Antony Satya Vivek Vardhan Akisetty1, Rakesh Jena2, Rajas Paresh Kshirsagar3, Om Goel4, Prof.(Dr.) Arpit Jain5 & Prof. (Dr) Punit Goel6
1Southern New Hampshire University, Manchester NH, US antony.satya.a@gmail.com
2Scholar Biju Patnaik University of Technology, Rourkela, Bhubaneswar, Odisha 751024, rakesh.public2@gmail.com
3N.Y. University, Malad (W), Mumbai – 400064, Maharashtra, India, rajaskshirsagar@gmail.com
4ABES Engineering College Ghaziabad, omgoeldec2@gmail.com
5 KL University, Vijaywada, Andhra Pradesh, dr.jainarpit@gmail.com
6Maharaja Agrasen Himalayan Garhwal University, Uttarakhand, drkumarpunitgoel@gmail.com
Abstract
The advent of Natural Language Processing (NLP) has revolutionized customer support, enabling businesses to enhance service delivery through automated conversational agents. These AI-driven tools utilize advanced NLP techniques to understand and respond to customer inquiries, providing immediate assistance and fostering a seamless user experience. This paper explores the integration of NLP in automated customer support systems, highlighting its capabilities in natural language understanding, sentiment analysis, and context awareness. By analyzing various implementations of conversational AI agents across industries, we identify best practices that enhance customer interaction and satisfaction. Additionally, we discuss the challenges faced in deploying these technologies, such as ensuring data privacy, maintaining context, and handling diverse linguistic nuances. The findings suggest that leveraging NLP not only improves operational efficiency but also significantly enhances customer engagement, leading to increased loyalty and retention. Ultimately, this research underscores the potential of conversational AI in transforming customer support into a more efficient and responsive service.
Keywords
Natural Language Processing, Automated Customer Support, Conversational AI, Customer Engagement, Sentiment Analysis, AI-driven Solutions.
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