Yes, we are here again for the 4th time reviewing CXL Institute’s Digital Analytical Mini degree. As always I start by saying analytics is the sexiest word, for at least the professionals who understand it, most of the students and professionals are following this as a career, rather for the pay than its actual understanding and passion. Let’s not argue over this, since it has lots of points balancing on either side of the equation.
Before I go any further I will just give a brief on myself, I am Nischith a sales & marketing professional working in the health sector. I live in Bangalore India and I am from Mysore, City of Heritage.
The information shared below is based on the learnings from CXL Institute, you need to have a bare understanding of what Digital Marketing or Google analytics is, as CXL themselves say their courses are not for beginners. Let’s dive in, I hope I give you a good insight into their teaching.
Today we will look at some of the features you need to look into to master Google Analytics. This is beyond basic traffic tagging and tracking of results.
First, have your google analytics-ready, more importantly, views, filters ready. Make sure you understand where your traffic is coming from, set your goals. If you have all this great we will start off then.
We will go with Clean Data in Mind,
- Filtering Out SPAM
We will look at 2 things here
What Google Analytics SPAM looks like?
Steps to Remove SPAM
In Google Analytics everything that's recorded is not necessarily from an actual user, It can be spam-generated traffic and fortunately, there are someway you can actually filter that out.
What SPAM looks like in Google Analytics
Dirty data is hiding the story that Google Analytics naturally wants to tell you, right? The more you could get the data cleaned the more you are able to tell the story efficiently.
Just go into your backup data(view) which is not filtered with bot data and now just go to your acquisition report to all traffic report and there go to sources/medium report and check the number of users and later go back to the production view(master view- where bot filters are checked) and follow the same source/medium report there is a difference in the numbers this is the spam or ghost or crawlers. Google has done a tremendous job in avoiding number of spam traffic reduce, but still there is spam to look out for. This is not a one day affair, you need to go back and keep checking for any spams traffic.
Now let's see how spam traffic looks like,
These spams appear in all places, even in language.
Now lets see how to filter it out:
Go to filters, but before going there you need to check for spam hits from different referral sources and follow the below steps
- Filter Name: exclude Spam hits
- Filter Type: Custom > exclude
- Filter Field: Hostname
- Filter Pattern: seostory.xyz|sorrycure.se
- Apply the filter to exclude Spam hits
So, now the other solution is to include the hostnames which you are sure you get traffic, this is just the tip of the iceberg,
refer below links for further understanding.
Again to get clean data you need to clear internal traffic
For example, you have your dev-ops team working on the website and you need to exclude those hits, otherwise, it would affect the priority decision taken for or against the reporting analytics.
Let see how to do that
- Go to All Filters and add filter
- Filter Name field, “Exclude Internal IP”.
- Filter Type, choose Custom.
- Filter Field drop-down menu, select IP Address.
- Filter Pattern field, enter the IP address you want to filter and apply
But practically there are always more than 1 IP addresses, so we usually follow below steps.
- using regular expression you need to enter all IP addresses you would want to exclude.
- For example for the two addresses 22.214.171.124 and 255.255.255.7 you can enter 192\.138\.1\.1|255\.255\.255\.7
- Using regex — regular expression is quite helpful
- Follow the same as above, but in the filter pattern use “\” before every “.” and using a pipe “|” .
We have seen how to filter spam, how to exclude IP addresses, now let's see how to see the uniform hostname, URI, search term, and campaign names since GA is case sensitive.
The users visiting your website with a different letter casings ex: India.com, INDIA.COM & india.com. creating the below filter makes the hostnames consistent.
- Filter Name: Lowercase india.com Hostname
- Filter Type : Custom > Lowercase
- Filter Field : Hostname
Lowercase Request URI
Similar to the previous filter this filter aggregates all the URIs to be lowercase.
- Filter Name : Lowercase india.com Request URI
- Filter Type : Custom > Lowercase
- Filter Field : Request URI
Lowercase Search Term
The users visiting your website with different search terms, Politics in India or POLITICS IN INDIA or politics in India all these are same but should be visible also as the same search term.
- Filter Name : Lowercase india.com Search Term
- Filter Type : Custom > Lowercase
- Filter Field : Search Term
Lowercase Campaign Dimensions
Usually there are multiple campaigns initiated by the marketing department across different products and services.mostly all the time marketing teams use tools, such URL Builder,to generate a campaign URL. However, sometimes two campaign names might be named the same for the same intent of the marketing goal. Here there are chances that different letter casings might be used, this would make GA to record the data for each campaign separately.to make the campaign names consistent following filter has to be created,
- Filter Name: Lowercase india.com Campaign Name
- Filter Type: Custom > Lowercase
- Filter Field: Campaign Name
So one tip you need to learn regex -regular expression it would be quite beneficial to filter data in one statement,
link for your convenience REGEX.
I would also want you to understand the concept of Cross-Domain Tracking, I will just tell you the concept but for the fix I have shared the links for your help.
What is Cross-Domain?
Let's take an example a user(#123) from Facebook visits mysite.com having a product and then adds the product to the cart and moves to the cart.com page and then moves to Purchase & thank you page in mysite.com
You need to go to the basics now, if you have visited 2 domains here mysite.com, cart.com, and back to mysite.com. Here user #123 in the funnel process will not be visible if he goes to the second website cart.com and again the return to mysite.com there is a gap , there is a wrong story to the viewer. cart.com becomes a referrer which is not, attribution to be given to facebook.
This is where we need to understand the cross-domain plugin in GA.As below image shows after the cross-domain fix. After the fix GA recognizes cart.com as a cross-domain. This avoids unwanted data which might arise in the case of 2 or more domains involved in the users journey.
Refer to below links to know further on how to fix cross domain issues in GA
We have discussed today mostly on Clean Data.
Thanks to Mr.Mercer
Next week we will see another topic of interest.