Course 2025-2026 a.y.

30420 - MARKETING ANALYTICS

Department of Marketing

Course taught in English

Class timetable
Exam timetable
25
BEMACS (8 credits - I sem. - OB  |  SECS-P/08)
Course Director:
LIYANG ZHOU

Classes: 25 (I sem.)
Instructors:
Class 25: LIYANG ZHOU


Suggested background knowledge

Background knowledge on statistics, economics, and econometrics would be strongly recommended. In addition, data analysis and relevant coding skills would be assets.

Mission & Content Summary

MISSION

In today's information-driven economy, firms increasingly rely on data pertaining to markets, products, and consumer behavior to inform strategic decision-making in areas such as pricing, advertising, and customer targeting. When correctly used, these data serve as critical inputs for developing effective marketing strategies. This course equips students with the analytical tools and methodological frameworks necessary to leverage such data for strategic marketing applications. The emphasis is on secondary data, i.e., data generated from actual consumer behavior or firm-level decisions. Examples include aggregate market-level data (e.g., car sales statistics), disaggregate panel data (e.g., household grocery purchases), and individual-level digital traces (e.g., online clickstream data). In contrast, primary data, which are collected through surveys or conjoint studies specifically for a particular research purpose, are covered in the Marketing Research class.

CONTENT SUMMARY

Course topics:

This list is tentative - some topics may be modified or added on the syllabus.

 

  1. Market and Consumer-level analysis. We cover:
    • Consumer choice model.
    • Marketing Mix and Market Response Model.
  2. Advertising, Brand, and Customer Analytics
    • Advertising metrics
    • Brand management and brand valuation
    • Two sides of customer value: value to customers and values to firms
    • Customer acquisition and retention
    • Valuing customers and customer metrics
  3. Social Media and Marketing:  
    • Marketing stategy in online environment
    • Online marketing metrics
    • Social media and social networks

Intended Learning Outcomes (ILO)

KNOWLEDGE AND UNDERSTANDING

At the end of the course student will be able to...
  • Understand and interpret marketing and consumer data. 
  • Learn the marketing metrics and tools for analyzing customers and firm decisions.
  • Learn the principle of customer management in terms of acquisition and retention.
  • Communicate a story using data and data visualization.

APPLYING KNOWLEDGE AND UNDERSTANDING

At the end of the course student will be able to...
  • Analyze and interpret customer decisions using panel data.
  • Analyze customer profitability and brand equity.
  • Prioritize customers and select appropriate actions across different segments.
  • Analyze firm marketing decisions (e.g., advertising) and measure its performance.
  • Analyze consumers and firm decisions in online contexts.

Teaching methods

  • Lectures
  • Practical Exercises
  • Collaborative Works / Assignments

DETAILS

All methods other than face-to-face lectures are used to provide exercises and examples of the application of theoretical concepts and models.


Assessment methods

  Continuous assessment Partial exams General exam
  • Written individual exam (traditional/online)
     x
  • Collaborative Works / Assignment (report, exercise, presentation, project work etc.)
 x    
  • Peer evaluation
 x    

ATTENDING STUDENTS

With the purpose of measuring the acquisition of the above-mentioned learning outcomes, the students’ assessment is based on the following main components:

 

*Group Assignment (40%)

Designed to assess students’ ability to identify marketing problems, analyze customer or firm decisions using panel data, and propose actionable solutions. Students will apply

selected methods and tools from the course to real-world marketing analytics challenges, gaining hands-on experience in problem-solving and data interpretation.

 

*Written Exam (50%)

The exam includes a mix of open- and closed-ended questions aimed at evaluating students’ understanding of consumer data analytics, customer management principles,

and their ability to apply analytical methods to various marketing scenarios.

 

*Class Participation (10%)

Active engagement in class discussions, exercises, and case analyses contributes to the participation grade.

 


NOT ATTENDING STUDENTS

Written Exam (100%)

The exam includes a mix of open- and closed-ended questions that covers all chapters of the text book. The exam aims to assess students’ understanding of the mechanisms of consumer data analytics as well as principles of customer and marketing management.

 


Teaching materials


ATTENDING STUDENTS

  • Lecture notes
  • Hand-outs
  • Software: Stata or Python (R is also permitted, but scripts may not be provided for all tasks)

 

Recommended Reference

  • Peter C. Verhoef, Edwin Kooge, and Natasha Walk (2016), Creating Value with Big Data Analytics: Making Smarter Marketing Decisions, Routledge; ISBN-10: 9781138837973; ISBN-13: 978-1138837973

NOT ATTENDING STUDENTS

 

Textbook for non-attending students:

Peter C. Verhoef, Edwin Kooge, and Natasha Walk (2016), Creating Value with Big Data Analytics: Making Smarter Marketing Decisions, Routledge; ISBN-10: 9781138837973; ISBN-13: 978-1138837973

Last change 03/09/2025 15:16