BDA5002 Marketing AnalyticsBahçeşehir UniversityDegree Programs ELECTRIC-ELECTRONIC ENGINEERING (ENGLISH, NON-THESIS)General Information For StudentsDiploma SupplementErasmus Policy StatementNational QualificationsBologna Commission
ELECTRIC-ELECTRONIC ENGINEERING (ENGLISH, NON-THESIS)
Master TR-NQF-HE: Level 7 QF-EHEA: Second Cycle EQF-LLL: Level 7

Course Introduction and Application Information

Course Code Course Name Semester Theoretical Practical Credit ECTS
BDA5002 Marketing Analytics Fall 3 0 3 8
This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester.

Basic information

Language of instruction: English
Type of course: Departmental Elective
Course Level:
Mode of Delivery:
Course Coordinator : Dr. Öğr. Üyesi SERKAN AYVAZ
Course Lecturer(s): Dr. Öğr. Üyesi SERKAN AYVAZ
Course Objectives: Marketing Analytics develops and utilizes quantitative marketing decision models to plan, implement, and analyze marketing strategies and tactics.
The course objectives are to help the students understand how analytical techniques and quantitative models can enhance decision-making by converting data and information to insights and decisions, help the students learn to view marketing phenomena and processes in a quantitative fashion, and expose the students to successful use of marketing analytics.

Learning Outcomes

The students who have succeeded in this course;
1-)Understand how analytical techniques and quantitative models can enhance decision-making by converting data and information to insights and decisions.

2-)Learn to view marketing phenomena and processes in a quantitative fashion

3-)Understand basic concepts and successful usage of marketing analytics.

Course Content

In this course, concepts, methods and applications related to Marketing analytics will be studied with decision modeling. An analytical approach will be presented to topics such as market segmentation, targeting, positioning, pricing and promotional planning.

Weekly Detailed Course Contents

Week Subject Related Preparation
1) Introduction to Marketing Analytics
2) Linear Regresyon Kullanan Market Response Modelleri
3) Market Response Models Using Logistic Regression
4) Segmentation & Marketing Using Cluster Analysis
5) Segmentation & Marketing Using Discriminant Analysis
6) Customer Value and Loyalty Data
7) Customer Lifetime Value and Prediction of Customer Value
8) Pricing & Sales Promotion Decisions - Deciding on the “Right” Pricing Approach
9) Pricing & Sales Promotion Decisions - Tactical Pricing
10) Retail Analysis - Market-Basket Data
11) Advertising Models
12) Project Presentations
13) Project Presentations

Sources

Course Notes / Textbooks: There is no required text book.
The PowerPoint presentations/class notes will also be available on the ItsLearning website following each class.
References: • Principles of Marketing Engineering by Gary L. Lilien et al. 2012. ISBN-978-0985764807
• Marketing Analytics: Data-Driven Techniques by Wayne Winston. 2014. ISBN-978-1118373439

Evaluation System

Semester Requirements Number of Activities Level of Contribution
Application 10 % 15
Project 1 % 25
Midterms 1 % 20
Final 1 % 40
Total % 100
PERCENTAGE OF SEMESTER WORK % 35
PERCENTAGE OF FINAL WORK % 65
Total % 100

Contribution of Learning Outcomes to Programme Outcomes

No Effect 1 Lowest 2 Low 3 Average 4 High 5 Highest
           
Program Outcomes Level of Contribution
1) Have sufficient background and an ability to apply knowledge of mathematics, science, and engineering to identify, formulate, and solve problems of electrical and electronics engineering.
2) Be able to define, formulate and solve sophisticated engineering problems by choosing and applying appropriate analysis and modeling techniques and using technical symbols and drawings of electrical and electronics engineering for design, application and communication effectively.
3) Have an ability to design or implement an existing design of a system, component, or process to meet desired needs within realistic constraints (realistic constraints may include economic, environmental, social, political, health and safety, manufacturability, and sustainability issues depending on the nature of the specific design).
4) Elektrik ve elektronik mühendisliği yapabilmek ve yeni uygulamalara uyum gösterebilmek için gerekli yenilikçi ve güncel teknikler, beceriler, bilgi teknolojileri ve modern mühendislik araçlarını geliştirmek, seçmek, uyarlamak ve kullanmak.
5) Be able to design and conduct experiments, as well as to collect, analyze, and interpret relevant data, and use this information to improve designs.
6) Be able to function individually as well as to collaborate with others in multidisciplinary teams.
7) Be able to communicate effectively in English and Turkish (if he/she is a Turkish citizen).
8) Be able to recognize the need for, and to engage in life-long learning as well as a capacity to adapt to changes in the technological environment.
9) Have a consciousness of professional and ethical responsibilities as well as workers’ health, environment and work safety.
10) Have the knowledge of business practices such as project, risk, management and an awareness of entrepreneurship, innovativeness, and sustainable development.
11) Have the broad knowledge necessary to understand the impact of electrical and electronics engineering solutions in a global, economic, environmental, legal, and societal context.