In recent years, machine learning is widely used to support human decision making in several related scientific areas such as medical, biological, image processing and so on. However in market classification, marketing segmentation is facing numerous challenges in defining specific target customer zones to help enterprises launching their marketing strategies. On the other hand, modern technologies and programming languages are providing support for statistical estimations and graphic visualizations, especially in the R language. In this paper, a k-means machine learning (ML) algorithm with an R language implementation is utilized for marketing segmentation in a specific case study of Black Friday for determining potential customer zones to make reasonable marketing strategies.
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K-means Clustering Using R A Case Study of Market Segmentation
Semantic Scholar · Computer Science · 2019
Abstract
In recent years, machine learning is widely used to support human decision making in several related scientific areas such as medical, biological, image processing and so on. However in market classification, marketing segmentation is facing numerous challenges in defining specific target customer zones to help enterprises launching their marketing strategies. On the other hand, modern technologies and programming languages are providing support for statistical estimations and graphic visualizations, especially in the R language. In this paper, a k-means machine learning (ML) algorithm with an R language implementation is utilized for marketing segmentation in a specific case study of Black Friday for determining potential customer zones to make reasonable marketing strategies.