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Course 2019-2020 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


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. 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 using aggregate and disaggregate (panel) data. We cover:
    • Consumer choice model.
    • Advertising Response Model.
    • Linking marketing metrics to financial performance market.
  2. Customer Relationship Management (CRM) and One-to-One Marketing. We focus on the key questions driving firm strategy in many forward-thinking firms today:
    • If you are starting a new business or a new product line, how ought you to go about acquiring new customers?
    • Once you have a core base of good customers, how do you go about finding more customers like the profitable customers you have?
    • How do you strengthen the relationships with your profitable customers and build their loyalty?
    • How do you prevent your good customers from leaving you for your competitors?
  3. Social media marketing:  
    • 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 principle of customer management in terms of acquisition and retention.
  • Get the principles of digital marketing in terms of online advertising and social media.
APPLYING KNOWLEDGE AND UNDERSTANDING
At the end of the course student will be able to...
  • Analyze and interpret customer decisions using panel data.
  • Prioritize customers and select appropriate actions across different segments.
  • Define and market products in digital settings.

Teaching methods
  • Face-to-face lectures
  • Exercises (exercises, database, software etc.)
  • Case studies /Incidents (traditional, online)
  • Individual assignments
  • 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    
  • 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 assignments aimed to test the students’ ability to analyze and interpret customer decisions using panel data, prioritize customers and select appropriate actions across different customers segments.
    • Students gain experience by applying some of the methods and tools learned in the course to solving real-world business analytics problems.
    • Written exam. The written exam consists of exercises and open 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 business analytics tasks.
    • Class Participation
    NOT ATTENDING STUDENTS

    Written individual exam.


    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

     

    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 02/09/2019 14:23