'Anyone in the marketing world knows how tough it can be to get noticed by the right person. Competition is fierce. The consumer market is saturated with products, brands, and businesses that take up space and the 'attention market share' from millions of customers every day.' This is especially true in the context of the Web. Whether your website is a storefront, an informational site, or a mixture of both Web Analytics constitutes a fundamental skill if you want to standout and get in touch with your target audience.
This is a technical course that empowers students to deal with online marketing and customer experience in a non data-starved environment as the web is. The student will develop practical activities where the visitor characteristics and behavior are analyzed.
The Web Analytics course is focused on providing the student with the understanding of the main methods and tools available in this context. Due to its popularity and usefulness Google Analytics will be our tool of choice. The course seeks to provide a set of methods/tools to ensure student will be able to monitor and measure the effects of a website in the business.
The course does not assume familiarity of the student with Web Analytics, but it is highly recommended that the student understands the fundamentals of e-commerce, and has at least intermediate computer literacy/skills (no programming skills needed).
Weekly - Available soon
Total - Available soon
Kaushik, A., Web Analytics 2.0. Wiley Publishing, Inc., Indianapolis, Indiana, 2010. ISBN: 978-0-470-52939-3.
Clifton, B., Advanced Web Metrics with Google Analytics. Wiley Publishing, Inc., Indianapolis, Indiana, 2008. ISBN: 978-0-470-25312-0.
Hu, Yu Jeffrey. 'Performance-based pricing models in online advertising.' Available at SSRN 501082 (2004).
Lectures and class discussions (students are expected to actively participate in the discussions) Practical classes (computer laboratory).
Team practical work (group projects).
Course project and Individual essays 50%. Minimum (Overall) Grade 8/20 5 Individual Essays (15% each – no minimum grade)
1 Group Project (25% Maximum number of group members 3 – no minimum grade) Final examination 50%. Minimum Grade 8/20
CUC1. Web Analytics Overview;
CUC2. Web traffic and business;
CUC3. Web analytics 1.0, 2.0 and 3.0;
CUC4. Standard Metrics, different metrics to measure the success your website;
CUC5. Data Sources, available methodologies to capture data and accuracy issues;
CUC6. Digital Advertising, pricing models, conversion funnel and remarketing;
CUC7. Google Analytics.