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FUNDAMENTALS OF CUSTOMER RELATIONSHIP MANAGEMENT SYSTEMS

Course
MISY474 - FUNDAMENTALS OF CUSTOMER RELATIONSHIP MANAGEMENT SYSTEMS
Department
Management Information Systems - English - Undergraduate
Course Type
Course
Status
Required
Language
English
Credit
3
ECTS
6
T+P+L
0 + 0 + 3
Course Coordinator(s)
Dr. Inst. Tuğça KOKKOZ
Prerequisite
-
Keywords

Course Description

This course provides a comprehensive introduction to Customer Relationship Management (CRM) from an information systems perspective. Students will explore how organizations use CRM systems to manage customer interactions, analyze behavior, and support marketing, sales, and service functions. Topics include CRM architecture, customer data analytics, system implementation, and integration with enterprise platforms (e.g., ERP, e-commerce). Emphasis is placed on understanding the role of CRM in customer lifecycle management, personalization, and long-term customer value creation. Students will work with CRM software to gain hands-on experience in managing contact databases, segmenting customers, and designing service workflows. By the end of the course, students will understand how to evaluate, implement, and leverage CRM solutions to enhance business performance and customer satisfaction.

FUNDAMENTALS OF CUSTOMER RELATIONSHIP MANAGEMENT SYSTEMS

Evaluation Tools (Active Term)

Item Type Weight (%)
MIDTERM Midterm 35
Assignment Assignment 20
Final Final 45
Total 100

Course outcomes

  1. 01 To enhance awareness and increase understanding the CRM responsibility
  2. 02 To examine why do customer defect.
  3. 03 To define the customer service excellence.
  4. 04 To manage for customer satisfaction.

Course Syllabus

Week Topic
Week 1 Welcoming the students – Introducing Syllabus
Week 2 CRM Strategic Framework & Processes
Week 3 Types of CRM & Positioning
Week 4 Strategy Development (Business & Customer)
Week 5 Strategy Development (Business & Customer)
Week 6 Strategy → Execution (roadmap, capability gaps)
Week 7 Value Creation (customer value, firm value, CLV)
Week 8 Midterm Week
Week 9 Midterm Week
Week 10 Value Creation (customer value, firm value, CLV)
Week 11 Information Management (architecture, analytics)
Week 12 Information Management (architecture, analytics)
Week 13 Performance Assessment (KPI, BSC, linkage)
Week 14 Organization & Implementation (readiness, change, cases)
Week 15 General review before final exam

Reference Books & Course Materials

  1. 01 Adrian, P. (2007). Handbook of CRM: Achieving Excellence in Customer Management

Learning Outcomes

  1. L01 Define and describe the fundamental concepts and objectives of CRM in business contexts. SOLO 3
  2. L02 Students will be able to classify different types of CRM and compare their strategic positioning in organizations. SOLO 4
  3. L03 Analyze business and customer perspectives and develop effective CRM strategies that align with organizational goals SOLO 4.5
  4. L04 Design and evaluate execution roadmaps by identifying capability gaps in CRM initiatives. SOLO 5
  5. L05 Analyze and evaluate the value creation process by linking customer value, firm value, and CLV. SOLO 3.5
  6. L06 Analyze and integrate multiple channels to ensure a seamless CRM process across customer touchpoints. SOLO 4.5
  7. L07 Analyze and manage customer information processes to support effective CRM decision-making. SOLO 4
  8. L08 Evaluate CRM performance through key metrics and assess improvement opportunities in the process SOLO 4.5
  9. L09 Organize and design structures for CRM implementation and evaluate organizational readiness for change SOLO 5

Program Outcomes

  1. P01 Apply data science principles and techniques to challenges in real life situations, and effectively communicate their solutions.
  2. P02 Identify and implement data analysis methodologies based on theoretical ideas, ethical code, and in-depth knowledge of the underlying data.
  3. P03 Analyze the guiding concepts and assessment procedures for information analysis in real-life applications.
  4. P04 Design and apply relevant data analysis models to find obscure solutions to business-related problems.
  5. P05 Utilize modern computing techniques to handle real-world problems characterized by massive amounts of data, such as parallel and distributed computing and machine learning.
  6. P06 Configure and administer the software tools required to efficiently produce usable information from any size of structured and unstructured datasets.
  7. P07 Administer or manage data science tools and techniques to organize and complete projects aimed at gaining useful insight from complex data.
  8. P08 Think critically and imaginatively, conceiving real-world issues from several angles, and work well in a variety of teams to solve issues cooperatively.
  9. P09 Be able to effectively integrate data‐based solutions into the user environment and help non-technical professionals in exploring, visualizing, and using these solutions
  10. P10 Understand their obligations under professional and ethical standards in relation to matters like data ownership and citation, data security and sensitivity and the privacy implications of data analysis.

Po-Lo Matrix

LO P01 P02 P03 P04 P05 P06 P07 P08 P09 P10 Average
L01 - - - - - - - - - - -
L02 - - - - - - - - - - -
L03 - - - - - - - - - - -
L04 - - - - - - - - - - -
L05 - - - - - - - - - - -
L06 - - - - - - - - - - -
L07 - - - - - - - - - - -
L08 - - - - - - - - - - -
L09 - - - - - - - - - - -