Economics
Bachelor	Length of the Programme: 4	Number of Credits: 240	TR-NQF-HE: Level 6	QF-EHEA: First Cycle	EQF: Level 6

ECTS Course Information Package

School/Faculty/Institute

Faculty of Engineering

Course Code

IE 432

Course Title in English

Marketing Analytics

Course Title in Turkish

Pazarlama Analitiği

Language of Instruction

Type of Course

Ters-yüz öğrenme,Lecture

Level of Course

İleri

Semester

Spring

Contact Hours per Week

Lecture: 3

Recitation: -

Lab: -

Other: -

Estimated Student Workload

157 hours per semester

Number of Credits

6 ECTS

Grading Mode

Standard Letter Grade

Pre-requisites

MATH 227 - Probability and Statistics for Engineering I
IE 104 - Computational Methods for IE

Co-requisites

None

Expected Prior Knowledge

Basic principles of computational methods and introductory level probability and statistics

Registration Restrictions

Overall Educational Objective

To learn the basics of marketing analytics processes with hands-on applications using modern tools

Course Description

This course provides an introduction to the basic concepts of marketing analytics. Topics include market response models, customer segmentation, basket analysis and pricing models. The subjects covered throughout the course provide students with the required knowledge in the design and management of marketing analytics. The course considers both the systems observed in real-life applications and the basic analytical methods to provide insights for effective management.

Course Learning Outcomes and Competences

Upon successful completion of the course, the learner is expected to be able to:
1) Understand the basics of using programming for marketing analytics;
2) Demonstrate an understanding of the key methods for customer response prediction;
3) Understand the key methods for customer segmentation;
4) Function effectively as a member of a team;
5) Organize and deliver effective verbal, written, virtual, and graphical communications.

Program Learning Outcomes/Course Learning Outcomes	1	2	3	4	5
1) Relates economic knowledge with other social sciences and mathematics, and utilizes it in interdisciplinary analyses
2) Differentiates between the interactions of various fields of economics and synthesizes these distinctions
3) Analyzes economic phenomena by modeling microeconomic and macroeconomic theories using mathematical and statistical tools
4) Evaluate alternative theoretical approaches to solving complex economic problems and rationally apply their findings in decision-making processes
5) Analyze and compare different economic systems using quantitative techniques
6) Apply economic theoretical knowledge and models to issues related to the Turkish and global economies and design evidence-based policy recommendations
7) Analyzes economic data using econometric and statistical methods and presents the results using appropriate software programs
8) Conducts and reports on all stages of economic analysis in accordance with scientific and ethical principles
9) Uses written and spoken English (at least CEFR B2 level) in scientific knowledge sharing
10) Integrates social responsibility into economic decision-making processes
11) Develops the learning competencies necessary for further studies with a high degree of autonomy

Relation to Program Outcomes and Competences

N None	S Supportive	H Highly Related

	Program Outcomes and Competences	Level	Assessed by
1)	Relates economic knowledge with other social sciences and mathematics, and utilizes it in interdisciplinary analyses	N
2)	Differentiates between the interactions of various fields of economics and synthesizes these distinctions	N
3)	Analyzes economic phenomena by modeling microeconomic and macroeconomic theories using mathematical and statistical tools	N
4)	Evaluate alternative theoretical approaches to solving complex economic problems and rationally apply their findings in decision-making processes	N
5)	Analyze and compare different economic systems using quantitative techniques	N
6)	Apply economic theoretical knowledge and models to issues related to the Turkish and global economies and design evidence-based policy recommendations	N
7)	Analyzes economic data using econometric and statistical methods and presents the results using appropriate software programs	N
8)	Conducts and reports on all stages of economic analysis in accordance with scientific and ethical principles	H
9)	Uses written and spoken English (at least CEFR B2 level) in scientific knowledge sharing	H
10)	Integrates social responsibility into economic decision-making processes	H
11)	Develops the learning competencies necessary for further studies with a high degree of autonomy	H

Prepared by and Date	ÖZGÜR ÖZLÜK , December 2019
Course Coordinator	ÖZGÜR ÖZLÜK
Semester	Spring
Name of Instructor

Course Contents

Week	Subject
1)	Introduction to Marketing Analytics
2)	Introduction to R
3)	Introduction to R
4)	Segmentation by Clustering
5)	Segmentation by Clustering
6)	Segmentation by Clustering
7)	Predicting Customer Response: Logistic Regression
8)	Predicting Customer Response: Logistic Regression
9)	Predicting Customer Response: RFM Analysis
10)	Developing Customers: Basket Analysis
11)	Retaining Customers: Customer Lifetime Value
12)	Retaining Customers: Churn Modeling
13)	Presentations
14)	Presentations
15)	Final Exam/Project/Presentation Period
16)	Final Exam/Project/Presentation Period

Required/Recommended Readings

Marketing Analytics, W. L. Winston, 1st Edition, WILEY, 2014

Teaching Methods

Lectures using “flipped classroom” as an active learning technique and contact hours

Homework and Projects

- Problems from textbook (they will not be collected and not graded, quiz questions will be very similar or identical to the problems). - A term project that covers all topics learned in this course.

Laboratory Work

Computer Use

Other Activities

Assessment Methods

Assessment Tools	Count	Weight
Quiz(zes)	4	% 20
Project	1	% 20
Midterm(s)	1	% 25
Final Examination	1	% 35
TOTAL		% 100

Course Administration

asland@mef.edu.tr
-
Exams and quizzes: Closed book and closed notes. Homework: Problems from textbook will be given as extra course material (they will not be collected and not graded, quiz questions will be very similar or identical to the problems). Rules for attendance: YÖK regulations. Rules for late submission of assignments: N/A Missing a quiz: No make-up will be given for the missed quizzes. For certain excuses (decided by the instructor) the percentage of the missed quiz may be added to the midterm or to the final. Missing a midterm: You are expected to be present without exception and to plan any travel around these dates accordingly. Medical emergencies are of course excluded if accompanied by a doctor’s note. A note indicating that you were seen at the health center on the day of the exam is not a sufficient documentation of medically excused absence from the exam. The note must say that you were medically unable to take the exam. Provided that proper documents of excuse are presented, missed midterm by the student will be given the grade of the final exam. No make-up will be given. If you fail to take the exam on the assigned day and do not have a valid excuse, you will be given zero (0) on the exam. Employment interviews, employer events, weddings, vacations, etc. are not excused absences. Eligibility to take the final exam: YÖK regulations. Missing a final: Faculty regulations. A reminder of proper classroom behavior, code of student conduct: YÖK Regulations Statement on plagiarism: YÖK Regulations

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
Course Hours	14	1	3	1	70
Homework Assignments	14	2			28
Quiz(zes)	4	3	1		16
Midterm(s)	1	20	2		22
Final Examination	1	18	3		21
Total Workload					157
Total Workload/25					6.3
ECTS					6