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This instalment of the Analytics Alphabet involves everything to do with E: Entrances, Exit Pages, Exit Rate, Ecommerce and Exclusions.
Exits and entrances are often under-used metrics, but useful for evaluating how people enter your site, where they land, where they leave and where you might have to do some work on your site to prevent them from doing so.
On the “All Pages” report within the Behaviour > Site Content section there is a metric labelled as “Entrances.” This dimension provides insight into how many times a visitor has entered the site via a specific page URL.
This metric is extremely important when reviewing bounce rate as the volume of entrances to a page will have significant bearing on which pages with poor bounce rate need to be tackled first.
It is also useful to filter this data further to include the traffic source (select a secondary dimension) to understand which source is driving the most entrances to a page, as well contributing to a high bounce rate.
Remember to assess bounce rate in accordance with the business objectives of the site - see duration (avg. visit) for ways to diagnose the significance of the result.
Entrance pages for an organic traffic source could also be indicative of which keywords have been searched for. This can help breakdown the hidden data for (not provided) results as the content on the page can be indicative of the search terms used (e.g. a page about cars will rank well for car phrases, whilst one on bikes should rank well for bike phrases). This approach will not work on broader content pages like the homepage as they may rank for too many diverse phrases.
Exit page results can be found in Behaviour > Site Content. Exit pages are a list of URLs from which a user has left a site.
Exits is the number of times visitors have left your site from a specified page/ group of pages, while % Exits or Exit Rate is the percentage of site exits that occurred from a specified page/ group of pages.
For pages that are usually landing pages (so entrance pages to the site), bounce rate is an important indicator because it shows you the occasions on which that page was the only one visited. For all other pages, exit rate is more useful as they were never the only pages visited in a session but if they were the last pages visited, that may pose some questions.
If you have a high exit rate, it’s important to analyse the type of page.
If it is the completion of a goal or a page where you wouldn’t expect a quick decision (for example, a product page where visitors see your offer, but might exit to compare other offers), then you would expect a high % of exits.
But if it’s a middle page or critical within the path to conversion (for example the basket page), a high exit % might be a cause for concern.
Are there any errors, anything deterring the visitor from staying? Is it difficult to find the next logical step in the path to conversion? Are there links that cause ‘leakage’ to external sites and therefore your visitor is lost? These should be questions you ask yourself and investigate further.
Aggregated exit rates can often be a misleading metric and therefore we only recommend looking at it at a detailed level or in conjunction with site surveys and qualitative analysis of the page.
Every ecommerce website should have ecommerce tracking setup in order to find out where customers are coming from, and how profitable they are. Setting up ecommerce tracking requires a savvy web developer as it does require additional code work to pull in the additional revenue, quantity and product detail parameters.
Full details for implementing conversion tracking can be found here:
Not all elements are compulsory; however some are and must be included in the code (look for the ‘required’ label). This code needs to be implemented on the confirmation page.
Many of the values in ' ' need to be replaced with the items and values of the confirmed basket. For example – all underlined needs to be replaced dynamically and reflect what the customer has purchased.
'XXXXXXX', // transaction ID - required
'11.99', // total - required (insert total basket value in numeric values)
'1.29', // tax
'5', // shipping
// add item might be called for every item in the shopping cart (if a customer buys more than one item, the developer needs to add this code for each item)
'1234', // transaction ID - required (should be the same as above)
'DD44', // SKU/code - required
'T-Shirt', // product name
'Green Medium', // category or variation
'11.99', // unit price - required
'1' // quantity - required
Make sure the analytics profile is set to “Yes, an Ecommerce site” in the Profile settings section as well before proceeding any further. Look in Admin – View Settings – Ecommerce Settings for this feature.
Once implemented correctly the output of sales data can be found in the Conversions section of analytics. This section will provide insight into the products bought, number of sales per date and transaction ID details. This view is extremely useful for optimisation to ROI. All this data can be segmented by traffic source.
The ecommerce results can also be found in the Acquisition section, as a tabbed data set. This is really useful for quick analysis of how traffic sources are performing with regards to revenue, avg. value and conversion rate.
When interpreting data it is important to decide whether certain users, metrics or dimensions should be excluded to ensure insight is as useful as possible.
From a user perspective it is always worthwhile excluding IP addresses of internal company users and related parties (like agencies) to prevent their usage from skewing results and decision making. This can be done in the Admin section of the analytics profile.
From a dimension or metric perspective there is an advanced filter option on every data view which can be customised to allow data sets to include or exclude specific criteria. This is found by clicking on “advanced” by the search box.
Understanding what proportion of organic traffic is brand vs. non brand is a common exclusion task.
Websites may require additional URL parameters to track visits and referring sources (e.g. sessionid or affiliateid) or to change and determine page content (e.g. sort=price_ascending).
By default, Google Analytics will record all of these URLs uniquely and report against them in the Content section. This may potentially create reams of content page results which are only different due to one number – not very helpful when it’s not the URL but the content page which is being scrutinised for performance.
If a site suffers from lots of the same URL being displayed in the page content results but only an ID or filter category is creating the duplication, consider removing any non-important query string parameters. To do this go to Admin > View > View Settings and enter in any parameters which need to be excluded in the “Exclude URL Query Parameters” box.
Up next time, Filters and Goals.
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Ensure nothing holds your e-Commerce site back from performing at its best.