Study Material / Marketing Analytics (April 2026)
Marketing Analytics
April 2026
3 credits
12 weeks
Prof. Swagato Chatterjee
IIT Kharagpur
Practice
Solutions
The students of this course should have already attended Marketing Management and Introduction to Business Analytics. Therefore we expect them to know basics of marketing and business analytics tools. In this course we will combine various concepts of marketing and business analytics in storytelling and problem solving. Real life marketing problems are often solved through a sequence of quantitative approaches. Identifying that sequence in the context of various marketing problems is important. This course will help the students in building the same.
Last updated in March 2026.
Week 1
  • Introduction to R programming
  • Introduction to R programming (Contd.)
  • Introduction to R programming (Contd.)
  • Introduction to R programming (Contd.)
  • Introduction to R programming (Contd.)
  • Introduction to R programming (Contd.)
Week 2
  • What Consumers Want
  • What Consumers Want (Contd.)
  • What Consumers Want (Contd.)
  • What Consumers Want (Contd.)
  • What Consumers Want (Contd.)
  • What Consumers Want (Contd.)
Week 3
  • Segmentation Targeting and Positioning
  • Segmentation Targeting and Positioning (Contd.)
  • Segmentation Targeting and Positioning (Contd.)
  • Segmentation Targeting and Positioning (Contd.)
  • Segmentation Targeting and Positioning (Contd.)
Week 4
  • Demand Forecasting and Pricing
  • Demand Forecasting and Pricing (Contd.)
  • Demand Forecasting and Pricing (Contd.)
  • Demand Forecasting and Pricing (Contd.)
Week 5
  • Pricing
  • Pricing (Contd.)
  • Pricing (Contd.)
  • Pricing (Contd.)
  • Pricing (Contd.)
  • Pricing (Contd.)
  • Pricing (Contd.)
Week 6
  • Marketing Mix Models and Advertising Models
  • Marketing Mix Models and Advertising Models (Contd.)
  • Marketing Mix Models and Advertising Models (Contd.)
  • Marketing Mix Models and Advertising Models (Contd.)
  • Marketing Mix Models and Advertising Models (Contd.)
Week 7
  • Recommendation Engine and Retail Analytics
  • Recommendation Engine and Retail Analytics (Contd.)
  • Recommendation Engine and Retail Analytics (Contd.)
  • Recommendation Engine and Retail Analytics (Contd.)
  • Recommendation Engine and Retail Analytics (Contd.)
  • Recommendation Engine and Retail Analytics (Contd.)
Week 8
  • RFM and Market Basket Analysis
  • RFM and Market Basket Analysis (Contd.)
  • RFM and Market Basket Analysis (Contd.)
  • RFM and Market Basket Analysis (Contd.)
  • RFM and Market Basket Analysis (Contd.)
Week 9
  • Customer Churn and Customer Lifetime Value
  • Customer Churn and Customer Lifetime Value (Contd.)
  • Customer Churn and Customer Lifetime Value (Contd.)
  • Customer Churn and Customer Lifetime Value (Contd.)
  • Customer Churn and Customer Lifetime Value (Contd.)
  • Customer Churn and Customer Lifetime Value (Contd.)
Week 10
Topics not available for this week.
Week 11
Topics not available for this week.
Week 12
Topics not available for this week.
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