We love digital - Call
03332 207 677 and say hello - Mon - Fri, 9am - 5pm
Call 03332 207 677
Unlike 08 numbers, 03 numbers cost the same to call as geographic landline numbers (starting 01 and 02), even from a mobile phone. They are also normally included in your inclusive call minutes. Please note we may record some calls.
If you use Google Analytics but have never used the pivot chart, you’re missing out! There are some wonderful insights and cross-analysis opportunities that only a pivot can give you. Plus they’re actually not that hard to get your head round!
They are great for understanding the detail behind the data better, comparing performance, identifying trends and issues and making good decisions quickly.
To get started with Pivot Charts, navigate to a standard report then click the far right graph option:
They look a little useless when you first click them as they show the same dimension on both axis, however, it’s easy enough to make it useful – just change the ‘Pivot by’ option to another dimension. Here’s an example of a nice simple one:
Which Browser is used with which Operating Systems?
Note: it’s beneficial to click the line between the menu and the report in order to shrink it out of the way and give you more space to see the juicy reports in.
Let’s break it down:
There are additional things you can apply here but we’ll come to those once we’ve covered the basics.
As you can see, it shows the browser on the left hand side, just like normal. It then breaks down the visits for each browser by which operating system the user was on. We can see that Chrome is used on a range of operating systems whereas Internet Explorer is mainly used on Windows. This particular report could be used to help you identify platform combinations to test your website on.
Let’s look at another example. Say you have a website that offers its services in different cities and has a page for each location. In this example you can cross reference these pages against user locations, like so:
Are my location/store pages used by people with IPs in the same City?
Here we can see that the pages for a specific region do see a rise in visits from people in that location. However, it also highlights that although Birmingham is one of the cities sending the most traffic, the Birmingham page does not feature in the top viewed pages – this suggests that it is hard to find, doesn’t suit the users or perhaps the pages are split out into smaller areas around Birmingham which means the views are distributed across more pages.
You can also tell from this that people view pages about locations that they are not in. This is most likely due to the users’ IP being based in a different city to them but also the fact that people will look for services outside of their physical location in a number of situations. All reporting platforms will leave finding the reason for behaviour up to you, but at least this helps build up a picture so you can make the data come to life and depict user situations and identify how you can help improve the site for them.
So now that we’ve covered two nice simple examples, let’s take it up a level and introduce more data – if more data isn’t for you, skip to the bottom for some more examples to use. To make the most of this report you can add the following functionality:
Let’s take a look at each of these:
Let’s start by adding another metric which will allow us to see two statistics for each column and row of the report. This is beneficial because one metric means very little on its own. Introducing a second metric gives you a way of understanding the activity better, putting the first metric into context and spotting trends or anomalies.
In this next example the company has websites for a number of different countries, they each have their own Google Analytics account but we also use a master account to review the data for all the sites in one place. So to analyse whether or not the global strategy is working, we can use a report such as this one:
Worldwide cross domain strategy review
Although I’ve blurred the actual numbers you can see the concept behind this report; you hope for high numbers for the correct location and good bounce rates when users land on the right domain for their country but always keep a look out for surprises! A good variation on this report is the conversion rate metric too. Just click Goals or Ecommerce at the top and select conversion rate as the second metric.
Whenever I talk about analytics I can’t stress enough the importance of using more than one metric. Comparing information really gives it context and makes it much more useful. Would you compare house prices without putting the data alongside how many bedrooms each has? So why look at visits alone and assume it tells you enough?
The next way to add additional information is to apply a Secondary Dimension. Hopefully you’re used to using these in standard reports, but if you’re not, they’re great for breaking the dimension down. A great example is to look at a keyword report and apply a Secondary Dimension for landing page:
An example of a secondary dimension
And to use it in a Pivot Chart would do a similar thing:
Which keyword and landing page combo works best in each city?
Keyword and Landing page ecommerce data by City. This helps us to see which keywords and landing pages work in different locations.
Another great Secondary Dimension is ‘Visitor Type’ which breaks out new and returning visitors, like so:
Are returning visits from certain keywords better than their new visit counterparts and where are the hidden keyword gems for successful new visits for each city?
The next step to make the two above examples even better is to introduce Advanced Segments…
As I said before, there are ways to make the data even more granular, which can be done very well with advanced segments. They also present the data very clearly.
Combining the above two examples, we can review keyword and landing page ecommerce results per country, while comparing new and returning traffic for each, like so:
Differences in new and returning traffic for source / mediums in different countries
The next example uses three advanced segments to show mobile, desktop and tablet traffic broken down by source / medium and landing page, to help you plan a mobile marketing and website strategies:
Mobile strategy planning
Now here’s an example of a similar report but with a secondary dimension for landing page and breaking the data down by City for location strategy planning:
Local / National mobile strategy planning
While we’re on the topic of mobile analysis, if your website uses a mobile subdomain, this report is great for finding out whether or not mobile users on each device are actually happy using your mobile subdomain or whether they prefer to use the desktop version of the site:
Does my mobile subdomain work well on all devices?
Once you’ve created your first pivot table you will realise that they are hard to manage within the interface itself. I definitely recommend using the export csv function in order to be able to manipulate the data to your heart’s content!
For even more information about Pivot Charts in GA, I found this super duper guide by Himanshu Sharma when I was halfway through the above post, so there’s extra tidbits of information on there if this hasn’t quenched your thirst for awesome reports enough yet.
There are so many ways to combine data and different pivots suit different websites, I can’t possibly come up with every combination so it would be great to hear the ones that work well for you. Please leave your examples in the comments for everyone to enjoy.
We continue to go from strength to strength here at Koozai, and we are very proud to announce that our London branch has expanded into even bigger and better offices.
Google Tag Manager (GTM) is a powerful tool and when properly understood and implemented, can be an SEO’s best friend.
However, before you can actually begin a migration to GTM, you need to take some key steps to ensure everything goes to plan.