Postgraduate Course: Marketing Decision Analysis (CMSE11120)
||College||College of Arts, Humanities and Social Sciences
|Credit level (Normal year taken)||SCQF Level 11 (Postgraduate)
||Availability||Available to all students
|Summary||This course aims to introduce students to the theoretical frameworks and tools used in marketing decision analysis. Students will earn an appreciation of the range of marketing metrics available to aid in the development and evaluation of marketing strategy as well as how to use basic modelling techniques to support marketing decision-making and planning. The course will also introduce students to basic computer software support for marketing decision analysis and the use of management science techniques through worked examples examining common marketing problems and decisions.
This course aims to introduce the student to the theory and practice of marketing decision analysis, build knowledge and understanding of the relevant literature on marketing decision analysis, develop a critical appreciation of modelling approaches for marketing decision analysis and illustrate the central role of marketing decision analysis and its relevance to business.
Introduction to Course
Customer Relationship Management
Student Learning Experience
Students will participate in lectures where they will be introduced to key ideas and concepts relevant to the study of marketing decision analysis, participate in discussion both inside and outside of the classroom, prepare reports for the class related to the topics introduced in lectures, engage in assessed work relevant to the study of marketing decision analysis, learn to identify material relevant to the course, assimilate knowledge through independent reading and research, and undertake critical reflection on their own learning.
Entry Requirements (not applicable to Visiting Students)
||Other requirements|| For Business School PG students only, or by special permission of the School. Please contact the course secretary.
Information for Visiting Students
|High Demand Course?
Course Delivery Information
|Academic year 2020/21, Available to all students (SV1)
|Learning and Teaching activities (Further Info)
Lecture Hours 16,
Seminar/Tutorial Hours 6,
Formative Assessment Hours 8,
Summative Assessment Hours 22,
Revision Session Hours 2,
Programme Level Learning and Teaching Hours 3,
Directed Learning and Independent Learning Hours
|Assessment (Further Info)
|Additional Information (Assessment)
||Short Reports 30%
assess learning outcomes 1, 2, 3 and 4.
Individual Essay 70%
assesses learning outcomes 1, 2, 3 and 4
||Feedback on formative assessed work will be provided within 15 working days of submission, or in time to be of use in subsequent assessments within the course, whichever is sooner. Summative marks will be returned on a published timetable, which has been made clear to students at the start of the academic year.
|No Exam Information
On completion of this course, the student will be able to:
- Define, explain and critically discuss a range of marketing metrics and performance measures used to measure the value of products, customers and distribution channels
- Explain and build simple models to support marketing decisions
- Critically discuss the uses and limitations of marketing metrics and modelling approaches
- Synthesise and critically assess the literature on the use of metrics and models to aid marketing decision making
|P.W. Farris, N.T. Bendle, P.E. Pfeifer and R.J. Reibstein (2017), Key Marketing Metrics (2nd Edition), Financial Times Prentice Hall: Harlow. ISBN: 9781292212470|
S.C. Albright and W.L Winston (2011), Management Science Modeling (International Edition of 4th Edition), South Western.
|Graduate Attributes and Skills
||By the end of this course, students will be able to:
- Critically assess the use of metrics and models to aid marketing decision making;
- Select appropriate metrics to measure the effectiveness of marketing activities;
- Identify and develop simple models to analyse marketing strategy;
- Interpret and communicate quantitative data and results;
- Collect, analyse and synthesise relevant information to explain and illustrate the role of metrics and modelling in marketing decision making.
|Course organiser||Prof Tom Archibald
Tel: (0131 6)50 4604
|Course secretary||Ms Emily Davis
Tel: (0131 6)51 7112