Marketing Intelligence ("engineering") [ NELMA2407 ]
5.0 crédits ECTS
30.0 h
1q
Language |
French
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Place of the course |
Namur
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Prerequisites |
The course is designed for students with some background in quantitative methods as well as some exposure to basic marketing concepts.
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Aims |
This course considers marketing intelligence as understanding markets and consumers in order to enhance marketing managers' decision making. This course thus deals with concepts, methods, and applications of decision modelling to address current issues faced by marketing managers. It will provide students with skills to translate conceptual understanding into specific operational plans.
The contribution of this Teaching Unit to the development and
command of the skills and learning outcomes of the programme(s) can be
accessed at the end of this sheet, in the section entitled
“Programmes/courses offering this Teaching Unit”.
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Evaluation methods |
- Classe participation
- Case studies
- Written exam on theoretical concepts
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Teaching methods |
Each concept/issue covered in classroom has a software implementation (computer room) with the resolution of a case study.
The course is taught in French but the slides, case studies and reference book are in English.
- Reference book: Lilien, G.L., and Rangaswamy A (2002), Marketing Engineering, 2nd Ed., Prentice-Hall.
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Bibliography |
The course starts with a general introduction to marketing intelligence and marketing engineering as well as to marketing decision models and modelling. The topics covered are segmentation, new product diffusion forecasting, advertising budgeting, pricing and sales force allocation.
More specifically, this course aims at helping students understand by means of various examples et case studies, how analytical techniques and computer decision models can enhance decision making by converting data and information about markets to insights ("intelligence") and decisions. It also provides students with software tools that will enable them to apply the methodological approaches taught in the course to real marketing decision problems.
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Other information |
Table des matières
- Session 1 : Introduction to marketing engineering
- Session 2 : Introduction to marketing models and modelling
- Sessions 3 to 5 : Segmentation approaches and case study
- Sessions 6 & 7 : New product diffusion models and case study
- Sessions 8 & 9 : Pricing methods and case study
- Sessions 10 & 11 : Advertising budgeting and case study
- Sessions 12 & 13 : Salesforce allocation and case study
- Session 14 : Look back and course evaluation
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Cycle et année d'étude |
> Master 60 of arts in Management
> Master [60] in Management
> Master [120] in Management
> Master 120 of arts in Business engineering
> Master in Management, Teaching Focus
> Master [120] in Business engineering, professional focus
> Master [120] in Management, Professional Focus
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Faculty or entity in charge |
> EAFN
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