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Using Google Analytics to Spot Conversion Leaks

Posted by admin on April, 8th 2011

Google Analytics can be an extremely valuable tool for spotting what elements are working and what could be improved on your website.

As an SEO company we are now becoming more and more involved with Conversion Optimisation, the process of converting visitors into customers or subscribers on a website also known as the ‘science of selling‘.  Increasing traffic levels by performing search engine optimisation is a key focus for many website owners… conversion optimisation on the other hand is just as valuable as it can produce bigger and longer lasting results from existing traffic levels.

Performing both search engine optimisation and conversion optimisation gives a double positive effect:

How to use Google Analytics to spot a conversion leaking element

Google Analytics can give vital clues about what could be changed on a website to improve conversion rates.  A great way of spotting conversion leaks are comparison charts based on user data on Google Analytics; below is a step-by-step guide to draw out basic conversion statistics:

Firstly select the type of data you want to analyse, in this example I am monitoring different versions of Flash installed on visitor’s computers.  You can find this menu on the left hand side of the Dashboard.

You should now see a result page similar to the example above.  Currently this isn’t much help unless I wanted to see what version of Flash visitors to the site are using.

The little tab highlighted here in the top right corner can turn the pie chart in to a comparison chart, all we need now is something to compare…

The data out in order of the number of visits per different version of Flash.  I’ve used the comparison chart to show the average time spent on the website compared to the average.

Shockingly this example above shows a 47% ‘time-on-site’ drop for non-flash users; this is shown clearly with the big red bar on the chart.  The website in question had a small Flash banner on it’s homepage and this data shows how damaging it was to visitors trying to use the site who didn’t have Flash installed and how it must have harmed conversion rates.

Using this method for different screen resolutions or different browsers may show some alarming results on your own website. Use it to test out if your website is IE6 friendly for example or if people with small monitor resolutions convert as well as the average.

How to use Google Analytics to spot a conversion leaking page

Another thing you should be looking at are the individual pages on your website, which one’s are holding you back? Which web pages could be either improved or taken out completely?

There is a useful feature which shows which pages on your website people visited and then left (exited) the entire site…

Find the top exit pages tab on the left hand side of the dashboard.

Sort the top exit pages by percentage of people who exited (highlighted here in red).  This could bring up lots of obscure pages depending on your URL structure.

If your website has many URL’s containing parameters then things will look a bit messy now.

I’ve noticed that every product URL on the ecommerce website I’m looking at has the string “product.aspx” with in the URL.  I can draw out all the relevant product pages on the site by filtering the pages using the filter options below (highlighted and zoomed).

If there was multiple sections of the website I’d like to include in the stats (for example products pages AND category pages) then the “Advanced Filter” option can be used to add multiple filter metrics.

The last thing to do is to sort the data by the “Exit Percentage” again (if you used a filter) and then use the “Weighted Sort” option that appears above.  This uses a combination of the percentage of people leaving a webpage and the number of visits that page receives overall, highlighting the most important pages overall to correct.

You can see in the example above that the “Cherry Blossom Branch Lights” product page had 11,310 pageviews and and exit percentage of 65.11%.  This under-performing page alone therefore caused a whacking 7,364 people to leave the website who could have possibly have bought something else on the site or at least got more exposed to the brand.  This would be an ideal product to remove from the site or perhaps take a better image of if it had bad photography.

This technique can be used for normal non-ecommerce websites with great effect also, you could see if a certain sales page was under-performing or which sets of keyword traffic was more valuable.

Conclusion

Spotting conversion leaks doesn’t take much time and could quickly spot which pages/elements of your website need improvement to enhance your existing traffic.

If you manage an analytics account for a large organisation you can quickly fire off a .PDF document showing the conversion leak evidence to your boss or web developer:

You can save the file in .PDF format for a report or a CSV format for use in excel spreadsheets to make graphs of the data.

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