Two-tiered Clustering Classification Experiments for Market Segmentation of EFTPOS Retailers

Australasian Journal of Information Systems

Grace W Rumantir¹  Ashishkumar Singh¹ 

[1] Monash University

关键词: Market Segmentation;    Clustering;    Decision tree;    Business Rules Extraction;    RFM Analysis;    EFTPOS.;   

DOI  :  10.3127/ajis.v19i0.1184

学科分类：计算机科学（综合）

来源: University of Canberra * Faculty of Information Sciences and Engineering

【 摘 要 】

This paper proposes the application of clustering and classification techniques on finding groupings of retailers who use the Electronic Funds Transfer at Point Of Sale (EFTPOS) facilities of a major bank in Australia. The RFM (Recency, Frequency, Monetary) analysis on each retailer is used to reduce the large data set of customer purchases through the EFTPOS network for the purpose of the retailer clustering. We then incorporate attributes of the EFTPOS transaction data in addition to the derived RFM attributes to build a decision tree to facilitate the extraction of business rules that explain the characteristics of the retailer clusters.

【 授权许可】

Unknown