AKTU Marketing Analytics (BMBAMK02) Syllabus PDF – MBA (Business Analytics) 3rd Semester
Marketing Analytics BMBAMK02
All syllabus, notes, question bank & PYQ for this subject
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- Semester 3
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Syllabus — Marketing Analytics
Download PDFBMBAMK02 · 3 credits · L-T-P 3-0-0
Course Objectives
- Understand and explain the fundamental concepts and scope of Marketing Analytics.
- Apply various analytical tools to extract marketing insights from empirical data across different marketing functions.
- Interpret and examine marketing data to support effective marketing decision-making.
- Evaluate marketing data to draw meaningful inferences that support descriptive, predictive, and prescriptive analyses.
- Formulate data-driven strategies and recommendations to address key marketing challenges faced by managers.
Unit -1: Introduction to marketing Analytics (6 hrs.)
Meaning, characteristics, advantages and disadvantages of marketing analytics, Market Data Sources (Primary and Secondary). Market Sizing: Stakeholders, Applications & Approaches (Top-down and Bottom-up), PESTLE Market Analysis, Porter Five Force Analysis
Unit-2: Pricing Analytics (9 hrs.)
Pricing Policy and Objectives, Estimating Demand: Price Elasticity, Estimating Linear and Power Demand Curves, Optimize Pricing, Incorporating Complementary Products, Pricing using Subjective Demand Curve, 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, Revenue Management: Markdown Pricing and Handling Uncertainty
Unit-3: Sales Forecasting (8 hrs.)
Introduction, Simple Linear Regression & Multiple Regression model to forecast sales, Forecasting in Presence of Special Events, Modeling trend and seasonality; Ratio to moving average forecasting method, Using S curves to Forecast Sales of a New Product
Unit-4: Customer Analytics (9 hrs.)
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 Market Segmentation: The segmentation-targeting-positioning (STP) framework, Segmentation, The concept of market segmentation, managing the segmentation process, Deriving market segments and describing the segments using Cluster analysis,
Unit-5: Retailing & Advertising Analysis (8 hrs.)
Market Basket analysis: Computing two way and three-way lift, RFM Analysis, Allocating Retail Space and Sales Resources: Identifying the sales to marketing effort relationship & its modeling, optimizing sales effort.
Advertising Analysis: Measuring the Effectiveness of Advertising, Pay per Click (PPC) Online Advertising
Course Outcomes
| CO Code | Course Outcome | Bloom’s K Levels |
| CO1 | Understand the concepts, characteristics, and analytical tools related to marketing analytics. | K1, K2 |
| CO2 | Apply pricing analytics techniques to estimate demand, optimise pricing, and develop profit-maximising strategies. | K3, K4 |
| CO3 | Develop and use forecasting models to predict sales, including regression and trend-based methods. | K3, K5 |
| CO4 | Analyse customer data to estimate customer lifetime value and perform market segmentation using STP and cluster analysis. | K4, K5 |
| CO5 | Evaluate retail and advertising strategies using market basket analysis, RFM, PPC, and space/resource optimisation methods. | K5 |
Suggested Readings
- Marketing Analytics: Data-Driven Techniques with Microsoft Excel by Wayne L Winston Wiley India Pvt. Ltd.
- Marketing Analytics: Strategic Models and Metrics by Stephan Sorger, Create Space Publishing
- Marketing Engineering and Analytics by Gary Lilen, Arvind Rangaswamy,and Arnaud De Bruyn, Decision Pro, Inc.
- Marketing Metrics by Dugar Anurag, SAGE Publishing India
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