Question 1

In a competitive business environment, especially in the case of a mature market, offering high-level quality services is essential for mobile phone network operators to remain competitive in the market. In the mobile telephony market, the days of voice-only calls are long gone. Mobile phone users are free to select the way of usage that suits their needs. Some customers only use them occasionally and mainly for receiving incoming calls. Others are addicted to their devices and cannot live without them. Some treat them as electronic gadgets while others treat them as a tool for work.

As a marketer of a mobile phone network operator, you have decided to segment your customers according to their usage behaviours. Your plan is to use customer usage history to reveal the natural groupings in the customer base. Some of the fields related to phone usage are listed in Table 1.

Table 1. Customers telephony usage fields

Field name	Type	Description
Fixed_out_calls	Continuous	Monthly average number of outgoing calls to fixed telephone lines
Fixed_out_mins	Continuous	Monthly average number of minutes of outgoing calls to fixed telephone lines
Mobile_out_calls	Continuous	Monthly average number of outgoing calls to mobile telephone lines
Broadband_days	Continuous	Days with broadband traffic
Braodband_traffic	Continuous	Monthly average broadband traffic
International_out_calls	Continuous	Monthly average number of outgoing calls to international telephone lines

(a) Based on the above information, describe a potential business problem where cluster analysis can be applied. Then, develop a data mining objective that can address the problem. (6 marks)

(b) With reference to the CRISP-DM framework, discuss how you plan to carry out this data mining project. Be sure to differentiate the various stages in CRISP-DM. (30 marks)

(c) Suppose association analysis is used for this project.

(i) Describe a data mining objective that can defend the decision to use association analysis in this project. (2 marks)

(ii) Is there any data preparation needed before applying association analysis? Take one (1) field from Table 1 as an example to explain how to prepare the data. (6 marks)