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A240A0040 Marketing Analytics, 6 cr 
Code A240A0040  Validity 01.08.2019 -
Name Marketing Analytics  Abbreviation Marketing Analy 
Credits6 cr   
TypeBasic studies  
ClassCourse   
  Grading scaleStudy modules 0-5,P/F 
  Eligibility for post-graduate studiesno
    Allowed to study several timesno
Organisation LUT School of Business and Management 

Teachers
Name
Christoph Lohrmann 
Anssi Tarkiainen 

Description by Study Guide
Note 

Location: Lappeenranta

This course is only for master's level students.

If there are more students than the course can take, then students are accepted in the following order: students from MBAN programme, students from MIMM programme, other master’s programme students, other students.

 
Year 

M.Sc. (Econ. & Bus. Adm.) 1

 
Period 

4

 
Teaching Language 

English

 
Teacher(s) in Charge 

Associate Professor, D.Sc. (Econ.) Anssi Tarkiainen,
Junior Researcher, M.Sc. (Econ.) Christoph Lohrmann

 

 

 
Aims 

The aim of the course is to offer extensive knowledge on the use of various analytical techniques in marketing. By the end of the course, students will be able to:
- give examples for the process of decision support in marketing
- use and interpret data in marketing problems
- distinguish between different forms of marketing analytics applications
- identify and use analytics tools (e.g text mining or recommendation systems) for specific problems in marketing
- perform marketing analytics tasks within RStudio
- interpret the results of the analytics methods
- create reports containing the information on the data, tools and results

 
Contents 

Core content: role of data in modern marketing, traditional methods (clustering, forecasting), machine learning-based methods in marketing (recommendation systems, text mining) and other selected contents.
Exercise classes accompany the lecture, in which the students will be introduced to selected examples for which they wil perform programming tasks together with the lecturer in class that are related to the content of each week's lecture.

 
Teaching Methods 

Lectures 21 h, computer room tutorials 21 h, course assignments involving data analysis with software 70 h. Written exam and preparation for the exam 48 h. Total workload for the student 160 h.

 
Examination in Examination schedule (Yes/No) 

Yes

 
Examination in Moodle (Yes/No) 

No

 
Examination in Exam (Yes/No) 

No

 
Assessment scale and assessment methods 

Grading 0-5. Course assignments (70% of the grade), written examination (30% of the grade).

 
Course Materials 

Leskovec, J., Rajaraman, A., Ullman J. D. (2014), Mining of Massive Datasets, 2nd edition, Oxford University Press, retrieved from: http://www.mmds.org/ />Additional material will be distributed during the course via Moodle.

 
Prerequisites 

A240A0030 Introduction to Analytics with R or A220A0010 Free Analytics Environment R course. Basic knowledge in statistics.

 
Limitation for students? (Yes, number, priorities/Leave empty) 

Yes. 100, priority to MBAN students (Master's program in Business Analytics), then students from MIMM and MSF programme, other master's programme students, other students.

 
Places for exchange-students? (Yes, number/No) 

No

 
Places for Open University Students?(Yes, number/No) 

No

 


Current and upcoming courses
Functions Name Type cr Teacher Timing
  Marketing Analytics  COURSE  Christoph Lohrmann,
Anssi Tarkiainen 
02.03.20 -17.04.20 -

Upcoming exams
Functions Name Type cr Teacher Timing
Register Marketing Analytics  EXAM  Christoph Lohrmann,
Anssi Tarkiainen 
24.04.20fri 08.30-11.30