• Apoorv Malekar
• Prajakta Wagaj
• Arya Kulkarni
• Rupali Dalvi

In the modern telecom industry, business intelligence systems play a crucial role in analyzing vast amounts of data to enhance customer satisfaction, improve service personalization, and drive customer retention. This paper presents a Deep Learning-based Business Intelligence System specifically de signed for telecom clients. The system leverages deep learning models, including collaborative filtering and content-based filtering techniques, to analyze customer behaviour, usage patterns, and service preferences. By integrating these models, the system accurately predicts the most suitable mobile plans for individual customers, offering personalized recommendations that cater to unique user requirements. The proposed system utilizes a combination of data from customer demo graphics, usage history, and real-time network analytics to generate a holistic view of each customer’s needs. This approach enables telecom providers to make data-driven decisions and enhances their ability to upsell and cross-sell services effectively. Additionally, the deep learning framework helps identify customer segments that may be at risk of churn, providing actionable insights for targeted retention strategies. Experimental results demonstrate the sys tem’s efficacy in producing accurate recommendations and its potential to improve customer engagement and loyalty in the telecom sector. The study underscores the transformative impact of deep learning in business intelligence applications and offers a scalable solution for telecom operators to deliver personalized customer experiences and improve overall operational efficiency.

Business Intelligence, Telecom Recommendations System, Telecom Clients, Telecom Plans, Hybrid Filtering

"Enhancing Telecom Service Personalization with Hybrid Filtering Techniques", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 5, page no.b267-b272, May-2025, Available :http://www.jetir.org/papers/JETIR2505131.pdf

"Enhancing Telecom Service Personalization with Hybrid Filtering Techniques", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 5, page no. ppb267-b272, May-2025, Available at : http://www.jetir.org/papers/JETIR2505131.pdf