
Web Analytics
Code
400029
Academic unit
NOVA Information Management School
Credits
7.5
Teacher in charge
Teaching language
Portuguese. If there are Erasmus students, classes will be taught in English
Objectives
Today, the Internet and all the services that are linked to it are a source of data of an extreme dimension. This information is a source of knowledge that can be a critical factor in the success of organizations. The main objective of the course is the application of quantitative methodologies to the data generated by Websites and by its integration with other sources of data. Furthermore, to explore how these analyses and knowledge can be incorporated in the decision processes.
Prerequisites
Basic Web and Digital Marketing knowledge.
Subject matter
1.2. Key questions associated with web analytics 2.0 1.3. Definition of web analytics 2.0
1.4. Change: yes we can!
2. The awesome world of clickstream analytics: metrics
2.1. Standard metrics revisited: eight critical web metrics:
- 2.1.1. Visits and visitors
- 2.1.2. Time on page and time on site
- 2.1.3. Bounce rate
- 2.1.4. Exit rate
- 2.1.5. Conversion rate
- 2.2. Web metrics demystified
- 2.3. The awesome world of clickstream analytics: practical applications
- 2.4. Metrics solutions
3. Evolution of Pricing Models and Funnel Conversion
3.1. Definition of cost models (CPC, CPM, CPA...)
3.2. Advantages and disadvantages of cost models
3.3. Practical examples and demonstration of comparative tables 3.4. Funnel: from attention to conversion
3.5. The role of landing pages
3.6. Anatomy of a landing page and importance for conversion 3.7. Analysis of the client / campaign situation
4. Web Analytics Framework
4.1. Analytics Thinking
4.2. Objectives definition
4.3. Web Analytics Framework: practical applications
5. Google Analytics
- 5.1. Introduction to Google Analytics
- 5.1.1. How Google Analytics works
- 5.1.2. Accounts, profiles and users
- 5.1.3. Navigation in Google Analytics
- 5.1.4. Metrics – the essential
- 5.1.5. The main areas of Google Analytics reports
- 5.1.6. Practical configuration of a Google Analytics account
- 5.1.7. Profiles
- 5.1.1. How Google Analytics works
- 5.2. Traffic sources
- 5.2.1. Direct, referring and Search traffic
- 5.2.2. Search Engine Optimization
- 5.2.1. Direct, referring and Search traffic
5.3. Content
- 5.3.1. Exit pages and arrival pages
- 5.3.2. Event tracking and AdSense
- 5.3.3. Site Search
- 5.3.4. A/B Experiments
- 5.4. Visits
- 5.4.1. Geographic and language information
- 5.4.2. Visitor behaviour
- 5.4.3. T echnical reports
- 5.4.4. Benchmarking
- 5.4.1. Geographic and language information
- 5.5. Advanced Segments and Filters
- 5.5.1. The importance of segmentation
- 5.5.2. Segments vs. Profiles
- 5.5.1. The importance of segmentation
- 5.6. Site objectives
- 5.6.1. Defining objectives, according to website
- 5.6.2. Funnels
- 5.6.3. Objectives reports
- 5.6.4. Dashboards configuration for different management areas
- 5.6.1. Defining objectives, according to website
- 5.7. Reports Personalization: practical applications
- 5.8. Multi-channel Funnels
- 5.8.1. Direct and Indirect Conversions
- 5.8.2. Attribution Models
- 5.8.1. Direct and Indirect Conversions
Bibliography
Kaushik, Avinash (2010) “Web Analytics 2.0: The Art of Online Accountability and Science of Customer Centricity”. Wiley publishing, inc.
Brent Dykes (2011) “Web Analytics Action Hero: Using Analysis to Gain Insight and Optimize Your Business”. Peachpit
Hunt, Ben (2011) “Convert!: Designing Web Sites to Increase Traffic and Conversion”. Wiley publishing, inc.
Advanced Web Metrics with Google Analytics (Paperback) by Brian Clifton
Teaching method
Evaluation method
Courses
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- Marketing Intelligence
- PostGraduate Information Systems and Technologies Management
- Knowledge Management and Business Intelligence
- PostGraduate in Information Management and Business Intelligence in Healthcare
- PostGraduate in Intelligence Management and Security
- PostGraduate in Marketing Intelligence
- PostGraduate in Enterprise Information Systems
- Marketing and Research and CRM
- PostGraduate in Information Analysis and Management
- PostGraduate in Digital Enterprise Management
- Information Systems and Technologies Management
- PostGraduate Risk Analysis and Management
- PostGraduate in Knowledge Management and Business Intelligence
- PostGraduate Marketing Research e CRM
- PostGraduate Digital Marketing and Analytics
- Information Analysis and Management
- PostGraduate in Information Systems Governance