Web Analytics

Course Description

This course is designed to help learners develop a solid understanding of the basic concepts and techniques that they will encounter as practitioners in the web analytics field. Learners in this course will expand their knowledge through games, videos, case studies, quizzes, and other engaging content. Topics of major concern that are discussed in Module 1 include a summary of web analytics concepts and important terms, along with the organizations and personnel who use web analytics. The course defines key performance indicators and discusses how they are chosen and implemented. A discussion of segmentation follows, with strategies for how to categorize website visitors. Students will also learn how to plan and assess website business strategies using web analytics.

In Module 2, learners will explore reporting and dashboards as they relate to web analytics. Students will gain an understanding of how to plan for and design dashboards and how qualitative research offers deeper business insights. In addition, students will learn how to conduct split and multivariate testing, and implement web analytics best practices.

Learning Outcomes

After completing this course, the learner should be able to:

• Define web analytics.
• Define key terms used in web analytics.
• Explain how web analytics evolved.
• Discuss how different organizations use web analytics.
• Identify who uses web analytics in an organization.
• Explain the difference between search engine optimization (SEO) and search engine marketing (SEM)
• Describe the difference between metrics and KPIs.
• Describe what segmentation is and how it can improve the usability of a website.
• Describe what dashboards are and why they are useful.
• Identify what should go into a dashboard.
• Define the difference between implicit and explicit data.
• Explain the use of dynamic content.
• Describe landing page optimization best practices.
• Articulate the importance of experimentation and testing in web analytics.
• Explain the differences between A/B and multivariate testing.
• Identify where a visitor is in the buying cycle and purchase funnel.
• Define common e-commerce metrics.
• Describe how surveys and qualitative information is used in web analytics.
• Identify when it is appropriate to include developers and page tagging.