Course Objective

To equip students with an understanding of the “importance and role of marketing analytics” in modern business enterprises and how business firms can take advantage with the help of marketing analytics. Further, for students who wish to specialize in analytics, the course provides a strong foundation for the application of marketing analytics with analytical platforms.

Learning Outcomes:

At the end of the course the student should be able to

  1. Explain the importance of marketing analytics and applications.
  2. Handle the available business information/data more efficiently.
  3. Use analytical tools like R, SAS and MS excel efficiently in order to take managerial decisions more effectively

Detailed Syllabus

1. Introduction to Marketing Analytics: Definition, relevance and scope marketing analytics, recent trends in marketing analytics

2. Consumer Behaviour: Consumer Decision Making Models, Process Oriented Models of the Consumer Choice Process

3. Customer-Centric Marketing Models: Models of Customer Value, Decision Models for Customer Relationship Management (CRM), RFM Analysis

Customer Management

4. Organizational Buying Models: General Models of Organizational behaviour, Group Choice and Bargaining

5. Price: Microeconomic view of pricing

Developing demand and cost information for pricing decisions

6. Product: Decision Models for Product Design, New Product Planning, Types of New Product Situations, The adoption process for new products, Aggregate Diffusion Models: Models of First Purchase, Repeat-Purchase Models for New Products

7. Advertisement and Promotions: Message and Copy Decisions, Media Selection and Scheduling, Sales Promotion: Types and Effects Promotion Models

8. Strategy: Marketing Planning and Strategy Decisions, Managing the Marketing Mix, Designing Database Marketing Communications, Multiple Campaign Management

9. Decision Support and Implementation:

Advances in Marketing Management Support Systems, Implementation, Use and Success of Marketing Models, Marketing Engineering: Models that Connect with Practice, Industry-Specific Models, Return on Marketing Models, Models for the Financial-Performance Effects of Marketing.