To read the full version of this content please select one of the options below:

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

Serhat Peker (Department of Information Systems, Middle East Technical University , Ankara, Turkey)
Altan Kocyigit (Department of Information Systems, Middle East Technical University , Ankara, Turkey)
P. Erhan Eren (Department of Information Systems, Middle East Technical University , Ankara, Turkey)

Marketing Intelligence & Planning

ISSN: 0263-4503

Article publication date: 6 May 2017

Downloads
2557

Abstract

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.

Keywords

Citation

Peker, S., Kocyigit, A. and Eren, P.E. (2017), "LRFMP model for customer segmentation in the grocery retail industry: a case study", Marketing Intelligence & Planning, Vol. 35 No. 4, pp. 544-559. https://doi.org/10.1108/MIP-11-2016-0210

Publisher

:

Emerald Publishing Limited

Copyright © 2017, Emerald Publishing Limited