Abstract

Customer segmentation is the process of grouping customers based on similar characteristics such as behavior, shopping habits…so that businesses can do marketing to each customer group effectively and appropriately. Customer segmentation helps businesses determine different strategies and different marketing approaches to different groups. Customer segmentation helps marketers better understand customers as well as provide goals, strategies and marketing methods for different target groups. This paper aims to examine the customer segmentation using clustering method in statistics and unsupervised machine learning. The algorithms used are K-means and Elbow which are famous algorithms that have been successfully applied in many areas such as marketing, biology, library, insurance, finance... The purpose of clustering is to find meaningful market segments. However, the adoption and adjustment of parameters in the algorithms so as to find significant customer segmentations remain a challenge at present. In this paper, we used data of customers of Thu Duc CoopExtra and found significant customer segmentations which can be useful for more effective marketing and customer care by the supermarket.