Web Analytics

It’s hard to find an area in the field of data mining which deals with more data than the web. The whole web is exploding with information. As of May'09 there were an estimated 109.5 million websites operating over the web. Add to that the information about every click, ad impression, purchase and the information captured by the underlying infrastructure (routers, servers, gateways ...) and soon you'll be inundated with more data than you know what to do with.

Web analytics aims to use the information as mentioned above to optimize one's WebPages to achieve higher clicks, conversions, ROI etc.

There are a variety of tools available for analyzing the activity of users on your website. Google analytics is by far the most popular. It's admired for its simplicity of design and powerful features.






You can get a wide range of data using these tools. For example - where do your users come from, most popular keywords driving your traffic, bounce rate, demographic distribution, conversion rate, time spent per visit etc. You can even get information about how your peers are doing - by enabling benchmarking in Google Analytics you can view metrics of websites in the similar category.

However, the tools mentioned above invariably give the answer to “what” rather than “why”. The hard part is to come with an answer to why things are the way they are. For example you can have all sorts of statistics about clicks, impressions, bounce rates, average time spent, most viewed pages etc but unless you tie these with an explanation as to why these are happening web analytics will not be as fruitful as it can be.

One of the good things about web analytics or web in general is its dynamic nature. If you have good traffic on your website you can analyze effects of changes within hours or a few days. Which on many occasions means you don’t have to wreck your brain on discussing whether something will work or not. You can just try it out and quickly find out the answer to whether it’s working or not.