This lecture presents an overview of the Web analytics process, with a focus on providing insight and actionable outcomes from collecting and analyzing Internet data. The lecture first provides an overview of Web analytics, providing in essence, a condensed version of the entire lecture. The lecture then outlines the theoretical and methodological foundations of Web analytics in order to make obvious the strengths and shortcomings of Web analytics as an approach. These foundational elements include the psychological basis in behaviorism and methodological underpinning of trace data as an empirical method. These foundational elements are illuminated further through a brief history of Web analytics from the original transaction log studies in the 1960s through the information science investigations of library systems to the focus on Websites, systems, and applications. Following a discussion of on-going interaction data within the clickstream created using log files and page tagging foranalytics of Website and search logs, the lecture then presents a Web analytic process to convert these basic data to meaningful key performance indicators in order to measure likely converts that are tailored to the organizational goals or potential opportunities. Supplementary data collection techniques are addressed, including surveys and laboratory studies. The overall goal of this lecture is to provide implementable information and a methodology for understanding Web analytics in order to improve Web systems, increase customer satisfaction, and target revenue through effective analysis of userWebsite interactions. Table of Contents: Understanding Web Analytics / The Foundations of Web Analytics: Theory and Methods / The History of Web Analytics / Data Collection for Web Analytics / Web Analytics Fundamentals / Web Analytics Strategy / Web Analytics as Competitive Intelligence / Supplementary Methods for Augmenting Web Analytics / Search Log Analytics / Conclusion / Key Terms / Blogs for Further Reading / References

Autorentext

Bernard J. Jansen, P.D., is a Principal Scientist in the artificial intelligence center of the Qatar Computing Research Institute. He is a West Point graduate with a Ph.D. in computer science from Texas A&M University. Professor Jansen is editor-in-chief of the journal Information Processing & Management. Kholoud Khalil Aldous, Ph.D., is a Post Doctoral Researcher at Qatar Computing Research Institute. She got her Bachelor's and Master's degrees in Computer Science from Qatar University. She has a Ph.D. in computer science and engineering from Hamad Bin Khalifa University. Her research interest relates to user engagement on social media platforms. Joni Salminen, PhD., is a faculty member of the School of Marketing and Communication, University of Vaasa, Finland, and he is also an Adjunct Professor at the Turku School of Economics at the University of Turku. Previously, he worked as a Scientist at the Qatar Computing Research Institute, Hamad Bin Khalifa University. Joni's current research interests relate to user personas, quantitative UX, and human-centered AI. Hind Ali Almerekhi, Ph.D., is a research associate at Qatar National Research Fund (QNRF), Doha, Qatar. She received a B.E. degree in computer science in 2012 and an M.S. degree in computer science in 2015 from Qatar University. She is a graduate of the Ph.D. program at the College of Science and Engineering, Hamad Bin Khalifa University, and her research interests span a range of critical areas, including machine learning and online hate in social media. Soon-gyo Jung is a software engineer at Qatar Computing Research Institute, Doha, Qatar. He has been working on data analytics/data-driven/data intensive systems by applying research-oriented full-stack software engineering skills (Computer Science, Data Science/Analytics) for years. He received the B.E. degree in computer software from Kwangwoon University, Seoul, Korea, in 2014, and an M.S. degree in electrical and computer engineering from Sungkyunkwan University, Suwon, Korea, in 2016.

Inhalt
Understanding Web Analytics.- The Foundations of Web Analytics: Theory and Methods.- The History of Web Analytics.- Data Collection for Web Analytics.- Web Analytics Fundamentals.- Web Analytics Strategy.- Web Analytics as Competitive Intelligence.- Supplementary Methods for Augmenting Web Analytics.- Search Log Analytics.- Conclusion.- Key Terms.- Blogs for Further Reading.- References.