OUR ACADEMIC DEPARTEMENTS |
Lesson details
INTRODUCTION TO ANALYTICAL CUSTOMER RELATIONSHIP MANAGEMENT | |||
2022-2023 | EnIESEG School of Management
(
IÉSEG
)
| ||
Class code : | 2223-IÉSEG-MDM1S1-MKT-MM1CI09UE | MARKETING |
Level | Year | Period | Language of instruction |
---|---|---|---|
MSc in Digital Marketing & CRM | 1 | S1 | EnEnglish |
Academic responsibility | K.COUSSEMENT |
---|---|
Lecturer(s) | K.COUSSEMENT |
- This class exists in these courses :
- IÉSEG > MSc in Digital Marketing & CRM > MSc in Digital Marketing & CRM - Semester 2 > 2,00 ECTS
Prerequisites
Basic competencies in marketing
Learning outcomes
At the end of the course, the student should be able to :
° Identify the opportunities of analytical customer relationship management in order to boost their expertise in the field
° Distinguish the drivers for effective analytical customer relationship management strategy by critically proposing solutions to unexpected challenges in the field of data science
° Apply in-depth knowledge to manage successfully customer relationships
° Construct expert knowledge from cutting-edge information (LO5.B)
° Formulate strategically-appropriate solutions to complex and unfamiliar challenges in their professional field (LO7.B)
° Effectively apply in-depth specialized knowledge to take advantage of contemporary opportunities in their professional field (LO7.C)
Course description
Nowadays, there is a tremendous increase in customer information which is available for the marketer. Indeed, companies are collecting different types of information from their customers like social media information, purchasing behavior, complaining behavior, socio-demographic information, etc. Consequently, knowing how to use this new information to improve customer relationships could be of high benefit for every marketer because better decisions could be based upon that. This course tries to fulfill the gap by introducing students to the field of analytical Customer Relationship Management, and more in particular, descriptive versus predictive analytics
Class type
Class structure
Type of course | Numbers of hours | Comments | |
---|---|---|---|
Independent work | |||
Research | 4,00 | ||
Reference manual 's readings | 15,00 | ||
Independent study | |||
Group Project | 15,00 | ||
Face to face | |||
lecture | 16,00 | ||
Total student workload | 50,00 |
Teaching methods
- Case study
- Coaching
- Interactive class
- Presentation
- Project work
- Research
Assessment
Type of control | Duration | Number | Percentage break-down |
---|---|---|---|
Continuous assessment | |||
Participation | 5,00 | 1 | 20,00 |
Others | |||
Group Project | 10,00 | 1 | 40,00 |
Written Report | 10,00 | 1 | 40,00 |
TOTAL | 100,00 |
Recommended reading
- - Kristof Coussement, Koen W. De Bock, Scott A. Neslin. Advanced Database Marketing: Innovative Methodologies & Applications of Managing Customer Relationships. Gower (Ashgate) 2013. -
- - Robert C. Blattberg, Byung-Do Kim, Scott A. Neslin. Database Marketing: Analyzing and Managing Customers. Springer (2008). -
* This information is non-binding and can be subject to change