Facebook pixel
Info
Foto sezione
Logo Bocconi

Course 2021-2022 a.y.

30420 - MARKETING ANALYTICS

BEMACS
Department of Marketing

Course taught in English


Go to class group/s: 25

BEMACS (8 credits - I sem. - OB  |  SECS-P/08)
Course Director:
SUNGKYUN MOON

Classes: 25 (I sem.)
Instructors:
Class 25: SUNGKYUN MOON


Suggested background knowledge

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


Mission & Content Summary
MISSION

In today’s information economy companies have access to data about markets, products, customers, and much more. When deciding on issues such as pricing, advertising or targeting these data can be very valuable to companies if used correctly. This course provides you with the tools and methods that allow you to leverage data to help shape a marketing strategy. We focus on secondary data, i.e., data that originates from consumer behavior or firm decisions. Examples for secondary data are aggregate market data (e.g., car sales data), disaggregate panel data (e.g., consumer grocery shopping data) and individual level data (e.g., Clickstream data that tracks consumers behavior online). Primary data, on the other hand, are collected specially for the purpose in mind, e.g., through survey or conjoint, and are covered in the Marketing Research class.

CONTENT SUMMARY

The course has three major parts:

 

  1. Market and Consumer-level analysis. We cover:
    • Consumer choice model.
    • Marketing Mix and Market Response Model.
    • Linking marketing metrics to financial market performance.
  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
    • Vauing 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 the mechanisms of consumer data analytics.
  • Learn the marketing metrics and tools for analyzing customers and firm decisions.
  • Learn the principle of customer management in terms of acquisition and retention.
  • Get the principles of digital marketing in terms of online advertising and social media.
  • Learn the measurement of marketing performances.
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
  • Face-to-face lectures
  • Guest speaker's talks (in class or in distance)
  • Exercises (exercises, database, software etc.)
  • Case studies /Incidents (traditional, online)
  • Group assignments
DETAILS

All methods others than face-to-face lectures are used to give evidence to the application of theoretical concepts and models.


Assessment methods
  Continuous assessment Partial exams General exam
  • Written individual exam (traditional/online)
  •     x
  • Group assignment (report, exercise, presentation, project work etc.)
  • x    
  • Active class participation (virtual, attendance)
  • 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 assignments aimed to test the students’ ability to identify a marketing problem, analyze and interpret customer decisions or firm marketing decisions using panel data, and find possible solutions. Students gain experience by applying some of the methods and tools learned in the course to solving real-world marketing analytics problems.
    • Written exam. The written exam consists of open/closed answers questions aimed to assess students’ understanding of the mechanisms of consumer data analytics and principles of customer management as well as students’ ability to apply the methods learned in the course in various marketing analytics tasks.
    • Class Participation.
    NOT ATTENDING STUDENTS

    Written exam. The written exam consists of open/closed answers 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

     

    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 31/08/2021 14:26