A New Approach to Analyse Human-Mobile Computer Interaction  

This paper describes a tool for log file recording and a method for quickly and easily analysing human-computer interaction with mobile devices. The tool logs screenshots and quantitative interaction data, such as number of clicks and timestamps. The analysing tool provides the ability to evaluate the interaction sequences and to export an MS Excel®-sheet for statistical analysis. To evaluate the tool, a usability study was conducted comparing the effectiveness of this tool in the laboratory and in the mobile context. Findings show that the tool is the first step toward a very effective, unobtrusive analysing method for user interaction in the mobile context. Combined with debriefing methods, it would be an optimized way for usability testing with mobile devices.

Kawalek, Jurgen, Annegret Stark and Marcel Riebeck. Journal of Usability Studies (2008). Articles>Human Computer Interaction>Wireless Web>Log Analysis

Measuring Website Performance: Part 3

Your web server archives the information needed to generate these numbers and many others. The raw data is stored on the server in what is known as a log file. The statistics referenced above are best accumulated through the use of a log analysis program to convert your hard-to-read server log files into an understandable format.

Shreves, Ric. Water and Stone (2004). Articles>Web Design>Assessment>Log Analysis

Analyzing Your Traffic  

Discover your site’s findability triumphs and tragedies with traffic analysis systems.

Walter, Aarron. Building Findable Websites (2008). Articles>Web Design>Audience Analysis>Log Analysis

Web Log Analysis

Getting to know your audience is key to designing a successful website. Because your audience may be spread around the world, learning about the users of your site may be quite a challenge. Even if you think you have a pretty good idea of who your audience is, in many cases, there's a lot of information that you won't know--for example, what browsers your users are using, whether or not they are connecting from on or off campus, or what pages they find most useful.

Novogrodsky, Seth. University of California Berkeley (2000). Articles>Web Design>Audience Analysis>Log Analysis

Web Traffic Analytics and User Experience

As a specialist in the user, you gain knowledge through observation and direct questioning of individual users. Now, you can add to that insights gained from data pulled during their actions on the site. By looking at this information, you will get a fuller picture of user behavior, not in a lab, but in the true user environment.

Diamond, Fran. Boxes and Arrows (2003). Articles>Web Design>User Experience>Log Analysis

What's Important to Measure on Your Website?

Websites are very measurable. However, reams of data can be time consuming and confusing. The knack is to know what is really important to measure. This includes the following: reader actions; reader numbers; most and least popular pages; subscribers; external links; search keywords; page size; broken links and malfunctioning processes.

McGovern, Gerry. New Thinking (2003). Articles>Web Design>Audience Analysis>Log Analysis

Are You Using the Wrong Web Metrics?

Do you base success on measuring the volume of visitors and page impressions? Such measures may in fact reflect the failure--rather than the success--of your website.

McGovern, Gerry. New Thinking (2006). Articles>Web Design>Audience Analysis>Log Analysis

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>Audience Analysis>Log Analysis

Why Web Usage Statistics are (Worse Than) Meaningless

Web usage statistics, such as those produced by programs such as analog cannot be used to make strong inferences about the number of people who have read a website or webpage. Although those who compile these statistics usually try to make this clear, people still insist on misusing them to make overly strong inferences. Attaching meaning to meaningless numbers is worse than not having the numbers at all. When you lack information, it is best to know that you lack the information. Web statistics may give the user a false sense of knowledge which can be worse than being knowingly ignorant.

Goldberg, Jeffrey. Goldmark (1995). Articles>Web Design>Audience Analysis>Log Analysis

Wiki Analytics

Are there algorithmic ways of determining the health of a Wiki? There are likely a number of different patterns of healthy Wikis and, more importantly, healthy Wiki-based communities. If we can identify and visualize these patterns, we can apply these analytics to: understand the patterns of interactions in a healthy community; aid the community to use the Wiki more effectively; and encourage developers to facilitate these patterns in the tool itself.

Socialtext (2009). Articles>Web Design>Wikis>Log Analysis

Analytics According to Captain Kirk

By seeing all of the available data in one chart, associations, patterns and conclusions can be drawn simply by comparing the relationships as they are presented. This is something that I learned from Edward Tufte.

Bailey, Matt. Lyris (2008). Articles>Web Design>Technical Illustration>Log Analysis