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@article{186379,
        author = {Vikas Gupta},
        title = {Enhancing Telecom Sales Funnels with AI-Driven Opportunity Forecasting},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {6},
        pages = {1344-1351},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=186379},
        abstract = {In today’s rapidly evolving telecommunications industry, Artificial Intelligence (AI) is redefining how sales funnels operate—particularly in the SMB segment where agility and personalization are paramount. This review explores the role of AI-driven opportunity forecasting in optimizing the lead-to-order (L2O) journey. By integrating predictive analytics, machine learning models, and CRM automation tools, telecom operators are achieving significant gains in sales forecasting accuracy, lead conversion rates, and overall operational efficiency. A Salesforce-based case implementation is analyzed to illustrate real-world effectiveness, showcasing a 35–40% improvement in sales cycle efficiency. The review further evaluates current research trends, practical challenges, and future avenues for AI adoption in telecom sales. With AI’s continued evolution, the path forward involves greater model transparency, integration with generative AI, and democratization of forecasting tools for smaller operators.},
        keywords = {AI in Telecom; Opportunity Forecasting; Lead-to-Order Automation; CRM Intelligence; SMB Sales Optimization; Predictive Analytics; Machine Learning in Sales; Salesforce Automation; Sales Funnel Optimization},
        month = {November},
        }