Study Programmes 2016-2017
INFO2054-1  
Marketing Analytics
Duration :
30h Th
Number of credits :
Master in management (120 ECTS)5
Lecturer :
Michael Schyns
Language(s) of instruction :
English language
Organisation and examination :
Teaching in the second semester
Units courses prerequisite and corequisite :
Prerequisite or corequisite units are presented within each program
Learning unit contents :
No company can survive without a good management information system.  Nowadays, a company must be able to collect, analyze and handle huge volume of data in order to answer managerial questions and/or offer new top value services.  Amazon, Google, Facebook  are obvious successful stories confirming the importance of data management. 
Three keywords to define the course:


  • Management field: Decision Making
  • Approach: Data analysis (Analytics)
  • Theory (basics) and applications
In this course, the main question is:  How to transform raw "stupid" data into valuable "actionable" information?  Common applications in marketing and sales are the analysis of customer loyalty, the analysis of the market basket, the identification of prospective customers)...  Common applications in eCommerce are recommendation tools, converting clicks into customers...  Other common applications in Supply Chain Management are revenue management (e.g. airline ticketing), capacity management, diagnosis of production faults, forecasting demand, predictive modeling, advanced reporting based on ERP systems... Common applications in finance are fraud detection, credit risk analysis, risk profile, pricing...
This course covers techniques such as:


  • advanced reporting with Excel (DB functions, filters, pivot table...)
  • data analysis and reporting with advanced visual tools like "Tableau"
  • data mining tools: data preparation and market basket analysis
  • additional datamining tools (depending on time) - segmentation/clustering - decision trees - linear and logistic regression
Learning outcomes of the learning unit :
  • Gaining the knowledge and understanding of the chosen concentration field.
  • Understanding and being able of using modelization methods.
  • Capacity to research autonomously and methodically the information needed to solve a complex, transversal management problem.
  • Integrate autonomously researched information, tools, knowledge and context to build and propose original, creative and viable solutions to concrete complex management problems whether real or simulated.
  • Providing concrete solutions to a management problem, integrating modelization methods and/or a dimension of technology, innovation or production.
  • Developing a critical sense (arguing).
  • Professional capacity for written communication.
Prerequisite knowledge and skills :
Basic computer skills
Planned learning activities and teaching methods :
Theory is immediately illustrated by small examples.  Students perform exercises on computer during the lectures.  Real cases are considered (e.g. revenue management, bankruptcy detection, customer choice...)
They will acquire a basic theoretical knowledge but also learn to use professional tools like Excel for basic reporting, Tableau for  advanced visual reporting, SAS Enterprise Miner (datamining).
The students have also to complete an in-depth analysis on a provided dataset as a group project
A flipped classroom approach is used for some chapters.  The students have to prepare some topics before the lecture thanks to an online tutorial.  The lecture will focus on the difficulties encountered during the preparation.
The project and the preparations are compulsory.  A student will not be allowed to sit the exam (failure mark) while he has not completed all his/her assignments. 
Mode of delivery (face-to-face ; distance-learning) :
All lectures are given in a computer room.
Recommended or required readings :
Required: 
Slides on Lol@
Recommended:
Introduction to Data Mining, Pang-Ning Tan, Michael Steinbach, Vipin Kumar, Pearson Inertnational.
SAS e-course: "Applied Analytics Using SAS Enterprise Miner"
Assessment methods and criteria :
First session
Three parts:


  • Project - 1/3
  • Theory - 1/3
  • Practice on computer - 1/3
Second session:
Two parts:


  • Theory - 1/3
  • Practice on computer - 2/3
Remarks:
The project and the preparations are compulsory.  A student will obtain a global failure mark while he has not completed all his/her assignments (first and second sessions). The marks for the (group) project are not anymore taken into account during the second session but one question could imply a modification of the project.
Work placement(s) :
Organizational remarks :
The examinations are organized twice a year during the official sessions.  All the students sit the exam in Liège.  Due to the nature of this course, we have never accepted to organize any additional exam at a different date and/or at a different location (even for students from abroad).
Contacts :
M. Schyns, HEC-ULg, N1 M.Schyns@ulg.ac.be
S. Aerts, HEC-ULg, N1 Stephanie.Aerts@ulg.ac.be