Google Analytics IQ Lesson 3: Fundamentals

Google Analytics IQ Lessons

3. Fundamentals

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Based on Google’s Conversion University

3.1. Profiles in GA
• If you manage analytics for diferent
organizations, you’ll want an account for each.

• You can create up to 25 analytics accounts per
Google username. However, you can be added as
an administrator to an unlimited number.

• To give others access to your GA, you use the
User Manager (from the Analytics Settings).
• Inside it you can view the users who currently have access

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3.1. Profiles in GA
• There are two types of GA users:
• “Administrators” full access and can modify settings.
• “Users” only have read access to reports.

• If you manage the analytics services for several
websites which belong to diferent
organizations, the best practice is to create a
separate Analytics account for each
• If not any Administrators you created on the account
would have access to all the reports for all the
websites.
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3.1. Profiles in GA
• On your Analytics Settings page, you can see a list of
the profiles that belong to the account.
• Profiles are very flexible -- they are basically just a set
of rules that define what data is to be included in the
reports:
• You’ll have a separate profile for every domain or
subdomain.
• A profile that tracks only a certain part of a site or that
only tracks a certain kind of traffic.
• Profiles with diferent set of reports. You could give some
users access to one and other users to another.
• Each user would only see reports that apply to them.
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3.1. Profiles in GA
• A profile consists of settings that define the reports
that you see. These include user access, goals, and
filter settings (up to 50 profiles /account - you’ll need
to be an Administrator to add a new profile.)
• You can see the diferent domain tracking in the
tracking code number for each profile:

• The longer number (Xs), is the GA
• Then, “dash 1” and “dash 2” are the property number
• Profiles 1 and 2 are tracking the same domain = “duplicate
profiles” for containing diferent subsets of data
• Profile 3 is tracking another domain (diferent property #) 5

3.2. Campaign Tracking & Adwords
• GA allows you to track and analyze all of your
marketing campaigns. There are two ways to
track ad campaigns:

• For AdWords campaigns, you should enable keyword
autotagging. This allows to automatically populate
your reports with detailed AdWords information.
(You’ll need to link your AdWords and GA.)

• Manually tag links with campaign-identifying
information. You may also choose to manually tag
AdWords links. (The tags are campaign variables that
you append to the end of your URLs.)
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• By linking GA to AdWords account, you get advanced reporting
that measures performance and ROI for your AdWords campaigns.

• Within AdWords, select GA under the Reporting tab to link your
accounts (you’ll need administrator privileges in Analytics to link
them). If you don’t have a GA account, you’ll be able to create one.

• When you link them, you should enable "Destination URL
Autotagging” to diferentiate paid ads from SEO and referrals and
to see more info in the AdWords section of your Traffic Sources
reports.

• Your cost data 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.
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• Be aware that you can only link one Analytics
account to one AdWords account.
• For administration purposes, you will want to
create a new Analytics account for each
AdWords account.
• Note that once you have linked them, the
time zone in GA will automatically take that of
the AdWords Account (if they are diferent).

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• Autotagging works by adding a unique id, or g-c-l-i-d, to the end of your
destination URLs, which allows Analytics to track and display click details in your
reports.

• 3rd party redirects and encoded URLs can prevent autotagging from working
properly.

• Notice that the first query parameter is always preceded with a question mark. Subsequent
values are separated using ampersands.

• To enable autotagging, select “My Account” > “Account Preferences” > Make sure
that the Tracking option reads “yes”. If it says “no”, click the edit link, check the
box for “Destination URL Autotagging” > “Save Changes”.

• When linking for the first time your AdWords account to Analytics, you’ll be
prompted to automatically select “Destination URL Autotagging” and “Cost Data
Import”.

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• All AdWords cost data from an account will be imported into any
profile in which the Apply Cost Data checkbox is selected.

• 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.

• Make sure both your AdWords and Analytics accounts are set to
the same currency so that ROI data is accurately calculated.

• And finally, note that Google Analytics is only able to import cost
data from AdWords, and not from other ad networks.

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• You may notice diferences between the data in GA and AdWords:

• AdWords tracks clicks, while Analytics tracks visits.
• Some visitors who click may have JavaScript, cookies, or images
turned of, so Analytics won't report these visits, but AdWords will
report the click.
• Maybe the GA Tracking Code on your landing page doesn’t execute.
• Google AdWords automatically filters invalid clicks from your reports,
Google Analytics will still report the visits.
• AdWords data is uploaded once a day to Analytics so the results for
each may be temporarily out of sync.
• 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.

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• GA automatically tracks all of referrals and
searches that send you traffic.
• However, if you are running ad campaigns, you
should add tags to the destination URLs of your
ads.
• If you manually tag your AdWords ads, the
reports will only show you information by
Campaign and Keyword.
• If you enable auto-tagging, you’ll see much more
detail. The AdWords reports will show you results
by ad group, matched search query, placement
domain and many other AdWords attributes.
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• To tag a URL, you add ‘?’ to the end, followed by your tag. The variables
and values are listed as pairs separated by ‘=’ and each pair is separated
by ‘&’. There are five variables you can use when tagging URLs:

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• Let’s look at where information from each of the tags shows up in your
reports:

• Source: All Traffic Sources report. This report will include not only all the sources you tagged,
but also sources like “direct” and website names.

• Medium: You can see also see traffic by medium in the All Traffic Sources report. In
addition to all the mediums you tagged, you’ll also see mediums such as “referral” and
“organic”.

• Campaign: will appear in the Campaigns report.

• Term: Keywords report.

• Content: Ad Versions report.

• You can also segment on any of these variables.
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• 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.
• The URL builder can only construct one URL at a time.

• If you have many 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.

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3.3. Analysis focus - Adwords
• The Adwords Report gives you post click performance for
your traffic from Adwords so you can see what happened
afer visitors clicked on your ad. You can review usage
metrics, goal conversions, e-commerce activity, ROI… Others:
• Impressions: number of times your ad was displayed
• CTR: clicks/impressions
• Revenue per click, ROI and margin help you assess keyword keyword
profitability.
• If RPC are 0 and ROI -100% it is because you have 0 revenue, make sure you’ve set
goal values and enabled e-commerce tracking.
• Before you delete negative ROI consider if you have enough data (too short time
ranges?)

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3.3. Analysis focus - Adwords
• The Adwords Report organises data according to campaign, ad
group and keyword. Click on any of them to see the drilldown – all
metrics are available at each level.
• You can also organise according to a variety of Adwords
dimensions (match type, etc) – only available with autotagging.
• Use Day Parts Report to find out which times of day your campaign
is most efective.
• Destination URLs Report which URLs received traffic from
Adwords, so you can see which one performed better.
• Overview gives you shortcut links to common used analysis.
• To find our which placements work best, look on overview and
navigate to the Placement Report.
• Keyword Position reports tells you how ad position afected your
keywords performance.
• Use the TV Campaigns Report to track your TV campaign with time,
type of audience and program you targeted.
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3.4. Goals and Funnels
• Defining site goals and tracking goal conversions assesses how well your site meets its
business objectives.

• A goal represents an activity or a level of interaction with your website that’s important to
the success of your business.

• There are three types of goals in GA:
• A URL Destination goal is a page that visitors see once they have completed an activity
• 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.

• For each URL Destination goal you can also define a funnel = the set of steps, or pages, that
you expect visitors to visit on their way to complete the conversion.

• Defining a funnel is valuable because it allows you to see where visitors enter and exit the
conversion process.

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• To set up a goal: Settings page and edit the the profile for which you want to configure it. Then
look for the “Goals” section.

• You can create up to 4 sets of 5 goals each.

• To define a URL Destination Goal:
• You don’t have to enter the entire URL, simply enter the request URI (what comes afer the domain or hostname).
• You can also enter a name for the Goal (it will appear in your conversion reports).

• Defining a funnel is optional: add the URLs (or URIs) of the pages leading up to the goal URL and
provide a name for each step in the funnel

• The match type defines how Google Analytics identifies a goal or funnel step. Three types:

• “Head Match” is the default. 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.
• “Exact Match” means that the URL of the page visited must exactly match what you enter for the Goal URL. Exact
Match can only be used to match one single page.
• “Regular Expression Match” gives you the most fexibility. 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.

• Check “Case Sensitive” if you want the URLs you entered into your goal and funnel to exactly
match the capitalization of visited URLs.
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• Threshold goals (Time on Site and Pages per Visit) are useful for
measuring site engagement, whereas URL Destination goals are best for
measuring how frequently a specific activity has been completed.

• “Goal Value” allows you to specify a monetary value for goal. You should
only do this for non-ecommerce goals.
• GA will be able to calculate metrics like average per-visit-value and ROI. These metrics
will help you measure the monetary value of a non-ecommerce site.

• There is an important diference between goal conversions and e-
commerce transactions: a goal conversion happens once during a visit,
but an e-commerce transaction can occur multiple times during a visit.

• If you are using a filter that manipulates the Request URI, make sure that
your URL Destination goal is defined so that it refects the changed
Request URI field.
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• If you define a funnel for a goal, you have the
Funnel Visualization report:
• Lef: how visitors entered. Right: where they leave
and go.
• The middle shows you how visitors progress, how
many of them continue on to each step.

• The Reverse Goal Path report (available with or
without funnel) lists the navigation paths that
visitors took to arrive at a goal page and shows
you the number of conversions in each path.

• 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 efective site.

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3.5. Filters
• Google Analytics filters provide you with an extremely fexible way of
defining what data is included in your reports.

• You can use the Filter manager to create new filters, to edit their settings,
and to delete them. To apply filters to a profile, you edit the profile.

• 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.

• You can set up filters from the Analytics Settings page:
• Begin by editing the profile. Then, under “Filters Applied to Profile”, click “Add Filter”.
• Now you have two options: add a new filter or apply an existing filter.
• 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.
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3.5. Filters
• GA provides 3 predefined filters:

• “Exclude all traffic from a domain”: GA 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.

• “Exclude all traffic from an IP address”, removes traffic from addresses
entered into the IP address field. This filter is generally used to exclude your
internal company traffic.

• “Include only traffic to a subdirectory”, 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.

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3.5. Filters
• In addition you can also create custom filters. To create a
custom filter, select “Custom filter” from the “Filter Type”
drop-down. Each custom filter has three main parts:

• “Filter Types”. There are six filter types available and each one serves a
specific purpose.

• “Filter Field”. There are numerous fields you can use to create your filter (Eg.:
Request URI, Visitor Country…). Complete list of fields can be in the Analytics
Help Center.

• “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.
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3.5. Filters
• Filter types:

• Exclude and Include filters are the most common. They allow you to segment
your data in many diferent 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. They are very useful for consolidating line items in a report when the
only diference between the multiple entries is that sometimes the URL or
keyword appears with a diferent combination of upper/lowercase letters.

• Search and Replace filters replace one piece of data with another. They are
ofen used to replace long URL strings with a shorter string that is easier to
read and identify.

• You can use Advanced filters to remove unnecessary data, replace one field
with another, or combine elements from multiple filter fields.
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3.5. Filters
• You can track and segment multiple sites from the same Analytics
account, using the same JavaScript code. And once you’ve defined a filter,
you can apply it to a single profile or across several profiles.

• By setting up multiple profiles and applying filters creatively to each of
them, you have a great deal of reporting and analysis fexibility.

• Again, you use the Filter manager to create and manage filters. To apply
filters to a profile, you edit the profile.

• You can also use profiles and filters together to create customized data
views. Remember, you always want to maintain a profile that contains all
of your data.

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3.5. Filters
• If your subdomains are totally separate businesses, and you don’t need
cumulative traffic, then you could simply create a unique profile for each.
– To do this, 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.

• If you want to analyze the traffic aggregated across both, you could set up
at 3 duplicate profiles. Then, you’d apply an Include filter to two of them:

• In this scenario, you’d install identical tracking code on every page of the
site regardless of subdomain.
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3.5. 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.

• 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.

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3.6. Regex
• A regular expression is a set of characters and metacharacters that are
used to match text in a specified pattern. You can use regular expressions
to configure fexible goals and powerful filters.
• For example, if you want to filter out a range of IP addresses.

• Metacharacters are characters that have special meanings in regex.
1.) DOT

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3.6. Regex
2.) BACKSLASH

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3.6. Regex
3.) RANGES AND CHARACTER SETS

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3.6. Regex
4.) QUANTIFIERS AND REPETITION

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3.6. Regex
5.) GROUPING

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3.6. Regex
6.) ANCHORS

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3.6. Regex
7.) SHORTHANDS AND CHARACTER CLASSES

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3.6. Regex
There are several common uses for regex within GA:

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3.7. Cookies
• Some web sites store information about you or your computer in a
small file called a cookie, stored on your hard drive. There are 2
types:
• First-party: 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.

• Users can choose whether to allow some, none, or all types on
their computers. 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.

• Sites that run GA issue first party cookies that allow the site to
uniquely, but anonymously, identify individual visitors.

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3.7. Cookies
• Cookies can be set with or without an expiration date:

• 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.

• Many kinds of sites require that visitors have cookies enabled:
• to login to many online shopping carts and to use web mail.

• First party cookies (GA’s) 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. Webs can’t access to any information on your computer unless
you provide it. And since GA only uses first party cookies, GA cookies can
only be read by the website that created them. 38

3.7. Cookies
• Google Analytics sets five first-party cookies:

• The __utmv cookie is optional, and will only be set if the _setVar()
method is called (explained later)
• All are persistent except __utmc cookie.
• All cookies are browser-specific.
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3.7. Cookies
__utma – visitor identifier

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3.7. Cookies
__utmb and __utmc – Session Identifiers

•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.

•Key diference: __utmb is persistent, expiring 30 minutes afer it is created.
__utmc is temporary.
• Each time the visitor navigates to a new page and the JavaScript in the GA Tracking
Code is executed, the __utmb cookie is refreshed and set to expire in 30 minutes.
As long as the visitor remains active on the site, the session remains active.
• 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, a new __utmb cookie is
created and, so this is a new session.
• So, why is the __utmc cookie needed? If 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.

Note that it is possible to adjust this behavior customizing the GA Tracking
code, you can make the session timeout length anything you want.
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3.7. Cookies
__utmz – Campaign Cookie

•It stores the campaign tracking values that are passed via tagged campaign URLs (utm_source, utm_medium,
and utm_campaign) and will show up in your All Traffic Sources report.

•Preceding the campaign tracking values, you will see four numbers:
– domain hash
– Timestamp
– “session number”: increments for every session during which the campaign cookie gets overwritten.
– “campaign number”: increments every time you arrive at the site via a diferent 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.
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3.7. Cookies
__utmz – Campaign Values

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3.7. Cookies

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3.8. E-Commerce
• If your site sells products or services online, you can use GA to track sales
activity and performance.

• The Ecommerce reports show you your site’s transactions, revenue, and many
other commerce-related metrics. .
– the products that were purchased from your online store
– your sales revenue
– your e-commerce conversion rate, and
– the number of times people visited your site before purchasing

• E-commerce metrics are also available on the Ecommerce tab which appears
in many reports.

• In order to use e-commerce reporting, you’ll need to do three things:

1) Enable e-commerce reporting within your Analytics website profile.
2) Add or make sure that you’ve added the GA Tracking Code to your receipt page
3) 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 => See next slide!
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3.8. E-Commerce

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3.8. E-Commerce
_addTrans() – Creating the transaction

•Your code will need to dynamically retrieve the values from your merchant sofware 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.
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3.8. E-Commerce
_addItem() – Providing Product Details

•As with _addTrans(), you can leave only some of the fields blank.Your code will need to dynamically
retrieve the values from your merchant sofware 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 (use the
same Order ID that you used in the previous step)
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3.8. E-Commerce
_trackTrans() – Recording the Transaction

•This happens to send the transaction information to Google Analytics.
•Remember that all of the e-commerce code must appear afer the Google Analytics Tracking Code calls
_trackPageview().
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3.8. E-Commerce
• Generally, you’ll be placing ecommerce tracking code on
a secure shopping cart page.
• The standard GA 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.
• For many e-commerce websites, the checkout process
occurs on a separate domain or subdomain.
• 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 here (more on it in the
module on tracking domains and subdomains)

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3.9. Revenue
• The Goal Conversion tab displays a metric called Per Visit
Goal Value. It is calculated based on the goal values that you
set.
• The Ecommerce tab displays three revenue related metrics:
Revenue, Average Value, and Per Visit Value .
• The diference: Per Visit Value is calculated using e-commerce
revenue. Per Visit Goal Value is calculated using static goal values.

• There are a few places where Goal Value and Ecommerce
Revenue are summed:
– On the Clicks tab, the Revenue per Click, ROI, and Margin are based on
the sum total of Goal Values and Ecommerce Revenue.
– In the Content reports, the $ Index metric is also based on the sum
total of Goal Value and Ecommerce Revenue (see next)
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3.9. Revenue
• The $ Index metric appears in most of the Content reports and it allows you to identify the
pages that have the most impact on site profitability.
• The calculation for $ Index assigns the highest values to pages that are frequently viewed
prior to high value conversions or transactions.

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3.9. Revenue
• $ Index uses unique pageviews. This means that a page is only counted
once per visit, even if a person views the page multiple times before
converting.

• Also, only pageviews that precede the conversion or transaction are
counted.

• If you aren’t tracking ecommerce revenue in Google Analytics and you
haven’t assigned values to your goals, all of your $ Index values will be
zero.

• Finally, $ Index is most useful as a point of comparison or a ranking
metric, not as a standalone number. It’s designed to help you identify the
pages on your site that are most valuable.

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3.10. Domains and Subdomains
• A domain is a hostname that represents a numeric IP address
on the internet. It allows us to easily identify a website by a
name instead of having to use a long string of numbers.

• You may sometimes need to track activity across multiple
domains: if a session spans multiple domains, it would not be
possible to track the session as a single visit attributed to one
visitor. So, you’ll need a way of sharing the cookie
information between the two domains.

• Using the _link() method, allows GA Analytics to track a user
across multiple domains by sending cookies via URL
parameters (2 steps)
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• To track across domains, you’ll need to follow two steps.
1) Add a few lines to the GATC on all pages of each site:
Call _setDomainName() with an argument of “none”.
call _setAllowLinker() with an argument of “true”.

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2) Update all links from Google.com to YouTube.com (following example)
and vice versa using _link(). Now, when a user clicks on a link that takes them
to the other domain, the session information is preserved and the user is
identified as being the same visitor across both domains.

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If you use a form to transfer your visitors from one domain to another, you
will need to use the _linkByPost() method instead of the _link() method.
• This situation occurs most ofen with third party shopping carts, to send cookie data to
other domains in pop-ups or iFrames.

To use forms to transfer from one domain to another, you must modify all
the appropriate forms with the code.

The _linkByPost() method will change the form action by adding query-string
parameters to the value in the action attribute when the visitor submits the
form.

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• You may also sometimes need to track across multiple subdomains. A
subdomain is part of a larger domain and frequently each subdomain
contains the pages for a specific department or ofering.

• As with multiple domains, you need to explicitly share the cookie
information between subdomains or you’ll lose session information. If
you don’t share cookie information between your subdomains, it may
appear as though your own site is a referrer since only one domain is
recognized as the main domain.

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• To track across multiple subdomains, call _setDomainName() and
specify your parent domain name as the argument. This will allow
the GATC to use the same cookies across the subdomains.

• A side efect of using this method is that your reports may not
diferentiate between visits to identically named pages within the
various subdomains.

• You can prevent this with 2 best practices:
1) Create separate profiles for each subdomain. This way, you’ll be
able to see reports for each subdomain.
– Set up duplicate profiles - one master profile, plus one profile for each
subdomain.

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2) If you track several subdomains within one profile, your reports may not
diferentiate between visits to identically named pages within the various
subdomains:
– This is because the reports only show the Request URI. The hostname is
stored in the Hostname data field in GA.
– So, once you’ve called _setDomainName() to set your primary domain name,
visits to both subdomains will be interpreted as the same page.

• To correct this, you can
set up an advanced
filter to include the
subdomain in your
reports as shown:

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Google Analytics IQ Lesson 3: Fundamentals

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