Enhancing airline customer relationship management data by inferring ties between passengers

Michael Farrugia*, Aaron Quigley

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

In the airline industry, as in many other industries, customer data is predominantly based on quantitative data. This quantitative data is collected as a by-product of the various business process involved from the booking of a flight through flight departure. By contrast, this paper explores the possibility of augmenting this quantitative data with relational data by identifying links between passengers. These links can represent different relationships such as booked-with, travelled-with, or hassame- address. Different methods and types of relationships are proposed and discussed, along with the business benefits such relational data adds to current customer information systems. Finally, we propose visual approaches to facilitate the exploration of this data by business analysts in marketing, sales and customer loyalty business units.

Original languageEnglish
Title of host publicationProceedings - 12th IEEE International Conference on Computational Science and Engineering, CSE 2009 - 2009 IEEE International Conference on Social Computing, SocialCom 2009
Pages795-800
Number of pages6
Volume4
DOIs
Publication statusPublished - 4 Dec 2009
Event2009 IEEE International Conference on Social Computing, SocialCom 2009 - Vancouver, BC, Canada
Duration: 29 Aug 200931 Aug 2009

Conference

Conference2009 IEEE International Conference on Social Computing, SocialCom 2009
Country/TerritoryCanada
CityVancouver, BC
Period29/08/0931/08/09

Fingerprint

Dive into the research topics of 'Enhancing airline customer relationship management data by inferring ties between passengers'. Together they form a unique fingerprint.

Cite this