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EXAMINING THE ROLE OF AI-DRIVEN CRM IN ENHANCING CUSTOMER LOYALTY IN THE DIGITAL ERA

Sparsh Chhabra Chhabra

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Paper Contents

Abstract

In the digital era, businesses are increasingly leveraging artificial intelligence (AI) to enhance customer relationship management (CRM) and drive customer loyalty. This paper examines the role of AI-driven CRM systems in strengthening customer loyalty by analyzing their impact on personalization, customer engagement, and retention. AI technologies, such as machine learning algorithms and natural language processing, enable businesses to gather and analyze vast amounts of customer data, leading to more accurate insights into customer preferences and behaviors. These insights facilitate highly personalized interactions, which are crucial for building and maintaining strong customer relationships.The study explores how AI-driven CRM systems enhance personalization by providing tailored recommendations and content based on individual customer data. It also investigates the role of AI in improving customer engagement through automated and intelligent communication channels, such as chatbots and virtual assistants, which offer timely and relevant responses to customer inquiries. Additionally, the paper discusses how AI-driven CRM tools contribute to customer retention by predicting churn and identifying opportunities for proactive intervention. By examining case studies and current research, this paper highlights the transformative potential of AI in CRM strategies and its implications for customer loyalty. The findings indicate that AI-driven CRM systems not only enhance the efficiency of customer interactions but also foster deeper emotional connections between brands and customers. Ultimately, this paper underscores the importance of integrating AI into CRM practices to achieve competitive advantage and sustained customer loyalty in the rapidly evolving digital landscape.

Copyright

Copyright © 2024 Sparsh Chhabra. This is an open access article distributed under the Creative Commons Attribution License.

Paper Details
Paper ID: IJPREMS40800021827
ISSN: 2321-9653
Publisher: ijprems
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