Data mining techniques customer relationship management : a case study for Doğuş Otomotiv
dc.contributor.advisor | Yarman, Bekir Sıddık Binboğa | en_US |
dc.contributor.author | Gören, Olga Ufuk | en_US |
dc.contributor.other | Işık Üniversitesi, Fen Bilimleri Enstitüsü, Enformasyon Teknolojileri Yüksek Lisans Programı | en_US |
dc.date.accessioned | 2019-05-30T02:51:09Z | |
dc.date.available | 2019-05-30T02:51:09Z | |
dc.date.issued | 2003-10 | |
dc.department | Işık Üniversitesi, Fen Bilimleri Enstitüsü, Enformasyon Teknolojileri Yüksek Lisans Programı | en_US |
dc.description | Text in English ; Abstract: English and Turkish | en_US |
dc.description | Includes bibliographical references (leaves 174-177) | en_US |
dc.description | xvi, 182 leaves | en_US |
dc.description.abstract | Customer Relationship Managment has recently become a very important investment for many companies. The value of the customer is expressed more clearly with this new concept and it's demonstrated through its applications. The increased importance of focusing on the customer has been recognized in related academic studies in recent years. CRM has great importance in helping companies find the answers to questions such as ''What types of customers exist in which markers?'', ''What do they demand from companies?'', ''Who should be targeted as a customer?''. In fact it is a corporate strategy itself. In order to be successful, a company needs to combine the whole CRM concept with its vision. Furthermore, CRM is a strategy which aims to increase the improtance of every stakeholder of the company. With CRM, it is easy to realize the great value sone data for future of a company even though such data for the future of a company even though such data were not considered important in the past. CRM also provides ways of evaluating these data, and creating new goals out of results. The aim of this thesis is to study the CRM implementation process and show how customer data is being classified, analyzed and assessed, making use of the results of RFM analysis and demographical analysis as implemented in Doğuş Otomotiv. The importance of this thesis is that it keeps customers and their information in a data warehouse, so as to be available for effective use and analysis when needed. This analysis will help companies organize their marketing and sales activisties so as to respond to the right customer, at the rigth time, in the right way, and at the right place within their market. | en_US |
dc.description.abstract | Müşteri ilişkileri yönetmi son yıllarda şirketler için çok önemli bir yatırım aracı olmuştur. Müşteirye verilen değerin bu kavramla daha net bi şekild eifade edildiği ve uygulamalarla da gösterildiği kesindir. Ne tarz müşteriler vardır, bizden ne talep etmektedir, hedef kitlemiz kimler olmalıdır gibi soruların cevabını bulmamızda önemli görevler ifşa etmekle birlikte, CRM aslında başlı başına bir şirket stratejisidr. Bu uygulamanın başarısı için bir şirketin bütün olarak CRM kavramını vizyonuyla bağdaştırması gereklidir. Müşteri odaklılığın artan önemi son yıllarda bu konudaki akademik çalışmaları da yaygınlaştırmıştır. Ayrıca CRM kavramı bir şirketin tüm paydaşlarına değer katmayı hedeflemektedir. Bu uygulamada belki eskiden hiç değer verilmeyen ve artık olan bazı verilerin şirketin geleceğine katkı sağlayacak kadar değerli olduklarını farketmek zor olmamıştır. CRM kavramı bu verilerin yorumlanmasını ve bunlardan yeni şirket hedefleri çıkarılmaısnı sağlamıştır. Bu tezin amacı bu stratejinin CRM süreci uygulamasında işleyişini görmek ve bu süreçte müşteri verilerinin nasıl verimli bir şekilde gruplandığını analiz edildiğini ve yorumlandığını Doğus Otomotiv bünyesinde uygulanacak RFM analizi ve demografik analiz sonuçlarıyla göstermektedir. Bu tezin önemi CRM uygulamalarında müşteri ve onu hakkındaki bilgilerin bir veri ambarında saklanıp ihtiyaca göre doğru bir şekilde analiz edilmesidir. Bu analiz şirketin pazarlama ve satış aktivitelerini bulundukları pazarda doğru müşteriye doğru zamanda, doğru şekilde ve doğru yerde yapmalarına yardımcı olacaktır. | en_US |
dc.description.tableofcontents | DEFINITIONS AND BACKGROUND OF CUSTOMER, CRM & DATA MINING | en_US |
dc.description.tableofcontents | Customer | en_US |
dc.description.tableofcontents | Definition of Customer | en_US |
dc.description.tableofcontents | Types of Customer | en_US |
dc.description.tableofcontents | The Evolution and Transformation of Customers | en_US |
dc.description.tableofcontents | Definitions and History of CRM | en_US |
dc.description.tableofcontents | Definition of CRM | en_US |
dc.description.tableofcontents | History of CRM | en_US |
dc.description.tableofcontents | Data Mining | en_US |
dc.description.tableofcontents | Definition of Data Mining | en_US |
dc.description.tableofcontents | Understanding the Background of Data-Mining | en_US |
dc.description.tableofcontents | THE TRANSFORMATION OF DATA | en_US |
dc.description.tableofcontents | Definition and Architecture of Data | en_US |
dc.description.tableofcontents | Data Quality | en_US |
dc.description.tableofcontents | Importance of Data Quality | en_US |
dc.description.tableofcontents | Issues on Data Quality | en_US |
dc.description.tableofcontents | Influence of Data Quality on Business Domains | en_US |
dc.description.tableofcontents | Standardization and Process of Combining and Integrating of Data | en_US |
dc.description.tableofcontents | Metadata | en_US |
dc.description.tableofcontents | Creating a Data Mart Model, Data Separation, Transportation and Cleansing | en_US |
dc.description.tableofcontents | Creating a Data Mart Model | en_US |
dc.description.tableofcontents | Data Separation | en_US |
dc.description.tableofcontents | Data Transport and Cleansing | en_US |
dc.description.tableofcontents | Transformation of Data Mart to Data Warehouse | en_US |
dc.description.tableofcontents | Data Warehouse Definition and Characteristics | en_US |
dc.description.tableofcontents | Definition of Data Warehouse | en_US |
dc.description.tableofcontents | Characteristics ofthe Data Warehouse | en_US |
dc.description.tableofcontents | Data Warehousing: Today | en_US |
dc.description.tableofcontents | Data Warehouse Approaches | en_US |
dc.description.tableofcontents | Selecting the Right Data | en_US |
dc.description.tableofcontents | Data Warehousing and Customer Relationships | en_US |
dc.description.tableofcontents | From Data Warehousing to Data Mining | en_US |
dc.description.tableofcontents | CRM: THE CONCEPT, APPLICATION, AND METHODOLOGY | en_US |
dc.description.tableofcontents | Customer Centricity & Birth of CRM | en_US |
dc.description.tableofcontents | The Customer-Centric Marketing Model | en_US |
dc.description.tableofcontents | Customer-Centric Enterprise Management | en_US |
dc.description.tableofcontents | CRM and the New Marketing Paradigm | en_US |
dc.description.tableofcontents | Measuring and Optimizing CRM | en_US |
dc.description.tableofcontents | CRM: An Overview | en_US |
dc.description.tableofcontents | CRM: Definition | en_US |
dc.description.tableofcontents | Major Types ofCRM | en_US |
dc.description.tableofcontents | Tools to Support CRM Programs | en_US |
dc.description.tableofcontents | Integration and the Implication for CRM | en_US |
dc.description.tableofcontents | Architecture of CRM | en_US |
dc.description.tableofcontents | Analytical CRM | en_US |
dc.description.tableofcontents | Operational CRM | en_US |
dc.description.tableofcontents | Collaborative CRM | en_US |
dc.description.tableofcontents | DATA MINING AND DATA MINING TECHNIQUES | en_US |
dc.description.tableofcontents | Introduction to Data Mining | en_US |
dc.description.tableofcontents | What Is Data Mining? | en_US |
dc.description.tableofcontents | Benefits and Uses of Data Mining | en_US |
dc.description.tableofcontents | Data Mining Styles | en_US |
dc.description.tableofcontents | Hypothesis Testing | en_US |
dc.description.tableofcontents | Knowledge Discovery | en_US |
dc.description.tableofcontents | Processes of Data Mining Styles | en_US |
dc.description.tableofcontents | Applications of Data Mining | en_US |
dc.description.tableofcontents | Market Management | en_US |
dc.description.tableofcontents | Risk Management | en_US |
dc.description.tableofcontents | Attrition | en_US |
dc.description.tableofcontents | Fraud Management | en_US |
dc.description.tableofcontents | Success Factors for DM Application | en_US |
dc.description.tableofcontents | Data Mining Operations and Techniques | en_US |
dc.description.tableofcontents | Data Mining Operations | en_US |
dc.description.tableofcontents | Data Mining Techniques | en_US |
dc.description.tableofcontents | Searching for the Right Technique | en_US |
dc.description.tableofcontents | Common Characteristics of Data Mining Techniques | en_US |
dc.description.tableofcontents | CASE STUDY FOR DOGUŞ OTOMOTİV | en_US |
dc.description.tableofcontents | RFM Analysis | en_US |
dc.description.tableofcontents | Recency Implementation | en_US |
dc.description.tableofcontents | Frequency Implementation | en_US |
dc.description.tableofcontents | Monetary Implementation | en_US |
dc.description.tableofcontents | Results of RFM Analysis | en_US |
dc.description.tableofcontents | Basic Data Mining Implementation (Demographical Analysis) | en_US |
dc.description.tableofcontents | First Analysis for Volkswagen Brand | en_US |
dc.description.tableofcontents | Second Analysis for AUDI Brand | en_US |
dc.identifier.citation | Gören, O. U., (2003). Data mining techniques customer relationship management : a case study for Doğuş Otomotiv. İstanbul: Işık Üniversitesi Fen Bilimleri Fakültesi. | en_US |
dc.identifier.uri | https://hdl.handle.net/11729/1601 | |
dc.institutionauthor | Gören, Olga Ufuk | en_US |
dc.language.iso | en | en_US |
dc.publisher | Işık Üniversitesi | en_US |
dc.relation.publicationcategory | Tez | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.rights | Attribution-NonCommercial-NoDerivs 3.0 United States | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/us/ | * |
dc.subject | Customer relationship management | en_US |
dc.subject | Case study | en_US |
dc.subject | CRM recency | en_US |
dc.subject | Data mining | en_US |
dc.subject | Frequency | en_US |
dc.subject | Monetary | en_US |
dc.subject | RFM analysis | en_US |
dc.subject | CRM | en_US |
dc.subject | Doğuş Otomotiv | en_US |
dc.subject | Müşteri ilişkileri yönetimi | en_US |
dc.subject | RFM analizi | en_US |
dc.subject | Vaka analizi | en_US |
dc.subject | Veri madenciliği | en_US |
dc.subject.lcc | HF5415.125 .G67 2003 | |
dc.subject.lcsh | Marketing -- Data processing. | en_US |
dc.subject.lcsh | Data mining. | en_US |
dc.subject.lcsh | Business enterprises -- Computer networks -- Management. | en_US |
dc.title | Data mining techniques customer relationship management : a case study for Doğuş Otomotiv | en_US |
dc.title.alternative | Müşteri ilişkileri yönetimi için veri madenciliği teknikleri: Doğuş Otomotiv vaka analizi. | en_US |
dc.type | Master Thesis | en_US |
dspace.entity.type | Publication |