What is Web Analytics?
“Web analytics is the measurement, collection, analysis and reporting of
internet data for purposes of understanding and optimizing web usage.
Web analytics is not just a tool for measuring website traffic but can be used as a
tool for business research and market research, as well as a means to determine
and improve upon the effectiveness of a web site. It helps one to estimate how
traffic to a website changes after the launch of a new advertising campaign. Web
analytics provides information about the number of visitors to a website and the
number of page views. It helps gauge traffic and popularity trends which is useful
for market research.”
* Wikipedia
Why use web analytics?
“If you can’t measure it, you can’t manage it! ”
Google Analytics
What are the different choices in web analytics?
Other analytics packages:
1. eLogic
2. Shiny Stat
3. Site Meter
4. Stat Counter
5. W3 Counter
More……….
Google Analytics
Google Analytics – Setting up an account
1. Setting up a Google Account – search “Google Account”
2. Navigate to Google.com/analytics
Google Analytics
Google Analytics – Setting up an account (continued…)
- Enter general website information
Google Analytics
Google Analytics – Setting up an account (continued…)
- Enter website profile information
Google Analytics
Google Analytics – Setting up an account (continued…)
- Copy and Install Tracking Codes:
Google Analytics
Google Analytics – Setting up an account (continued…)
-
Ecommerce (Where applicable):
Please visit
http://code.google.com/apis/analytics/docs/tracking/gaTrackingEcommer
ce.html
for eCommerce integration
Google Analytics
Google Analytics – Understanding the User Interface (UI)
Google Analytics
Google Analytics – Home Tab
-
Real-Time offers a unique look of what’s currently occurring on the website
Locations shows the location of the current users on the website
Traffic Source shows where these users came from
Content shows which pages these users are interacting on
Google Analytics
Google Analytics – Understanding the User Interface (UI)
Audience: data includes Demographics (location,
language, etc.), New vs. Returning, Technology
(Browser information, Windows/Mac), Mobile (type
of mobile device, etc.)
Advertising: Link to Adwords
Traffic Sources: Sources of traffic, separation
between paid and unpaid traffic
Content: Overview page usage, site speed, entrance
and exit pages, bounce pages.
Conversion: Goal information, funnels, financial
(revenues), product performance, multi-channel
Funnels, etc.
Help Center
Google Analytics
Google Analytics – Traffic Sources
Google Analytics
Google Analytics – Traffic Sources
Search Traffic Report – This report lets you see a breakdown of organic vs. paid
search traffic (Traffic Type), along with the search engines, keywords, and
campaigns (Source) that are sending traffic.
Direct Traffic Report – The information in this report lets you see which of your
URLs are the most popular destinations for direct traffic: which URLs people can
easily remember (e.g., google.com), which addresses appear most often in autocompletion, or which of your pages are bookmarked the most.
Referral Traffic Report - The information in this report lets you see which
domains (and pages in those domains) are referring traffic to your site, how much
traffic they're referring, which landing pages are the most popular referral
destinations, and the extent to which those referred visitors interact with your
site.
Google Analytics
Google Analytics – Organizing Traffic Sources
Google Analytics
Google Analytics – Traffic Sources (Understanding UTM Variables)
- Organizing traffic by classification (IE. Paid Search, Affiliates, Email, etc.)
- Google Analytics allows traffic to be ‘tagged’ using UTM variables.
Most Common UTM Tags
- utm_source = traffic source
- utm_medium = delivery method
- utm_campaign = name to help you keep track of different campaigns
- utm_term = used to identify keywords
- utm_content = used for split testing or separating 2 ads that go to the
same URL
* To create the URL just add a "?" at the end of the URL and then an "&"
between each one of the terms
Slickdeals.net
Paid Click
www.MySite.Com
www.MySite.com?utm_source=AFF&utm_medium=CPA&utm_campaign=Slickdeals.net
Google Analytics
Google Analytics – Organizing Traffic Sources
Google Analytics
Google Analytics – Introduction to Filters
Filters allow you to limit and modify the traffic data that is included in a
profile. For example, you can use filters to exclude traffic from particular IP
addresses, focus on a specific subdomain or directory, or convert dynamic
page URLs into readable text strings. Always use filters with a new profile.
Predefined filters:
Exclude/Include only traffic from the domains: use this filter to
exclude/include only traffic from a specific domain, such as an ISP or company
network.
Exclude/Include only traffic from the IP addresses: use this filter to
exclude/include only clicks from certain sources. You can enter a single IP
address, or a range of addresses.
Exclude/Include only traffic to the subdirectories: use this filter to
exclude/include only traffic to a particular subdirectory (such as
www.example.com/motorcycles).
Google Analytics
Google Analytics – Custom Filters
Exclude Pattern: This type of filter excludes log file lines (hits) that match the Filter
Pattern. Matching lines are ignored in their entirety; for example, a filter that excludes
Netscape also excludes all other information in that log line, such as visitor, path, referral,
and domain information.
Include Pattern: This type of filter includes log file lines (hits) that match the Filter
Pattern. All non-matching hits are ignored and any data in non-matching hits is
unavailable to the reports.
Lowercase / Uppercase: Converts the contents of the field into all uppercase or all
lowercase characters. These filters only affect letters, and do not affect special characters
or numbers.
Search & Replace: This is a simple filter that you can use to search for a pattern within a
field and replace the found pattern with an alternate form.
Advanced: This type of filter allows you to build a field from one or two other fields. The
filtering engine applies the expressions in the two Extract fields to the specified fields
and then constructs a third field using the Constructor expression.
Google Analytics
Google Analytics – Filters (continued…)
Google Analytics
Google Analytics – Filters (continued…)
Walk through an advanced filter entry.
Google Analytics
Google Analytics – eCommerce
** Attribution **
Google Analytics
Google Analytics – eCommerce (Attribution)
Google Analytics attributes goals and revenue to the first click of the last
session.
Session: A session is initiated when a user lands on your site. A new session
is created when:
• More than 30 minutes have elapsed between pageviews for a single
visitor.
• At the end of a day.
• When any traffic source value for the user changes. Traffic source
information
includes:utm_source, utm_medium, utm_term, utm_content, utm_id,
utm_campaign, and gclid.
Google Analytics
Google Analytics – eCommerce (Multi-Channel Attribution)
- An ad is clicked, a purchase is made: Not so simple
When a customer buys or converts on your site, most conversion tracking
tools credit the most recent link or ad clicked. In reality though, customers
research, compare and make purchase decisions via multiple touch points
across multiple channels. So marketers that measure return solely on the
last channel that a customer touches before conversion are getting an
incomplete picture, and potentially missing out on important opportunities
to reach their customers.
Multi-Channel Funnels reports are generated from conversion paths, the
sequences of interactions (i.e. clicks/referrals from channels) during the 30
days that led up to each conversion and transaction. The conversion paths
are collected via the Google Analytics visitor cookie which records
interactions by the same browser and machine. The Multi-Channel Funnels
data combines the Google Analytics conversion data with the sequence of
interactions captured in the visitor cookie.
Google Analytics
Google Analytics – eCommerce (Multi-Channel Attribution)
Assisted Conversion Report
Google Analytics
Google Analytics – eCommerce (Multi-Channel Attribution)
The Assisted Conversions Report
This report shows how many conversions were assisted by each channel
(Assisted Conversions), how many were completed by each channel (Last
Interaction Conversions), and value of these conversions (Assisted
Conversion Value and Last Interaction Conversion Value). The ratio of
Assisted/Last Interaction Conversions shows whether the channel primarily
assisted conversions (values of 1.5 and higher) or completed conversions
(values approaching 0).
Google Analytics
Google Analytics
End of Session 1
Q&A
Google Analytics
Google Analytics – Content Walkthrough
Content Overview provides an at-a-glance overview of the key pageview
metrics for your site
Google Analytics
Google Analytics – Landing Pages
Google Analytics
Google Analytics – Navigational Summary
Navigation Summary allows you to trace the path of users from specific pages on
your site. Using ‘advanced segmentation’, you can narrow down the traffic
criteria.
Google Analytics
Google Analytics – Advanced Segmentation
A segment is a subset of your data. Usually, it refers to a subset of visitors whose
behavior you would like to see and analyze. For instance, usually you are looking at
all visits to your site. You may want to analyze only the "Paid Traffic" or "Visits with
Conversions" or "Organic traffic" segments and even compare these segments side
by side in reports. Advanced Segmentation allows you to isolate and analyze these
subsets of your traffic.
Google Analytics
Google Analytics – Advanced Segmentation
Google Analytics
Google Analytics – Create a Custom Advanced Segmentation
Advanced Segments can be
created using any analytics
variable permutations:
Examples:
1- Traffic with Conversions
2- Paid Traffic with
Conversions
3. Traffic from a keyword that
converted or achieved a goal
Google Analytics
Google Analytics – Filters (continued…)
Walk through an Advanced Segmentation Entry
Google Analytics
Google Analytics – Understanding Goals, Funnels, and Events
Google Analytics
Google Analytics – Understanding Goals, Funnels, and Events
Analytics offers four kinds of goals for different types of conversions:
URL Destination
The conversion occurs because a specific page (or virtual page) is viewed by the
visitor. For example, if you have a lead-generation website that presents a page
that thanks the user for sending contact requests, you could set the URL
to/sales/thankyouforcontactingus.html.
Time on Site
The conversion occurs after a specific period of time has elapsed for the visit. For
example, you could use this type of goal to determine how many visitors stay
longer than two minutes on your newly redesigned shopping page.
Pages/Visit
The conversion occurs after a defined number of pages have been viewed for
the visit. You could use this type of goal when you anticipate visitors to view a
set of 3 pages minimum, for example.
Event
The conversion occurs because an action has been triggered on an event. In
order to set this kind of goal, you must first set up event tracking on your site
with at least one named Event category.
Google Analytics
Google Analytics – Understanding Goals, Funnels, and Events
Event tracking allows you to track and measure user activity separately from
pageviews
Examples:
• Any Flash-driven element, like a Flash website, or a Flash Movie player
• Embedded AJAX page elements
• Page gadgets
• File downloads
• Load times for data
Google Analytics
Google Analytics – Understanding Goals, Funnels, and Events
Event Components
Category: A category is the root level of event tracking and is the base level for
sorting your events. Some example categories are "Videos" and "Downloads".
Action: An action is a descriptor for a particular event. Typical examples include
clicking the Play or Stop buttons for a video. However, actions can be described
by any string you specify. You can, for example, have an action called Video
almost finished that triggers when the play-back slider on a video reaches the
90% mark.
Label: A label is an optional descriptor that you can use to provide further
granularity to your event tracking. You can specify any string for a label.
Value: A value is a numerical variable that you can assign to any event that
you've assigned to a category. You can have explicit values, such as "30", or
inferred values based variables you define elsewhere, such as "downloadTime".
Implicit Count: The implicit count is a count of the number of interactions with
an event category.
Google Analytics
Google Analytics – Event Example
Google Analytics
Google Analytics – Understanding Goals, Funnels, and Events
The Funnel
Visualization Report
This report shows where
visitors enter and
abandon the funnel for
the goal you have
selected. Shown within
each box is the number
and percentage of
visitors who continued
during each step. The
boxes on the right hand
side show how many
people abandoned each
step and where they
went. The boxes on the
left show how people
arrived into the funnel
and where they came
from.
Google Analytics
Google Analytics – Understanding Goals, Funnels, and Events
To create a goal and
funnel, go to setup and
click on Profiles 
Goals  URL
Destination
Google Analytics
Google Analytics – Annotations
Annotations allow you to create
personalized notes in your analytics.
Now, no more wracking your brain
for (or reanalyzing) that incredible
peak in traffic last August or that dip
in your goal conversions the month
before. Instead, you merely write a
note in your analytics when
something unusual happens.
Examples: “New Site
Launched.” “Fall AdWords
campaign began.” “New blogpost
retweeted and retweeted.”
Google Analytics
Google Analytics – Annotations
How annotations look in GA reports
Google Analytics
Google Analytics – Helpful Resources
•
•
•
•
Analytics Help
Google Analytics
Google Analytics – Takeaways
1. Tag all traffic.
2. Always leave an unfiltered profile for backup.
3. Setup multiple funnels to understand how visitors are interacting
with specific parts of your site.
4. Data is great, too much data is overwhelming.
5. Annotate
6. Learn how to use “HELP”
7. Test, measure, adjust…… repeat…
Google Analytics
Q&A
Rafael.Chemtob@Gmail.com
Google Analytics