Advanced segments allow a good Google Analytics user become a Great analytics user – for that matter, a great internet marketer.

I manage PPC campaigns for clients over at this internet marketing company and as such, build many different campaigns with different focuses.  Some are interested in leads, others sales and some understand the importance of “micro conversions” or steps in the overall sales process.  For clients who understand the value of micro conversions (visits to key pages, downloads of white-papers, views of video’s etc), setting up goals around these items is your first step.  With advanced segments, you are able to take aspects of traffic and measure its performance against these goals.

How to Create an Advanced Segment

1. First, have a plan for what element of traffic you want to analyze.  For this example, lets look to segment all “paid” traffic as my client wishes to see how his paid ads are performing in Google, Yahoo and MSN in addition to the paid banner ads.

2. To do this, pull “medium” from the dimensions drop down over into the dotted line box, the condition should be “matches exactly” and then type “cpc” into the box.

3. Click “add or statement” and repeat step 2 but type “banner” in the box where “cpc” was typed before.  NOTE: In order for this segment to result in traffic, your banner ads links need to be tagged properly using Google’s URL builder and the medium function will have needed to be tagged with “banner”

4. Be sure to name the advanced segment – “Paid Traffic” for example would make a nice title.

5. Click “test segment” to ensure your filter is working properly and results in a positive number of visitors.

6. Save the segment and return to the Google Analytics dashboard.

Above the date range, there is a drop down for Advanced Segments, select this and open up the options for Google’s pre-defined Advanced Segments, and (to the right) your new segment.  Select the option from the check box and vola! You should now see how your paid traffic performs in comparison to All traffic (or any other advanced segment you created).

Filter Name: Display Full URL

Filter Purpose: This filter comes in handy when you are tracking multiple sub domains or third party domains in one profile.  Before I continue, if you are attempting to do this, make sure you read how here and understand that you will “break” the site overlay report.  Applying this filter will show you the full URL from you main site, sub domain or third party domain.

Filter Difficulty: Easy

Instructions:

Create a test profile – always a good idea when testing with filters.

Filter Name: Display Full URL

Filter Type: Custom Filter

Advanced

Field A -> Extract A = Referral – (.*)

Field B -> Extract B = User Defined – $A1

Case Sensitive – NO

Filter Credit: Reuben Yeu – Online Marketing and SEO Consultant

Filter Purpose: Whether your website serves a large organization or is a small “mom and pop shop” filtering out internal traffic can make a big difference in the statistics you generate from Google Analytics – or any analytics package for that matter.  If you measure Goals (and I strongly recommend you do), in general, an internal visitor to the site (employee etc) is less likely to complete a goal (form fill out or purchase) as that isn’t their intention of visiting the site.  Further to that, many large organizations set their computers to default to the company home page as the first site a browser loads when opening.  As a result, you would most likely see an abnormally high bounce rate, low page views and skewed numbers to your return visitor stats.  Thus, filtering out your internal traffic is very important.

Filter Difficulty: easy – moderate (depending on if you have multiple IP ranges to filter).

Instructions:

1. Make a record of the individual IP addresses and a list of the IP ranges for your company.

2. Create individual IP filters for the individual IP addresses, be careful to use the proper regular expressions when creating your filter.  For example, the IP address 173.32.223.162 should be entered in as  173\.32\.223\.162

3. Take your IP ranges and enter them into Google’s handy IP Address Exclusion generator here: http://www.google.com/support/analytics/bin/answer.py?hl=en&answer=55572

An individual IP Address Exclusion should look like this:

An IP range filter, using Google’s tool above, should look like this:

Filter Name: IP Address Filter

Filter Type: Exclude All Traffic from an IP Address

Filter Field: IP Address

Filter Purpose: To ensure URL’s and pages that can be visited/accessed using both upper case and lower case characters are reported as the same page.  For example:

www.analyticscookies.com/Google-Analytics.html

www.analtyticscookies.com/google-analytics.html

are reported as the same page.  Without this filter, Google Analtyics will report these pages as unique, when they should be the same.

Filter Difficulty: easy

Instructions: As with every filter, be sure to create a test profile so as to keep your main site data in tact.

Filter Name:Force Lowercase

Filter Type: Custom Filter, Lowercase

Filter Field: Request URI

Filter Credit: Google

There are 4 types of cookies that fall into two categories.

• First Party Cookies
• Third Party Cookies
• Persistent Cookies
• Temporary Cookies

First Party vs. Third Party Cookies

“Back in the day” analytics providers used third-party cookies which meant, when you visited a site, www.analyticscookies.com for example, the cookie was sent from the vendor – www.omniture.com for example.  These third-party cookies handled visitors who navigated across multiple, unrelated domains within a companies site.  Due to issues around privacy and issues around some companies using third-party cookies to provide personal information, users began to block third-party cookies.  Most analytics vendors have now switched to first-party cookies.

A first-party cookie is now primarily used because web users tend to delete or reject them less frequently.  As a result, they do a very good job of tracking repeat visitors.  In fact, some sites like gmail won’t work unless you accept first party cookies.

Persistent vs. Temporary Cookies

A temporary cookie (also called transient or session cookie) is used to track a users session.  When a user visits a site, performs some actions (clicks, navigates, perhaps fills out a form) these are tracked as a session.  The cookie is set when you visit a site and deleted when you leave – hence the name “temporary”

A persistent cookie is set when a user visits a website for the first time.  It will remain on a users computer for the duration that the website determines – more often than not, about 18 months.  Persistent cookies remain until a users either deletes the cookie.  If and when the cookies is deleted, and a user returns to the same website, the analytics package would define this second visit as a “new visit.”  This, along with many other reasons are why analytics systems are never “perfect” and any good web analytics consultant should educate their clients of the limitations of some systems.