What Stats Should you be Interested In?

If you run a blog or website, chances are there are loads of stats at your disposal. Everything from referrers to bounce rates. Keywords and heat maps. Digging into stats packages such as Google Analytics can be daunting even if you know what everything means. If you don’t, it can be downright traumatic. Stats are always usefull, but you have to know what to look for, and what the data means when you get to it. In this post I’ll run through some of the stats you should be paying attention to, what they mean, and how you can create actionable tasks based on the data.

  • Referrers – Simply put, this is a list of sites that send visitors to your site, or page. This is important for a number of reasons. Firstly, it can alert you to other sites in your niche that are linking to you, and we all know how important networking is these days. Secondly, if you’ve been spending some time promoting your content, you can very easily see what’s working and to what extent. If you are paying for promotion, these stats become even more important. I touch upon using referrers to generate content in a previous post.
  • Bounce Rates – The bounce rate is the percentage of visitors that leave after reading just the first page. So they come to your blog, for example, read the post and then bounce straight back off the site to do something else. Ideally you want to get the bounce rate as low as possible by driving visitors to other relevant content on your site. Typically, visits from place such as digg have a very high bounce rate. In a perfect world you would have two similar pages of content, each with a similar number of visitors so you can experiment with different methods of reducing the bounce rates. It’s also interesting to see the varying bounce rates when comparing visitors from different sources. I’ve written about reducing bounce rates previously. Going hand in hand with the bounce rate is the number of page views per visit.
  • Keywords – Most sites receive a fair amount of traffic from search engines. Fortunately search engines (and stats packages) allow for the queries each user entered to be seen. These keywords can be important not only to see if you are getting the sort of visitors you are expecting, but also what content is popular amongst the general search engine using public.
  • Popular Click Areas – There are a number of ways the different stats packages approach this data. Some will show some sort of heatmap, with areas that are clicked often highlighted by colours. The other approach is to show how often each link is clicked. This is really a personal thing, depending on what you prefer. The crux of the issue though, is that at the end you know which links have been clicked more than others. This should give you and idea of not only what areas of the site are popular, which is useful for ad placements, but also which links work, which can be useful for tweaking the wording of your post titles and links. Once again, this is something that it’s nice to experiment with, just to see how big a difference things like wording and link placements make.
  • Visitor Data – This covers a multitude of stats. Most packages record things such as visitor location, browser, resolution and time on site. All this information can be used to tailor your site to your visitors. It can also come in very handy when going through a redesign, especially if half of your visitors are still on IE5 and a 480 x 640 resolution. You may want to make sure you have that audience covered.

There are lots of tutorials out there on how to easily access and understand statistics.   For me though, the most important part is knowing how to use the data once you’ve got it.   Typically, the more imaginative you can be when interpreting the stats the more you’ll get out of them.   It’s important that bloggers get past the headline “visits” stat and move onto working smarter with stats.

If you liked this post, why not have a look at Monetising your Blog, 5 Simple Steps to a Better blog and One Week to a Professional Blog.