UNIQUE SERIES AKTU Syllabus
BMBMK02

Marketing & Web Analytics

L-T-P3-0-0 Session2025-26 TypeTheory
Appears in 1 semester

MBA General · Sem 3 (Specialization: Marketing (MK))

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Syllabus

5 units · 36 lecture hours
Unit1

Unit 1

4 hrs

Introduction to Marketing Analytics: Meaning, Characteristics, Advantages & Disadvantages of Marketing Analytics, Market Data Sources: Primary & Secondary Market Sizing: Stakeholders, Applications, Top-down & Bottom-up Approaches, PESTLE Analysis & Porter’s Five Forces Model for market evaluation

Unit2

Unit 2

8 hrs

Pricing Analytics: Pricing Policy & Objectives, Demand Estimation: Price Elasticity, Linear & Power Demand Curves, Optimizing Pricing and Subjective Demand Curves, Pricing Multiple Products ,Price Bundling: Pure vs. Mixed Bundling Nonlinear Pricing & Profit Maximization Strategies, Revenue Management: Markdown Pricing & Uncertainty Handling, Price Skimming and Sales Promotions

Unit3

Unit 3

7 hrs

Sales Forecasting & Customer Analytics: Linear & Multiple Regression for Forecasting, Seasonality & Special Events Modeling, Ratio to Moving Average Methods-Curve Forecasting for New Products, Customer Lifetime Value (CLV): Concept, Estimation & Business Implication, Market Segmentation: STP Framework, Clustering for Segment Derivation, Describing Market Segments

Unit4

Unit 4

8 hrs

Retailing, Advertising & Web Analytics Retail Analytics: Market Basket Analysis (2-way & 3- way lift), RFM Analysis, Retail Space & Sales Resource Allocation. Advertising Analytics: Advertising Effectiveness, PPC, Online Ads. Introduction to Web Analytics: Key Terms, Process, Offsite vs. Onsite Web Analytics, Web Analytics Tools & Metrics: Hits, Page Views, Bounce Rate, Traffic Source Google Analytics Overview KPIs: Need, Characteristics, Perspective & Usage Custom Campaigns & Content Reports

Unit5

Unit 5

9 hrs
  • Social Media, Web Analytics Tools & Qualitative Analysis: Facebook Analytics: Demographics, Engagement & Post Performance, Social Campaign Analysis: Goals & Outcomes Analytics for
  • Instagram, Twitter, LinkedIn, YouTube Organic vs. Paid Traffic, Benchmarking Web Analytics Tools: A/B Testing, Online Surveys, Web Crawling & Indexing, NLP Techniques for Micro-text Analysis Google Website Optimizer: Working & Implementation. Qualitative Techniques: Heuristic Evaluation, Site Visits, Surveys (Post-visit & Online)Web Analytics 2.0 vs. 1.0,Competitive Intelligence, Website Traffic Trends & Overlap
Course Objectives6 points
  • The objective of this course is to:
  • To introduce the concept, scope, and importance of Marketing Analytics in data-driven decision-making.
  • To equip students with pricing, sales forecasting, and customer analysis techniques using quantitative models.
  • To enable understanding and application of various retailing, advertising, and web analytics methods.
  • To familiarize students with tools and frameworks used in social media and digital analytics platforms.
  • To develop competence in interpreting qualitative insights from digital interactions through modern web tools and methods.
Course Outcomes (COs)6 outcomes

After completion of the course student will be able to:

  1. CO1Understand the meaning, characteristics, and applications of marketing analytics and market evaluation tools such as PESTLE and Porter’s Five Forces. (Understand)K2
  2. CO2Apply pricing analytics techniques including bundling, nonlinear pricing, and revenue management to solve pricing problems. (Apply),K3
  3. CO3Use regression models and forecasting techniques to estimate sales and customer lifetime value. (Analyze),K4
  4. CO4Analyze & Evaluate customer behavior through segmentation, clustering, and retail metrics like RFM and basket analysis. (Evaluate)K5
  5. CO5Evaluate the effectiveness of online advertising and interpret web analytics metrics using tools such as Google Analytics. (Evaluate)K5
  6. CO6Develop insights using social media analytics, A/B testing, and qualitative tools like heuristic evaluations and surveys. (Create)K6

Suggested Readings

  1. Marketing Analytics: Data-Driven Techniques with Microsoft Excel by Wayne L Winston, Wiley India Pvt. Ltd.
  2. Marketing Analytics: Strategic Models and Metrics by Stephan Sorger, Create Space Publishing
  3. Marketing Engineering and Analytics by Gary Lilen, Arvind Rangaswamy,and Arnaud De Bruyn, Decision Pro, Inc.
  4. Marketing Metrics by Dugar Anurag, SAGE Publishing India\
  5. Avinash Kaushik, Web Analytics 2.0: The Art of Online Accountability and Science of Customer Centricity,
  6. 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

Official AKTU syllabus

This subject is on page 16, 17 of the original AKTU PDF.

Official AKTU syllabus PDF ↗