AI-Powered CRM Solutions: Salesforce's Data Cloud as a Blueprint for Future Customer Interactions

Dr. Carlos, Martínez and Sofía, Gómez (2022) AI-Powered CRM Solutions: Salesforce's Data Cloud as a Blueprint for Future Customer Interactions. International Journal of Trend in Scientific Research and Development, 6 (6). pp. 2331-2346. ISSN 2456-6470

Text 289 AI-Powered CRM Solutions Salesforce's Data Cloud as a Blueprint for Future Customer Interactions.pdf Download (1MB)

Abstract

In today's rapidly evolving digital landscape, Artificial Intelligence (AI) has emerged as a transformative force in the way businesses engage with their customers. This article explores the innovative intersection of AI and Customer Relationship Management (CRM) solutions, with a particular focus on Salesforce's Data Cloud as a blueprint for future customer interactions. The integration of AI within CRM systems has enabled businesses to leverage vast amounts of data to deliver personalized, predictive, and seamless customer experiences. By examining Salesforce's Data Cloud, which harnesses AI-powered tools to optimize customer data management, we highlight how organizations can enhance customer engagement, drive sales growth, and improve decision-making processes. This article provides a comprehensive analysis of the evolving CRM landscape, the benefits of AI-driven insights, and the challenges businesses face in implementing AI technologies. Furthermore, it offers practical strategies for leveraging AI-powered CRM solutions to foster stronger, more meaningful relationships with customers, ultimately positioning companies to thrive in the competitive digital economy. The future of CRM is no longer about merely managing customer relationships but about anticipating and shaping customer needs in real-time with AI at the forefront.

Item Type:	Article
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:	Postgraduate > Master's of Islamic Education
Depositing User:	Journal Editor
Date Deposited:	20 Nov 2024 11:10
Last Modified:	20 Nov 2024 11:10
URI:	http://eprints.umsida.ac.id/id/eprint/14647

Actions (login required)

View Item