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I’m a big fan of using Google Analytics data in novel ways to help you to understand what is happening on your website. One of these ways is to look at convertibility of each page. Its the equivalent of comparing the percentage of users who converted with the percentage of users who were not interested across every page of your website independently.
This can identify some fascinating discoveries such as identifying pages that have a high frequency of visitors but a lower than average convertibility (these are your leaky buckets) or pages with high levels of conversion compared to other pages – we can drill down and ask, “why these pages / products?”
I like to plot results on a scatter plot as it makes it so easy to see outliers.
The example below is a scatter plot that I created by comparing convertibility score to page views.
Other useful reports of a similar nature include abandonment frequency of pages and even individual events, revenue attribution by pages and events and one of my personal favourites is correction frequency. Correction frequency shows if users are repeating the same action several times, which can indicate that errors on the website or usability issues are impacting the user from completing what they are attempting to do.
For example, if you see certain search queries or form fills with a high correction frequency it could mean that the search is returning the wrong items or that the form isn’t working correctly.
I have an advanced report that I have created for this kind of deep dive into ecommerce user behaviour which I call a Detailed Interaction Report.