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@article{190370,
        author = {Saksham Jain and Manan Saraswat and Mitali Gupta and Muskan Soni},
        title = {AI-Based Predictive Analytics and Its Influence on Online Retail Performance},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {8},
        pages = {1431-1436},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=190370},
        abstract = {The rapid expansion of online retail has increased the need for accurate and data-driven decision-making. Artificial Intelligence (AI) based predictive analytics has become a key tool for online retailers to analyse customer data, forecast demand, and improve marketing effectiveness. This research paper examines the influence of AI-driven predictive analytics on online retail performance, with special focus on targeted marketing strategies.
The study uses a qualitative research approach based on secondary data collected from academic journals, industry reports, and company disclosures. The findings indicate that predictive analytics helps online retailers improve personalised marketing, customer engagement, demand forecasting, inventory management, and pricing decisions. At the same time, challenges such as high implementation costs, data privacy concerns, and ethical issues related to AI adoption are also identified. The study concludes that responsible and strategic use of AI-driven predictive analytics can provide online retailers with a long-term competitive advantage.},
        keywords = {AI-driven Retailing, Predictive analytics, Targeted marketing, E-Commerce},
        month = {January},
        }