Market Segmentation


EOI: 10.11242/viva-tech.01.05.001

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Citation

Vikas Soni, Shubham Yadav, Hritik Vishwakarma, Akshata Raut, "Market Segmentation", VIVA-IJRI Volume 1, Issue 6, Article 8, pp. 1-5, 2023. Published by Computer Engineering Department, VIVA Institute of Technology, Virar, India.

Abstract

Nowadays retail industry is facing major challenges in order to know their customer and optimize their businesses. So, a business needs a proper analyser, in order to know their customer behaviour and response toward their products. This proposed system describes a proper way to target special customers from a business perspective. The most crucial step in knowing your customer is to properly segment them according to their previous purchase history. So, for segmenting the customer into proper groups we used the K-means algorithm. In this proposed system, we will perform one of the most essential applications of machine learning, Customer Segmentation by using K-Means Clustering Algorithm. Then we will explore the data upon which we will be building our segmentation model. Furthermore, through the data collected, we can gain a deeper understanding of customer preferences as well as the requirements for discovering valuable segments that would reap them maximum profit. This way, we can achieve the marketing techniques more efficiently and minimize the possibility of risk to the investment. After segmenting the customers into successful clusters of the same properties, market strategy can be applied.

Keywords

Customer, K-means Algorithm, Maximum Profit, Purchase, Segmentation

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