Revolutionizing Telecom Commerce with AI/ML: A Comprehensive Study on API-Driven Customer Interaction and Automation

Rahul Khurana

Abstract: Telecom commerce is a complex and dynamic domain that involves multiple products, services, and channels. Customers frequently encounter challenges when finding, comparing, and purchasing the best options. Traditional e-commerce platforms are not designed to manage the nuances and variations of telecom products, such as compatibility, availability, or personalization. In this paper, we propose a novel approach to revolutionize telecom commerce with AI/ML using 300+ APIs. These APIs enable customers to interact with a chatbot through natural language commands, guiding them through the purchase journey. The chatbot integrates with a commerce platform that handles complex configurations, pricing, credit checks, and encryption using domain-specific APIs. We present diagrams illustrating the system?s architecture and argue that this approach enhances customer satisfaction and loyalty while reducing operational costs and increasing revenue for telecom providers.

Keywords: AI, ML, Telecom Commerce, Chatbots, API Integration, Natural Language Processing, Customer Interaction, eCommerce, Personalization, Secure Transactions, Digital Economy, Customer Journey, Product Configuration, User Experience, Automation, Customer Satisfaction, Operational Efficiency, Revenue Enhancement

How to Cite?: Rahul Khurana, "Revolutionizing Telecom Commerce with AI/ML: A Comprehensive Study on API-Driven Customer Interaction and Automation", Volume 13 Issue 10, October 2024, International Journal of Science and Research (IJSR), Pages: 757-759, https://www.ijsr.net/getabstract.php?paperid=SR241011105152, DOI: https://dx.doi.org/10.21275/SR241011105152