#13794
Everything served to a visitor -- from the first page through marketing, sales, and product fulfillment -- generates data about the customer. Web marketers can tap into this 'free' source of profile data for just the cost of converting existing data into a format that can be used by a data-analysis program.
Allen, Cliff. ClickZ (2001). Articles>Usability>Web Design>Log Analysis
#19027
Once upon a time, if it was on the web, it was good. If it did tricks, so much the better. And how did a company know if its website was really good? Of course, by measuring traffic. The more traffic, the better, right?
Jaleshgari, Ramin. CIO Magazine (2000). Articles>Web Design>Usability>Log Analysis
#19023
Measuring User Motivation from Server Log Files 
Estimating user interest and motivation by just counting page requests from a World Wide Web server log (or 'hits') provides a distorted metric of user activity. Some of the reasons why this metric is unreliable are that the path dependent nature of hyperlink usability treats index and navigational aid pages as equal to the goal, because differenes in web browsers can determine how effectively users can percieve content and navigational alternatives, and because the poorly designed structure and content of the documents themselves can inhibit users from finding what they are looking for. This paper proposes that measures of how much time users spend looking at a page are better estimates of user interest than page hits, providing simple human factors principles have been applied. An extended example of how this method might be used to collect and analyze data is also included. The types of decisions that can be made by authors and system administrators based on a time-based metric of user interest is summarized.
Fuller, Rodney and Johannes J. de Graaff. Microsoft (1996). Articles>Web Design>Usability>Log Analysis
#19025
Server log files are records of Web server activity (or server activity for any digital medium). They provide details about file requests to a server and the server response to those requests. Collecting and analyzing these files can provide: information about who is coming to your Web site; what information they're requesting; their navigation and behavior. What types of data you collect on your server depends on how it has been set up and defined by the technical staff.
Usability.gov (1998). Articles>Web Design>Usability>Log Analysis
#19024
When analyzing numbers related to the growth of a website, I normally recommend looking at them on a logarithmic scale. The reason is that the Web and the Internet both experience exponential growth. Therefore, Web statistics are better analyzed in terms of growth rates than in terms of linear growth.
Nielsen, Jakob. Alertbox (1998). Articles>Web Design>Usability>Log Analysis
