Courses Exchange Display 2018-2019

Course Description To PDF
Course title Marketing Analytics
Course code EBC4081
ECTS credits 6,5
Assessment None
Period Start End Mon Tue Wed Thu Fri
2 29-10-2018 21-12-2018 X/E X/E
Level Advanced
Coordinator Niels Holtrop
For more information:
Language of instruction English
After this course, the student should be able to:
1. Explain and work with the basic concepts of several standard market response models used to evaluate marketing actions, and explain and work with several methods used to manage a customer base
2. Explain and understand existing marketing models and methods published in the academic literature
3. Evaluate existing marketing models and methods published in the academic literature
4. Understand the difference between several data types, and specify a suitable market response or customer based model depending on the data type
5. Estimate a market response or customer based model using empirical data and statistical software
6. Interpret an estimated a market response or customer based model - in the context of the data underlying the model - , and draw managerial implications
7. Report in writing about the data analysis process and its managerial implications
Marketing analytics is defined as “a technology-enabled and model-supported approach to harness customer and market data to enhance marketing decision making” (Lilien 2011). In this course students will be exposed to a variety of ways in which the data richness available to modern firms can be used to guide the decision making process of managers, and improve the accountability and impact of marketing.
Consistent with the definition of marketing analytics, two perspectives will be taken in this course: The market and the customer perspective. From the market perspective, we will investigate how firms can gain model-based insights in the effectiveness of broad market actions such as (online and offline) advertising and price promotions in order to improve future decisions. From the customer perspective, we will focus on marketing actions aimed directly to specific customers with the aim to acquire, retain or develop these customers. Students will be exposed to the existing academic literature on these topics to bring their knowledge up-to-date.
Using real-life datasets students will gain hands-on experience with several methods in each of the two subfields. An important focus of the course is understanding the data analysis process and its managerial implications, and communicating the outcomes thereof. In this way data driven insights has an impact on the decision-making process within firms.
The literature will consist of a bundle of academic papers and book chapters. A detailed literature list will be available on the Eleum site of the course
All students who are admitted to the Master of Science in International Business can follow this course. In the assignments, students will have to use regression analysis and SPSS. So a background in regression analysis and SPSS is necessary.
Teaching methods PBL / Presentation / Lecture / Assignment / Groupwork
Assessment methods Attendance / Participation / Written Exam / Assignment
Evaluation in previous academic year For the complete evaluation of this course please click "here"
This course belongs to the following programmes / specialisations
Master Business Research IB Electives
Master Business Research - Operations Research IB Electives
Master Human Decision Science Electives
Master International Business - Accountancy Electives
Master International Business - Controlling Electives
Master International Business - Entrepreneurship and SME Management Electives
Master International Business - Organisation: Management, Change and Consultancy Electives
Master International Business - Strategic Corporate Finance Electives
Master International Business - Strategic Marketing Compulsory Courses
Master International Business - Strategy and Innovation Electives
Master International Business - Sustainable Finance Electives
SBE Exchange Master Master Exchange Courses
SBE Non Degree Courses Master Courses