Please note! Course description is confirmed for two academic years, which means that in general, e.g. Learning outcomes, assessment methods and key content stays unchanged. However, via course syllabus, it is possible to specify or change the course execution in each realization of the course, such as how the contact sessions are organized, assessment methods weighted or materials used.
LEARNING OUTCOMES
The student understands how data about customers and the firm s marketing activities can be collected and leveraged to improve marketing productivity and organizational performance. The student understands the statistical and mathematical principles underlying modern marketing analytics tools. The student knows how to apply various techniques in the marketing analytics toolkit in order to harness actionable insights from data concerning the firm s customers, products, marketing communications and pricing.
Credits: 6
Schedule: 20.04.2021 - 03.06.2021
Teacher in charge (valid 01.08.2020-31.07.2022): Alexei Gloukhovtsev
Teacher in charge (applies in this implementation): Robert Kreuzbauer
Contact information for the course (applies in this implementation):
CEFR level (applies in this implementation):
Language of instruction and studies (valid 01.08.2020-31.07.2022):
Teaching language: English
Languages of study attainment: English
CONTENT, ASSESSMENT AND WORKLOAD
Content
Valid 01.08.2020-31.07.2022:
The course provides an overview of the applications of marketing analytics in organizations, and covers concepts and tools such as return on marketing investment, customer lifetime value, price and advertising elasticity, marketing experiments, and applications of machine learning to marketing.
Applies in this implementation:
Update for the Spring 2021 teaching:
The course provides an overview of the applications of marketing analytics in organizations, and covers concepts and tools such as cluster analysis, conjoint analysis, Bass forecasting model, factor and regression analysis.
Assessment Methods and Criteria
Valid 01.08.2020-31.07.2022:
Independent assignments: 40 %
Exam: 60 %
Spring 2021:
Independent assignments: 40 %
Quizzes: 60 %
Workload
Valid 01.08.2020-31.07.2022:
Online course:
6 credits, 160 hours:
* Independent study (including video lectures)
* Exam (3 h)Lecture-based course:
6 credits, 160 hours:
* Lectures
* Exercises
* Individual assignments
* Exam preparation
* Exam (3 h)Spring 2021:
6 credits, 160 hours:
* Lectures
* Exercises
* Individual assignments
* Exam preparation
* Quizzes
DETAILS
Study Material
Valid 01.08.2020-31.07.2022:
Venkatesan, R., Farris, P., & Wilcox, R. T. (2014). Cutting-edge marketing analytics: real world cases and data sets for hands on learning. Pearson Education.
Recommended. (Availability)
Additional reading assigned assigned by the professor.
Applies in this implementation:
Recommended textbook for the Spring 2021 course: Gary L. Lilien, Arvind Rangaswamy, Arnaud De Bruyn, Principles of Marketing Engineering and Analytics 3rd edition, 2017, Decision Pro
Prerequisites
Valid 01.08.2020-31.07.2022:
23A00110 Markkinoinnin perusteet or equivalent (an introductory course in marketing) and 30A02000 Tilastotieteen perusteet (an introductory course in statistics)
SDG: Sustainable Development Goals
10 Reduced Inequality
16 Peace and Justice Strong Institutions