AKTU Digital Marketing and E-Commerce Analytics (BMBAMK04) Syllabus PDF – MBA (Business Analytics) 4th Semester

Course Objectives

1. Understand key concepts and metrics in social media and web analytics.
2. Explore digital platforms and techniques for data collection and audience insights.
3. Apply tools like Google Analytics, A/B testing, and NLP for campaign analysis.
4. Interpret web and social analytics to enhance digital marketing decisions.
5. Analyze campaign performance and implement qualitative evaluation techniques.

Unit 1 (8hrs)

Introduction to Web Analytics: Definition, Process, Key terms: Site references, Keywords and Key phrases; building block terms: Visit characterization terms, Content characterization terms, Conversion metrics; Categories: Offsite web, on site web; Web analytics platform, Web analytics evolution, Need of web analytics, Advantages & Limitations.

Unit 2 (8hrs.)

Basics of social network analysis: Nodes, ties, influencers, Structure and types of social networks, Capturing Web Data: Web logs, Beacons, JavaScript tags, Packet sniffing, Types of outcome data: E-commerce, Leads, Brand Advocacy, Competitive Data sources: Panel-based, ISP-based, Search engine data, Organizational structure and data governance in analytics, Understanding types and sizes of data in analytics, Use of cookies, page definitions, and link coding issues

Unit 3 (8hrs.)

Web Metrics & Analytics: Common metrics: Hits, Page views, visits, unique page views, Bounce, Bounce rate & its improvement, Average time on site, Real time report, traffic source report, custom campaigns, content report, Google analytics; Key Performance Indicator: Need, characteristics, perspective and uses.

Graphs and Matrices- Basic measures for individuals and networks. Random graphs & network evolution, Social Context: Affiliation & Identity Web analytics tools: A/B testing, online surveys, Web crawling and Indexing. Natural Language Processing Techniques for Micro-text Analysis

Unit 4 (8hrs.)

Facebook Analytics: Parameters, reach, engagement, post-performance, Campaign goal setting and evaluation, Instagram, Twitter, LinkedIn, YouTube analytics overview, Google AdWords and traffic classification (organic vs paid), Introduction to Google Website Optimizer, Implementation technologies and performance concerns, Limitations and privacy concerns in digital analytics

Unit 5 (8hrs.)

Qualitative Analysis: Heuristic evaluations: Conducting a heuristic evaluation, Benefits of heuristic evaluations; Site Visits: Conducting a site visit, Benefits of site visits; Surveys: Website surveys, Post-visit surveys, creating and running a survey, Benefits of surveys.

Web analytics 2.0: Web analytics 1.0 & its limitations, Introduction to WA 2.0, competitive intelligence analysis and data sources; website traffic analysis: traffic trends, site overlap and opportunities.

Course Outcomes

Suggested Readings

1. Rob Stokes, (2014), e marketing: The Essential Guide to Digital Marketing, Quirk Education.
2. Tuten & Bikramjit Rishi, Social Media Marketing, 3 rd Ed. 2020, SAGE Publishing India
3. Dave Chaffey, Fiona Ellis-Chadwick, Richard Mayer, Kevin Johnston, (2012), Internet Marketing: Strategy, Implementation and Practice, Prentice Hall.
4. Liana Evans, Social Media Marketing: Strategies for Engaging in Facebook, Twitter & Other Social Media, Que Publishing.
5. Vandana Ahuja, (Digital Marketing, 1stedition, Oxford University Press.
6. Avinash Kaushik, Web Analytics 2.0: The Art of Online Accountability and Science of Customer Centricity, Clifton B., Advanced Web Metrics with Google Analytics, Wiley Publishing, Inc.2nd ed.
7. Kaushik A., Web Analytics 2.0, The Art of Online Accountability and Science of Customer Centricity, Wiley Publishing, Inc. 1st ed.
8. Sterne J., Web Metrics: Proven methods for measuring web site success, John Wiley and Sons
9. Annmarie Hanlon, Digital Marketing, SAGE Publishing India