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Information Journal Paper

Title

Customers Clustring Analysis Based on WRFM Model UsingNon-Supervisory Data Mining Approach (Case study of hygienic and cosmetic products)

Pages

  198-223

Abstract

 In today's competitive world where companies are faced with a huge amount of customer information due to the growth and development of information technology and the creation of various databases, the use of customer relationship management tools that can accurately and timely identify and monitor customer needs and expectations Becomes more necessary, one of the techniques that can play a key and fundamental role in this period along with this important category is Data mining of customer databases. The purpose of this study is to analyze customers Clustering based on the WRFM Model using non-supervisory Data mining methods, the researchers seek to discover the existing rules and patterns to provide more effective strategies for each group of customers, especially key customers, in order to have a better profitability and performance for the organization. Using available purposive sampling method, 64858 samples have been selected from the database of customers who have used hygienic and cosmetic products in the period of 2018-2019. The weight of WRFM attributes has been determined by surveying 3 sales experts (senior managers) of the company. Clementine and SPSS soft wares were used for data analysis. According to the research model, 4 customer categories: Specific and key, Potential golden, lost Uncertainty, New Uncertain were identified and named, and different strategies have been presented for each of these customer categories Also the result show that K-mean Clustering with six clusters and purity of 0. 744% had better performance than other Clustering methods.

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    APA: Copy

    Bashardoust, Omid, ASGHARIZADEH, EZZATOLLAH, & AFSHAR KAZEMI, MOHAMMAD ALI. (2022). Customers Clustring Analysis Based on WRFM Model UsingNon-Supervisory Data Mining Approach (Case study of hygienic and cosmetic products). MODERN RESEARCHES IN DECISION MAKING, 7(1 ), 198-223. SID. https://sid.ir/paper/1045843/en

    Vancouver: Copy

    Bashardoust Omid, ASGHARIZADEH EZZATOLLAH, AFSHAR KAZEMI MOHAMMAD ALI. Customers Clustring Analysis Based on WRFM Model UsingNon-Supervisory Data Mining Approach (Case study of hygienic and cosmetic products). MODERN RESEARCHES IN DECISION MAKING[Internet]. 2022;7(1 ):198-223. Available from: https://sid.ir/paper/1045843/en

    IEEE: Copy

    Omid Bashardoust, EZZATOLLAH ASGHARIZADEH, and MOHAMMAD ALI AFSHAR KAZEMI, “Customers Clustring Analysis Based on WRFM Model UsingNon-Supervisory Data Mining Approach (Case study of hygienic and cosmetic products),” MODERN RESEARCHES IN DECISION MAKING, vol. 7, no. 1 , pp. 198–223, 2022, [Online]. Available: https://sid.ir/paper/1045843/en

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