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@article{192438,
        author = {Om Nagre and Ruturaj Daphal and Siddhant Marne and Prof. Shobha Raskar},
        title = {AdFlow: An AI-Powered Two-Phase Framework for Automated Social Media Advertising and Analytics},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {9},
        pages = {1179-1184},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=192438},
        abstract = {Modern digital marketing demands a shift from reactive, manual campaigns to proactive, data-driven strategies. This paper presents AdFlow, a novel two-phase framework that integrates predictive analytics with automated cross-platform execution to address key industry challenges. Phase 1 employs a collaborative filtering model for user targeting (achieving 85% precision, 88% recall) and a generative AI module for dynamic content creation. Phase 2 handles intelligent orchestra- tion across social media platforms via APIs, featuring dynamic budget allocation and a continuous feedback loop. In a six-week experimental evaluation, AdFlow demonstrated a 30% increase in Click-Through Rate (CTR) and a 15% reduction in Cost-Per- Acquisition (CPA) compared to baseline methods. The framework effectively mitigates scalability issues, platform complexity, and the limitations of reactive optimization, providing an end-to-end solution for automated social media advertising.},
        keywords = {AI Marketing, Social Media Advertising, Pre- dictive Analytics, Generative AI, Cross-Platform Automation, Collaborative Filtering},
        month = {February},
        }