construct
your URLs.
You enter in the destination URL and the values for each campaign variable.
You should always use source, medium and campaign name.
The URL Builder can be found via the link displayed here on the slide, or you
can search for “URL Builder” in the Analytics Help Center.
The URL builder can only construct one URL at a time, so you probably won’t
want to use it to construct every URL for every campaign.
GENERATING URLS
If you have a large number of URLs to tag, you can use spreadsheets to
automate the process.
Generate a sample URL in the URL Builder and create a simple spreadsheet
formula.
Spreadsheets can make it much easier to generate thousands of tagged URLs.
BEST PRACTICES FOR TAGGING LINKS
Stick to these best practices when tagging your advertising campaigns.
If you use AdWords, be sure to enable auto-tagging. Otherwise, you’ll miss out
on important information that can help you optimize your AdWords campaigns.
Second, for each campaign, use the URL Builder to create a template URL.
Then, copy and paste from the template to create the rest of the URLs for the
campaign.
Third, use consistent names and spellings for all your campaign values so that
they are recorded consistently within your Analytics reports

28. Finally, use only the campaign variables you need. You should always use
source, medium, and campaign name, but term and content are optional.
_______________________________________________________________
___________
FUNDAMENTALS (SECTION 3)
•Analysis Focus – AdWords
Review:
- Site Usuage Metrics
- Goal conversions
- Eccomerce Activity
- Revenue Metrics
Visits = # of visits received from Adwords keyword campaigns
Impressions = # of times ad shown
clicks = # clicks from which you paid or received
CTR – click thru rate – how many times your ads were displayed
(impressions, clicks, cost, CTR)
Revenue per click / return on investment & margin can help you access
keywrod profitability
set match types to compare diffetrent types of data
Effective time of day?
Day Parts
Visits vs Transactions then view the data hourly
_______________________________________________________________
___________
FUNDAMENTALS (SECTION 3)
GOALS IN GOOGLE ANALYTICS:
GOALS
Defining site goals and tracking goal conversions is one of the best ways to
assess how well your site meets its business objectives. You should always try
to define at least one goal for a website.
So what is a goal? In Google Analytics, a goal represents an activity or a level
of interaction with your website that’s important to the success of your business.
Some examples of goals are an account signup, a request for a sales call, or
even that the visitor spent a certain amount of time on the website.
GOALS – 4 TYPES
There are four types of goals in Google Analytics.

29. A URL Destination goal is a page that visitors see once they have completed an
activity. For an account sign-up, this might be the “Thank You for signing up”
page. For a purchase, this might be the receipt page. A URL Destination goal
triggers a conversion when a visitor views the page you’ve specified.
A Time on Site goal is a time threshold that you define. When a visitor spends
more or less time on your site than the threshold you specify, a conversion is
triggered.
A Pages per Visit goal allows you to define a pages viewed threshold. When a
visitor views more pages –or fewer pages –than the threshold you’ve set, a
conversion is triggered.
An Event goal allows you to attach a conversion to an event that you have
defined. We’ll learn about events in a subsequent lesson.
GOALS IN REPORTS
You can see total conversions and conversion rates for each of your goals in
your reports.
FUNNELS
For each URL Destination goal that you define, you can also define a funnel. A
funnel is the set of steps, or pages, that you expect visitors to visit on their way
to complete the conversion.
A sales checkout process is a good example of a funnel. And the page where
the visitor enters credit card information is an example of one of the funnel
steps.
So, the goal page signals the end of the activity — such as a “thank you” or
“confirmation” page — and the funnel steps are the pages that visitors
encounter on their way to the goal.
WHY DEFINE FUNNELS
Defining a funnel is valuable because it allows you to see where visitors enter
and exit the conversion process.
For example, if you notice that many of your visitors never go further than the
“Enter shipping information” page, you might focus on redesigning that page so
that it’s simpler.
Knowing which steps in the process lose would-be customers allows you to
eliminate bottlenecks and create a more efficient conversion path.
SETTING UP GOALS

30. To set up a goal, first go the Account Administration page. Click the account
and web property for which you want to configure a goal.
Select the profile to which you want to add the goal.
Then, click the goals tab and click the plus-Goal link in one of the Goal sets.
You can create up to 4 sets of 5 goals each.
DEFINING URL DESTINATION GOALS
To define a URL Destination Goal, select URL Destination as the goal type.
Next, enter the URL of the goal page. You don’t have to enter the entire URL.
You can simply enter the request URI – that’s what comes after the domain or
hostname.
So, if the complete URL is www.googlestore.com/confirmation.php, you only
need to enter /confirmation.php.
Make sure that the URL you enter corresponds to a page that the visitor will
only see once they complete the conversion activity. So, pick something like the
Thank You page or a confirmation page for your goal.
You can also enter a name for the Goal — here we’ve entered “Completed
Order”. This name will appear in your conversion reports.
Defining a funnel is optional. To define your funnel steps, you add the URLs of
the pages leading up to the goal URL. Just as with goals, you don’t have to
enter the entire URL of a funnel step — just the request URI is fine.
Provide a name for each step in the funnel — here we’ve entered “Select gift
card “ for Step 1. The names you enter will appear in your reports.
Next, we’ll talk about the Match Type setting.
GOAL URL MATCH TYPES
The match type defines how Google Analytics identifies a goal or funnel step.
You have three choices for the Match Type option.
“Head Match” is the default. It indicates that the URL of the page visited must
match what you enter for the Goal URL, but if there is any additional data at the
end of their URL then the goal will still be counted. For example, some websites
append a product ID or a visitor ID or some other parameter to the end of the
URL. Head Match will ignore these.
Here’s another example, illustrated on this slide: If you want every page in a
subdirectory to be counted as a goal, then you could enter the subdirectory as
the goal and select Head Match.

31. “Exact Match” means that the URL of the page visited must exactly match what
you enter for the Goal URL. In contrast to Head Match, which can be used to
match every page in a subdirectory, Exact Match can only be used to match
one single page. Also notice that Exact Match does not match the second
pageview, “/offer1/signup.html?query=hats” because of the extra query
parameter at the end.
“Regular Expression Match” gives you the most flexibility. For example, if you
want to count any sign-up page as a goal, and sign-up pages can occur in
various subdirectories, you can create a regular expression that will match any
sign-up page in any subdirectory. Regular Expressions will be covered in a later
module.
When you use Regular Expression Match, the value you enter as the goal URL
as well as each of the funnel steps will be read as a Regular Expression.
Remember that regardless of which option you choose, Google Analytics is only
matching Request URIs. In other words, the domain name is ignored.
CASE SENSITIVE SETTING
Check “Case Sensitive” if you want the URLs you entered into your goal and
funnel to exactly match the capitalization of visited URLs.
DEFINING THRESHOLD GOALS
To define a Time on Site goal, select Time on Site as the goal type. Next, select
“Greater than” or “Less than” and enter an amount of time, for example 15
minutes. We’ll discuss goal value shortly.
To define a Pages per Visit goal, select Pages per Visit as the goal type. Next,
select “Greater than”, “Equal to”, or “Less than” and enter a number of pages.
Threshold goals are useful for measuring site engagement, whereas URL
Destination goals are best for measuring how frequently a specific activity has
been completed. If your objective is for visitors to view as much content as
possible, you might set a Pages per Visit goal. Or, if you have a customer
support site and your objective is for visitors to get the information they need in
as short a time as possible, you might set a Time on Site goal with a “Less than”
condition.
GOAL VALUE
The “Goal Value” field allows you to specify a monetary value for goal. You
should only do this for non-ecommerce goals.
By setting a goal value, you make it possible for Google Analytics to calculate
metrics like average per-visit-value and ROI. These metrics will help you
measure the monetary value of a non-ecommerce site.

32. Just think about how much each goal conversion is worth to your business. So,
for example, if your sales team can close sales on 10% of the people who
request to be contacted via your site, and your average transaction is $500, you
might assign $50 or 10% of $500 to your “Contact Me” goal.
Again, to avoid inflating revenue results, you should only provide values for
non-ecommerce goals.
GOAL CONVERSIONS VS TRANSACTIONS
There is an important difference between goal conversions and e-commerce
transactions.
A goal conversion can only happen once during a visit, but an e-commerce
transaction can occur multiple times during a visit.
Let’s say that you set one of your goals to be a PDF download and you define it
such that any PDF download is a valid goal conversion. And let’s say that the
goal is worth $5.
In this case, if a visitor comes to your site and downloads 5 PDF files during a
single session, you’ll only get one conversion worth $5. However, if you were to
track each of these downloads as a $5 e-commerce transaction, you would see
5 transactions and $25 in e-commerce revenue.
You’ll learn how to set up ecommerce tracking and how to track PDF downloads
in later modules.
FILTERS & GOAL TRACKING
If you are using a filter that manipulates the Request URI, make sure that your
URL Destination goal is defined so that it reflects the changed Request URI
field. For example, in the slide, we have a profile that defines /thankyou.html as
a URL Destination goal. But we have another profile with a filter that appends
the hostname to the Request URI. So, for this profile, we need to change the
goal definition accordingly.
FUNNEL REPORTING
If you define a funnel for a goal, Google Analytics populates the Funnel
Visualization report, shown here in the slide.
On the left, you can see how visitors enter your funnel. On the right, you can
see where they leave the funnel and where they go.
The middle shows you how visitors progress through the funnel — how many of
them continue on to each step.
In this example, we can see that there were 9,283 entrances at the top of the
funnel and 187 completed orders, at the bottom of the funnel.

33. This report is very useful for identifying the pages from which visitors abandon
your conversion funnel.
REVERSE GOAL PATH REPORTING
Here’s another report in the Goals section. It’s the Reverse Goal Path report.
You can see this data even if you haven’t defined a funnel. It lists the navigation
paths that visitors took to arrive at a goal page and shows you the number of
conversions that resulted from each path.
In this example, we can see that 97 of the conversions resulted from the first
navigation path that’s shown.
This is a great report for identifying funnels that you hadn’t considered before
and it can give you great ideas for designing a more effective site.
___________________________________________________________
FUNDAMENTALS (SECTION 3)
FILTERS IN GOOGLE ANALYTICS
FILTERS
Google Analytics filters provide you with an extremely flexible way of defining
what data is included in your reports and how it appears.
You can use them to customize your reports so that data that you deem useful
is highlighted in interesting ways. Filters can also help you clean up your data
so that it is easier to read.
There are two types of filters in Google Analytics – predefined filters and custom
filters.
HOW DO FILTERS WORK?
Filters process your raw traffic data based on the filter specifications. The
filtered data is then sent to the respective profile.
Once data has been passed through a filter, Google cannot re-process the raw
data.
That’s why we always recommend that you maintain one unfiltered profile so
that you always have access to all of your data.
CREATING AND EDITING FILTERS
To set up a goal, first go the Account Administration page. Click your desired
account.

34. You can use the Filters tab to create new filters, edit their settings, and apply
them to profiles.
HOW TO SETUP FILTERS
To create a new filter you will need to complete several fields, including the filter
name and type.
If you elect to create a custom filter, you will need to complete several additional
fields.
PREDEFINED FILTERS
Google Analytics provides three commonly used predefined filters.
The first filter called “Exclude traffic from domains” excludes traffic from the
domain that you specify in the Domainfield. If you apply this filter, Google
Analytics will apply a reverse lookup with each visitor’s IP address to determine
if the visitor is coming in from a domain that should be filtered out. Domains
usually represent the ISP of your visitor although larger companies generally
have their IP addresses mapped to their domain name.
The second filter, “Exclude traffic from IP addresses”, removes traffic from
addresses entered into the IP address field. This filter is generally used to
exclude your internal company traffic.
The third filter, “Include traffic subdirectories”, causes your profile to only report
traffic to a specified directory on your site. This is typically used on a profile that
is created to track one part of a website.
BEST PRACTICE FOR FILTERS
As a best practice, we recommend that you create a filter to exclude your
internal company traffic from your reports.
To do this you can use the predefined filter “Exclude traffic from IP addresses”.
You will need to enter your IP address or range of addresses into the ‘IP
address” field.
CREATING CUSTOM FILTERS
In addition to the pre-defined filters that Analytics offers, you can also create
custom filters.
Custom filters offer you greater control over what data appears in your profiles.
To create a custom filter, select “Custom filter”. Additional fields will appear
when you choose this option.
CUSTOM FILTERS

35. Each custom filter has three main parts.
The first part of a custom filter is “Filter Types”. There are six filter types
available and each one serves a specific purpose. We’ll look at these in a
minute.
The second part is the “Filter Field”. There are numerous fields you can use to
create your filter. Examples of some commonly used fields are the “Request
URI” and “Visitor Country” fields.
The complete list of fields can be found through the link shown here or you can
search for “filter fields” in the Analytics Help Center.
The third part of a custom filter is the “Filter Pattern”. This is the text string that
is used to attempt to match pageview data. The pattern that you provide is
applied to the field and, if it matches any part of the field, it returns a positive
result and causes an action to occur. You’ll need to use POSIX Regular
Expressions to create the filter pattern. Learn more in the module on Regular
Expressions.
FILTER TYPES
Here’s a chart that describes the filter types.
Exclude and Include filters are the most common types. They allow you to
segment your data in many different ways. They’re frequently used to filter out
or filter in traffic from a particular state or country.
Lowercase and Uppercase filters do not require a filter pattern, only a filter field.
Lowercase and Uppercase filters are very useful for consolidating line items in a
report. Let’s say, for example, that you see multiple entries in your reports for a
keyword or a URL, and the only difference between the multiple entries is that
sometimes the URL or keyword appears with a different combination of
uppercase and lowercase letters. You can use the Lowercase and Uppercase
filters to consolidate these multiple entries into a single entry.
Search and Replace filters replace one piece of data with another. They are
often used to replace long URL strings with a shorter string that is easier to read
and identify in your reports.
You can use Advanced filters to remove unnecessary data, replace one field
with another, or combine elements from multiple filter fields. For example, a
best practice when tracking multiple subdomains in a single profile is to append
the subdomain name to the page names. You can do this by creating an
advanced filter that appends Hostname to Request URI.
Let’s look at an example of a Search and Replace filter.

36. EXAMPLE: SEARCH AND REPLACE FILTER
Here’s an example of how you might use a Search and Replace filter.
Let’s say that your website uses category IDs as an organizational structure.
So, in your Pages report, you’d see a list of Request URIs that indicate the
different pages on your site.
The page “/category.asp?catid=5” is actually the Google Store Wearables page.
You could make the Pages report more meaningful by replacing “catid=5” with a
descriptive word, like “Wearables”.
Here’s what the Search and Replace filter might look like. This particular filter
would overwrite the entire Request URI with “Wearables.”
This is a simplified example to give you an idea of how you can use filters.
FILTERS AND PROFILES
Once you’ve defined a filter, you can apply it to a single profile or across several
profiles.
So, for example, in the slide, the graphic shows a single web property with two
profiles.
Filter 1 has been applied to both profiles.
Filter 2 has been applied only to Profile 2.
By setting up multiple profiles and applying filters creatively to each of them,
you have a great deal of reporting and analysis flexibility.
CUSTOMIZE DATA VIEWS
You can also use profiles and filters together to create customized data views.
Let’s say that you want to have two different views of your data — one view
includes only traffic to a subdomain and the other view only includes customers
from a specific geographic region.
To do this, you’d set up Profile 2 and Profile 3 as shown here in the chart.
Or, for example, you might want to set up a profile that only inlcudes Google
AdWords traffic. We’ll look at how to do this in the next slide. Remember, you
always want to maintain a profile that contains all of your data. That’s Profile 1
in the chart.
HOW TO INCLUDE ONLY GOOGLE ADWORDS TRAFFIC
To set up a profile that includes only Google AdWords traffic, you need to apply
the two Custom Include filters shown in the slide.
In filter one, you’ll filter on campaign source for a pattern of google.

37. In filter two, you’ll filter on campaign medium for a pattern of cpc.
You can apply these two filters in any order.
TRACKING SUBDOMAINS
Let’s look at how you can use profiles and filters to track subdomains.
If your subdomains are totally separate businesses, and you have no need for
reports that include cumulative traffic to both, then you could simply create a
unique web property for each subdomain.
Google Analytics creates a unique web property ID for each web property you
set up.
The web property ID comprises the letters “U” “A”, followed by the account ID,
followed by another number that distinguishes the web property from other web
properties in the account.
In the slide example, web property 1 is distinguished by a dash 1. Web property
2 is distinguished by a dash 2.
So, you’d install the “dash 1” version of your tracking code on your Subdomain
A pages, and the “dash 2” version of your tracking code on your Subdomain B
pages.
But what if you want to analyze the traffic aggregated across both subdomains?
In this case, you could set up 3 duplicate profiles under a single web property.
Then, you’d apply an Include filter to two of the profiles.
Profile 1 includes all traffic to both subdomains.
Profile 2 only includes traffic to subdomain A.
Profile 3 only includes traffic to subdomain B.
In this scenario, you’d install identical tracking code on every page of the site
regardless of subdomain.
BEST PRACTICES FOR FILTERS & PROFILES
When setting up profiles and filters for your Analytics account, you should
always create one unfiltered profile that can be a back-up in case your filters do
not function as planned or you need more data than you originally thought.
Remember, once your raw data has passed through filters, Google cannot go
back and reprocess the data. So, maintaining an unfiltered profile provides you
with a backup.
BEST PRACTICES FOR INCLUDE AND EXCLUDE FILTERS
You can apply multiple include and exclude filters to a single profile, but keep in
mind that when more than one filter is applied, the filters will be executed in the
same order that they are listed in your Profile Settings.

38. In other words, the output from one filter is then used as the input for the next
filter.
The example shown here illustrates that if you want to include only users from
California and Texas, you cannot create two separate include filters because
they will cancel each other out. The solution is to create one filter that uses a
regular expression to indicate that the Visitor Region should be California or
Texas.
ONE ADWORDS ACCOUNT, MULTIPLE URLS
If you drive traffic from AdWords to multiple sites, each of which is tracked in a
separate Analytics profile, you’ll need to apply a filter to each site’s profile.
Because, when you apply cost data from an AdWords account, data from the
entire account is applied to each profile – Google Analytics doesn’t
automatically match campaigns to specific profiles.
To illustrate what would happen if you don’t apply a filter, let’s imagine that you
have two sites and you spend $50 to drive traffic to each of them.
Without a filter, the Clicks tab on each profile would include $100 worth of cost
data instead of just the $50 you spent for that site.
So, for each profile that should include a subset of your AdWords data, you’ll
need to create a custom include filter.
FILTERS FOR COST SOURCES
Create a custom filter and select the Include filter type.
For the filter field, select “Campaign Target URL”. This field only applies to
Google AdWords data.
Use a regular expression to create the filter pattern based on the AdWords
destination URL that is applicable to this profile.
Once you’ve saved this filter, only AdWords data for this profile will be displayed
in the reports.
_______________________________________________________________
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FUNDAMENTALS (SECTION 3)
REGEX AND GOOGLE ANALYTICS
REGULAR EXPRESSIONS (REGEX)
A regular expression is a set of characters and metacharacters that are used to
match text in a specified pattern.

39. You can use regular expressions to configure flexible goals and powerful filters.
For example, if you want to create a filter that filters out a range of IP
addresses, you’ll need to enter a string that describes the range of the IP
addresses that you want excluded from your traffic.
Let’s start off by looking at each metacharacter.
Metacharacters are characters that have special meanings in regular
expressions.
DOT .
Use the dot as a wildcard to match any single character.
The operative word here is “single”, as the regex would NOT match Act 10,
Scene 3. The dot only allows one character, and the number ten contains two
characters — a 1 and a 0.
How would you write a regular expression that would match “Act 10, Scene 3”?
You could use two dots.
To make your regex more flexible, and match EITHER “Act 1, Scene 3” or “Act
10, Scene 3”, you could use a quantifier like the + sign.
But we’ll talk about repetition a bit later in this module.
BACKSLASH
Backslashes allow you to use special characters, such as the dot, as though
they were literal characters.
Enter the backslash immediately before each metacharacter you would like to
escape.
“U.S. Holiday” written this way with periods after the U and the S would match a
number of unintended strings, including UPS. Holiday, U.Sb Holiday, and U3Sg
Holiday.
Remember that the dot is a special character that matches with any single
character, so if you want to treat a dot like a regular dot, you have to escape it
with the backslash.
You’ll use backslashes a lot, because dots are used so frequently in precisely
the strings you are trying to match, like URLs and IP addresses.
For example, if you are creating a filter to exclude an IP address, remember to
escape the dots.

40. CHARACTER SETS AND RANGES []
Use square brackets to enclose all of the characters you want as match
possibilities. So, in the slide, you’re trying to match the string U.S. Holiday,
regardless of whether the U and the S are capitalized.
However, the expression won’t match U.S. Holiday unless periods are used
after both the U and the S. The expression also requires that the H is
capitalized.
There is a regex you can write to match all of these variations. The question
mark used here is another “quantifier”, like the ‘+’ sign mentioned earlier.
Again, we’ll talk about repetition in the next slide.
You can either individually list all the characters you want to match, as we did in
the first example, or you can specify a range.
Use a hyphen inside a character set to specify a range. So instead of typing
square bracket 0 1 2 3 4 5 6 7 8 9, you can type square bracket 0 dash 9.
And, you can negate a match using a caret after the opening square bracket.
Typing square bracket caret zero dash nine will exclude all numbers from
matching.
Note that later in this module, you will see the caret used a different way—as an
anchor.
The use of the caret shown here is specific to character sets, and the negating
behaviour occurs only when the caret is used after the opening square bracket
in a character set.
QUANTIFIERS AND REPETITION ? + *
Now let’s talk about using quantifiers to indicate repetition.
In earlier examples, we’ve used the plus sign and the question mark.
The question mark requires either zero or one of the preceding character. In the
expression “3-1-?” , the preceding character is a 1. So, both 3 and 3-1 would
match.
The plus sign requires at least one of the preceding character. So, “3-1-+”
wouldn’t match just a 3. It would match 3-1, 3-1-1, and so on.
The asterisk requires zero or more of the preceding character. In the
expression, “3-1-*”, the preceding character is a 1. So it would match 3, 3-1-, 3-
1-1, and so forth.

41. You can also SPECIFY repetition using a minimum and maximum number
inside curly brackets.
Recall that a dot matches any single character. What would you use to match a
wildcard of indeterminate length?
Dot star will match a string of any size. Dot star is an easy way to say “match
anything,” and is commonly used in Google Analytics goals and filters.
GROUPING
It is handy to use the parentheses and the pipe symbol (also known as the OR
symbol) together.
Basically, you can just list the strings you want to match, separating each string
with a pipe symbol — and enclosing the whole list in parentheses.
Here, we’ve listed four variations of “US” that we’ll accept as a match for US
Holiday.
If it’s not in the list, it won’t get matched. That’s why “US Holiday” won’t get
matched if one of the periods is missing.
In our list, we’ve accounted for both periods missing, but not for just one period
missing.
Using question marks, the second regex in the slide will match all of the above.
ANCHORS
The caret signals the beginning of an expression. In order to match, the string
must BEGIN with what the regex specifies..
The dollar sign says, if there are any more characters after the END of this
string, then it’s not a match.
So, caret US means start with US. US Holiday matches, but “Next Monday is a
US Holiday” does not match.
Holiday$ means end with Holiday. US Holiday still matches, but “US Holiday
Schedule” does not match.
Anchors can be useful when specifying an IP address. Take a look at these
examples.
SHORTHAND CHARCTER CLASSES D S W
Some character classes are used so commonly that there is a shorthand you
can use instead of writing out the ranges within square brackets.

42. Let’s look at the example of a simplified regex that could match an addres:
Backslash d means match any one digit zero through nine.
Use curly brackets and a minimum and maximum number to specify how many
digits to match.
Backslash d followed by 1 comma 5 in curly brackets means that the address
must contain at least one digit, and at most five digits.
Backslash s means that the number should be followed by one space,
backslash w means match any alphanumeric character and the star means
include as many alphanumeric characters as you want.
“345 Embarcadero” matches, but just “Embarcadero” does not, because this
regex requires the string to start with a number.
If you want to make the number optional, group the first part of the regex with
parentheses–including the space–and follow it with the question mark.
REGEX REVIEW
Let’s review.
In the example on the slide, we’ve created an expression that will match the
strings Google or Yahoo, regardless of whether or not Google and Yahoo are
capitalized.
Here, we’ve created an expression that will match URLs for internet and
theatrical movie trailers.
The first part of the expression indicates that the URL can begin with anything.
Then the expression specifies that the URL must end with
index.php?dl=video/trailers/ and then either internet or theatrical.
The $ sign ensures that any URLs that are any longer than this won’t get
included in the match.
COMMON USES FOR REGUALR EXPRESSIONS
You’ll find lots of applications for regular expressions in Google Analytics.
Some common examples are:
• filtering out internal traffic by specifying a set of IP addresses
• setting up a goal that needs to match multiple URLs
• tracking equivalent pages in a funnel
• and using the filter box that appears on your reports to find specific entries in a
table.
REGEX FILTERS

43. Here’s an example of a custom filter that uses a very simple regular expression.
googlestaore.com
REGEX GOALS
Here’s a regular expression used to define a goal URL.
.*index.php?dl=video/trailers/(internet|theatrical)$
REGEX AND TRACKING EQUIVALENT PAGES
Here’s how you might use regular expressions to group pages or funnel steps
on your site.
Using a regular expression allows you to track them as one funnel step rather
than tracking each page or action individually.
Learn how goals and funnels work in the module on goals.
/downloads/casestudy/careerbuilder
/downloads/casestudy/roche
/downloads/casestudy/ .*
REGEX WITHIN THE REPORT INTERFACE
And, here’s an example of using regular expressions within your reports.
We’re using the Search filter to display all the rows in the table that contain
Google or Yahoo.
(gG)oogle|(yY)ahoo
REGEX GENERATOR FOR IP ADDRESS RANGES
Google Analytics provides a tool that makes it easier to generate a regular
expression that matches a range of IP addresses.
It’s called the Regular Expression Generator and you can find it at the URL
shown in the slide.
Or, you can search for Regular Expression Generator in the Google Analytics
Help Center.
http://support.google.com/googleanalytics/bin/answer.py?hl=en&answer=55572
POINTS TO REMEMBER

44. You’ll find a number of useful applications for regex as you use Google
Analytics.
But, it’s important that you think through all the implications of each expression
that you use when you set up a filter or a goal.
It’s easy to make a mistake and not get the data or the result you’re looking for.
Set up a duplicate profile to test your regex statements. After enough data has
been collected, check your results and make sure they’re what you expect.
Remember to always maintain a backup profile that includes all your data.
There are lots of regex resources on the web. To get started, just search for
regex
_______________________________________________________________
_____
_______________________________________________________________
_______
FUNDAMENTALS (SECTION 3)
COOKIES AND GOOGLE ANALYTICS
WHAT ARE COOKIES?
Some web sites store information about you or your computer in a small file
called a cookie. The cookie is stored on your hard drive.
Sites that run Google Analytics issue first party cookies that allow the site to
uniquely, but anonymously, identify individual visitors.
So, when a visitor returns to a site that runs Google Analytics, the site is able to
remember that the visitor has been to the site before and Google Analytics will
only count that visitor once in unique visitor calculations.
There are two types of cookies. First-party cookies are set by the domain being
visited. Only the web site that created a first-party cookie can read it. This is the
kind of cookie used for Google Analytics tracking.
Third-party cookies are set by third party sites — basically sites other than the
site being visited.
Users can choose whether to allow some, none, or all types of cookies to be set
on their computers.
However, if a user does not allow cookies at all, they may not be able to view
some Web sites or take advantage of customization features.

45. PERSISTENT VS. TEMPORARY COOKIES
Cookies can be set with or without an expiration date. This detail is important in
order to understand how Google Analytics tracks visits and unique visitors.
Persistent cookies have an expiration date, and remain on your computer even
when you close your browser or shut down. On return visits, persistent cookies
can be read by the web site that created them.
Temporary cookies do not have an expiration date, as they are only stored for
the duration of your current browser session. As soon as you quit your browser,
temporary cookies are destroyed.
COOKIE-BASED VISITOR TRACKING
While it’s impossible to determine the exact number of web visitors who have
cookies enabled or disabled, available statistics suggest that the vast majority
of visitors enable cookies.
Many kinds of sites require that visitors have cookies enabled.
For example, you need to have cookies enabled in order to login to many online
shopping carts and to use web mail.
First party cookies, which are the kind used for Google Analytics, are allowed by
a majority of visitors.
Cookie tracking makes it possible to correlate shopping cart transactions with
search campaign information, and perform other visitor analysis.
Remember — websites only have access to the information that you provide.
Websites can’t get your email address or access to any information on your
computer unless you provide it. And since Google Analytics only uses first party
cookies, Google Analytics cookies can only be read by the website that created
them.
THE utm FIRST-PARTY COOKIES
Google Analytics sets the five first-party cookies shown in the slide.
The __utmv cookie is optional, and will only be set if the _setVar() method is
called. You will learn about _setVar() in the module on Custom Visitor
Segmentation.
All of the Google Analytics cookies are persistent except for one. The __utmc
cookie is a temporary cookie that is destroyed when the visitor quits the
browser.
Each of the other Google Analytics cookies has an expiration date set in the
future, meaning that the cookie will persist on the user’s computer until it
expires, or until the user deletes it from their computer.

46. EXAMPLE: GOOGLE ANALYTICS COOKIES
Here’s an example of the cookies set by the Google Store. You can see that
__utma, __utmb, __utmc, and __utmz have been set. We’ll learn more about
each cookie shortly.
First, let’s try a brief experiment. Which of the sites that you’ve visited are using
Google Analytics?
To find out, open your browser’s cookie window. You’ll usually find it under your
browser’s “Options” or “Preferences”.
Now, in the cookies window, search for underscore underscore u-t-m. You
should see all the different Google Analytics cookies set by all the sites that
you’ve visited that use Google Analytics.
All cookies are browser-specific. So, if you’ve already been to a site, but you
open a different browser to visit that site again, another set of Google Analytics
cookies will be set.
Now, before we continue, search for the Google Store cookies by typing the
domain name “googlestore.com” into the Cookies search box.
If you’ve never visited the Google Store, go to googlestore.com now so that
cookies are created.
__utma – VISITOR IDENTIFIER
Select the Google Store __utma cookie. In the cookie information, note the
“Content” and expiration date for the cookie.
The first number in the content of every Google Analytics cookie is called the
“domain hash.” It represents the domain that you visited and that set these
cookies. Google Analytics applies an algorithm to the domain and outputs a
unique numeric code that represents the domain. Each Google Analytics cookie
set by the domain will begin with this number.
The next number is a random unique ID.
The three subsequent numbers are timestamps. They represent the time of the
initial visit, the beginning of your previous session, and the beginning of your
current session. The timestamps represent the number of seconds since
January 1, 1970.
Notice that the last three timestamps are the same. What does this tell you?
The last number, the session counter, can give you the answer. The last
number tells you the number of times you have visited this site. This number will

47. increment each time you visit the site. The session counter here is “1”, and the
last three timestamps are all the same because this is your first visit to the site.
The random unique ID combined with the first timestamp make up the visitor ID
that Google Analytics uses to identify unique visitors to the site. These details
allow Google Analytics to calculate the number of unique visitors and number of
visits.
Look at your Google Store __utma cookie.
How many times have you visited the Google Store? If you think you’ve visited
more times than is indicated by the cookie, remember that the cookie only
includes the number of times you visited from this computer using this browser.
Also, if you have cleared your cookies at some point, it is only counting from the
last time you cleared your cookies.
When does this cookie expire? You should see that the date is two years from
last the time you visited.
_utmb & _utmc – Session IDENTIFIERS
The __utmb and __utmc cookies together identify a session.
The content of the __utmc cookie is simply the domain hash.
The content of the __utmb cookie will also be the domain hash plus, if the site is
using ga.js, some additional values.
The key difference between the two cookies is that __utmb is a persistent
cookie with an expiration date that is set 30 minutes after it is created. While
__utmc is a temporary cookie that is destroyed as soon as the visitor quits the
browser.
Let’s review what you know about a session, or visit, in Google Analytics. First
note that the terms “session” and “visit” are used interchangeably. A session is
defined by 30 minutes of inactivity or if a visitor quits the browser.
Each time the visitor navigates to a new page and the JavaScript in the Google
Analytics Tracking Code is executed, the __utmb cookie is refreshed and set to
expire in 30 minutes.
This is how a session can be 2 hours long. As long as the visitor remains active
on the site, the session remains active.
But if the visitor stays on a page for more than 30 minutes, the __utmb cookie
will be destroyed. The next time the visitor loads a page, Google Analytics won’t
find a__utmb cookie. Instead, a new __utmb cookie is created and, from the
standpoint of tracking, this is a new session.

48. So, why is the __utmc cookie needed? Let’s say a visitor quits and starts the
browser and comes back right away to the same site. Since the __utmc cookie
was destroyed, Google Analytics will know that this is a new session.
So, to summarize, when the visitor loads a page, the JavaScript in the Google
Analytics Tracking Code checks for both the __utmb and __utmc cookies. If
either one is missing, it notes this as a new session, and creates whichever
cookie– __utmb, __utmc, or both– was missing.
Note that it is possible to adjust this behavior. With a small customization to the
Google Analytics Tracking code, you can make the session timeout length
anything you want. You’ll learn about this in the Code Customizations module.
__utmz – CAMPAIGN COOKIE
The __utmz cookie stores the campaign tracking values that are passed via
tagged campaign URLs.
So, for example, if a visitor comes to your site on a link tagged with campaign
variables utm_source, utm_medium, and utm_campaign, the values for these
variables will be stored in the __utmz cookie.
Preceding the campaign tracking values, you will see four numbers stored in
the __utmz cookie.
The first number is the domain hash, as with the other Google Analytics
cookies.
The second number is a timestamp.
The third and fourth numbers are the “session number” and “campaign
number”, respectively.
The “session number” increments for every session during which the campaign
cookie gets overwritten.
The “campaign number” increments every time you arrive at the site via a
different campaign or organic search, even if it is within the same session.
The __utmz cookie has a six month timeout, meaning that a visit will be
attributed to a particular campaign for up to six months, or until the __utmz
cookie is overwritten with another value.
You can modify the six month timeout and you can change the rules which
govern when the __utmz cookie value is overwritten. You’ll learn how in the
Code Customizations module.
The __utmz data shown here would show up in your All Traffic Sources report
as coming from the source / medium “google / organic”.
Now, in your browser’s cookie window, select the __utmz cookie from your visit
to googlestore.com. Assuming that it was a direct visit, you’ll see
“utmcsr=(direct)” and “utmcmd=(none)”. Your visit will show up in the Google
Store’s Google Analytic’s account as coming from the source / medium “direct /
none”.

49. __utmz – CAMPAIGN VALUES
The slide shows how the values in the __utmz cookie map to campaign
variables.
For example, the utmcsr value in the __utmz cookie is the source, or the value
that was assigned to utm_source in the tagged link.
utmcsr in __utmz is the Source (utm_source)
utmccn in __utmz is the Campaign (utm_campaign)
utmcmd in __utmz is the Medium (utm_medium)
utmctr in __utmz is the Keyword (utm_term)
utmcct in __utmz is the Ad Content (utm_content)
CAMPAIGN VALUES: FROM TAGGED URL TO COOKIE
So, if you reached “somesite.com” via a tagged URL that looks like this, then
the __utmz cookie would look like this.
If the URL looks like this…..
http://www.somsite.com?utm_source=newsletter&utm_campaign=urhcin5&utm
_medium=cpc&utm_term=web+analytics&utm_content=banner_ad
…then the cookie will look like this:
utmz=171169442.1108858716.3.2utmcsr=newsletter|utmccn=urchin5|utmcmd=
cpc|utmctr=web+analytics|utmcctbanner_ad
__utmv – VISITOR SEMENTATION
The __utmv cookie is for custom visitor segmentation. You’ll only see this
cookie if the site calls the _setVar() method. This cookie contains the domain
hash, and one other value: the value you assign using _setVar().
For example, suppose all site visitors who log in get set to “Member”, while
those who do not log in remain unassigned. The Google Analytics account
owner would then be able to compare “Members” to those who are “(not set)”
and see whether, for example, Members convert more often or spend more
money on the site.
The __utmv is a persistent cookie that expires after 2 years.
Try searching your browser cookies for “utmv”. Any sites that appear will be
those that use the Google Analytics custom segmentation feature.
Refer to the module on Custom Visitor Segmentation to learn more about
_setVar() and the __utmv cookie.

50. _______________________________________________________________
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FUNDAMENTALS (SECTION 3)
E-COMMERCE TRACKING:
E-COMMERCE REPORTS
If your site sells products or services online, you can use Google Analytics e-
commerce reporting to track sales activity and performance.
The Ecommerce reports show you your site’s transactions, revenue, and many
other commerce-related metrics.
REPORT EXAMPLES
Some examples of the kind of information you can get from the e-commerce
reports include:
- the products that were purchased from your online store
- a list of transactions, and
- the number of times people visited your site before purchasing
THE E-COMMERCE TAB
E-commerce metrics are also available on the Ecommerce tab which appears in
many reports.
For example, on the Ecommerce tab of the AdWords Campaigns report, you
can see how much revenue is associated with your AdWords campaigns.
HOW TO TRACK ECCOMERCE
THREE STEPS
In order to use e-commerce reporting, you’ll need to do three things.
FIRST, enable e-commerce reporting within your Analytics website profile.
SECOND, add or make sure that you’ve added the Google Analytics Tracking
Code to your receipt page or “Transaction Complete” page.
FINALLY, you’ll need to add some additional e-commerce tracking code to your
receipt page so that you can capture the details of each transaction.
Let’s take a look at each step.

51. STEP 1: ENABLE E-COMMERCE REPORTS
Step 1 is simply to enable the E-commerce selection for the profile.
Click the Account Administration icon. Navigate to the desired account and web
property.
Select the desired profile and click the Profile Settings tab.
You’ll then see the screen shown here.
Select “Yes” next to E-commerce Website and save your changes.
STEP 2: ADD GOOGLE ANALYTICS TRACKING CODE
For Step 2, add the Google Analytics Tracking Code to your receipt page. In
Step 3, you’ll be adding some ecommerce tracking code to the basic tracking
code.
STEP 3 ADD CODE TO TRACK TRANSACTIONS
Here’s an example of what the ecommerce tracking code on your receipt page
might look like. Remember, you’ll be sandwiching this code into the basic
Google Analytics Tracking Code.
In the first part of the code, there is a call to the _addTrans() method. The call to
_addTrans() tells Google Analytics that a transaction has occurred.
The arguments to _addTrans() provide details about the transaction — for
example an Order ID, the total order amount, and the amount of tax charged.
After the call to _addTrans(), there must be at least one call to the _addItem()
method. This call provides Google Analytics with details about the specific item
purchased.
Finally, there is a call to the trackTrans() method which sends all the data to
Google Analytics.
Let’s look at each method in more detail.
CREATING THE TRANSACTION: _addTrans()
The _addTrans() method establishes a transaction and takes the arguments
shown here.
Your code will need to dynamically retrieve the values from your merchant
software to populate these fields.
You can type single-quote single-quote to leave an optional field blank, but note
that Order ID and Total are required.

52. PROVIDING PRODUCT DETAILS: addItem()
For each item that a visitor purchases, call _addItem(). If more than one item is
purchased, you’ll call _addItem() multiple times.
As with _addTrans(), you can leave some of the fields blank, but note that
Order ID, SKU or Code, Price and Quantity are required arguments.
Use the same Order ID that you used in the call to addTrans().
If you’re not sure how to write this code, contact your merchant software
provider.
RECORDING THE TRANSACTION: _trackTrans()
Finally, after the calls to _addTrans() and _addItem(), you’ll need to call
_trackTrans() to send the transaction information to Google Analytics.
Remember that all of the e-commerce code must appear after the Google
Analytics Tracking Code calls _trackPageview().
SECURE PAGES
Generally, you’ll be placing ecommerce tracking code on a secure shopping
cart page.
The standard Google Analytics Tracking Code automatically detects when an
https protocol is being used.
So you won’t need to add any special tracking code for secure pages.
SHOPPING CARTS ON OTHER DOMAINS OR SUBDOMAINS
For many e-commerce websites, the checkout process occurs on a separate
domain or subdomain.
For example, if you send customers from www.mystore.com to
cart.mystore.com, you’re sending them to a subdomain.
If either of these scenarios applies to your site, you’ll need to add some code to
some of your pages so that you can track activity across domains and
subdomains.
The specific methods you’ll use are listed on the slide and you can learn how to
use them in the module on tracking domains and subdomains.
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