Applying data mining and RFM model to analyze customers' values of a veterinary hospital

Jo Ting Wei, Shih Yen Lin, You Zhen Yang, Hsin-Hung Wu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

Due to fierce competition, veterinary hospitals have to maintain good relationship with their existing customers and attract new customers. In order to identify critical customers, data mining techniques particularly cluster analysis are viewed as a vital tool to facilitate customer relationship management. This study uses a veterinary hospital located in Taichung City, Taiwan as an example by analyzing its transactions data focusing solely on dogs in 2014 with 4,472 customers. Recency, frequency, and monetary are the three input variables for cluster analysis. A combination of self-organizing maps and K-means method is used for cluster analysis. The results show that seven out of twelve clusters are found to be the best or loyal customers, while three clusters are uncertain or lost customers. Two clusters with relatively higher recency values than average can be viewed as new customers. When customers are classified, this veterinary hospital can provide different marketing strategies to meet different customer needs.

Original languageEnglish
Title of host publicationProceedings - 2016 IEEE International Symposium on Computer, Consumer and Control, IS3C 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages481-484
Number of pages4
ISBN (Electronic)9781509030712
DOIs
Publication statusPublished - 2016 Aug 16
Event2016 IEEE International Symposium on Computer, Consumer and Control, IS3C 2016 - Xi'an, China
Duration: 2016 Jul 42016 Jul 6

Other

Other2016 IEEE International Symposium on Computer, Consumer and Control, IS3C 2016
CountryChina
CityXi'an
Period16-07-0416-07-06

Fingerprint

Cluster analysis
Data mining
Data Mining
Customers
Self organizing maps
Cluster Analysis
Marketing
Model
Customer Relationship Management
K-means
Taiwan
Self-organizing Map
Transactions

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Computer Networks and Communications
  • Computer Science Applications
  • Energy Engineering and Power Technology
  • Control and Systems Engineering
  • Control and Optimization

Cite this

Wei, J. T., Lin, S. Y., Yang, Y. Z., & Wu, H-H. (2016). Applying data mining and RFM model to analyze customers' values of a veterinary hospital. In Proceedings - 2016 IEEE International Symposium on Computer, Consumer and Control, IS3C 2016 (pp. 481-484). [7545236] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IS3C.2016.126
Wei, Jo Ting ; Lin, Shih Yen ; Yang, You Zhen ; Wu, Hsin-Hung. / Applying data mining and RFM model to analyze customers' values of a veterinary hospital. Proceedings - 2016 IEEE International Symposium on Computer, Consumer and Control, IS3C 2016. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 481-484
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Wei, JT, Lin, SY, Yang, YZ & Wu, H-H 2016, Applying data mining and RFM model to analyze customers' values of a veterinary hospital. in Proceedings - 2016 IEEE International Symposium on Computer, Consumer and Control, IS3C 2016., 7545236, Institute of Electrical and Electronics Engineers Inc., pp. 481-484, 2016 IEEE International Symposium on Computer, Consumer and Control, IS3C 2016, Xi'an, China, 16-07-04. https://doi.org/10.1109/IS3C.2016.126

Applying data mining and RFM model to analyze customers' values of a veterinary hospital. / Wei, Jo Ting; Lin, Shih Yen; Yang, You Zhen; Wu, Hsin-Hung.

Proceedings - 2016 IEEE International Symposium on Computer, Consumer and Control, IS3C 2016. Institute of Electrical and Electronics Engineers Inc., 2016. p. 481-484 7545236.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Wei JT, Lin SY, Yang YZ, Wu H-H. Applying data mining and RFM model to analyze customers' values of a veterinary hospital. In Proceedings - 2016 IEEE International Symposium on Computer, Consumer and Control, IS3C 2016. Institute of Electrical and Electronics Engineers Inc. 2016. p. 481-484. 7545236 https://doi.org/10.1109/IS3C.2016.126