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Google just announced four new features in Google Analytics. These features are in beta and are being rolled out to all GA accounts so hopefully you’ll have access to them very soon. Two of these features are intended for deep-dive analysis and offer an incredible amount of insight right at your fingertips! If you are interested in saving time and doing better analysis, keep reading. 🙂 The two new features are:

  • Secondary dimensions
  • Pivoting

To find out more, keep reading or watch our video:

Secondary Dimensions

Personally I’ve found this new feature to be extremely helpful. It has helped me focus more on analysis and less on digging through reports (yay!) and it definitely decreased the steps taken to get to a particular report. Secondary Dimensions allow users to view two different dimensions within the same GA report. This makes analyzing your data more efficient and saves you time. Instead of having to run different reports and compare the data, you’re able to run the report and see the data side by side. Let me show you an example:

One of our clients observed a sudden spike in their direct traffic. We needed to ascertain where the traffic was coming from. Since the client had attended a couple of recent trade-shows, our initial assumption was that this spike in direct traffic resulted from the buzz around the shows. Stop – do not settle on this conclusion so easily! We’ve been trained to use data to validate assumptions and conclusions.

In the “All Traffic Sources” report, I selected traffic sources by medium, and then I added a secondary dimension for “Country/Territory”, and voilà, the report was created and it showed us that out of 1972 direct visits, 1037 were from Pakistan.


Wait a second, we knew that the trade-shows where in the US and not in Pakistan, and the client’s target audience is US-based as well. It turns out that this particular client has an offshore software development office in Pakistan. which explained the recent spike in traffic as the developers were making updates to the site.

Even without the Secondary Dimension feature this same information is available, but you would have to leave the current report and go to a “direct segment” and then look at a geography report to find the information that is now available using the secondary dimensions feature (with one click). As stated earlier, deep dive analysis at your fingertips! 🙂


If you are an Excel geek, and I might qualify for one 🙂 , you know what pivoting is all about. But for the purpose of this post, pivoting in Google Analytics will allow you to see additional metrics in the same view.

For example, say you are looking at your top landing page report. With secondary dimensions, you can now view the visitor type (new versus returning) as well.


This above report is for a news website, “/” is the homepage, and “/Politics” is the politics page. We see that the bounce rate for the “/Politics” page is much higher for new visitors than for the Returning Visitors. Time for action! Equipped with the new findings, you can review the “/Politics” page content and/or layout and assess how to further engage the new visitors. Keep in mind that when you are doing this type of analysis, keep statistical significance in mind; don’t waste time on something that is not statistically significant such as a seldom visited page.

With pivoting, the deep dive analysis is about to go into over drive. So while I am in the same GA report, it occurred to me that the client makes frequent updates to their homepage and maybe some browser incompatibilities have been introduced along the way. With a couple of clicks, I can get the insight I am looking for.

In the Secondary Dimensions drop-down, I selected “Browser”, then I selected the “Pivot” view and I choose “Operating System”. Here you go, all the cool analytics data you want right here in one table. We are now seeing:

  • Home page (our landing page in this example)
  • Viewed by browser type (IE, Firefox, Chrome, and more)
  • Viewed by Operating System (Windows, Mac, and more)
  • By Entrances and the respective Bounce Rate
  • Wow, a lot of numbers to view, but the report is much more insightful and there is so much context!


What do I do next? Easy! Meet with the web design team, share the data, and hopefully help the team prioritize fixing browser incompatibility issues starting with Firefox on Mac, and then Safari on Windows. Obviously, if you are not happy with the 34.27% Bounce Rate of traffic on Internet Explorer, then you’d want to allocate time to improve it on this segment of traffic since Internet Explorer represents a significant percentage of the total.

So to summarize, the secondary dimensions and pivoting features in Google Analytics allow us to dig much deeper into the data, and all done on-the-fly. Give these features a try and let us know what you think.

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