Sometimes the amount of data available in Google Analytics can be very overwhelming. Filtering lets you include or exclude specific data in your Google Analytics accounts which can be great for reporting. It narrows your focus to a particular set of information by applying filters to views (formerly known as profiles).
However, before you add a filter to an analytics view, always, always, always make sure there is one untouched view with no filters. Since filters are permanent changes to data, you want to always have one view that has no modifications.
Fortunately, Google Analytics offers a number of predefined filters which makes this process relatively easier for people uncomfortable writing any kind of code. I’ll say it again though – never, ever apply a filter to your only view. Since I’ve made that point pretty clear, let’s go over some use cases for filters.
Exclude office traffic
A commonly used filter is one that excludes your office IP address from a view. If you have an office where a lot of staff are accessing your site, it can skew your data by showing their traffic combined with your prospects. Exclude this office traffic with a filter that removes data from your office IP address. You could also exclude the IP address for your staff’s home computers too — or ask them to stay off the company website outside of the office!
View specific campaign data
Consider a filter to include only data on a specific campaign in your view. I had a case where a third-party agency wanted to see a client’s analytics data to see if the data in analytics matched the data they were seeing from the banner campaign being run on their end. The client did not want all their data viewable by this third party agency during this short term campaign so I added a new view with a filter for only this campaign data. Then I gave the agency access to this view only so they could see the results of their banner campaign without having knowledge of the client’s overall digital marketing strategy.
Specific geographic areas
Perhaps your business is international and you have staff assigned to each country with different goals and strategies for their region. In this case, you probably have an extraordinary amount of data that is time consuming to drill into for the people assigned to that particular region. You can create a filter to include only a specific country. Share out this new country specific view with the people assigned to that country so they are focused on only the areas they are assigned and are not distracted by large amounts of data.
Let’s talk about mobile…
In this day and age, everyone on the marketing team needs to be thinking about mobile marketing strategies. However, let’s say you have a development team though that is focused specifically on enhancing the mobile experience for visitors. Create a filter for them that includes only traffic from mobile devices.
Do you have staff assigned to work on the blog only? Create a filter that includes only traffic to the subdirectories, such as “/blog” (or whatever this URL is on your site). Your blog traffic is likely very different from your site as a whole. Blog visitors are people who are interested in learning something new or are in research mode and not necessarily in buying mode.
Clean up tagging
If multiple people are tagging your campaigns, you may have a source of “Email”, “email”, and “EMAIL” for the same exact campaign. With a lowercase filter for campaign attributes, you are telling Google to see these various spellings for email as the same thing. This is good practice for your source, medium, and name fields. The best practice though happens outside of Google Analytics. Keep a spreadsheet for your entire team to use for campaign parameters. This will save you some work later on if everyone is using the same naming conventions in campaign tagging.
Bots and spiders
Seeing bots and spiders in analytics data is a thorn in the side for most marketers. Fortunately, Google announced a filter for that this summer. This is seen in the Admin panel for the view and in “view settings.” The checkbox will “exclude all hits from known bots and spiders”. Naturally, there could be new bots and spiders that Google hasn’t identified yet, but it’s still a huge help for getting rid of the junk.
The bottom line
These suggestions can make life easier for staff by only providing the data they need, as well as offer options for confidentiality requirements by giving people only what they need to see. Keep in mind that filters affect data moving forward so if there’s a change you want to see in historical data, you can use advanced segments. These are temporary changes to the data and can go back in time to provide what you need without making permanent modifications.