In April 2009, Google announced that they were making some changes to how the referral URL would look like on their search engines.
One of the key information that’s provided here is the listing’s organic ranking (cd parameter). This can be found in the referral URL property (or document.referrer when referring to the DOM).
It’s been more than 1.5 years since the announcement so I figured that the gradual roll out would be almost complete (I still see instances of the old referral URL being used though) so I decided to implement a filter for Google Analytics that will pull in the organic ranking data and show it in the keyword reports.
Before we get into it, there’s something important to know about the cd parameter. Traditionally in SEO, we’ve always known the SERPs to contain 10 organic listings (as shown below).
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I’ve taken some time out to write a script that provides a nice API to access Google cookies. If you’ve seen the Google cookies before, they can look pretty cryptic and will require you to memorise the syntax of how the cookies are formed which you don’t necessarily want to do to save brain space.
I won’t really go into the intricate details of Google cookies so this post will assume you know what you’re looking for. I may write up a post to explain more in-depth how Google cookies work later on. In the mean time, you can watch this presentation by Google on cookies (it’s pretty good!) or read the documentation to find out more about Google cookies.
So how is this useful? Well it really depends. You may use it to read GA campaign values and integrate it with your CRM system to track where your leads/sales are coming from or write custom scripts that integrate with GA (i.e. custom variables). It’s really up to you!
Anyway, on to the script.
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Thought I’d share a post on how to use advanced filters in Google Analytics and what are some scenarios where they can come in handy.
Advanced filters are very useful for extracting information from available fields (i.e. campaign source, campaign term) using regular expressions and then using the extracted information to manipulate other fields in Google Analytics so that you can customise how data is recorded in your reports.
First of all, before you use advanced filters, it is important that you have some kind of basic knowledge on regular expressions. If you don’t, then perhaps it’s a good idea to read up on what those cryptic symbols mean and how they’re very useful in pattern matching.
If you’ve read my previous post about the GAIQ exam tips, you’ll notice in the section called Adwords Information, I talked about how the initial update by Google on how their cost data import update affected traffic reports in Google Analytics and how we’ve been debating in the GAAC forums about accounts that don’t have cost data import enabled treat Adwords traffic as direct instead of cpc. This will affect the traffic reports by over inflating direct traffic and slowly diminishes cpc traffic.
This really isn’t good as it doesn’t give you an accurate representation on how your online marketing activities are performing. With high direct traffic, you’d probably think, “Holy cow! My website brand really rocks and I don’t have to spend much money on online advertising anymore. Thus, you decide to cut down your Adwords spend or other forms of online advertising.”
One way to overcome that was to manually utm tag your destination URLs which would’ve been a big pain in the butt if you’ve got a large Adwords account with many campaigns and adgroups.
So finally Google made a post about a week ago about another update to the adwords cost data reporting that reverts back to how Google Analytics originally reported traffic from Adwords.
Now if you’ve got your Google Analytics account linked to Adwords, have auto tagging enabled but don’t have Adwords cost data applied, your Adwords traffic will now show as google/cpc, as it was originally.
What you should expect is a drop in direct traffic and a gradual increase in cpc traffic in your traffic reports.
Working in a Google Analytics Authorised Consultants (GAAC) accredited company and also having a Google Analytics Individual Qualification (GAIQ), it is essential that I master the art of setting up goals and funnels in Google Analytics for our clients.
A goal can be a very important metric for a client to track such as sales, newsletter sign-ups, and registrations. Of course goals are not just limited to those but can be extended to whatever you would define as an important action on the website to track. Not only is tracking important, but it is also vital that you gain insight into what’s going on in the goal process from funnels.
A funnel is a visual representation of what’s happening during each step of your goal. It gives you great insights into the drop off rates of each step so that you can make informed decisions on improving your goal process and landing pages to increase conversion rates. You can accurately pinpoint which step of the goal process are you getting high drop off rates.
This can help you identify problems such as the checkout button not working, too many call to actions that lead to other goals, not best practice usability and so on.
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