The Application of Data Mining to Support Customer Relationship Management at Ethiopian Airlines

Denekew, Abera Jembere (2003) The Application of Data Mining to Support Customer Relationship Management at Ethiopian Airlines. Masters thesis, Addis Ababa University.

PDF (The Application of Data Mining to Support Customer Relationship Management at Ethiopian Airlines) DENEKEW, ABERA JEMBERE.pdf - Accepted Version Restricted to Repository staff only Download (1MB) | Request a copy

Abstract

Airlines are being pushed to understand and quickly respond to the individual needs and wants of their customers due to the dynamic and highly competitive nature of the industry. Most airlines use frequent flyer incentive programs and maintain a database of their frequent flyer customers to win the loyalty of their customers, by awarding points that entitle customers to various travel benefits. Customer relationship management (CRM) is the overall process of exploiting customer- related data and information, and using it to enhance the revenue flow from an existing customer. As part of implementing CRM, airlines use their frequent flyer databases to get a better understanding of their customer types and behavior. Data mining techniques play a role here by allowing to extract important customer information from available databases. This study is aimed at assessing the application of data mining techniques to support CRM activities at Ethiopian Airlines. The subject of this case study, the Ethiopian Airlines’ frequent flyer program, has a database that contained individual flight activity and demographic information of over 35,000 program members. Having the objective of filling the gap left by a related research, which was carried out by Henok (2002), this study has used the data mining database prepared by Henok (2002). In the course of using the database to attain the objective of this research, a data preparation tasks such as driving new attributes from the existing original attributes, defining new attributes and then preparing new data tables were done. The data mining process in this research is divided into two major phases. During the first phase, since there has been an attempt to use three different data mining software, data was prepared and formatted into the appropriate format for the respective data mining software to be used. The second phase, which is model building phase, was addressed in two sub-phases, the clustering sub-phase and the classification sub-phase, the major contribution of this study. In the clustering subphase the K-means clustering algorithm was used to segment individual customer records into clusters with similar behaviors. In the classification sub-phase, J4.8 and J4.8 PART algorithms were employed to generate rules that were used to develop the predestined model that assigns new customer records into the corresponding segments. As a final output of this research, a prototype of Customer Classification System is developed. The prototype enables to classify a new customer into one of the customer clusters, generate cluster results, search for a customer and find the cluster where the customer belongs, and also provides with the description of each customer clusters. The results from this study were encouraging and confirmed the belief that applying data mining techniques could indeed support CRM activities at Ethiopian Airlines. In the future, more segmentation and classification studies by using a possible large amount of customer records with demographic information and employing other clustering and classification algorithms could yield better results

Item Type:	Thesis (Masters)
Subjects:	H Social Sciences > H Social Sciences (General) H Social Sciences > HE Transportation and Communications Z Bibliography. Library Science. Information Resources > Z665 Library Science. Information Science
Divisions:	Africana
Depositing User:	Selom Ghislain
Date Deposited:	02 Oct 2018 11:26
Last Modified:	02 Oct 2018 11:26
URI:	http://thesisbank.jhia.ac.ke/id/eprint/5861

Actions (login required)

View Item