Web Analytics: Future Applications in Predicting Modeling

Web Analytics: Future Applications in Predicting Modeling

A lot of time and effort is being channeled in the area of web analytics. This terms refers to:

“[t]he measurement of data as it relates to an Internet site, including the behavior of visitors, the amount of traffic, the conversion rates, web server performance, user experience, and other information in order to understand and proof of results and continually improve the results of a site towards a set of objectives.”

Since web analytics is another area of predictive modeling, we must ask whether the methodologies, analytics software, and visualization tools develop in web analytics could have impact in other industries that use predictive modeling like healthcare, banking, insurance, retail, and manufacturing industries. I think that the processes and software developed for web analytics will ultimately be use in many other industries because the intersection of the Internet and other industries is already a reality.

Predictive modeling and web analytics have the same objective, to provide a measurement (or baseline) and to predict future behavior. One of the key contributions of web analytics has been software that can withstand the rigors of commercial use. The scalability components of web analytics are crucial for other industries in which large databases has become the norm.

Another significant issue that web analytics has contributed to the area of predictive modeling is the ability to come together and provide a series of metrics and benchmarks for the industry. Although some may disagree with this assessment, if we look at the history healthcare industry it apparent that the inability to agree upon benchmarks and metrics have negatively impacted the cost of healthcare in the United States. Moreover, those involved in web analytics could give industries like banking, insurance, and retail an innovative new look at what needs to be measured.

A third issue that web analytics have contributed to the issue of predictive analytics is the healthy, spirited, and robust exchange in the area of privacy. The Internet has created and raised serious, relevant, and pertinent questions regarding privacy that other industries could find beneficial.
A fourth area that web analytics has contributed to predictive modeling are the development of new return on investment (ROI) models in business. As companies adopt for these ROI models for their advertisement, new media, and marketing strategies they may find that these models are also applicable to other lines of businesses.

Last but not least, web analytics have contributed to a new set of visualization tools that summarize previously hidden nuggets of gold in a way that can be easily understood and act upon.