2015
DOI: 10.14569/ijarai.2015.041007
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Application of K-Means Algorithm for Efficient Customer Segmentation: A Strategy for Targeted Customer Services

Abstract: Abstract-The emergence of many business competitors has engendered severe rivalries among competing businesses in gaining new customers and retaining old ones. Due to the preceding, the need for exceptional customer services becomes pertinent, notwithstanding the size of the business. Furthermore, the ability of any business to understand each of its customers' needs will earn it greater leverage in providing targeted customer services and developing customised marketing programs for the customers. This unders… Show more

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Cited by 31 publications
(12 citation statements)
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“…K-means clustering is a type of unsupervised learning method, enabling us to find and analyze the intrinsic underlying patient subgroups without any pre-defined subgroup labels. In real-world scenarios, clustering is a widely used technique for customer segmentation 17 .…”
Section: Methodsmentioning
confidence: 99%
“…K-means clustering is a type of unsupervised learning method, enabling us to find and analyze the intrinsic underlying patient subgroups without any pre-defined subgroup labels. In real-world scenarios, clustering is a widely used technique for customer segmentation 17 .…”
Section: Methodsmentioning
confidence: 99%
“…Cluster analysis is an unsupervised machine learning technique for finding structure or revealing patterns in large, unexplored datasets [47,48]. It is frequently used for customer segmentation, i.e., to group customers based on the similarity of their purchasing habits and demographic characteristics [49]. 'Unsupervised learning' refers to the fact that the algorithm works with unlabelled data (no predefined groupings) and attempts to 'learn' some sort of structure from the input data.…”
Section: Step 2: Classification Of Contributorsmentioning
confidence: 99%
“…Specifically, K-means clustering aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean. In real-world scenarios, clustering is a widely used technique for customer segmentation [21].…”
Section: Plos Onementioning
confidence: 99%