Computer Science

Computer Science ›› 2018, Vol. 45 ›› Issue (11A): 436-438.

• Big Data & Data Mining • Previous Articles     Next Articles

Segmentation of Baidu Takeaway Customer Based on RFA Model and Cluster Analysis

BAO Zhi-qiang1, ZHAO Yuan-yuan1, ZHAO Yan1, HU Xiao-tian1, GAO Fan2   

  1. Department of Communication and Information Engineering,Xi’an University of Posts and Telecommunications,Xi’an 710121,China1
    The Ninth Research Institute of the General Department of the Fourth,Aerospace Science and Technology Group,Wuhan 430040,China2
  • Online:2019-02-26 Published:2019-02-26

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Abstract: In view of the characteristics of Baidu Take-out industry,such as large number of customers,large consumption data,high dimensions and so on,this paper proposed an improved RFM model based on perspective of customer consumption behavior,and uses the AHP algorithm to determine the weight of each variable in the model.K-Means clustering algorithm is used for customer segmentation,and the customer’s personal value for the business is computed and determined .The results of data analysis show that the customer segmentation method based on the improved RFM model canmake merchants adopt targeted strategies for customers with different values.

Key words: Baidu takeaway, Client subdivision, Improved RFM model, K-Means clustering

CLC Number: 

  • F270
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