%0 Journal Article
	%A Rachid Ait daoud and  Abdellah Amine and  Belaid Bouikhalene and  Rachid Lbibb
	%D 2015
	%J International Journal of Computer and Information Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 104, 2015
	%T Customer Segmentation Model in E-commerce Using Clustering Techniques and LRFM Model: The Case of Online Stores in Morocco
	%U https://publications.waset.org/pdf/10002969
	%V 104
	%X Given the increase in the number of e-commerce sites,
the number of competitors has become very important. This means
that companies have to take appropriate decisions in order to meet the
expectations of their customers and satisfy their needs. In this paper,
we present a case study of applying LRFM (length, recency,
frequency and monetary) model and clustering techniques in the
sector of electronic commerce with a view to evaluating customers’
values of the Moroccan e-commerce websites and then developing
effective marketing strategies. To achieve these objectives, we adopt
LRFM model by applying a two-stage clustering method. In the first
stage, the self-organizing maps method is used to determine the best
number of clusters and the initial centroid. In the second stage, kmeans
method is applied to segment 730 customers into nine clusters
according to their L, R, F and M values. The results show that the
cluster 6 is the most important cluster because the average values of
L, R, F and M are higher than the overall average value. In addition,
this study has considered another variable that describes the mode of
payment used by customers to improve and strengthen clusters’
analysis. The clusters’ analysis demonstrates that the payment method is
one of the key indicators of a new index which allows to assess the
level of customers’ confidence in the company's Website.
	%P 1993 - 2003