Direct marketing using fuzzy clustering of customers (Case study of a mobile phone company)
Mahmoud Dehghan Nayeri, Malihe Rostami
This study is done to consider and cluster customers of a mobile phone service provider that randomly selected from the community. The data which is collected from the customer consists of three parts. The first section includes indicators that have been selected to perform clustering analysis. The second part is the amount of customers' consumption from a variety of services and the third part include other mobile services. This research in term of purpose is survey descriptive research. After fuzzy clustering and efficiency indicators considering, the calculations showed that two clusters was appropriate. The first cluster includes the majority of women with lower incomes and less job stability and less loyalty to the company and the second cluster includes the men with higher income and job stability and loyalty. The results indicate that overall the uses of the long-distance telephone service have most income and the wireless networks have the lowest income. Paging extra services and voice mail have the most demand, call waiting and having some lines in the same time and dialogue divert have the lowest demand among the customers. The results in the mobile market and determine the appropriate strategy for each part to develop direct marketing is very useful.