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A Comprehensive Strategy for Using Web Site Statistics
Track The Effectiveness Of Your Marketing Effort
Part 1
By Carlton Lovegrove
Originally Published: March, 15 2005
An important component of any ecommerce initiative is to track the effectiveness of the marketing effort. Through careful analysis of a web site's statistics much information can be gleaned that can be further used to fine tune the advertising, web site content, and customer relationship management strategies and policies. These are all important elements of Internet Marketing plans and strategies that can ultimately dictate the success or failure of any ecommerce initiative.
Surfing the World Wide Web involves traversing the connections among hyperlinked documents. It is one of the most common ways of accessing web pages. Theories and models are beginning to explain how observed patterns of surfing behavior emerge from fundamental human information search processes. Therefore, the ability to predict surfing patterns has the potential to be instrumental in solving many problems facing producers and consumers of web page content. For instance, web site designs can be evaluated and optimized by predicting how users will surf through their structures. Web client and server applications can also reduce user perceived network latency by pre-fetching content predicted to be on the surfing path of individual users or groups of users with similar surfing patterns. Systems and user interfaces can be enhanced by the ability to recommend content of interest to users, or by displaying information in a way that best matches users' interests. Proper analysis of a web site's activity is therefore an important process that supports an enhanced and intelligent design of a web site.
A common and popular source of tracking data and statistics for any website is the log file on the web server. Most web servers have a system for recording all requests for web site objects to a log file. The data in the log file indicates which objects were requested, when, and information about whom or what requested them. Therefore, with the appropriate software that is used to process this data, company managers and executives can measure the success of their websites and develop appropriate strategies to address weaknesses and enhance their prospects for future success by assessing their site's
visibility
(the ease with which customers can locate your site),
navigability
(the paths that customers use to navigate through your site), and the
usability
(how easy is it for customers to use your site).
However, complete reliance on data collected in log files has its pitfalls, some of which will be discussed in this article. Other tools such as tracking counters help overcome some of the problems encountered with log file analysis. Therefore, an intelligent selection of site statistics software requires the ability to recognize the strengths and weaknesses of each tool in order to effectively strike a balance that realizes the missions and goals of your organization. Understanding the statistics provided by web site analysis software is critical in order to properly interpret, evaluate, and design subsequent marketing strategies.
Log file data
While web servers have the ability to record vast amounts of information, relatively few fields are typically recorded. Several formats have evolved from the Common Logfile Format (CLF), including the Extended Logfile Format (ECLF) as well as a variety of customized formats. For the most part, the following fields are recorded by web servers:
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the time of the request in seconds,
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the machine making the request is recorded as either the domain name or IP address,
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the name of the requested URL as specified by the client,
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the size of the transferred URL, and
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various HTTP related information like version number, method, and return status.
Various web servers also enable other fields to be recorded, the most common of which are:
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the URL of the previously viewed page (the “referrer” field),
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the identity of the software used to make the request (the “user agent” field), and
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a unique identifier issued by the server to each client (typically a “cookie”).
Understanding how all of this data is interpreted and displayed in a user readable format for subsequent decision analysis is an important component of any statistical analysis. It is therefore crucial that users be aware that there are different ways that the statistical analysis software can present the data to you. Subsequent sections of this article address some of the important decisions that the statistical analysis software must make when creating reports on your web site activity.
Continued:
A Comprehensive Strategy for Using Web Site Statistics Part 2 >>>
Carlton Lovegrove is a PhD of Information Systems
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