Learning outcomes
Regarding student’s competences, the course mainly develops knowledge and reasoning, scientific and systematic approaches, personal development and to a lesser extent the other competences of the competency framework, i.e., corporate citizenship, innovation and entrepreneurship, professional development, teamwork and leadership as well as communication and interpersonal skills.
Objectives
The Customer Relationship Management course aims at providing students with an understanding of the principles, techniques and practices of CRM, that is appreciate the complexity of valuing customers, of collecting and managing relationship data, of identifying and targeting the most profitable ones, of satisficing and retaining them. It also aims at sharing the excitement and the organizational, technological and strategic challenges that services companies face when implementing CRM solutions.
Content
The topics and issues covered are
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CRM definition, principles and concepts: relationship management, trust, commitment, customer acquisition, development, satisfaction, retention, loyalty, etc.
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Data management issues: managing points of contact, collecting relationship data, organizing and storing data, reporting, managing data quality and privacy
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Technological issues: IT, business intelligence, processes
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Analytical issues: KPIs & metrics, customer segmentations, customer lifetime value, RFM analysis, churn prediction, etc.
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Operational & organizational issues: marketing, sales and service business processes integration, multi-channel strategy, softwares, campaign management
Teaching methods
The course is taught by two university professors (half of the sessions each): Prof. Dr. P. Zidda (course coordinator; full professor at UNamur, researcher in the field of retailing, loyalty management and customer relationship marketing) and Prof. Dr. Philippe Baecke (visiting professor at UNamur, professor at Vlerick Business School; researcher and consultant in CRM).
The course alternates
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Classes (learning)
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Research article discussions (discerning)
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Exercises and case studies (thinking & applying)
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Practitioners lecturing (discovering)
and emphasizes interactions between students and lecturers through discussions, examples, articles, etc.
Evaluations
The evaluation of students will be made by means of a project (30-40%) and a written examination covering all the topics discussed in the classroom (70-60%). The exam will be composed of a theoretical part (concepts and theory) and an application part (exercise and/or short case study).
Recommended readings
Course material and recommended readings
The course pack (slides) is available before the course on the web platform.
The two key reference textbooks are
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Kumar, V., Reinartz, W. (2012). Customer Relationship Management: Concept, Strategy, and Tools. 2nd Edition. Berlin: Springer-Verlag.
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Kumar, V., Petersen, A. J. (2012). Statistical Methods in Customer Relationship Management. Chechester, UK: John Wiley & Sons.
Other readings:
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Egan, J. (2012). Relationship Marketing. 4th edition. Harlow, England: Pearson Education.
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Peelen, E. (2005). Customer Relationship Management. Harlow, England: FT Prentice Hall & Pearson Education.
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As well as papers in scientific and professional journals.
Language of instruction
English
Location for course
NAMUR
Organizer
Faculté des sciences économiques, sociales et de gestion
Rue de Bruxelles, 61
5000 NAMUR
Degree of Reference
Master's Degree
| Block | Credits |
Master 60 en sciences de gestion | 1 | 5 |
Master 120 en ingénieur de gestion, à finalité spécialisée en data science | 1 | 5 |
Master 120 en sciences de gestion, à finalité spécialisée en Transformation Digitale de l’Entreprise | 1 | 5 |
Master 120 en ingénieur de gestion, à finalité spécialisée en Analytics & Digital Business | 1 | 5 |
Master 120 en sciences de gestion, à finalité spécialisée en Business Analysis & Integration | 1 | 5 |
Master 120 en sciences de gestion, à finalité didactique | 1 | 5 |
Master 120 en ingénieur de gestion, à finalité spécialisée en Analytics & Digital Business | 2 | 5 |
Master 120 en ingénieur de gestion, à finalité spécialisée en data science | 2 | 5 |
Master 120 en sciences de gestion, à finalité spécialisée en Transformation Digitale de l’Entreprise | 2 | 5 |
Master 120 en sciences de gestion, à finalité didactique | 2 | 5 |
Master 120 en sciences de gestion, à finalité spécialisée en Business Analysis & Integration | 2 | 5 |