Abstract

This research project aims to enhance the business performance of the Egyptian Company for Glass Industries Company through the use of machine learning (ML) models and the segmentation of customers based on the total value of their orders. The Egyptian Company for Glass Industries is lacking both an ERP system and a customer segmentation plan. Poor performance and a small market share are the results. In order to forecast future order volumes using historical data, several machine learning (ML) models were developed, including linear regression, logistic regression, SVM, KNN, Naive Bayes, decision trees, gradient boosting, and neural networks. The performance is measured and compared using mean absolute error (MAE), and among all the models, linear regression has the lowest MAE. employing the KMeans model to separate customers into three categories, which aids in consumer segmentation.

Poster - Video - CV