Performance evaluation of different customer segmentation approaches based on RFM and demographics analysis

Sarvari P. A., Üstündağ A., TAKCI H.

KYBERNETES, cilt.45, sa.7, ss.1129-1157, 2016 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 45 Sayı: 7
  • Basım Tarihi: 2016
  • Doi Numarası: 10.1108/k-07-2015-0180
  • Dergi Adı: KYBERNETES
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.1129-1157
  • Anahtar Kelimeler: Customer segmentation, Performance evaluation, Association rule algorithm, Demographic variables, RFM analysis, Self-organizing map (SOM), DATA MINING TECHNIQUES, RELATIONSHIP MANAGEMENT, ALGORITHMS, DISCOVERY, PATTERNS, BEHAVIOR, COHORT, MODEL
  • Sivas Cumhuriyet Üniversitesi Adresli: Evet

Özet

Purpose - The purpose of this paper is to determine the best approach to customer segmentation and to extrapolate associated rules for this based on recency, frequency and monetary (RFM) considerations as well as demographic factors. In this study, the impacts of RFM and demographic attributes have been challenged in order to enrich factors that lend comprehension to customer segmentation. Different types of scenario were designed, performed and evaluated meticulously under uniform test conditions. The data for this study were extracted from the database of a global pizza restaurant chain in Turkey. This paper summarizes the findings of the study and also provides evidence of its empirical implications to improve the performance of customer segmentation as well as achieving extracted rule perfection via effective model factors and variations. Accordingly, marketing and service processes will work more effectively and efficiently for customers and society. The implication of this study is that it explains a clear concept for interaction between producers and consumers.