OUR ACADEMIC DEPARTEMENTS |
Lesson details
 | Customer Intelligence 2: Predictive Analytics | ||
2022-2023 | EnIESEG School of Management
(
IÉSEG
)
| ||
Class code : | 2223-IÉSEG-MDM1S2-MKT-MDMCI08UE | MARKETING | |
| Level | Year | Period | Language of instruction |
|---|---|---|---|
| MSc in Digital Marketing & CRM | 1 | S2 | EnEnglish |
| Academic responsibility | K.COUSSEMENT |
|---|---|
| Lecturer(s) | Dr. Kristof Coussement |
- This class exists in these courses :
- IÉSEG > MSc in Digital Marketing & CRM > MSc in Digital Marketing & CRM - Semester 2 > 2,00 ECTS
Prerequisites
The students should have followed 'Introduction to analytical Customer Relationship Management' course
Learning outcomes
At the end of the course, the student should be able to:
° spot complex problems to propose innovative solutions by transforming customer data using actionable predictive analysis.
° develop an expertise to use customer data him- or herself to improve the customer relationships through predictive modeling.
° manage successfully customer relationship.
° Breakdown complex organizational problems using the appropriate methodology (LO3.A)
° Propose creative solutions within an organization (LO3.B)
° Demonstrate an expertise on key concepts, techniques and trends in their professional field (LO7.A)
° Be a reference point for expertise-related questions and ambiguities (LO7.D)
Course description
This course introduces students to the basic principles of predictive analytics. This hands-on course introduces students how to use past information to predict future customer information.
A detailed overview of the course content is given below.
• Introduction to Predictive Analytics
• Understanding basic concepts and recognizing possible business applications
• Explaining the predictive modeling approach: Sample, Explore, Modify, Model and Assess
• Acknowledgment of the importance of data pre-processing
• Introduction to the most popular predictive modeling applications
• Understanding of the most popular evaluation metrics
Class type
Class structure
| Type of course | Numbers of hours | Comments | |
|---|---|---|---|
| Independent work | |||
| Research | 4,00 | ||
| Independent study | |||
| Estimated personal workload | 15,00 | ||
| 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
Details will be given in first lecture
| Type of control | Duration | Number | Percentage break-down |
|---|---|---|---|
| Others | |||
| Case study | 10,00 | 0 | 50,00 |
| Group Project | 10,00 | 0 | 50,00 |
| 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
