Statistical analysis of website usageAnalysing data from your website is important. Perception is often vastly different to reality. Website statistics can be misleading if not interpreted properly. A basic analysis can be done using statistics programs provided by your hosting company. Using these statistics, you should be able to evaluate;
Return on investment in SEO. Search engine optimisation companies who charge thousands of dollars for their services often base their claim on getting a handful of top search terms but it may be that only a handful of visitors actually find your website by typing in those search terms. Are you spending hundreds of dollars on hosting, management, search engine optimisation and copywriting a month for a website that no-one visits?
Are your premium google listings, google adwords, adverting costs from other search engines and websites providing a return on investment, or are you spending thousands of dollars for a handful of visitors?
Where are your visitors coming from?
What are the popular search terms and phrases used to find your website?
Are marketing campaigns like letter box drops, competitions, raffles, etc bringing more visitors to your website?
LimitationsWebsite data like all data collection has limitations. Currently all website statistical programs and web services on the internet assume that a unique user is equal to a unique I.P. Users may choose to access your website from different locations and/or may not have a static IP. Users of dial up internet will not have a static IP and so the website data will count them as a different visitor. Understanding the limitations, is important when interpreting data.
Many people believe that a popular website gets lots of hits. The number of hits is the equal to the number of file requests on a webpage, so if you have lots of images on your website, you will have lots of hits. The number of hits tells you nothing about the popularity of your website or whether your website is working for your business.
All the log analyzers and statistics programs available use simple mathematics. The problem is averages can lie if the proper mathematical model is not used. A statistician knows that averages, medians are meaningless without discussing variance, standard deviations, testing hypothesis, choosing the correct distribution, removing outliners.
Finding meaning in statisticsStatistics is not flawless but it will paint a picture and a good analysis of website usage will benchmark website performance against your desired outcomes and provide options for better website design.
Some questions statistical analysis may provide answers to include - How many visitors are coming to the website?
Where do visitors come from? If they come from search engines, what key words and phrases are they using to find your website?
How long do visitors stay on your website?
What are the click paths of various type of visitors to your website?
What linking sites do your visitors come from?
Do the statistics give an indication of demographics?
What is the main reason people come to the website to do, read or buy?
However if you want to measure improvement, you need to do a proper analysis and calculate standard deviation. Otherwise, you could prematurely come to a conclusion that there had been an improvement when perhaps it was only variance or seasonal factor that influenced the result.
Using raw logsProper statistical analysis can only be done using raw data and by importing data into mathematical programs or log analysing software and eliminating outliners.eg. eliminating the ip addresses of staff members from website usage data. Obviously this is more expensive and the scope and purpose of website statistical analysis must be determined. It is also necessary to compare various tools, as the way that each program manipulates the data will vary and some log analyzers may be programmed incorrectly. Just because it spits out an answer or pie graph does not mean that the answer is correct.
source:
http://www.passioncomputing.com.au/Website_Redesign/Statistical_analysis.aspx
