| Semester | Course Unit Code | Course Unit Title | T+P+L | Credit | Number of ECTS Credits |
| 3 | DSBE526 | MARKETING MODELLING | 3+0+0 | 3 | 7,5 |
|
Language of Instruction
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English
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Level of Course Unit
|
Master's Degree
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Department / Program
|
DATA SCIENCE
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Type of Program
|
Formal Education
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Type of Course Unit
|
Elective
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Course Delivery Method
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Face To Face
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Objectives of the Course
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Identifying the common models in marketing. Implementing advance quantitative marketing modeling techniques. Constructing marketing models for marketing analytics. Understanding demand models.
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Course Content
|
Marketing models are very important elements of real-world representation as models provide structural relations between marketing variables. Model building increases the quality of marketing decisions. Improved hardware and software enabled marketing managers to use marketing models as vital decision-making tools.
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Course Methods and Techniques
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|
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Prerequisites and co-requisities
|
None
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Course Coordinator
|
None
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Name of Lecturers
|
Dr. Fatma ÖZKÖSE https://scholar.google.com.tr/citations?user=cbxwni8AAAAJ&hl=tr f.ozkose@exeter.ac.uk; fpeker@erciyes.edu.tr
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Assistants
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None
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Work Placement(s)
|
No
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Recommended or Required Reading
|
Planned Learning Activities and Teaching Methods
Activities are given in detail in the section of "Assessment Methods and Criteria" and "Workload Calculation"
Assessment Methods and Criteria
|
In-Term Studies
|
|
Yarıyıl İçi Çalışmalarının Başarı Notunun Katkısı
|
1
|
%
30
|
|
Yarıl yılSonu Sınavı/Dönem Projesinin Başarı Notuna Katkısı
|
1
|
%
50
|
|
Ödev
|
1
|
%
10
|
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Sunum/Seminer
|
1
|
%
10
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Total
|
4
|
%
100
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ECTS Allocated Based on Student Workload
|
Activities
|
Total Work Load
|
|
Ev Ödevi
|
7
|
5
|
35
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Sınıf İçi Aktivitesi
|
15
|
1
|
15
|
|
Proje
|
2
|
20
|
40
|
|
Kişisel Çalışma
|
15
|
1
|
15
|
|
Öğretici Sunum/Açıklama
|
2
|
15
|
30
|
|
Yüz Yüze Ders
|
15
|
3
|
45
|
|
Derse Devam
|
15
|
3
|
45
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Total Work Load
| |
|
Number of ECTS Credits 7,5
225
|
Course Learning Outcomes: Upon the successful completion of this course, students will be able to:
| No | Learning Outcomes |
|
1
| Compare different models in marketing |
|
2
| Describe quantitative analysis in marketing |
|
3
| Formulate advance models in marketing |
|
4
| Stimulate different analytical models of marketing |
Weekly Detailed Course Contents
| Week | Topics | Study Materials | Materials |
| 1 |
Identifying the common models in marketing.
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| 2 |
Introduction to differential equations
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| 3 |
Understanding demand and supply models.
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|
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| 4 |
Constructing marketing models for marketing analytics.
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| 5 |
Data Structures, Estimation and Testing
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| 6 |
Parameter estimation for models related to marketing with the help of real data
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| 7 |
Using packaged computer programs for forecasting purpose
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| 8 |
Data visualization
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| 9 |
Deciding on the right marketing strategies as a result of the models proposed and the analyses.
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Contribution of Learning Outcomes to Programme Outcomes
Contribution: 1: Very Slight 2:Slight 3:Moderate 4:Significant 5:Very Significant
https://sis.agu.edu.tr/oibs/bologna/progCourseDetails.aspx?curCourse=75113&lang=en