Customer and Marketing Analytics


Course Objective

The overarching objective of this course is to equip students with the
knowledge and skills on how to approach marketing-related problems from
a rigorous, analytical, data-based perspective.
During the course, students will get acquainted with the various
practical customer analytics questions that managers may struggle with
(e.g.; how our products or services are perceived by the market
vis-à-vis the competition; how to segment the market based on usage and
attitudes; how to determine customers’ preferences over product
attributes; how to evaluate the effects of marketing activities).
Students will learn to work with different types of customer data (e.g.;
customer survey data, transactional data, marketing expenditure data)
and obtain rigorous knowledge of the data analysis techniques (e.g.;
factor analysis, conjoint analysis, cluster analysis, multiple
regression, and logistic regression) for solving the salient customer
analytics questions. Students will excel in applying these techniques in
the statistical software package SPSS and interpreting the output of
such applications in terms of the marketing research problem at hand.

On completion of this course, students will be able to:
- Demonstrate a command of a range of research skills and the ability to
apply those skills to address a customer analytics research problem.
- Demonstrate a critical understanding of the applicability of
quantitative (multivariate) methods and techniques commonly used in the
fields of academia and business
- Effectively apply appropriate multivariate data analysis methods to
solve practical customer analytics problems.
- Communicate and collaborate effectively with an international cohort
of classmates to design and produce case solutions or other
presentations, provided in English, to both academic and professional

Course Content

The past couple of decades have witnessed an unprecedented explosion in
the quantity and quality of information available to managers. To reach
well-informed decisions, marketing research practitioners and marketing
academics have developed and implemented a wide variety of analytical
tools and models. This course will familiarize you with the state-of-art
techniques and approaches that have become fundamental to marketing
decision making in order to collect, analyze, and act on customer
information. While the course guides you through the use of quantitative
methods, it is not a statistic or math course. Through a combination of
lectures and computer exercises, the course aims that you gain the
expertise and confidence to analyze real marketing problems in rigorous
manner, and support your analysis using appropriate analytical tools.

Teaching Methods

The course uses a combination of lectures and tutorials. The lectures
focus on probing, extending and applying the course concepts and
methods. Importantly, the lectures discuss for which marketing problems
the techniques are typically used and how conclusions can be made for
marketing management. The tutorials enable students to practice the
concepts and methods discussed during the lectures.

Method of Assessment

Individual Exam (100%)
The exam will consist of two parts: (1) SPSS part (20points) and (2)
Theoretical part (80 points). Example questions will be provided during
the review week.

In order to pass the course, an overall grade of 5.50 or higher must be
obtained. Importantly, a grade of 5.00 or higher must be obtained on
each component of the exam.


- Hair, Joseph F., William, C. Black, Barry J. Babin and Rolph E.
Anderson (2014), Multivariate Data Analysis (7th edition) – Pearson New
International Edition, Harlow (UK): Pearson Education Limited.

Recommended background knowledge

Knowledge of SPSS and basic statistics

General Information

Course Code E_MKT_CMA
Credits 6 EC
Period P2
Course Level 400
Language of Tuition English
Faculty School of Business and Economics
Course Coordinator dr. A. Aydinli
Examiner dr. A. Aydinli
Teaching Staff dr. A. Aydinli

Practical Information

You need to register for this course yourself

Last-minute registration is available for this course.

Teaching Methods Study Group, Lecture, Computer lab
Target audiences

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