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DOI: 10.14569/IJACSA.2025.0160456
PDF

AI-Driven Predictive Analytics for CRM to Enhance Retention Personalization and Decision-Making

Author 1: Yashika Gaidhani
Author 2: Janjhyam Venkata Naga Ramesh
Author 3: Sanjit Singh
Author 4: Reetika Dagar
Author 5: T Subha Mastan Rao
Author 6: Sanjiv Rao Godla
Author 7: Yousef A.Baker El-Ebiary

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 16 Issue 4, 2025.

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Abstract: The advent of Artificial Intelligence (AI) has dramatically altered Customer Relationship Management (CRM) by allowing organizations to anticipate customer behavior, customize interactions and automate service delivery. This research introduces an extensive AI-based predictive analytics framework aimed at improving customer engagement, retention and satisfaction using advanced Machine Learning (ML) and Natural Language Processing (NLP) methodologies. By using XGBoost for churn prediction and BERT-based models for sentiment analysis, the system efficiently handles both structured and unstructured customer data. The methodology involves sophisticated feature engineering, customer segmentation via K-Means clustering, and Customer Lifetime Value (CLV) prediction to aid data-driven business strategies. An NLP-driven chatbot offers real-time, personalized support, response time and improving user experience. Evaluation metrics such as accuracy, precision, recall and F1-score demonstrate the better performance of the proposed system compared to conventional CRM approaches. This work also addresses important issues such as data privacy compliance, algorithmic bias and explainability of AI decision-making. Ethical deployment and transparency of AI are emphasized for building confidence in automated CRM systems. Future evolution will tackle the use of reinforcement learning to facilitate learning-based interaction schemes and federated learning for trusted, decentralized management of data. This architecture does not only provide better CRM functionality but also builds a platform towards intelligent, responsible and scalable solutions for customer relations across industries.

Keywords: Artificial Intelligence; predictive analytics; customer relationship management; natural language processing; churn prediction

Yashika Gaidhani, Janjhyam Venkata Naga Ramesh, Sanjit Singh, Reetika Dagar, T Subha Mastan Rao, Sanjiv Rao Godla and Yousef A.Baker El-Ebiary, “AI-Driven Predictive Analytics for CRM to Enhance Retention Personalization and Decision-Making” International Journal of Advanced Computer Science and Applications(IJACSA), 16(4), 2025. http://dx.doi.org/10.14569/IJACSA.2025.0160456

@article{Gaidhani2025,
title = {AI-Driven Predictive Analytics for CRM to Enhance Retention Personalization and Decision-Making},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2025.0160456},
url = {http://dx.doi.org/10.14569/IJACSA.2025.0160456},
year = {2025},
publisher = {The Science and Information Organization},
volume = {16},
number = {4},
author = {Yashika Gaidhani and Janjhyam Venkata Naga Ramesh and Sanjit Singh and Reetika Dagar and T Subha Mastan Rao and Sanjiv Rao Godla and Yousef A.Baker El-Ebiary}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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