This free tool provides a new way to look at your site analytics – a visualisation showing the most popular areas of the site as concentric circles, sized according to how much traffic each path gets. Clicking on a circle brings up information about the audience which visited that area: how much they impact site[…]
I covered scroll tracking my previous post: Track and measure scrolling. This is a light weight version of the script. It should avert any jittery scrolling issues. It has one disadvantage – it only calculates the scroll distances (ie how many pixels is 25% of the page height etc) once on page load, so if[…]
1. Don’t actively maintain your Exclude URL query parameters list Google has this view setting as ‘optional’ but if you don’t set it up correctly and maintain it, then you can make a real mess of your data. The setting tells GA whether to treat each value of the query string parameter as a separate[…]
Update: there is a new lighter-weight version of the scroll tracking code here. The older version here has the advantage of automatically adapting to changes in page height if the browser window is resized or new content loads. However, I have had one report of this causing jittery scrolling, the lighter weight version is designed[…]
How bad is a bounce on your page? What does that high bounce rate mean? Interpreting bounce rate is not as simple as some guides put it. there are different kinds of bounces: bad, very bad, and not bad bounce rate is not an indicator of content engagement How Google Analytics measures bounce rate By[…]
This calculator tells you, given the split test data you have, how likely is it that one version is better than another.
A Bayesian approach avoids many of the issues with z tests and G tests, and can often enable you to draw meaningful conclusions, even where conversion rates and sample sizes are low.
The probabilities calculated go directly to the business question of which version is best.
Time on site is an incredibly useful metric, but fraught with difficulties of collection and interpretation. For example Google’s presentation in the behaviour/engagement reports, at first glance, makes visit duration look normally distributed, but they aren’t.
Using the analytics API in a spreadsheet enables a much closer look at the distribution of visit lengths.
Update: a better solution
Google now presents an inbuilt library for accessing Google analytics from Google docs. You can see how to use it with a ready-made and powerful solution for template driven analytics reports and dashboards here.
This post is left here in case it is of interest to anyone. However, this is no longer the best way of accessing the Google Analytics API from Google Docs. Google have made an interface available directly within docs script, as described in the Google Analytics blog.
The Google Analytics Reporting API enables you to automate reporting tasks, combine GA data with other information, apply analysis and visualisation tools, and access data you couldn’t easily reach via the Google Analytics UI.
As well as reducing repetitive work, this reduces your chance of errors, and enables you to build up more sophisticated analysis.