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How to Set Up and Use Content Groups in Google Analytics

Setting Up Content Grouping in Analytics

Finding specific details of large groups of pages can be a huge pain for the most experienced Google Analytics user. Measuring a variety of different video or blog pages can take a lot longer than it's worth to measure and as a result a lot of helpful actionable data is overlooked because it is too time consuming to get at.

Luckily, Google recently announced content groupings, a way to take content like blog posts or videos and group them together in a way that makes it easier to drill down into more detailed information about what kind of value are providing for your business.

According to Google:

"Content Grouping lets you group content into a logical structure that reflects how you think about your site or app, and then view and compare aggregated metrics by group name in addition to being able to drill down to the individual URL, page title, or screen name. For example, you can see the aggregated number of pageviews for all pages in a group like Men/Shirts, and then drill in to see each URL or title page."

Essentially, content grouping allows you to build out groups that can give you more helpful metrics about your site than a standard Google Analytics account is able to provide.

So how can you get this great asset to start working for your business? In order to access the content grouping feature in analytics, go to your Google Analytics account admin tab. There, you'll notice "Content Grouping" under the "View" menu:

Content Grouping in Analytics

There are three methods that a business can use to put content grouping to work: the "Tracking Code" method, the "Extraction" method and the "Rules" Method. In order to access these grouping options, click on "Content Grouping" and go to "New Content Grouping". There, you will be presented with each available option:

Types of Content Grouping

All of them are slightly different and actually offer some advantages and disadvantages over one another, so depending on what your business needs out of a content grouping one of these methods might be more helpful than another.

The Tracking Code Method

If you have the knowledge or have a developer on hand that can easily add some Google Analytics code to a page, then the tracking code method is a good way to go about setting up content groupings. This method is far and away the most technical route you can use to go about getting content groupings to start showing up on your Google Analytics account. With this tactic, the code will literally set the name of the content group when the page or screen renders. This method allows you to define 5 separate content groups, with each group tied to a content group that is numbered one through five.

If you're using Universal Analytics and hypothetically adding pages to content group 3, this is how the code would look:

ga('create', 'UA-XXXXXXXX-Y', 'example.com');
ga('set', 'contentGroup3', 'Group Name');
ga('send', 'pageview');

The biggest benefit to using this method is that you can adjust your content and content groups by simply adjusting the code. As mentioned above, the only real drawback to this tactic for content grouping is that it requires development knowledge or assistance to properly set up.

Extraction Method

The extraction method takes the name of your content groups from existing dimensions of data. The idea here is that you can use a regular expression parse of each dimension and extract the name of your group that way.

For example, the name of your content groups might be in the page title. If you then specified the group name as the page title dimension and then provided a regular expression, the value would be automatically extracted. Google Analytics will then use the value of the dimension as the group name.

The biggest advantage of this technique is that there is no coding involved and there is flexible collection of your data on analytics. The drawback is that regular expressions could feasibly need updating when new content is added to your website if it doesn't match your existing rules. You can find more on regular expressions here.

Rule Definition Method

The rules method has a lot in common with the extraction method. The major difference lies in the fact that you have to take the time to manually name each group you create, as the name is not automatically pulled from your dimension data or code like it is in the Tracking Code or Extraction methods. However, just like with the extraction method, you can create rules based on the different dimensions of data. The page title, page url, etc can all be pulled as long as the dimension value matches the rule that is being created.

The main benefit of this method is that it is by far the easiest way to build a content group. There is no coding involved at all and you don't need to know how to use regular expressions. The main drawback is that it takes time to manually name each group that you are creating.

Some Things to Note...

  • A page can only belong in one content group at a time. This means that you can't add a page to a number of different content groups all at once.
  • Unfortunately, content groups cannot be applied to historical data. This means that if you wanted to pull data about your blog pages from 2013 using this method, you would be left empty handed. The is sooner you can get this implemented, the sooner you can find out more interesting facts about your content.

Have you found content grouping to be helpful for your business? Do you have further questions about how to properly implement it? Let us know in the comments section below or by tweeting us @BFMweb.

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Comments on this post

  1. I’m always impressed by the BFM blog, especially the posts by Austin. I come here and look every once in a while for new updates by this writer–clean prose and relevant information for me and my job. Anyway, I don’t know if he’ll see this or not, but I just want BFM and other readers of this blog to know that Austin has a readership, and brings value to the site.

  2. You have brought up a very great points , thankyou for the post.

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