Bilgi Paketi / Ders Kataloğu
BDA 523 Marketing Analytics
MEF Üniversitesi
Akademik Programlar
Büyük Veri Analitiği (İngilizce) (Tezsiz)
Öğrenciler için Genel Bilgi
Diploma EkiErasmus Beyanı
Büyük Veri Analitiği (İngilizce) (Tezsiz)
Yüksek Lisans Programın Süresi: 1.5 Kredi Sayısı: 90 TYYÇ: 7. Düzey QF-EHEA: 2. Düzey EQF: 7. Düzey

Ders Genel Tanıtım Bilgileri

School/Faculty/Institute Gradutate School of Science and Engineering
Course Code BDA 523
Course Title in English Marketing Analytics
Course Title in Turkish Pazarlama Analitiği
Language of Instruction EN
Type of Course Flipped Classroom
Level of Course Intermediate
Semester Spring
Contact Hours per Week
Lecture: 3 Recitation: Lab: Other:
Estimated Student Workload 179 hours per semester
Number of Credits 7.5 ECTS
Grading Mode Standard Letter Grade
Pre-requisites None
Expected Prior Knowledge Basic probability knowledge
Co-requisites None
Registration Restrictions Only Graduate Students
Overall Educational Objective To learn the application of basic analysis, modeling and measurement methods on fundamental marketing problems from different industries.
Course Description The aim of the course is to give the basic understanding of analytics problems in marketing. Statistical methods, models, and cases are employed to illustrate approaches to marketing intelligence problems, such as forecasting, price sensitivity and campaign management.
Course Description in Turkish Bu dersin amacı, farklı endüstrilerde ortaya çıkan analitik problemleri ile ilgili genel bilgi bir vermektir. İstatistik metotlar, modeller ve vaka analizleri ile tahminleme, fiyat hassasiyeti ve kampanya yönetimi gibi problemlerle pazarlama analitiği incelenektir.

Course Learning Outcomes and Competences

Upon successful completion of the course, the learner is expected to be able to:
1) Pazarlama Analitiğine Giriş
2) Pazarlama Analitiğine Giriş
3) Pazarlamada Temel Metrikler
4) Pazarlamada Temel Metrikler
5) İş Tahmini
6) İş Tahmini
7) Çoklu Ürün İlişkilendirme Analizi
8) Çoklu Ürün İlişkilendirme Analizi
9) Müşteri Kaybı ve Yaşam Boyu Değer
10) Müşteri Kaybı ve Yaşam Boyu Değer
11) Fiyatlandırma ve Gelir Yönetimi
12) Fiyatlandırma ve Gelir Yönetimi
13) Kampanya Yönetimi ve Reklamcılık
14) Kampanya Yönetimi ve Reklamcılık
15) Proje/Sunum Dönemi
16) Proje/Sunum Dönemi
Program Learning Outcomes/Course Learning Outcomes 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
1)
2)
3)
4)
5)
6)
7)
8)
9)
10)

Relation to Program Outcomes and Competences

N None S Supportive H Highly Related
     
Program Outcomes and Competences Level Assessed by
1) S Participation
2) S HW
3) H Project
4) H Project
5) H Project
6) H Project
7) S Participation
8) S Project
9) S Project
10) N
Prepared by and Date ÖZGÜR ÖZLÜK , February 2024
Course Coordinator ÖZGÜR ÖZLÜK
Semester Spring
Name of Instructor Öğr. Gör. KALENDER KARAKOC

Course Contents

Hafta Konu
1)
2)
3)
4)
5)
6)
7)
8)
9)
10)
11)
12)
13)
14)
15)
16)
Required/Recommended Readings
Teaching MethodsFlipped classroom/Exercise/Laboratory/Active learning
Homework and ProjectsStudents are required to complete a portfolio to be able to enter the final exam
Laboratory WorkStudents will apply the methods they learned using R and Excel at the laboratory hours
Computer UseStudents will apply the methods they learned using R and Excel at the laboratory hours
Other ActivitiesNone
Assessment Methods
Assessment Tools Count Weight
Uygulama 4 % 20
Küçük Sınavlar 5 % 20
Ödev 6 % 40
Projeler 1 % 20
TOTAL % 100
Course Administration
02123953600

ECTS Student Workload Estimation

Activity No/Weeks Hours Calculation
No/Weeks per Semester Preparing for the Activity Spent in the Activity Itself Completing the Activity Requirements
Ders Saati 14 3 3 84
Uygulama 4 4 16
Proje 1 40 40
Ödevler 6 4 24
Küçük Sınavlar 5 3 0.5 17.5
Total Workload 181.5
Total Workload/25 7.3
ECTS 7.5