专题：Customer churn and segmentation

This cluster of papers focuses on customer equity management and prediction, utilizing data mining, machine learning, and segmentation techniques to understand customer churn, lifetime value, and profitability. It explores the impact of marketing strategies on customer retention and financial performance in various industries, particularly in telecommunications.
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E-Commerce Promotional Products Selection Using SWARA and TOPSIS

article Full Text OpenAlex 1547 FWCI592.7935

Progress in partial least squares structural equation modeling use in marketing research in the last decade

article Full Text OpenAlex 1050 FWCI191.6991

K-Means Clustering Approach for Intelligent Customer Segmentation Using Customer Purchase Behavior Data

article Full Text OpenAlex 185 FWCI24.3675

Examination of the Criticality of Customer Segmentation Using Unsupervised Learning Methods

article Full Text OpenAlex 179 FWCI68.4712

B2C E-Commerce Customer Churn Prediction Based on K-Means and SVM

article Full Text OpenAlex 140 FWCI19.5452

A review on customer segmentation methods for personalized customer targeting in e-commerce use cases

review Full Text OpenAlex 136 FWCI28.3143

Customer Churn in Retail E-Commerce Business: Spatial and Machine Learning Approach

article Full Text OpenAlex 126 FWCI15.7587

Assessing credit risk of commercial customers using hybrid machine learning algorithms

article Full Text OpenAlex 122 FWCI32.3924

Customer Churn Prediction in Telecommunication Industry Using Deep Learning

article Full Text OpenAlex 117 FWCI15.3201

Customer profiling, segmentation, and sales prediction using AI in direct marketing

article Full Text OpenAlex 116 FWCI24.2103