PGDM Core Subject

Market Research & Consumer Insights

Course Objective


1. Course Architecture & Flow

This course is designed to transition students from "assuming" what the customer wants to "proving" it through data. The flow follows the standard research lifecycle: Problem Definition → Data Collection → Analytical Modeling → Strategic Recommendation.

2. Standard Evaluation Scheme

In line with our Triple Specialization model, this course is 70% practical. There are no theoretical simulations; students must conduct actual field research.

Component

Weightage

Description & NBA Mapping

A. Continuous Internal Evaluation (CIE)

70 Marks

Focus: The Hands (Practical Application)

1. Research Lab (10 x 4 Marks)

40

Weekly lab work including survey design, SPSS/R analysis, and FGD transcripts.

2. Mid-Term Practical Test

20

Held at Session 10. Live data cleaning and hypothesis testing challenge.

3. Viva & Participation

10

Defense of research methodology.

B. End Term Examination (ETE)

30 Marks

Focus: The Head (Strategic Synthesis)

1. Research Grant Proposal / Defense

30

Scheduled Separately. Defending a full-scale market research project.

 

3. Detailed Syllabus (20 Sessions)

Course Code: MR-201 | Term: Term 2 | Credits: 3 (30 Hours) | Prerequisite: Statistics

Course Outcomes (COs)


 

Code

Course Outcome Description

Bloom's Level

PO Mapping

CO1

Construct a research design by identifying management problems and research objectives.

Create (L6)

PO1

CO2

Apply qualitative techniques (FGDs, Depth Interviews) to explore latent consumer needs.

Apply (L3)

PO2

CO3

Execute quantitative data collection using structured instruments and sampling techniques.

Apply (L3)

PO5

CO4

Analyse primary data using statistical tools to generate actionable business insights.

Analyse (L4)

PO2

 

Session Plan

Sess

Topic

Pre-Class Reading

Lab Assignment (4 Marks)

1

Intro: The Role of MR in Business

Marketing Research (Ch 1)

Lab 0: Identifying a Brand Problem

2

The Problem: Management vs. Research Problem

Article: "The Art of Asking Why"

Assign #1: Problem Definition Doc

3

Design: Exploratory vs. Descriptive Research

Malhotra & Dash (Ch 3)

Assign #2: Choosing the Design

4

Qualitative I: Focus Group Discussions (FGD)

Video: "Moderating an FGD"

Assign #3: FGD Discussion Guide

5

Qualitative II: Depth Interviews & Projective

Article: "Latent Needs"

Lab: Conducting a Depth Interview

6

Survey I: Measurement & Scaling (Likert/Semantic)

Research Methodology (Scaling)

Assign #4: Scaled Question Bank

7

Survey II: Questionnaire Design & Flow

Video: "Avoid Survey Biases"

Assign #5: Draft Digital Survey

8

Sampling I: Probability vs. Non-Probability

Sampling Techniques

Assign #6: Sampling Frame Design

9

Sampling II: Sample Size Calculation

Statistics for Research

Lab: Calculating Confidence Intervals

10

MID-TERM PRACTICAL

Review Sessions 1-9

Live Hypothesis Building (20M)

11

Field Work: Data Collection Strategies

Article: "Data Integrity"

Assign #7: Pilot Survey Report

12

Data Prep: Cleaning, Coding, & Cross-tabs

Video: "Data Cleaning in Excel/R"

Assign #8: Cleaned Dataset Prep

13

Analysis I: Descriptive Stats & Frequencies

SPSS/R Manual

Lab: Distribution Analysis

14

Analysis II: T-Tests & ANOVA (A/B Testing)

Video: "Testing for Significance"

Assign #9: Comparing Segments

15

Analysis III: Correlation & Regression

Article: "Drivers of Satisfaction"

Lab: Identifying Key Drivers

16

Analysis IV: Factor Analysis Basics

Advanced MR Techniques

Lab: Reducing Dimensions

17

Digital MR: Sentiment Analysis & Social Listening

Video: "Analyzing Online Reviews"

Assign #10: Web Scraping Lab

18

International MR: Cross-Cultural Challenges

International Business (Ch 12)

Lab: Global Survey Adaptation

19

Visualizing Insights: Executive Reporting

Storytelling with Data

Lab: Insight Dashboard

20

Synthesis: The Final Research Pitch

Review All Lab Outcomes

Lab: Final Methodology Defense

 

4. Recommended Resources

  • Textbook: Marketing Research: An Applied Orientation by Naresh K. Malhotra and Satyabhushan Dash.

Tool: Students will use Google Forms/SurveyMonkey for collection and Excel/R/SPSS for analysis.