Prerequisite Courses:
Course Language:
İngilizce
Course Coordinator:
Course Objectives:
To understand the concept of customer-oriented marketing, to learn the customer profile and follow-up with the support of data analysis and various applications.
Course Content:
Descriptive Data Analysis to learn the basic concepts of customer segmentation using excel and Python, market basket analysis to extract meaningful buying patterns from data, and identify potential lost customers.
Course Methodology:
1: Lecture, 2: Question-Answer, 3: Discussion, 4: Simulation, 5: Case Study
Course Evaluation Methods:
A: Exam, B:Presentation, C: Homework, D: Project, E: Laboratory
Vertical Tabs
Course Learning Outcomes
| Learning Outcomes | Teaching Methods | Assessment Methods |
| Makes the definition of customer-oriented marketing. | 1,2,5 | A,C |
| List the types of customer-oriented marketing. | 1,2,5 | A,C |
| Explain the strategies of customer-oriented marketing. | 1,2,5 | A,C |
| Makes customer-oriented marketing practices. | 1,2,5 | A,C |
| Explain the importance of customer segmentation. | 1,2,5 | A,C |
| Explains descriptive data analysis. | 1,2,5 | A,C |
Course Flow
| COURSE CONTENT | ||
| Week | Topics | Study Materials |
| 1 | Customer Centric Marketing | |
| 2 | Descriptive Data Analysis: Using current and historical data to identify trends and relationships | |
| 3 | Descriptive Data Analysis: Visualizations for data analysis using Excel and Python (Hands-on) | |
| 4 | Descriptive Data Analysis: Visualizations for data analysis using Excel and Python (Hands-on) | |
| 5 | Segmentation using Excel and Python | |
| 6 | Segmentation using Excel and Python: RFM Segmentation | |
| 7 | Segmentation using Excel and Python: Creating product affinity groups | |
| 8 | Midterm | |
| 9 | Segmentation using Excel and Python: Behavioural Clustering | |
| 10 | Segmentation: Wrapping up the result and driving insights using segments | |
| 11 | Market Basket Analysis | |
| 12 | Market Basket Analysis: Implementing the algorithm in Python | |
| 13 | Customer Churn Prediction | |
| 14 | Customer Churn Prediction: Implementing the algorithm in Python | |
| 15 | Final Exam | |
Recommended Sources
| RECOMMENDED SOURCES | |
| Textbook | |
| Additional Resources | Lecture notes |
Material Sharing
| MATERIAL SHARING | |
| Documents | Photocopy shareable. |
| Assignments | Shareable |
| Exams | - |
Assessment
| ASSESSMENT | ||
| IN-TERM STUDIES | NUMBER | PERCENTAGE |
| Mid-Term | 1 | 30 |
| Project | 1 | 20 |
| Final Exam | 1 | 50 |
| Total | 100 | |
| CONTRIBUTION OF FINAL EXAMINATION TO OVERALL GRADE | 50 | |
| CONTRIBUTION OF IN-TERM STUDIES TO OVERALL GRADE | 50 | |
| Total | 100 | |
Course’s Contribution to Program
| COURSE'S CONTRIBUTION TO PROGRAMME | |||||||
| No | Program Learning Outcomes | Contribution | |||||
| 1 | 2 | 3 | 4 | 5 | |||
| 1 | E-Commerce and Management graduated, Describe contemporary e-Commerce environment | X | |||||
| 2 | E-Commerce and Management graduated, Review concepts and terminology together with processes and management decisions involved | X | |||||
| 3 | E-Commerce and Management graduated, Apply techniques of using of JavaScript, Excel and Python documents to external resources | X | |||||
| 4 | E-Commerce and Management graduated, Demonstrate an understanding of transforming and presentation languages | X | |||||
| 5 | E-Commerce and Management graduated, Assess major e-Commerce opportunities, limitations, issues and risks | X | |||||
| 6 | E-Commerce and Management graduated, Skills in project and risk management, awareness about importance of entrepreneurship, innovation and long-term development, and recognition of international standards and methodologies. | X | |||||
| 7 | E-Commerce and Management graduated, Recognition of the need for, and the ability to access information, to follow recent developments in science and technology, and to engage in life-long learning. | X | |||||
| 8 | E-Commerce and Management graduated An ability to design, implement and evaluate an information system, component, process or program that meets specified requirements. | X | |||||
ECTS
| ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE DESCRIPTION | |||
| Activities | Quantity |
Duration (Hour) |
Total
Workload (Hour) |
| Course Duration (Including the exam week: 15x Total course hours/week) | 15 | 3 | 45 |
| Hours for off-the-classroom study (Pre-study, practice, review/week) | 15 | 3 | 45 |
| Homework/Presentation | 1 | 25 | 25 |
| Midterm | 1 | 15 | 15 |
| Final | 1 | 20 | 20 |
| Total Work Load | 150 | ||
| Total Work Load / 25 (h) | 6.0 | ||
| ECTS Credit of the Course | 6 | ||
None