JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY HYDERABAD

Course Objectives:

• To provide an understanding of Fundamentals of Marketing Analytics
• To elaborate on the scope of MS Excel for conduction of Marketing Analytics,
• To highlight the importance of Management of Customer Expectations through Marketing Analytics,
• To orient on the usage of Marketing Analytics for Product Pricing and
• To impart knowledge on Market Segmentation methods and Advertising using Marketing Analytics.

Course Outcomes

Students will be able to

• Learn the Concepts of Marketing Analytics and their relevance in business,
• Use MS Excel to deal with Marketing Data at basic level,
• Appreciate Customer’s journey through Product Selection Process and Customer Lifetime Value,
• Conduct Analysis in Determining the Pricing Strategies and
• Understand the Process of Optimizing Clusters and Measure the Effectiveness of Promotion.

UNIT - I: Introduction to Marketing Analytics

Definition, Need and Scope of Marketing Analytics,

Marketing Analytics Vs Marketing Research, Levels in Marketing Analytics, Adoption and Application of Marketing Analytics, Marketing Analytics and Business Intelligence. MS Excel as a Tool for conduction of Marketing Analytics. Using MS Excel to Organize and Summarize Marketing Data: Creation of Pivot Tables and Organizing Data.

UNIT - II: Summarizing Marketing Data

Summarizing Revenue Data: Month-wise and Product-wise

Slicing & Dicing of Data: Pareto Principle, Report Filters and Slicers. Demographic Analysis: Analyzing Sales Data by Age, Gender, Income and Location, Construction of Crosstabs of Two Demographic Variables. Using GETPIVOT Function for Pulling Data. Adding Data Labels and Data Tables.

UNIT - III: Customer Analytics

Customer Journey Mapping and the Process of Mapping (How to)

Metrics for Tracking Customer Experience: Customer Feedback Metrics & Behavior Derived Customer Metrics. Customer Persona, Building a Customer Persona and its Benefits, Parts of Buyer Persona. What Customer Wants: Using Conjoint Analysis for Levels in Consumer Decision Process in Product Choices and Product Attributes. Customer Lifetime Value (CLV). Calculating Customer Lifetime Value: Creating the Basic Customer Value Template, Measuring Sensitivity Analysis with Two-Way Tables, Estimating the Chance if Customer is still Active.

UNIT - IV: Pricing Analytics

Pricing, Goals of Pricing, Price Elasticity, Estimating Linear and Power

Demand Curves, Using Excel Solver to Optimize Price, Incorporating Complementary Products, Using Solver Table to Price Multiple Products and Finding Demand Curve for All Products. Price Bundling, Bundling Prices to Extract Consumer Surplus, Mixed Bundling, Using Evolutionary Solver to Find Optimal Bundle Prices. Price Skimming.

UNIT - V: Segmentation & Promotion Analytics

Segmentation Analytics: Cluster Analysis and its

Applications, Location-wise Clustering, Using Solver to find Optimal Clusters. Using Conjoint Analysis to Segment a Market, Using Decision Trees for Segmenting the Market. Promotion Analytics: Promotions and Types of Promotions, Discounting & Types of Discounting. Measuring the Effectiveness of Advertising: The Adstock Model. Media Selection Models: Linear Media Allocation Model, Quantity Discounts, Monte Carlo Media Allocation Simulation. Pay per Click Advertising.

Suggested Readings:

• Seema Gupta & Avadhoot Jathar, Marketing Analytics, Wiley, 2021.
• Wayne L. Winston, Marketing Analytics: Data Driven Techniques with Microsoft Excel, 2014.
• Chuck Hermann, Ken Burbary, Digital Marketing Analytics, Que Publishing, 2e, 2018.
• Moustusy Maity and Pavankumar Gurazada, Marketing Analytics for Strategic Decision Making, Oxford Higher education, 2021.
• Mike Grigsby, Marketing Analytics, Kogan Page, 2015.
• Robert Kozielski, Measuring Marketing Analytics, Emerald Publishing, 2018.  39 MBA FINANCE ELECTIVE