On default, Google Analytics tracks website behaviour from (almost) everyone that visits your website. For several reasons you should think about setting up different views and segment data before it is shown in Google Analytics.
If you haven’t read it yet, check out this article about Google Analytics filters and views.
It shows in great detail how to work with filters in Google Analytics and why they are so incredibly powerful.
Because of several reasons, I recommend to set up a view that only tracks your behaviour.
Tip 8: Create a Separate View With Only Your Google Analytics Data
Why to Separate Out Your Data?
If you need to test your Google Analytics implementation, a view that only includes traffic from your IP address really comes in handy.
Imagine your website receives 10.000+ visitors per day. How do you recognize your specific behaviour and actions?
In the past I have done tons of Google Analytics implementations and in my experience you simply need to test everything.
If you implement something (tricky), this separate view makes it easy to check whether things work the way you planned.
Set Up a View With One Include IP Filter
First of all, visit this website to retrieve your unique IP address. Save it in a temporary document.
Follow these steps to set this up in the correct way:
- Log in to your Google Analytics account
- Navigate to the appropriate account and property
- Create a new view for this property
- Create a new filter on your IP address
The Easy Way
This strategy applies if you only need to filter out one IP address:
The Hard Way (sometimes this is the only way)
What if you perform tests at two different IP addresses, both at home and at work?
Well, unfortunately adding two include filters of the same type doesn’t work. Most often this leads to zero data being collected in your Google Analytics view.
You can solve this by including two IP addresses in one filter:
This might look daunting at first. Read this post about regular expressions in Google Analytics to educate yourself on this topic.
A few things to note:
- ^ (it means your expression starts with the exact character(s) that is/are shown next to this icon)
- \ (this lets you “escape” special characters (“.” is an example of a special character))
- $ (it means your expression ends after the character in your expression)
- | (“if” statement; it makes it possible to include two or more IP addresses)
Note: this advanced filter might include data from colleagues who are on the same IP.
After saving your filter, you need to go to the filter section in your Google Analytics view.
Just select “Apply existing filter”, add the filter you have just created and you are ready!
Please note that it might take up a few hours before the filter becomes active.
How to Put Things in Practice
You might think great stuff, but how do I use this effectively? Read on!
Google Analytics offers very powerful real-time reports:
Imagine that your implementation is done or still waiting in a staging environment.
No matter what is the case, you can immediately test whether things work correctly.
Some things to consider testing:
- Traffic Sources: is my session (visit) registered on the appropriate medium and source? Did I implement campaign tracking correctly?
- Content: does my (virtual) pageview tracking work the way I want?
- Events: does my Google Tag Manager auto-event tracking works well?
- Conversions: did I set up my goals in the correct way?
I could make a list of 100 items, but I don’t. :-)
I like to leave some space for you to experiment and come up with great ideas by yourself!
There are definitely more solutions to check your implementation and data collection process. Read this great post by Cardinal Path for a list of debugging tools that might come in handy.
This is it! I am very curious to hear your opinion and experiences.
If anything is on your mind, please bring it up and add some extra value to this post.One last thing... Make sure to get my extensive checklist for your Google Analytics setup. It contains 50+ crucial things to take into account when setting up Google Analytics.