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Google Analytics Views and Filters

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In my previous post about creating a Google Analytics account, we discussed the Google Analytics account structure and the concept of properties inside the main account. Just to jog your memory, the best way to structure your Google Analytics account is to group all your digital assets together. ASPE, a family of six different training companies, owns six different websites. Therefore, each of our sites is a different property inside our one main ASPE Google Analytics account.

Let’s take this further and discuss views and filters. You can create different views inside of Google Analytics for each property. There are three standard recommended views for each property:

  1. Unfiltered (automatic) View
  2. Master View
  3. Test View

The Unfiltered View is automatically generated when you create a property inside of your account. This view will be your backup data. You don’t ever want to apply any settings or configurations to this view. The Master View is where you can incorporate all your settings needed to gain a realistic and useful understanding of your website activity. For instance, you might filter all your internal website traffic from this view so that the traffic generated from inside your organization doesn’t affect your choices based on the data you see. Finally, you should always, I repeat, YOU SHOULD ALWAYS have a Test View. Any time you need to make changes to your Analytics configuration, you should test those changes first to see how they will impact your data. That’s what the test view is for. Once you understand that impact, you can then apply those changes to the appropriate view.

Two very important things to remember about views are that:

  1. Once you delete a view it’s gone forever
  2. When you create a new view you’ll only have data from the date you created the view

Let’s look at an example of how ASPE might set up an account structure with multiple views:

We have our standard unfiltered, master, and test views, but we also have two additional views based on our training advisors territories. That way we can look at website traffic and behaviors specific to each of our training advisors’ regions.

The next layer of our account structure is filters inside of views. Filters provide a flexible way of modifying data within each view. You can set up a filter to exclude data, include data, or even change how data looks inside your reports.

During data processing filters are applied to the raw data that is collected from your site. It is this transformed data that you see in your reports. For instance, earlier I suggested adding a filter for excluding internal traffic, traffic from inside your organization from your view. That way, you’re only monitoring the activity and behaviors of your customers, not your employees. How is this done? With a filter that excludes all data from your business’s IP address.

Filters can also be used to clean up data. Have you ever typed in a URL with capital letters? For instance, ExampleWebsite.com? More than likely, you’re going to see the same website if you type in ExampleWebsite.com or examplewebsite.com. However, Google Analytics is case sensitive so the same page can show up in your reports multiple times. But if you use a lowercase filter, you can force all URLS to a single case.

Setting up Filters

The first thing you need to do when setting up a filter is identify what type of data you want to change. You do this by selecting a filter field. Some common filter fields include:

  • IP Address
  • Device Type
  • Geographic Location

Next, you’ll need to specify a condition, or set of rules for your filter. A common condition would be “matches a pattern” or “doesn’t match a pattern.” For instance you could use a country filter and your condition would be “matches US.” Then you need to choose the action Analytics will take if that condition is true. If your business is a US only business, you could exclude traffic that “doesn’t match US.”

When initially setting up your filters, you may want to look at some of the predefined filters. These are templates inside Google Analytics for some of the most commonly used filters. Once you’re comfortable with some of the predefined filters, you can move on to creating your own custom filters. Common filter types include:

  • include filters
  • exclude filters
  • uppercase filters

There are also advanced filters that allow you to remove, replace and combine filter fields in more complex ways. Once you’ve created a filter, it’s added to your filter library so you can reuse the ones you’ve already created and apply them to any view.

I’d like to add one final note, or best practice if you will, on using filters. Remember the test view we discussed earlier? It’s always best to try out a new filter in the test view before applying it to your master or custom view. That’s what it’s there for!

Good luck setting up your views and filters. Confused or have a method of your own? Let us know in the comments field! But stay tuned, next up we’re going to discuss setting up Goals and eCommerce inside of Google Analytics.

 

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