Brand Switching Pattern Discovery by Data Mining Techniques for the Telecommunication Industry in Australia
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Published:2016-11-29
Issue:
Volume:20
Page:
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ISSN:1449-8618
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Container-title:Australasian Journal of Information Systems
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language:
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Short-container-title:AJIS
Author:
Islam Md Zahidul,D’Alessandro Steven,Furner Michael,Johnson Lester,Gray David,Carter Leanne
Abstract
There is more than one mobile-phone subscription per member of the Australian population. The number of complaints against the mobile-phone-service providers is also high. Therefore, the mobile service providers are facing a huge challenge in retaining their customers. There are a number of existing models to analyse customer behaviour and switching patterns. A number of switching models may also exist within a large market. These models are often not useful due to the heterogeneous nature of the market. Therefore, in this study we use data mining techniques to let the data talk to help us discover switching patterns without requiring us to use any models and domain knowledge. We use a variety of decision tree and decision forest techniques on a real mobile-phone-usage dataset in order to demonstrate the effectiveness of data mining techniques in knowledge discovery. We report many interesting patterns, and discuss them from a brand-switching and marketing perspective, through which they are found to be very sensible and interesting.
Publisher
Australian Journal of Information Systems
Subject
Information Systems and Management,Human-Computer Interaction,Business, Management and Accounting (miscellaneous),Information Systems
Cited by
10 articles.
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