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Dr Adam Smith

This course is compulsory on the MSc in Marketing. This course is not available as an outside option.

Completion of the MSc in Marketing pre-sessional course, MG4E7 Business Fundamentals.

This course lays down the foundations of Marketing Analytics which is an absolute essential in the age of Big Data. The broad objective of this course is to provide a fundamental understanding of marketing analytics and research methods employed by well-managed firms. The course focuses on integrating problem formulation, research design, questionnaire construction, sampling, data collection and data analysis to yield the most valuable information. The course also examines the proper use of statistical applications as well as qualitative methods, with an emphasis on the interpretation and use of results. Since analytics is the discovery and communication of meaningful patterns in data, this course will also provide students with an analytics toolkit, reinforcing basic probability and statistics while throughout emphasizing the value and pitfalls of reasoning with data. Applications will focus on connections among analytical tools, data, and business decision-making. Advanced analytical tools will be discussed in-depth in the follow-up course Marketing Analytics II.

30 hours of lectures in the MT.

Students will be expected to produce 1 case study in the MT.

• Churchill, Gilbert A. Jr., and Dawn lacobucci. Marketing Research: Methodological Foundations. 8th ed. Chicago: The Dryden Press, 2002.

• Lehmann, Donald, Market Research and Analysis, Homewood, IL: Irwin (1989)

• Burchill, G. and C. H. Brodi, Voices Into Choices: Acting on the Voice of the Customer, Oriel Incorporated, 1997

• McQuaire, E. F. (1993), Customer Visits: Building a Better Market Focus, Newbury Park, Sage.

Coursework (50%), project (40%, 2500 words) and class participation (10%) in the MT.

Group Project (40%) - a non-assessed presentation and an assessed project report 2,500 word max

Individual take home assignment (50%), to be completed in 1 week at the end of the course

Class participation (10%)