Complete guide to Filter Verification in Google Analytics
Introduction to filter verification
In Google Analytics, a filter can permanently change the data that appears in a GA view.
Data once filtered (i.e. included, excluded or modified) can not be unfiltered.
So if you set up an incorrect filter, your historical data is skewed for good.
Therefore it is important that you test your filter before creating it.
The method of testing a filter before creating it is called ‘filter verification‘.
Google Analytics built-in verification tool
Google Analytics has got built-in verification tool for testing view filters which you can access while creating/editing a filter:
However this built-in verification tool has got following limitations:
#1 It can not be used to test IP based filters and other location based filters:
#2 It can not be used to test advanced filters:
#3 It can not be used again on an existing filter. If you try to test an existing filter by clicking on the ‘verify this filter’ link then you are likely to see following error message:
This filter would not have changed your data. Either the filter configuration is incorrect, or the set of sampled data is too small.
So if you want to test an existing filter again, via the GA built-in verification tool then first delete the filter and then create a new filter.
Creating a filter vs. Updating a filter
In GA, you create a filter by saving it once.
However when you save the same filter again, it updates the existing filter.
This filter update can take a long time (as much as 24 hours) to take effect.
So avoid testing your updated filter straightaway.
Configuring a filter
‘Setting up a filter’ is also known as ‘configuring a filter‘.
You can configure a filter by adding/changing various filter attributes like:
- Filter name
- Filter type (predefined or custom)
- Filter field
- Filter pattern
Following screenshot show the various filter attributes:
The order of filters
If you have created more than one filter in GA view then they are applied to your GA view data in the order in which you created them.
So existing filters are applied before new filters according to their current ranking position.
In the screenshot below:
The the filter named ‘exclude internal traffic-3’ has ranking of 1.
So this filter will be applied first to your data.
After this filter is processed then the second filter named ‘home’ will be applied to your data.
However you can change the filter order by clicking on the ‘Assign Filter Order’ button (see the screenshot above).
By changing the filter order, the filter named ‘home’ get the first rank and is applied first to your data:
Sometimes the order in which filters are applied to the data in your GA view can make it hard to test a filter.
So if your filter verification is not working then you may need to test the order of existing filters and/or remove other filters.
8 Steps process to testing a new filter in Google Analytics
Follow the steps below to test a new filter in GA:
Step-1:Create a test property in Google Analytics.
A test property is a duplicate of your live GA property.
Do not use live property to test your filters or to test anything.
This is because data once filtered can not be unfiltered in GA.
So if you accidentally applied a wrong filter, your GA data will get skewed for good.
Though GA filters are view based, i still recommend using the test view of your ‘test property’ as a best practice.
Step-2: Create a copy of the unfiltered view in your test property and name it ‘test view’:
Step-3: If you already have a test view, then remove any existing filter from it before you test your new filter.
Step-4: Make sure that your test view contains at least 7 days of historical data. This is because GA need at least 7 days of historical data before it can display the ‘filter verification preview table’.
Following is an example of filter verification preview table:
Through ‘filter verification preview table’ you can see, how your new filter will change the existing view data.
Step-5: Check through the reporting interface filter whether the data you want to filter (include, exclude or modify) actually exist in your test view.
Following is an example of ‘reporting interface filter’ (available in almost all GA reports):
If the data you want to filter do not already exist in your test view then you can not test your new filter.
If you still go ahead and test your new filter (by clicking on the ‘verify this filter’ link) then your filter won’t work because there is no existing data that match your filter criteria and you are likely to see following error message:
This filter would not have changed your data. Either the filter configuration is incorrect, or the set of sampled data is too small.
Step-6: Test your ‘filter pattern’ before you use it in your filter esp. if your ‘filter pattern’ contains Regular expressions (also known as ‘regex’).
Use Regex101 tool to create and test your regular expressions.
Use the ‘JavaScript’ flavour as Google Analytics accept POSIX JavaScript regular expressions.
Following is the interface of ‘Regex101’ tool:
Related Article: Google Analytics and Google Tag Manager Regex (Regular Expressions) Guide
Step-7: Once you have created and tested your regex using ‘Regex101’ tool then use the ‘reporting interface filter’ in your GA test view to test your regular expression one more time.
This is because there is no guarantee that the regex validated by ‘Regex101’ tool will almost always work correctly in GA:
Note: If the regex used in the ‘Filter pattern’ field is not correct and you clicked on the ‘verify this filter’ link then your filter won’t work because your filter criteria does not match the existing data and you are likely to see following error message:
This filter would not have changed your data. Either the filter configuration is incorrect, or the set of sampled data is too small.
Step-8: Enter the validated regex while creating a new filter in the ‘filter pattern’ field and then click on the ‘verify this filter’ link.
If you filter include/exclude/modify your data then you are likely to see ‘filter verification preview’ table.
If your filter does not include/exclude/modify your data then you are likely to see following error message:
This filter would not have changed your data. Either the filter configuration is incorrect, or the set of sampled data is too small.
What is the difference between Digital Analytics and Google Analytics?
99.99% of course creators themselves don’t know the difference between Digital analytics, Google Analytics (GA) and Google Tag Manager (GTM).
So they are teaching GA and GTM in the name of teaching Digital analytics.
They just copy each other. Monkey see, monkey do.
But Digital analytics is not about GA, GTM.
It is about analyzing and interpreting data, setting up goals, strategies and KPIs.
It’s about creating strategic roadmap for your business.
Digital Analytics is the core skill. Google Analytics is just a tool used to implement ‘Digital Analytics’.
You can also implement ‘Digital analytics’ via other tools like ‘adobe analytics’, ‘kissmetrics’ etc.
Using Google Analytics without the good understanding of ‘Digital analytics’ is like driving around in a car, in a big city without understanding the traffic rules and road signs.
You are either likely to end up somewhere other than your destination or you get involved in an accident.
You learn data analysis and interpretation from Digital analytics and not from Google Analytics.
The direction in which your analysis will move, will determine the direction in which your marketing campaigns and eventually your company will move to get the highest possible return on investment.
You get that direction from ‘Digital analytics’ and not from ‘Google Analytics’.
You learn to set up KPIs, strategies and measurement framework for your business from ‘Digital analytics’ and not from ‘Google Analytics’.
So if you are taking a course only on 'Digital Analytics’, you are learning to use one of the tools of ‘Digital analytics’. You are not learning the ‘Digital analytics’ itself.
Since any person can learn to use Google Analytics in couple of weeks, you do no get any competitive advantage in the marketplace just by knowing GA.
You need to know lot more than GA in order to work in digital analytics and marketing field.
So what I have done, if you are interested, is I have put together a completely free training that will teach you exactly how I have been able to leverage digital analytics to generate floods of news sales and customers and how you can literally copy what I have done to get similar results.
You can sign up for the free training here: https://learn.optimizesmart.
I truly hope you find it helpful.
My best selling books on Digital Analytics and Conversion Optimization
Maths and Stats for Web Analytics and Conversion Optimization
This expert guide will teach you how to leverage the knowledge of maths and statistics in order to accurately interpret data and take actions, which can quickly improve the bottom-line of your online business.
Master the Essentials of Email Marketing Analytics
This book focuses solely on the ‘analytics’ that power your email marketing optimization program and will help you dramatically reduce your cost per acquisition and increase marketing ROI by tracking the performance of the various KPIs and metrics used for email marketing.
Attribution Modelling in Google Analytics and Beyond
Attribution modelling is the process of determining the most effective marketing channels for investment. This book has been written to help you implement attribution modelling. It will teach you how to leverage the knowledge of attribution modelling in order to allocate marketing budget and understand buying behaviour.
Attribution Modelling in Google Ads and Facebook
This book has been written to help you implement attribution modelling in Google Ads (Google AdWords) and Facebook. It will teach you, how to leverage the knowledge of attribution modelling in order to understand the customer purchasing journey and determine the most effective marketing channels for investment.
Himanshu Sharma
Digital Marketing Consultant and Founder of Optimizesmart.com
Introduction to filter verification
In Google Analytics, a filter can permanently change the data that appears in a GA view.
Data once filtered (i.e. included, excluded or modified) can not be unfiltered.
So if you set up an incorrect filter, your historical data is skewed for good.
Therefore it is important that you test your filter before creating it.
The method of testing a filter before creating it is called ‘filter verification‘.
Google Analytics built-in verification tool
Google Analytics has got built-in verification tool for testing view filters which you can access while creating/editing a filter:
However this built-in verification tool has got following limitations:
#1 It can not be used to test IP based filters and other location based filters:
#2 It can not be used to test advanced filters:
#3 It can not be used again on an existing filter. If you try to test an existing filter by clicking on the ‘verify this filter’ link then you are likely to see following error message:
This filter would not have changed your data. Either the filter configuration is incorrect, or the set of sampled data is too small.
So if you want to test an existing filter again, via the GA built-in verification tool then first delete the filter and then create a new filter.
Creating a filter vs. Updating a filter
In GA, you create a filter by saving it once.
However when you save the same filter again, it updates the existing filter.
This filter update can take a long time (as much as 24 hours) to take effect.
So avoid testing your updated filter straightaway.
Configuring a filter
‘Setting up a filter’ is also known as ‘configuring a filter‘.
You can configure a filter by adding/changing various filter attributes like:
- Filter name
- Filter type (predefined or custom)
- Filter field
- Filter pattern
Following screenshot show the various filter attributes:
The order of filters
If you have created more than one filter in GA view then they are applied to your GA view data in the order in which you created them.
So existing filters are applied before new filters according to their current ranking position.
In the screenshot below:
The the filter named ‘exclude internal traffic-3’ has ranking of 1.
So this filter will be applied first to your data.
After this filter is processed then the second filter named ‘home’ will be applied to your data.
However you can change the filter order by clicking on the ‘Assign Filter Order’ button (see the screenshot above).
By changing the filter order, the filter named ‘home’ get the first rank and is applied first to your data:
Sometimes the order in which filters are applied to the data in your GA view can make it hard to test a filter.
So if your filter verification is not working then you may need to test the order of existing filters and/or remove other filters.
8 Steps process to testing a new filter in Google Analytics
Follow the steps below to test a new filter in GA:
Step-1:Create a test property in Google Analytics.
A test property is a duplicate of your live GA property.
Do not use live property to test your filters or to test anything.
This is because data once filtered can not be unfiltered in GA.
So if you accidentally applied a wrong filter, your GA data will get skewed for good.
Though GA filters are view based, i still recommend using the test view of your ‘test property’ as a best practice.
Step-2: Create a copy of the unfiltered view in your test property and name it ‘test view’:
Step-3: If you already have a test view, then remove any existing filter from it before you test your new filter.
Step-4: Make sure that your test view contains at least 7 days of historical data. This is because GA need at least 7 days of historical data before it can display the ‘filter verification preview table’.
Following is an example of filter verification preview table:
Through ‘filter verification preview table’ you can see, how your new filter will change the existing view data.
Step-5: Check through the reporting interface filter whether the data you want to filter (include, exclude or modify) actually exist in your test view.
Following is an example of ‘reporting interface filter’ (available in almost all GA reports):
If the data you want to filter do not already exist in your test view then you can not test your new filter.
If you still go ahead and test your new filter (by clicking on the ‘verify this filter’ link) then your filter won’t work because there is no existing data that match your filter criteria and you are likely to see following error message:
This filter would not have changed your data. Either the filter configuration is incorrect, or the set of sampled data is too small.
Step-6: Test your ‘filter pattern’ before you use it in your filter esp. if your ‘filter pattern’ contains Regular expressions (also known as ‘regex’).
Use Regex101 tool to create and test your regular expressions.
Use the ‘JavaScript’ flavour as Google Analytics accept POSIX JavaScript regular expressions.
Following is the interface of ‘Regex101’ tool:
Related Article: Google Analytics and Google Tag Manager Regex (Regular Expressions) Guide
Step-7: Once you have created and tested your regex using ‘Regex101’ tool then use the ‘reporting interface filter’ in your GA test view to test your regular expression one more time.
This is because there is no guarantee that the regex validated by ‘Regex101’ tool will almost always work correctly in GA:
Note: If the regex used in the ‘Filter pattern’ field is not correct and you clicked on the ‘verify this filter’ link then your filter won’t work because your filter criteria does not match the existing data and you are likely to see following error message:
This filter would not have changed your data. Either the filter configuration is incorrect, or the set of sampled data is too small.
Step-8: Enter the validated regex while creating a new filter in the ‘filter pattern’ field and then click on the ‘verify this filter’ link.
If you filter include/exclude/modify your data then you are likely to see ‘filter verification preview’ table.
If your filter does not include/exclude/modify your data then you are likely to see following error message:
This filter would not have changed your data. Either the filter configuration is incorrect, or the set of sampled data is too small.
What is the difference between Digital Analytics and Google Analytics?
99.99% of course creators themselves don’t know the difference between Digital analytics, Google Analytics (GA) and Google Tag Manager (GTM).
So they are teaching GA and GTM in the name of teaching Digital analytics.
They just copy each other. Monkey see, monkey do.
But Digital analytics is not about GA, GTM.
It is about analyzing and interpreting data, setting up goals, strategies and KPIs.
It’s about creating strategic roadmap for your business.
Digital Analytics is the core skill. Google Analytics is just a tool used to implement ‘Digital Analytics’.
You can also implement ‘Digital analytics’ via other tools like ‘adobe analytics’, ‘kissmetrics’ etc.
Using Google Analytics without the good understanding of ‘Digital analytics’ is like driving around in a car, in a big city without understanding the traffic rules and road signs.
You are either likely to end up somewhere other than your destination or you get involved in an accident.
You learn data analysis and interpretation from Digital analytics and not from Google Analytics.
The direction in which your analysis will move, will determine the direction in which your marketing campaigns and eventually your company will move to get the highest possible return on investment.
You get that direction from ‘Digital analytics’ and not from ‘Google Analytics’.
You learn to set up KPIs, strategies and measurement framework for your business from ‘Digital analytics’ and not from ‘Google Analytics’.
So if you are taking a course only on 'Digital Analytics’, you are learning to use one of the tools of ‘Digital analytics’. You are not learning the ‘Digital analytics’ itself.
Since any person can learn to use Google Analytics in couple of weeks, you do no get any competitive advantage in the marketplace just by knowing GA.
You need to know lot more than GA in order to work in digital analytics and marketing field.
So what I have done, if you are interested, is I have put together a completely free training that will teach you exactly how I have been able to leverage digital analytics to generate floods of news sales and customers and how you can literally copy what I have done to get similar results.
You can sign up for the free training here: https://learn.optimizesmart.
I truly hope you find it helpful.
My best selling books on Digital Analytics and Conversion Optimization
Maths and Stats for Web Analytics and Conversion Optimization
This expert guide will teach you how to leverage the knowledge of maths and statistics in order to accurately interpret data and take actions, which can quickly improve the bottom-line of your online business.
Master the Essentials of Email Marketing Analytics
This book focuses solely on the ‘analytics’ that power your email marketing optimization program and will help you dramatically reduce your cost per acquisition and increase marketing ROI by tracking the performance of the various KPIs and metrics used for email marketing.
Attribution Modelling in Google Analytics and Beyond
Attribution modelling is the process of determining the most effective marketing channels for investment. This book has been written to help you implement attribution modelling. It will teach you how to leverage the knowledge of attribution modelling in order to allocate marketing budget and understand buying behaviour.
Attribution Modelling in Google Ads and Facebook
This book has been written to help you implement attribution modelling in Google Ads (Google AdWords) and Facebook. It will teach you, how to leverage the knowledge of attribution modelling in order to understand the customer purchasing journey and determine the most effective marketing channels for investment.
Himanshu Sharma
Digital Marketing Consultant and Founder of Optimizesmart.com