Power Your UX Research with Google Analytics

google analytics user research

Combining user experience research with analytics brings in data driven approach to learn more about users, troubleshoot unanticipated problems and track goals. It doesn’t matter how well you have done your research for UX, you could always end up missing some use cases. It is important to optimize the design by getting feedback as soon as possible. With lean startups, gathering feedback rapidly and incorporating changes is critical.

Why Google Analytics (GA)?

Google Analytics is a great starting point to explore how people are using your website. It has significantly evolved since its launch and now staggering amount of information is available for generating insights. Here are some of the most important reasons why we recommend Google Analytics:

  • In terms of cost the basic version won’t cost you a dime.
  • Implementation is as easy as abc. All you need to do is place a JavaScript snippet in your website code.
  • There are plethora of options to slice and dice your data and create broad range of charts. This makes for great data visualisation.

A primer on GA tracking hierarchy

Before getting started with GA, let’s first understand the basic hierarchical structure. Given below are the three levels you’ll encounter in the admin panel.
google analytics tracking hierrachy

  • Account is your entry point to GA and it represents the highest level of your organisations.
  • Properties can represent different websites and mobile applications owned by your organisation. There can be multiple properties inside an account.
  • Views are the access point for the reports. You can set an additional level of filtering to your website data depending upon different conditions. For example you can choose to have one view for all the data and another view for traffic generated from PPC campaigns.

You can add users to your GA account and given them specific permission to restrict their access at different levels.

What to track?

Here we must understand that GA doesn’t play well when it comes to user context, purpose and driving factor. But, working with analytics means that we must have a clear-cut idea of what we can discover reasonably. Now, let’s get started.
Although bounce rate and average time on page are the very basic metrics to identify problem areas, we’ll look at seven other most important tracking features for UX analysis.

– In-Page Analytics

Under the Behaviour menu, you’ll find the In-Page Analytics report to begin with your research. It has been designed to communicate complex data to people who are not data analysts. You can infer the popularity of the links present on your page from this feature. Basically it shows the percentage of clicks each link gets on your page along with other metrics like pageviews, unique pageviews, average time and average page load time.

Another amazing thing about this report is an orange bar in the bottom showing percentage of people who click below the fold (fold depends on the size of browser). This should be quite important for long pages with valuable link below the fold. You would want to know whether visitors actually scroll through your page or not. In addition to this the “Browser Size” option let’s you see whether the feature that leads to conversion is visible to maximum number of users without scrolling. In case of teamwave’s landing page for private beta launch, you can see that the sign up form is visible to more than 95% of the visitors without scrolling.

teamwave in-page analytics

Essentially you will be able to answer following type of questions from the In-Page Analytics:

  • Whether or not your site visitors are able to see the content you want them to see
  • Does your web page layout need optimization?
  • Whether the call to action needs any tweaking or not

– Tracking user interaction

The default GA tracking code can report entry and exit path of website, type of device used and path taken by visitors while browsing your site. But, how to track a particular user interaction that doesn’t refresh your web page or take them to a new page? In this case we can do a very small alteration in the JavaScript code to track users’ action via something called as ‘Virtual Pageviews’.

For example, your web page makes JS/AJAX call that let’s user view web page via tabs without reloading the webpage. You can add following code in your JavaScript to tell GA to record this type of interaction as a virtual pageview:

ga(‘send’, { ‘hitType’: ‘pageview’, ‘page’: ‘/menu/tabs/product-specification/’, ‘title’: ‘Menu | Tabs – product-specification’ });

– Tracking behaviour flow

This reporting feature is important to find out the path taken by your site visitors while browsing through pages. You can access this section under the Behaviour menu. This report will help you in answering following type of questions:

  • What is it that people are doing and not doing on your site?
  • Which pages are getting missed out?
  • Are they taking any non-essential steps to arrive at a particular page?

What all steps do the visitors take before getting sidetracked and eventually exiting the website?
Given below is a screenshot of the behaviour flow.

Behaviour flow in google analytics

Last year the team Google put icing on the cake by adding support for creating ‘Content Groups’. You can create logical grouping of your site’s content to see whether the visitors are following the same path or not. This is most useful when the site has large number of pages.

– Setting goals and funnels

Goals are incredibly important to find out whether the digital properties are actually helping your business or not. You need to measure some key metrics like leads, account creations, demo sign-ups, business case downloads. It is possible to create maximum of 20 goals in the Admin section of your GA account. Key thing to understand here is that Goals must be based on the context. For example, the objective behind email subscription is different that the objective behind signing up for product trial.

Funnels are used to see the exact path taken by visitors to move through the goal completion process. You can define different steps that a user would take for each goal and later on analyze to find out where exactly people abandon your funnel. This would be helpful find out the exact page that needs optimisation.

You would be able to do the following by setting up goals and funnels:

  • Measure how well your website is achieving its business objectives
  • Locate the pitfalls in your ideal scenario of customer journey

– Creating advanced segments

Advanced segments are highly useful for gaining insights at the granular level. This feature helps you isolate audiences by implementing filters on the analytics views. For creating a new segment you can click on the “Add Segment” button present in the audience section. You can directly compare visitors based on various segments like demography, behaviour, date of first session, technology and traffic source.

For example, you can create advanced segment for female visitors who fall in the age group of 35-44 and land on the site from social media channels. It can be contrasted with another advanced segment by changing it to the male visitors to find out any significant change.

– Using user timings

User timings feature helps you measure how long it takes to load your website and also track time required to do certain things. You can access this under the “Site Speed” of “Behaviour” menu. This feature helps you answering following type of questions:

  • How long is it taking to complete the goals?
  • Where do the visitors get stuck most of the time?
  • What kind of interaction takes long time?

As GA time tracking doesn’t come by default, you would have to do few manual configurations. Basically, you can create timestamp at the very beginning of user’s starting point and create another at the end of goal (conversion). Finally by taking the difference of the timestamps you would be able to calculate the time taken to reach goal. Then you would need to pass the ga function “send” command, “timing” as hit type and four parameters:

  • Category – this is just the name of the logical group
  • Variable – this is the name of the event that would be tracked
  • Value – this is the time in milliseconds (calculated via custom code)
  • Label – this is an additional text to give more visibility

For example, in case of email subscription following would the ga function:

ga(‘send’, ‘timing’, ‘Sign up’, ‘Email subscription’, 40000, ‘New email list’);

– Finding friction with event tracking

Event tracking lets you track actions (downloading file, clicking on social media icon) irrespective of the change of url while browsing the website. You can access this report under the “Behaviour” menu.

By tracking events you would be able to figure out which events are most popular and which are events are not getting any attention from the users. Following parameters need to be passed to the ga function in order to track events:

  • Category – logical grouping of various events
  • Action – the action performed by the visitor
  • Label – the unique identifier of the event
  • Value – expected monetary value of the event

Here is an example of the custom ga code:

ga(‘send’, ‘event’, ‘ebooks’, ‘download’, ‘digital analytics white paper’, 50);


These are some of the key GA features to get you started with the process of UX research. They will give you lots of exciting data and it’s up to you to make the best out of them. It is also important for you to understand that you shouldn’t implement all of these just because you can. Analytics will help you explore identified problems, prove or disprove your hypothesis and give you deep understanding your website and visitors.

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