IEEE

Customer Segmentation using Clustering Techniques: Data-Driven Approach to Enhance Marketing Strategy

Abstract: Customer segmentation is a vital strategy for businesses seeking to enhance their marketing efforts and optimize resource allocation. This research focuses on segmenting customers using the ...
IEEE

Developing Personalized Marketing Strategies Based on Customer Behavior Analysis Using Clustering and Machine Learning

Abstract: This study introduces a data-driven approach to customer segmentation using clustering algorithms like K-Means, DBSCAN, hierarchical clustering, and PCA. Customers are segmented based on ...
National Academies of Sciences%2c Engineering%2c and Medicine

Making Machine Learning Safer in High-Stakes Settings

Machine learning, a key enabler of artificial intelligence, is increasingly used for applications like self-driving cars, medical devices, and advanced robots that work near humans — all contexts ...
IEEE

Optimizing Marketing Strategies: Predicting Customer Personality using Advanced Machine Learning Models

Abstract: In the competition of modern marketing, it is highly important to foresee the correct personality profiles of customers because this may further improve the result of marketing campaigns.
IEEE

An Effective Customer Segmentation using RFM Ranking Techniques

Abstract: Customer segmentation emerged as a technique to develop a relationship between customer buying behavior and company profits. With the ever-growing data within the market and the extreme ...
IEEE

Sentiment Analysis of Amazon Customer Review by Using Machine Learning Models

Abstract: Sentiment analysis is a powerful tool for understanding customer opinions and enhancing business decision-making processes. This study explores the sentiment analysis of a large dataset ...