Advanced Analysis in Google Analytics

Advanced Analysis – Powerful Reports

One of the benefits of using Google Analytics 360 is to access a new set of reports; “Advanced Analysis”. The reports allow you to explore, visualize and act on data from Google Analytics 360 in new ways. The reports are based on three different visualizations:

The reports in Advanced Analysis, unlike Data Studio, show only data from Google Analytics. In return, the reports are highly interactive. In this blog post we look at the “Segment Overlap” visualization, which is a Venn diagram that shows the overlap between different segments of users.

In the example, we have used data from the Google Merchandise Store and chosen to identify the extent to which visitors interact with different groups of products on the site. The product groups are Apparel, Bags and Drinkware.

The reports are  built by the toolbox on the left side of the page, where Segments, Dimensions and Metrics are selected (imported) from Google Analytics. Keep in mind that segments imported from Google Analytics must be created as “User scope” (ie a selection of users – not sessions) to allow the chart to show overlap.

The image above shows how three segments have been selected. The table below the Venn diagram shows the number of users in each segment. By adding the Revenue metric, we can see which revenue that is created by different user overlaps:

By adding one or more dimensions such as “Breakdown”, you can segment users even further. In this case we segment on the “Device Category” dimension shown on the Y axis and the combination / overlap of the segments on the X axis:


Use the data to improve customer experience

Now to the best part; For each segment, you can right-click and start interacting on that particular group of users. In the picture below, there are users who have seen both Apparel and Drinkware products on their phone. You can now choose to create a new segment of this particular user segment, build a target audience, or review the behaviour of these users in detail through User Explorer. This allows you to control keyword ads in Google Ads, programmatic media through Display & Video 360, and control A / B tests and content through Optimize 360 based on the discoveries you make in your data!

How does it work with Campaign Timeout in Google Analytics nowadays?

The other day we discussed Campaign Timeout in Google Analytics. In order to find out the correct answer we turned to Google and the first result led to a site where they stated that the campaign is prolonged each time a user comes to your site (if the traffic source is not changed. If you want to refresh your memory regarding traffic sources or attribution modelling in Google Analytics). Hmmm, that was not what I expected and remembered. I had to check it out by doing a test. Oh, the joy when I realized my memory did not fool me.

The short version:

If a user returns to your site by typing in the URL (hence direct traffic), the campaign is not prolonged (in the way that it did with ga.js).

The slightly longer version:

When Universal Analytics was rolled out in 2014, there was a change in how campaign timeout worked. This deals with for how long a traffic source is attributed even if the visitor comes as direct traffic. In the former, Classic Analytics (ga.js), the timeout was extended each time a visitor came to the site. This meant that a campaign or source of traffic could theoretically live forever.

Universal Analytics, hence now

Session timeout: 30 min

Campaign timeout: 6 months (default setting in Google Analytics)

1 sep 2018: Visit through campaign-tagged traffic source. Campaign timeout should now be 6 months ahead, March 1, 2019. Reported in Google Analytics as campaign traffic.

1 Nov 2018: Direct visit to Reported in Google Analytics as campaign traffic.

April 1, 2019: Direct visit to Reported in Google Analytics as direct traffic.


Classic Analytics, before 2014

Example from how it used to be, in the not to smart way:

Session timeout: 30 min

Campaign timeout: 6 months (default setting in Google Analytics)

1 Sep 2018: Visit to through a campaign-tagged traffic source. Reported in Google Analytics as campaign traffic. Campaign timeout should now be 6 months ahead, March 1, 2019.

1 Nov 2018: Direct visit to Reported in Google Analytics as campaign traffic. Campaign timeout moves forward 6 months ahead, May 1, 2019.

April 1, 2019: Direct visit to Reported in Google Analytics as campaign traffic. Campaign timeout moves forward 6 months ahead, Oct. 1, 2019.

And so, this could go on forever and ever (or as long as the visitor does not change traffic source, but continues to enter the site directly.)

This was a bit of a mess. So since 2014, it is more as you would expect.

So, if you read a blog post saying that the traffic source extends all the time (if the traffic source is not changed), you can dismiss it. So, that was Classic Analytics. Not now.

Then you can always discuss if six months is the ultimate length for how long you should give cred to a campaign, but we’ll take that in another blog post! If you want help with your campaign tagging you can use the GA Campaign URL addon. You can always contact Outfox if you would need assistance in your campaign management/analysis!

Add quantitative data to quantitative and get sort of qualitative data

It is not difficult to see which pages that are the most visited on a website. Just go to Google Analytics and click on the navigation to the left and click Content and then All Pages.

But. Often there are certain target groups for certain pages or categories of pages. How do we know if we reach that specific target group? In Google Analytics we can see what users have done, but we know little of what their intention was with the visit, and specifically, we do not know whether they have succeeded or not.

Happy days are here. There is the Outfox Survey, a web survey where the answers can be matched to the behaviour on site. We only ask three questions: In which role do you visit the website, what is your intention with the visit and did you succeed in solving your query.

Prioritized targets groups to study up close

By looking at a segment of your website’s prioritized users and see what their intentions are, and I like in particular to know more about those who have not found what they were looking for, I try to understand why they have not succeeded. Google Analytics is good at what, but not why.

When I have created a segment of those users I can look at the different reports in Google Analytics.

  • Which pages do they visit? Is there information missing on those pages or just not the information the user would expect?
  • What are they searching for in the internal site search? Are there queries that do not give the results that you would expect?
  • Which traffic sources do they come from? Which landing pages are common? Is there anything in the link between advertising and landing page that could be better?
  • Is there any device or browser that is more represented? This could help us in prioritizing when adapting pages and/or functions to mobile.
  • Which are the common exit pages? Are they pages that you would expect your visitors to leave your site from, or could they be pages where the visitor just gives up? What can we do to improve?

Well, the list could be even longer. So, if you have not yet made a survey (and yes, many people actually answer pop up surveys. We have about 25% answering rate on our surveys), contact us and we’ll make it happen.