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: 15.04.2020 - 27.05.2020
Teacher in charge (valid 01.08.2020-31.07.2022): Alexei Gloukhovtsev
Teacher in charge (applies in this implementation): Alexei Gloukhovtsev
Contact information for the course (valid 16.03.2020-21.12.2112):
Alexei Gloukhovtsev: firstname.lastname@aalto.fi
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:
Due to the recent Covid-19 outbreak, the course will be taught online in spring 2020. This will likely entail a combination of online lectures, webinars, and self-study material. We will likely need to adapt as the course progresses, once we find out what works well and what doesn't.
Some changes to the current timetable will likely be made to accommodate the transition to online learning. These will be updated to the course webpage as soon as I can confirm them. Please note that in case of conflicting information across platforms such as WebOodi, MyCourses, etc., information posted on this page takes precedence.
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
* QuizzesApplies in this implementation:
Even as a lecture-based course, student feedback from previous years suggests that the course material is fairly challenging. Students have found the course rewarding but noted that it does require a greater amount of work than many other marketing courses. Coupled with the additional challenges associated with migrating to a remote learning environment, please expect to be challenged and to invest a considerable amount of time into the course.
Final exam: the final exam will be adapted based on best-case practices from the upcoming exam week (period IV). Possible options include (but are not limited to) an online exam, take-home exam, or a combination of both.
Test?
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.
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
- Teacher: Alexei Gloukhovtsev
- Teacher: Axel Juslin
- Teacher: Henriikka Seittu