Eligibility- Students of BBA/MBA
Course Duration-12 weeks
COURSE DETAILS
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. 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.
Course objective:
To understand the basic concepts of Marketing Analytics
To study various tools to have marketing insights in various marketing areas through empirical data
To interpret the marketing data for effective marketing decision making
To draw inferences from data in order to answer descriptive, predictive, and prescriptive questions relevant to marketing managers
Course Plan:
| Week 1- introduction of R programming | Overview of R , Introduction to marketing Analytics Meaning, characteristics, advantages and disadvantages of marketing analytics, Market data sources (Primary and Secondary). The new realities of marketing decision making Market Sizing: Data sources, Stakeholders, Applications & Approaches (Top-down and Bottom-up) |
| Week 2-Customer value | Customer Lifetime Value: Concept, Basic Customer Value, Measuring Customer Lifetime value, Estimating Chance that customer is still active, Using Customer Value to value a business |
| Week 3- Analytics for customer segmentation and targeting | Segmentation and Targeting: The segmentation-targeting-positioning (STP) framework, Segmentation, The concept of market segmentation, Managing the segmentation process, Deriving market segments and describing the segments -Cluster analysis, Discriminant analysis, Targeting, |
| Week 4- Demand Forecasting and Pricing | Estimating Demand Curve: Estimating Linear and Power Demand Curves, Optimize Pricing, Incorporating Complementary Products, Using Pricing subjectively to estimate Demand Curves, |
| Week 5- pricing | Pricing Multiple Products, Price Bundling & Nonlinear Pricing: Pure Bundling & Mixed Bundling, Determine Optimal Bundling Pricing, Profit Maximizing strategies using Nonlinear Pricing Strategies, Price Skimming & Sales |
| Week 6- Marketing Mix models and Advertising models | Introduction of marketing mix, Advertising Analysis: Measuring the Effectiveness of Advertising, Optimizing advertising, Pay per Click (PPC) Online Advertising |
| Week 7- Recommender system | Promotion ,increase sales ,measuring sales , |
| Week 8- Market Basket Analysis | Market Basket analysis: Computing two way and three way lift Allocating Retail Space and Sales Resources: Identifying the sales to marketing effort relationship & its modeling, optimizing sales effort |
| Week 9- Customer life time value | Customer Lifetime Value: Concept, Basic Customer Value, Measuring Customer Lifetime value, Estimating Chance that customer is still active, Using Customer Value to value a business |
| Week 10- Text mining and sentiment analytics | Regression model to forecast sales, Modeling trend and seasonality; Ratio to moving average forecasting method, Using S curves to Forecast Sales of a New Product Conjoint analysis: Conjoint analysis as a decompositional preference model, Steps in conjoint analysis, Uses of conjoint analysis. |
| Week 11- Product innovation management | How to innovate new product,objectives need of new product innovation, procedure |
| Week 12- social networking analysis for marketing | Overview ,need of social networking ,tools of social networking analysis |
Teaching Pedagogy: It will include guest lectures, videos and info graphics, power point presentations, industry visit for better learning and understanding of the students. We will also cover role plays and different kinds of in house events to give clear vision to the students about this course.
Course outcome:
- Students will develop the skill in marketing analytics
- Students will be acquainted with better understanding of real life marketing data and its analysis
- Students will develop analytical skill for effective market decision making in real life environment.