Abstract

The purpose of this paper is to develop a forecasting model for retailers based on customer segmentation, to improve the performance of inventory. The research makes an attempt to capture the knowledge of segmenting the customers based on various attributes as an input to the demand forecasting in a retail store. The paper suggests a data mining model which has been used for forecasting demand. The proposed model has been applied for forecasting for grocery items in a supermarket. Based on the proposed forecasting model, the inventory performance has been studied by simulation. Hence, the proposed model in the paper results in improved performance of inventory. Retailers can make use of the proposed model for demand forecasting of various items to improve the inventory performance and profitability of operations. With the advent of data mining systems which have given rise to the use of business intelligence in various domains. Kayalvizhi Subramanian | Gunasekar Thangarasu "Developing a Forecasting Model for Retailers Based on Customer Segmentation using Data Mining Techniques" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | International Conference on Advanced Engineering and Information Technology , November 2018, URL: https://www.ijtsrd.com/papers/ijtsrd19127.pdf Paper URL: https://www.ijtsrd.com/computer-science/data-miining/19127/developing-a-forecasting-model-for-retailers-based-on-customer-segmentation-using-data-mining-techniques/kayalvizhi-subramanian

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