On the 18th April the BBC posted an article on how methods of gauging site success by measuring page views and using cookie tracking could be providing inaccurate figures.
The general gist of the article was that if you are using a cookie based analytics tool then the number of unique visitors you think your site might be getting could actually be way off the mark. This is because there are an increasing percentage of people who regularly delete cookies from their computer. So when they return to a site they are counted again as a new unique visitor.
This means that the number of people who you think are coming to your site is over estimated.
If this is the case then as the vast majority of recent web analytics tools use cookies based traffic then the majority of people are getting inaccurate figures.
But what can you do about it? Should we all go back to log file analysis that was claimed to be just as inaccurate in other ways, didn’t track in real time, took up a huge amount of space on servers?
Until web analytics companies come up with a new and even better way of tracking then certainly SME’s that don’t have the budget for large complex web statistics packages will have to put up with these reports of inaccuracies.
To be honest, the benefits and tracking options that tools such as Google Analytics offer to the SME for free far outweigh any reports of slight inaccuracies.
The same article from the BBC stated that using the number of page views as a measurement of success could also be giving a false impression of the success of a site. This is indeed true if you have a site that doesn’t require the view of many pages to convert a visitor to sale or enquiry. In some cases if people are entering your site through a highly niche product or service page, they might only need to view this page to gain enough information to make a decision to call the company up and order over the phone. Therefore an average of 1 page view per visit might be very successful for this site.
On the other side of the coin, a site with an average of 20 page views per visit might appear to be successful as it has such a high page count. However this might just mean that people are getting lost on the site. Always remember its quality of page and not quantity of pages that will result in a higher conversion rate for your site.
It has been mentioned that time spent on site is a better indicator of site success, however as with page views this can be ambiguous. A very clear, simple site with a high conversion rate might need visitors to spend little time on the site. Likewise a large and complicated site, or a site with video and audio content might have people spending a large amount of time on the site without converting at all.
So where does all this ambiguity leave the average SME? Well as long as you have a good understanding of how your site works, the amount of page views needed for a conversion and the rough amount of time it should take someone to follow the conversion funnel from start to finish, you should be able to use your web analytics to full effect.
Make sure before you do any analysis that you ask at least one or two people who haven’t seen your site before to carry out a set of tasks on the site, such as finding a product, conducting a search, or completing the sales process.
Armed with the amount of pages these testers took to do this, and how long it took them you can apply that to your web stats. If the number of pages that most people view is far higher, then your site is perhaps not working in the way you want it to.
Obviously the larger selection of people you can use to do this testing the better, but with the usual SME time and budget constraints this is not always possible.
One key point I would like to make is that what ever you decide to track on your site, and how you want to view success, MAKE SURE you track it in exactly the same way over time. It is impossible to gauge success if you are taking different measurements from month to month.
Good luck, it really is key you understand how people are using your site and get to grips with web analytics.