Customer segmentation in the digital marketing using a Q-learning based differential evolution algorithm integrated with K-means clustering.
Effective and well-structured customer segmentation enables organizations to accurately identify and comprehend the distinct characteristics and needs of various customer groups, thereby facilitating the development of more targeted marketing strategies. Contemporary artificial intelligence technolo...
Saved in:
| Main Author: | Guanqun Wang |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2025-01-01
|
| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0318519 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Implementation of the K-Means Algorithm for Customer Churn Segmentation in Developing Bank Marketing Strategies
by: Reva Nur Rahmadiana, et al.
Published: (2025-07-01) -
Identifying Customer Segmentation and Persona of Amazon Customer: An Approach Using K-Means Clustering
by: Rizki Agung Ramadani, et al.
Published: (2025-07-01) -
Improvement of Differential Privacy K-means Clustering Algorithm
by: GUO Rumin, et al.
Published: (2024-08-01) -
Enhancing Customer Segmentation Through Factor Analysis of Mixed Data (FAMD)-Based Approach Using K-Means and Hierarchical Clustering Algorithms
by: Chukwutem Pinic Ufeli, et al.
Published: (2025-05-01) -
Ultra Innovative Approach to Integrate Cellphone Customer Market Segmentation Model Using Self Organizing Maps and K-Means Methodology
by: mohammad reza karimi alavijeh, et al.
Published: (2016-07-01)