30727Harness the Predictive Power of Google Analytics - New Online Course offered by UCI Extension
- Mar 11 10:01 PM
UCI is offering a new course entitled:
Harness the Predictive Power of Google Analytics
Starting date: April 7, 2014
Ending date: May 25, 2014
Google Analytics (GA) provides sophisticated traffic information about a website and it delivers a comprehensive array of business intelligence and visitor behavior insights. GA data can be used to predict future events. The goal of this course is to teach how to effectively use GA data by building predictive models.
Predictive Analytics (PA) is a leading-edge technology that is being adopted by Fortune 500 corporations and coveted by many other entities in industry and academia. As the name suggests, it seeks to predict the outcome of certain events. The applications of PA are quite wide-ranging, for example:
- Predicting fraud in credit card usage.
- Determining whether a professional athlete’s compensation should be based on predictions of future performance.
- Predicting election outcomes.
PA is based on techniques such as Decision Trees, Naïve Bayesian statistics, Linear and Logical regression, Neural Networks and TreeNet. For unsupervised learning it also uses correlation and clustering. It is becoming a major component of Marketing and Management in most MBA programs.
One of the most difficult things in PA is the acquisition of high quality input data. If the input data is inaccurate or incomplete, predictive modeling results will be equally flawed. Since GA data is always complete and accurate, this resource can be used very effectively to predict some future events or trends.
R is a scripting language for statistical data manipulation and analysis. One of the primary applications of the R package is PA. Like Google Analytics, it is freely available. Once the predictive models are constructed, GA data is fed into R which becomes the work engine of the analysis.
This course is configured for professionals who are currently working with Google Analytics. It will provide insight into how the GA data can be used for prediction of future events using R package. This course will first cover the Google Analytics, Predictive Analytics techniques, and the R Statistical package. It will also discuss the problems faced in predicting events and trends.
Next, it will focus on 4 case studies where Google Analytics data is used for predicting certain events. These case studies are visitor segmentation, landing page experiments, choosing search engine ads, and predicting visits to a website. These case studies are not theoretical but based on real-world clients which have been purposely selected because they each incorporate a different PA technique. Other case studies can be built using one of these four case studies as the foundation.
Ash Pahwa, Ph.D., is an educator, entrepreneur, and technology visionary with over 25 years of industry experience. He has founded several successful technology companies during his career. His most recent company is A+ Web Services www.AplusWebServices.com which provides internet marketing and web analytics services. His expertise includes search engine optimization, web analytics, web programming, digital image processing, database management, digital video, and data storage technologies. He developed cellAnalyst image analysis software for the Microsoft Windows/.NET platform. cellAnalyst is also available as a web service. He developed iVision, an image database management system for storage and retrieval of biomedical images based on metadata, annotation, and content. iVision was developed under a research grant from National Institute of Health. He also taught a Digital Image Processing course at University of California, Irvine in winter of 2007. He earned his Ph.D. in Computer Science from the Illinois Institute of Technology in Chicago. He is listed in Who's Who in the Frontiers of Science and Technology. His complete bio and CV is available at www.AshPahwa.com.
Raven Analytics was founded in 2002 by Rahul Dodhia, Ph.D. (Columbia University). He has provided statistical consulting services to corporations and researchers for more than ten years in fields including market research, business data mining, risk analysis, biotechnology, medical device and pharmaceutical clinical trials analysis. Most recently, he has been involved in a number of ecommerce applications, including sizing the value of Ecommerce customers and the marketing effectiveness of various offline and online media.
As a senior researcher at NASA Ames Research Center and Columbia University, he developed models for the analysis of human cognition. This work has been published in various journals, including The American Statistician and The Journal of Cognitive Neuropsychology and has been presented at conferences hosted by The Society for Mathematical Psychology and The Psychonomic Society. He has also reviewed articles and manuscripts for The Journal of the American Statistical Association, Springer-Verlag, and Human Factors. Among the many university courses he has taught are graduate-level courses in quantitative analysis at Columbia University and NASA. He is also a member of many professional organizations, including The American Statistical Association.
Dr. Ash Pahwa
A+ Web Services
5405 Alton Parkway, Suite 5A-272
Irvine, CA 92604