PROPOSING A DATA MINING-BASED APPROACH FOR CUSTOMER MARKETS SEGMENTATION IN TELECOMMUNICATION INDUSTRY

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VELAYATI MOHAMMAD; HOSSEINZADEH LOTFI F.; SHAHRIYARI MOHAMMADREZA; RAHNAMA ROODPOSHTI F.

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Paper Information

Journal: Financial Economics Year:2018 | Volume:11 | Issue:41 Page(s): 243-266

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Title

PROPOSING A DATA MINING-BASED APPROACH FOR CUSTOMER MARKETS SEGMENTATION IN TELECOMMUNICATION INDUSTRY

Author(s)

VELAYATI MOHAMMAD | HOSSEINZADEH LOTFI F. | SHAHRIYARI MOHAMMADREZA | RAHNAMA ROODPOSHTI F. | Issue Writer Certificate

Keywords

CUSTOMER RELATIONSHIP MANAGEMENTQ2

CLUSTERINGQ2

TELECOMMUNICATIONQ1

DATA MININGQ1

EFFICIENT STRATEGYQ1

Abstract

Good decision-making and adoption of effective marketing, sale strategies and tactics are subjected to a proper understanding and identification of consumers and purchasers in organizations. Nowadays, marketing researchers are attempting to identify behavior of consumers in order to make suitable solutions for better and effective sale in order to expand market share. Manufacturer should be aware of perceptual, belonging and behavioral layers of potential purchasers in order to produce distribute and promote products regarding their decision-making structures and mechanisms. Innovators and designers of products can find expectations and satisfaction aspects of individuals by modeling and identifying behavioral pattern of consumers. A DATA MINING-based approach was proposed in this research to determine marketing policies related to each customer within ordering type investigating customers’ behavior. The proposed methodology used CLUSTERING of data extracted from database related to customer behavior. Then, this method supported two types of marketing policies considering financial class which customer belongs. In first policy, the customer consolidation or retention in its current financial class in underpinned; this policy introduces those projects or products that may be unknown or unused for customer making them loyal to organization or prolonging their orders for long term. Second policy is named motivational or promotional policy; this policy performs to encourage customers to be in higher financial classes. In this regard, some projects or products will be presented purposefully based on the analysis of behavior of customers at higher financial classes.

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APA: Copy

VELAYATI, MOHAMMAD, HOSSEINZADEH LOTFI, F., SHAHRIYARI, MOHAMMADREZA, & RAHNAMA ROODPOSHTI, F.. (2018). PROPOSING A DATA MINING-BASED APPROACH FOR CUSTOMER MARKETS SEGMENTATION IN TELECOMMUNICATION INDUSTRY. JOURNAL OF FINANCIAL ECONOMICS (FINANCIAL ECONOMICS AND DEVELOPMENT), 11(41 ), 243-266. SID. https://sid.ir/paper/229151/en

Vancouver: Copy

VELAYATI MOHAMMAD, HOSSEINZADEH LOTFI F., SHAHRIYARI MOHAMMADREZA, RAHNAMA ROODPOSHTI F.. PROPOSING A DATA MINING-BASED APPROACH FOR CUSTOMER MARKETS SEGMENTATION IN TELECOMMUNICATION INDUSTRY. JOURNAL OF FINANCIAL ECONOMICS (FINANCIAL ECONOMICS AND DEVELOPMENT)[Internet]. 2018;11(41 ):243-266. Available from: https://sid.ir/paper/229151/en

IEEE: Copy

MOHAMMAD VELAYATI, F. HOSSEINZADEH LOTFI, MOHAMMADREZA SHAHRIYARI, and F. RAHNAMA ROODPOSHTI, “PROPOSING A DATA MINING-BASED APPROACH FOR CUSTOMER MARKETS SEGMENTATION IN TELECOMMUNICATION INDUSTRY,” JOURNAL OF FINANCIAL ECONOMICS (FINANCIAL ECONOMICS AND DEVELOPMENT), vol. 11, no. 41 , pp. 243–266, 2018, [Online]. Available: https://sid.ir/paper/229151/en

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