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Published on Monday, April 11, 2016
To help us analyse and measure the performance of our content we use Google Analytics, which records the pages users visit.
This year we’ve made improvements to carlisle.gov.uk that allows us to comprehensively record information about users’ interactions across the site.
A quick way to see how your pages are doing is by mapping them against some key metrics and analysing how those metrics relate to each other.
Here’s what each metric means:
This represents the number of visits in which that page was viewed.
So, if a user visits a page 5 times during their browsing session, it will show up as 1 unique pageview in Google Analytics.
This is a count of every time that page was viewed.
For example, if someone visits page X, then goes to page Y and then page X again, then page X will be shown having 2 pageviews (and 1 unique pageview).
This is the number of times that page was the first page on the site viewed by users.
A simple calculation showing entrances to the page as a percentage of the pageviews.
The percentage of ‘single-page sessions’ - that is, users who viewed only this page and then left carlisle.gov.uk.
How long users view the page for on average (NB treat with caution - see below).
The percentage of exits that were made from the page (calculated as number of exits/number of pageviews).
By default, Google Analytics will order reports by the first metrics column. We can see in the above report that the homepage was the highest visited page followed by the Planning Pages.
The Unique Pageviews column will show you your most visited pages. Clicking on the down arrow at the top of the column will show the reverse order, i.e. the least visited pages.
Dividing the Pageviews metric by Unique Pageviews will show on average how many times a page was viewed during users’ sessions.
A high ratio (above 1.4) indicates a propensity for users to have to come back to that page within their session. This should be a primer for you to investigate the navigation from that page further to identify any issues.
(You’ll need to work this out yourself by exporting the data to a spreadsheet. Unfortunately Google doesn’t do this for you).
If the Entrances/Pageviews percentage metric is low on pages getting a reasonable amount of traffic then it suggests that users have a need for the page but most are having to navigate their way to get to it so better optimisation may be required.
Bounce rates should only be viewed against the Entrances metric and not with Pageviews.
A high bounce rate on navigation pages reveals a problem as it indicates users are not engaging with the page; changes should be made and measured again.
However, a high bounce rate on content pages is not necessarily a bad thing as users could have obtained the information they came for and did not need to go any further beyond the page.
The ‘average time on page’ metric provides a guide to how engaged users are with your page.
However, treat with caution. This is because it excludes data from sessions in which the page was the last one visited on carlisle.gov.uk (eg, it doesn’t include single page sessions).
So for pages with high bounce rates (such as news pages), the dwell time displayed by Google may be very wide of the mark. As a general rule, the lower the % Exits rate the more representative the average time on the page will be.
All of this is going to help us make decisions based on more reliable data. It'll give us more context about a user’s journey, which we will use to improve content and better meet user needs.
Tags: Ben Renucci