The Analycise™ methodology uses standard web server session log data to model client paths followed in using your site. This analysis of how users interact with your site, what pages they visit, and in what sequence, and for how long. This path analysis provides valuable management information. It gives you the insights needed to refine your site architecture and structure.
Fundamentally, the Analycise™ approach provides the explanations for the numbers you see in the standard web performance reports. It helps you to understand why you concentrate on entry pages, exit pages, pages views, and unique visitor counts.
The Starting Point - Counting Visitors
Each performance accounting approach hinges upon identifying and counting those visiting the site. Generally, each time we see a new sequence of requests for site content originating from a specific internet address we say we have a new visitor. Whether or not this is a unique visitor depends upon whether to address we have recorded as the source of the transactions is one we haven't seen before or if it is a new series of requests (separated by a specific amount of time, say, a half-hour) from an address we've already encountered. Due to different ways in which log analysis reporting programs count visitors, you might see slightly different numbers for total visits and unique visitor counts.
The Standard 'Pages Visited' Analysis
Once a session log has been dissected to identify the number of visitors received, there are a number of other summaries or tabulations that are prepared by the analysis programs. Typical reports often include the following types of reports.
Average Number of Pages Visited
The average number of pages visited is simply the total number of page views divided by the number of visits. Page views generally include the standard web pages and forms but typically exclude requests for graphical elements, pictures, and the like that are part of a single page.
Complications with this approach often arise from sites that use frames or various dynamically generated pages. Most log analysis tools identify how they define a page and what types of file extensions are excluded from page view counts.
Entry Page Analysis
Many webmasters pay significant attention to the various entry pages used by visitors in accessing their sites. Depending upon site complexity, users could have bookmarked any of a variety of pages from within a site. And, search engines could index pages other than the main or home page of a site. So, webmasters should expect many different pages to be used as the entry or start page for user visits.
Understanding alternate entry points is important because there may be certain inefficiencies if users start their visits on pages that weren't strictly designed for easy use. This can result in users becoming more frustrated, circling through the site to find the right starting point and the like.
Exit Page Analysis
An exit page analysis is also a valuable tool for webmasters. The exit page analysis shows the last page visited prior to leaving a site. Often this can provide useful information, particularly if the last page visited is a sales selection page, or some type of error page generated by the site. If the bulk of the exit points are error pages or other unexpected points in the site, webmasters can look for problems with their site design.
What This Doesn't Tell You
Knowing factual information about visitors, entry pages, exit pages and average page views is valuable. But what these standard tabulations can't provide are answers to some important questions, like:
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Why did I see the index page visited more times than I had visitors?
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How did visitors move from page to page?
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What will I need support additional visitors?
Answers to these questions require that you perform a statistical analysis of the session logs to create a model of site user behavior. This analysis and modeling process is sometimes called customer path analysis.
Customer Path Analysis
The purpose of the customer path analysis is to determine how users move from page to page within a web site. Many log files contain the key data needed for this type of analysis - even if they are in a simplified form. The key task is to isolate and identify each user's progress through the site.
By analyzing the addresses, time stamps, referring URL, and request fields in the log files, customer behavior can be easily identified. Transitions from page-to-page can be determined. Tracing a single user or a statistically significant subset of users is possible. Then, when this data has been statistically summarized, we can use other mathematical techniques to turn this data into information with management value. For example, it is possible to use some advanced matrix mathematics tools to create page-to-page 'transition probabilities' and then create a model that shows how users will work your site - depending upon where they enter the site.
A Combined Approach - The Analycise™ Methodology
The Analycise™ methodology combines the advantages of the precise analysis of session data with the simplicity of the tabulations webmasters most often see. It provides an explanation that links these tabulations together and reinforces their importance. And, it provides significant design related recommendations.
Design Implications
Design implications can range from simplifying site designs, to putting additional information on various pages, to eliminating the ability of users to enter a site using randomly bookmarked pages. The results of an Analycise™ site evaluation could also point to the need for controlling search engine robotic site searches and spidering. Many other useful design points can also be addressed, depending upon both the complexity of the site and site usage levels.
For More Information
For more information on the Analycise™ methodology, and what we can do for you and your site with our toolset, please contact:
Analycise™
James S. deBettencourt, Ph.D.
e-mail: jimdeb@analycise.com
phone: (847) 674-9848
