Posted by: bbannan | April 1, 2011

Logfiles, datamining & clickstream data – Renita

When considering a web-based design or product and to ensure success it would be in the designer’s best interest to consider extracting and analyzing data about their target audience experience with the product.  It is imperative for designers/developers to know what kind of impact, if any, the product is having on the target audience.  It is imperative that the designer becomes familiar with three elements that will help them to try to organize, analyze and interpret the needs, complaints and behaviors of the target audience.  Designers must consider log files, clickstream and data-mining.  Each element plays a significant role in interpreting, analyzing and improving a design/product. 

It is important for designers of any web-based design or product to become familiar with log files as understanding their purpose will be beneficial to the long-term success of your product or design.  Log files are used to collect data.  They have the capability to reveal how items were requested, where the request came from, browser and operating system information along with many other details about that particular connection session.  It is up to the designer to determine which information should be captured for general inquiry or design improvements. When considering log files to gain insight into the user experience, the type of log file that you choose will yield different data.  You must be clear on the type of information that needs to be obtained to accurately understand the user’s experience—regardless of the element used to obtain the information, whether it is access or server logs, caching or using cookies.

Another technique for determining a user’s experience is the clickstream analysis approach.  In this approach, you will be able to determine how users move through your site, it can yield collective patterns related to how people move through the site.    Clickstream analysis can reveal statistical data related the next pages and average paths elements.  Clickstream can also be used to assess the purchase path and will track shopping cart abandonment.

In Group 1, in developing geometry lessons using an itouch application and augmented reality, the use of log files and clickstream would be instrumental for teachers and school administrators to observe students’ pattern of behavior when exploring lesson etc.  Since the information will be on the school’s network and the population of the sample size is low, minimal effort will be needed to analyze the data.   Log files and clickstream data can provide vital information and statistical reporting to school administrators for additional buy-in regarding the possible use of augmented reality in other subjects.

Data mining refers to the extraction of hidden predictive information from large databases, is a powerful new technology with great potential to help companies focus on the most important information in their data warehouses. Data mining tools predict future trends and behaviors, allowing businesses to make proactive, knowledge-driven decisions (http://www.thearling.com/text/dmwhite/dmwhite.htm).  This can definitely be useful in the scenario in our group.  Having concrete information to show the school administrators will certainly initiate more interest.

One related article that I found printed in 2007 from the New York Times describes how data mining through the use of technology has been used in various scenarios.  The authors stated how data mining was an emerging phenomenon, yet it seems to be directly in-line with what we are discussing at this time.  Many more organizations are using data mining to

http://www.nytimes.com/2007/05/20/business/yourmoney/20compute.html

 In this digital, augmented, information age,  the use of log files, clickstream analysis and data mining can prove beneficial to the product designers however from a consumer perspective, I am not sure that I want  too much information known about my purchasing behaviors etc.,  as it could have negative implications in the future such as constant cost increases.

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