Brand Switching Pattern Discovery by Data Mining Techniques for the Telecommunication Industry in Australia

Md Zahidul Islam, Steven D’Alessandro, Michael Furner, Lester Johnson, David Gray, Leanne Carter


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.


decision tree; decision forest; ensemble of decision trees; data mining; brand switching; switching behaviour

Full Text:



Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Creative Commons License
ISSN: Online: 1326-2238 Hard copy: 1449-8618
This work is licensed under a Creative Commons Attribution-NonCommercial Licence. Uses the Open Journal Systems. Web design by TomW.