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We’re always looking at the data to see how our content is performing. The tools we’ve built show us trends and changes in usage - but what happens when we want to dig a bit deeper?
This was the challenge set by one of our colleagues who noticed a large spike in visits to a Universal Credit policy page. They wondered if all these users really did want to know about the policy - or whether they were instead looking for more practical content about how they would be affected.
Using analytics: the questions we asked
So, we turned to the analytics. The approach we took ran through four basic stages:
Identify the problem and develop a hypothesis (“lots of users are getting policy info when they don’t want this”)
Test hypothesis: where is the traffic coming from?
Develop solution: how do we direct traffic to the correct pages?
Through taking this approach, we found that lots of users were indeed using generic keywords to reach the policy page - and that when we changed the page to make it link more prominently to ‘practical’ content, over a third of visitors to the policy page followed this link. Further tweaks to wording helped to optimise the ‘practical’ content on Universal Credit as the first destination listed on Google for the subject, and get more people to the ‘right’ destination.
This is an approach that can be applied to pretty much any piece of content you’d like to understand a little better.
Download our practical guide
So we’ve written a practical guide to using Google Analytics, based on this case study, to demonstrate how to use Google Analytics to understand how people are reaching particular pages, and to test the effects of changes.
It’s a bit long for a blogpost, so we’ve turned it into a PDF.