Out of the box, third party analytics tools give you lots of data about your audience (see my tips for choosing the right analytics tool), but you will quickly reach a point where you don’t have all the data you need, specific to your business. I’ve worked with various analytics providers (e.g. Amplitude), and I have learnt the hard way what can easily go wrong with custom implementations, especially when it comes to making sense of the data. Page/screen tracking is one area I have run into issues in the past.

The purpose of this post is to give some tips for customising page tracking on your website or app to make the reports as useful as possible and to avoid having to re implement tracking.

I focus specifically on Google Analytics, but the principles can be applied to other tools, so please don’t be put off by this if you’re using one of Google’s competitors – its still relevant.

Page Name Tracking

The page report is really important to any implementation. It gives useful insights about each page on your site e.g. bounce rate, exit rate, behaviour flow etc… It is worth highlighting that this is not a custom variable. Out off the box, GA tracks the URL of your page, however depending on your site, it might be valuable to customise these values by overwriting them.

If your site is not content heavy and your URL structure is clean, then it might not be necessary to customise your page values, but its definitely worth including this in your planning and getting it right first time. Study your URL structure and ask yourself the following two questions:

Q1. Do you need to track every single dynamic URL on your site?

If a user logs into your site and they are assigned their own account page with a unique identifier in the url, is it important to track this in your page report? Wouldn’t it be more useful when looking at different page analytics reports to group these up, so you have an aggregated view of all account pages? As an example:

Example 1- Booking.com*

booking.com user account page

Every user that signs up to booking.com has their own account pages. This front page is a dashboard, where you get an overview of your future trips as well as some other headline information. The URL structure for this page ishttps://secure.booking.com/mydashboard/[username]

So my own personal dashboard URL is https://secure.booking.com/mydashboard/reckles

And the value in your GA page report would automatically be /mydashboard/reckles

It would be far more useful to overwrite this URL in your page report to simply be /mydashboard. This way you will have an aggregated view of this particular page, which will be cleaner, a lot more useful and give you the ability to be able to analyse how users navigate the site. I dare say booking.com have millions of registered users, so tracking every single unique dashboard in the page report would not be the most effective use of this report.

At this point you might be thinking, what if I wanted to see traffic volumes to a specific account holders dashboard?? Well, you definitely should track this and you can have the best of both… To do this, pass the unique identifier — in this example ‘reckles’ — to a custom dimension that fires on the page load, and set the scope to hit type. (If you don’t know what a custom dimension is, I will cover this in a subsequent post, or you can look through Google’s documentation on custom dimensions)

Depending on whether you are using Google Analytics Premium or not, I would also recommend sending the full URL to an additional custom dimension, so you have all bases covered. This can be useful for trouble shooting tracking later on if you suddenly find a dodgy value being passed to your page report. So for this specific page, in the end you will have the following values:

pageName = ‘/mydashboard’
customDimension[index] = ‘reckles’// this is the username
customDimension[index] = ‘https://secure.booking.com/mydashboard/reckles’ // this is the full url

Example 2 — ebay

Lets look at another example — a site with alot of user generated content. Below is a product page for ebay, which I’m sure we are all familiar with.

ebay football product page

The URL for this particular page is http://www.ebay.co.uk/itm/Nike-Team-Training-Football-/191843119904.

It goes without saying that ebay has millions of items listed on the site, and therefore millions of pages like this one.

By default the value passed to the page report in GA would be /itm/Nike-Team-Training-Football-/191843119904. I personally wouldn’t pass this complete URL as the page value. Instead I would just pass the beginning of the URL /itm. Every single item for sale on ebay has this URL structure, so by just using /itm you would get an aggregated view of all traffic to the product pages in your page report.

Like the booking.com example above, I would at the same time pass the unique identifier (product id) to a custom dimension. So in this example your tracking would look like this:

pageName = ‘/itm’
customDimension[index] = ‘191843119904’ // this is the product id
customDimension[index] = ‘http://www.ebay.co.uk/itm/Nike-Team-Training-Football-/191843119904′ // this is the full url

Why is this useful?

When it comes to analysing how users flow through your site you would be limited if you pass the full URL to the page name. In Google Analytics, you have two very useful reports which utilise your page name data.

The first useful report that uses (and only uses) your page name values, is the Navigation Summary

google analytics navigation summary screenshot

This tab enables you to select any page value in your report and see what the previous page path and next page path was.

google analytics navigation summary screenshot

Google Analytics Behavior Flow

The second useful report, is the behaviour flow report. This report visualises how users navigate your site:

google analytics page analytics

In both these reports, on a site like ebay that has millions of product pages, is it useful to see that there were 10 page views that navigated from page /itm/Nike-Team-Training-Football-/191843119904 to page /itm/Byron-Corner-Group-Sofa-Right-and-Left-Brown-and-Black-/281393227305 to page /itm/Red-Letter-Days-25-off-Hotel-Escape-for-Two-at-The-Crowne-Plaza-/121377820131? The reality is that with millions of pages, users are going to take all sorts of journeys, so an aggregated report with this setup is only going to show a handful of paths. Therefore I would argue that it would be more useful to see that 50,000,000 page views navigated from /itm to /itm to /itm instead.

I should point out that you can also use content grouping in the behaviour flow, which would achieve similar results. I will discuss this now.

Q2. Is your URL structure logical enough for you to group the content later on?

Your URLS might be jam packed with useful information and be beautifully logical/hierarchal, but even these lovely clean URLs could be limiting from a tracking perspective. For example, lets say you are a media website with hundreds or thousands of professionally written articles. its probably fair to assume you would want to keep the default values, and track the whole URL in your page report — its not user generated content. However, you might still want to group your content to get an aggregated view. This is where content grouping can help you out.

Content Grouping allows you to use your URL structure to create content categories in GA, and then use these content groups in your behaviour flow and page report. As a marketer you have complete control of this with no dev resource required. To better explain what I mean and show you how to use content grouping I am going to take the Guardian website as an example.

Example 3 — The Guardian

Below is a typical article on the Guardian website.

guardian newspaper article screenshot

The URL for this page is http://www.theguardian.com/travel/2016/apr/17/on-the-trail-of-maigrets-paris-city-guide.

As you can see, the URL is clean and has a clear structure: /[topic]/[year]/[month]/[day]/[title]

All of these values can be extracted and put into different content groups. For example, lets say you want to extract the topic from the URL.

  1. In your admin menu select Content Grouping / + New Content Grouping
  2. Give your content group a name. In this example I’m going to call it Article Topic
  3. Select Create a rule set and add the rule. Here I will use Page | contains | /travel/
google analytics content grouping settings

You can add as many values to this content group as you need. Once GA starts processing the data (usually the following day), you will be able to access these values in your page report and behaviour flow, by selecting the group name. e.g. Article Topic.

By using content grouping you can begin to see an aggregated view of how traffic navigates between article topics. For example you might see (surprisingly) that a large percentage of traffic is navigating between travel and sports articles. Or that traffic to lifestyle articles only navigate to other lifestyle articles before leaving the website.


Every tool has a slightly different way of tracking web pages, but the principles are all the same.

There is many ways you can structure your page names and various ways of implementing them, but the key is planning. It is very easy to implement the 3rd party tool and just accept the default values being passed to your page reports. But there is nothing worst than implementing the tool, only to find 2 months down the line that the reports don’t do what you want them to do and fail to fulfil the needs of the entire business.

Take your time and look at all of the reports that utilise the page reports. Talk to the teams that will be using the data and get their feedback on your tracking plan. The aim is to get it right first time.

*I have no affiliation with Booking.com, ebay or The Guardian. The examples I have used above are simply demonstrating how I would approach the page tracking on these particular sites, with the information I have. I have no visibility of business requirements or goals.

Growth Lead at Dailymotion, Richard has a passion for improving user experience and ROI through data and experimentation.

1,433 thoughts on “How To Track Your Web Pages

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