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Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM23873
Volume:
7 |
6 |
Jun 2023
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Artificial intelligence (AI) has revolutionized the field of customer relationship management (CRM), offering organizations new opportunities to improve their organizational performance and gain a competitive advantage. This research paper explores the impact of AI-powered CRM on organizational performance and competitive advantage by analysing quantitative data. A comprehensive literature review is conducted to examine the key concepts, theories, and frameworks related to CRM and AI, and to analyse how AI is being utilized in various industries and organizations. The paper discusses how AI-powered CRM can enhance organizational performance by improving customer engagement, personalization, and retention through advanced data analysis, predictive modelling, and automation. It also explores how AI-powered CRM can contribute to gaining a competitive advantage by providing organizations with insights into customer behaviour, preferences, and needs, and facilitating innovation, agility, and responsiveness. However, the paper also highlights potential challenges and limitations associated with AI-powered CRM, including issues related to data privacy, security, bias, and human-machine collaboration. The findings of this research suggest that organizations need to carefully consider the benefits, challenges, and ethical considerations of AI-powered CRM in order to effectively leverage its potential for enhancing organizational performance and gaining a competitive advantage in today’s dynamic business environment. Further research and best practices are recommended to guide organizations in implementing and optimizing AI-powered CRM strategies.
KEYWORDS
Publication Date
6/19/2023
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
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