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Article detail · 2017 · article

LRFMP model for customer segmentation in the grocery retail industry: a case study

ISSN0263-4503
YÖKSİS OpenAlex Open access · green SJR Q2 JCR Q3 Top 10%
Year2017
Citations113OpenAlex
Percentile%98.3
FWCI12.181.00 = world average
Scopus (SJR)Q2
WoS (JCR)Q3

Data source split

  • YÖKSİSYÖKSİS article record
  • YÖKSİS venueMarketing Intelligence Planning
  • Catalog match (ISSN)Marketing Intelligence and Planning
  • OpenAlexOpenAlex enrichment (abstract, citations, topics)

Abstract

OpenAlex English

Purpose The purpose of this paper is to propose a new RFM model called length, recency, frequency, monetary and periodicity (LRFMP) for classifying customers in the grocery retail industry; and to identify different customer segments in this industry based on the proposed model. Design/methodology/approach This study combines the LRFMP model and clustering for customer segmentation. Real-life data from a grocery chain operating in Turkey is used. Three cluster validation indices are used for optimizing the number of groups of customers and K-means algorithm is employed to cluster customers. First, attributes of the LRFMP model are extracted for each customer, and then based on LRFMP model features, customers are segmented into different customer groups. Finally, identified customer segments are profiled based on LRFMP characteristics and for each customer profile, unique CRM and marketing strategies are recommended. Findings The results show that there are five different customer groups and based on LRFMP characteristics, they are profiled as: “high-contribution loyal customers,” “low-contribution loyal customers,” “uncertain customers,” “high-spending lost customers” and “low-spending lost customers.” Practical implications This research may provide researchers and practitioners with a systematic guideline for effectively identifying different customer profiles based on the LRFMP model, give grocery companies useful insights about different customer profiles, and assist decision makers in developing effective customer relationships and unique marketing strategies, and further allocating resources efficiently. Originality/value This study contributes to prior literature by proposing a new RFM model, called LRFMP for the customer segmentation and providing useful insights about behaviors of different customer types in the Turkish grocery industry. It is also precious from the point of view that it is one of the first attempts in the literature which investigates the customer segmentation in the grocery retail industry.

Topics

Citations

OpenAlex cited_by_count. Not a WoS or Scopus citation count; those sources have no separate column here.

113citationsOpenAlex · cited_by_count (cache / database)

14 publications in the local catalog that cite this work (OpenAlex reference match; not the full global list).

  1. 2020 A Combined Approach for Customer Profiling in Video on Demand Services Using Clustering and Association Rule MiningCitations 31 · OpenAlex
  2. 2020 A Combined Approach for Customer Profiling in Video on Demand Services Using Clustering and Association Rule MiningCitations 31 · OpenAlex
  3. 2020 A Combined Approach for Customer Profiling in Video on Demand Services Using Clustering and Association Rule MiningCitations 31 · OpenAlex
  4. 2017 A hybrid approach for predicting customers’ individual purchase behaviorCitations 23 · OpenAlex
  5. 2017 A hybrid approach for predicting customers’ individual purchase behaviorCitations 23 · OpenAlex
  6. 2020 Customer Segmentation Based On Recency Frequency Monetary Model: A Case Study in E-RetailingCitations 22 · OpenAlex
  7. 2020 CUSTOMER SEGMENTATION AND PROFILING WITH RFM ANALYSISCitations 18 · OpenAlex
  8. 2023 Transactional data-based customer segmentation applying CRISP-DM methodology: A systematic reviewCitations 17 · OpenAlex
  9. 2022 Predicting Firms’ Performances in Customer Complaint Management Using Machine Learning TechniquesCitations 6 · OpenAlex
  10. 2020 RFM ve Uyum Analizi Kullanılarak Müşteri Segmentasyonunun BelirlenmesiCitations 3 · OpenAlex

Authors

3
  1. SERHAT PEKER 1
  2. ALTAN KOÇYİĞİT 2
  3. PEKİN ERHAN EREN ORTA DOĞU TEKNİK ÜNİVERSİTESİ 3