I use Google Analytics everyday and this book answered many questions that have been nagging at the back of my mind for months. If you are wondering what’s the best practice for tracking video or visits from image search with Google Analytics this book is definitely for you.

Here’s my top 5 of the Advanced Web Metrics
- powerful hacks and great examples
- 10 recommendations for web analytics accuracy
- ‘virtual pageviews’ for tracking transactions on non e-commerce sites
- using exitTracker to capture clicks on banners and other outgoing links
- changing referrer credited for conversion

Even though I’ve used Google Analytics a lot I didn’t know that GA keeps data for a minimum of 25 months and that the penultimate referrer gets credit from direct traffic transactions.

So just to sum up, it’s a great book for everyone who works with Google Analytics. Please bare in mind though that you need to have HTML/JavaScript knowledge to get the most out of the examples/hacks.

More about Advanced Web Metrics with Google Analytics
- Marshall Sponder Review
- Official book launch on Brian Clifton’s blog

Here’s an example of this type of a “content effectiveness” report

From looking at the table above you might think that it is important to invest in Product reviews and that Categories are not performing well. Does these numbers really tell you how effective your content is or is it just an indicator of where most of your visitors go?

The information that is missing in that report is the number of URLs. In order to calculate the effectiveness of your content you need to divide the number of visits by the number of URLs within this content group or site directory.

Content Effectiveness = Visits to a content group / URLs within this content group

The same table with this additional column and the Content Effectiveness metric added would look like this.

So now you can tell that the Categories are actually giving you 30 visits per URL, whereas products only 2.5. This might be due to the fact that you are driving most of your paid traffic to the category level pages but it might also mean that your product level pages are not optimised.

This is probably one of the most powerful metrics that you can use to find out what pages you should focus on and which pages are not worth your time.

When I tried to compare two date ranges I got the following error message
There was an error fetching data for this view.

Even reducing the date range to a few days period didn’t help. Google Analytics spitted out this error “Please try again. If you are experiencing long delays, please reduce the selected date range or disable date comparison. Thank you for your patience. ”

And finally my favorite one – an 404 error when trying to access one of the reports.

It’s not that I don’t like Google Analytics but if decide to use it commercially bare in mind that it doesn’t always work. If you have seen any other error messages in Google Analytics or any other web analytical software feel free to add a comment below.