Review on Customer Segmentation Methods Using Machine Learning

Abstract

This article is a review of the various methods and domains available in customer segmentation, specialized in the field of machine learning. Seven decades ago, John McCarthy coined the term ‘Artificial Intelligence’, commonly known as AI, in 1956. In the modern day, the term AI infers a very different world to that when it was introduced. With the compounding advancements in technology, it has now become a staple in almost every industry and service, even sprouting new fields such as machine learning, deep learning, and big data. One look into the marketing team of any big corporation suggests that it no longer only comprises sales reps and business administrators, but also data analysts as well. This is where machine learning and marketing combine to retain and gain customers in the form of customer segmentation. Customer segmentation is a way to cater to the tastes and preferences of groups of individuals rather than individuals themselves. It is also named market segmentation as it allows companies to perform ‘targeted marketing’. We have reviewed several research papers on segmentation using various methods, machine learning algorithms, their efficiency, and usage. This article explores the various ways that customer segmentation is useful and how it has evolved over the years while giving an overview of the various forms and domains available and practiced in the market.