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AI-Based Sales Forecasting Model for Digital Marketing

Author

Listed:
  • Siddhartha Negi

    (Maharaja Surajmal Institute, New Delhi, India)

  • Vinita Tomar

    (Maharaja Surajmal Institute, New Delhi, India)

  • Tarunim Sharma

    (Maharaja Surajmal Institute, New Delhi, India)

  • Ankush Kumar

    (Maharaja Surajmal Institute, New Delhi, India)

Abstract

In today’s competitive marketplace, accurately forecasting sales is crucial for business success. This article explores how artificial intelligence (AI) can transform digital marketing by utilizing advanced IT systems to collect and analyze customer feedback, providing valuable insights into consumer preferences and behaviors. The proposed method combines Support Vector Machines (SVMs) and Artificial Neural Networks (ANNs) to identify potential customers and uncover meaningful patterns in feedback. By integrating machine learning techniques, businesses can make data-driven decisions to refine marketing strategies, improve customer targeting, and personalize communication. This AI-powered approach enhances marketing performance by enabling more effective promotional strategies and better customer engagement, ultimately improving competitive positioning. By leveraging AI algorithms like SVMs and ANNs, companies can discover hidden patterns within large datasets, leading to better decision-making and increased customer satisfaction. The result is improved marketing efficiency and the ability to thrive in a more competitive environment, driving growth and fostering long-term success.

Suggested Citation

  • Siddhartha Negi & Vinita Tomar & Tarunim Sharma & Ankush Kumar, 2026. "AI-Based Sales Forecasting Model for Digital Marketing," International Journal of Research and Innovation in Applied Science, International Journal of Research and Innovation in Applied Science (IJRIAS), vol. 11(2), pages 1063-1070, February.
    • Handle: RePEc:bjf:journl:v:11:y:2026:i:2:p:1063-1070
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    References listed on IDEAS

    as
    1. Alim Al Ayub Ahmed & Sugandha Agarwal & IMade Gede Ariestova Kurniawan & Samuel P. D. Anantadjaya & Chitra Krishnan, 2022. "Business boosting through sentiment analysis using Artificial Intelligence approach," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(1), pages 699-709, March.
    2. Zirar, Araz & Ali, Syed Imran & Islam, Nazrul, 2023. "Worker and workplace Artificial Intelligence (AI) coexistence: Emerging themes and research agenda," Technovation, Elsevier, vol. 124(C).
    3. Sohrabpour, Vahid & Oghazi, Pejvak & Toorajipour, Reza & Nazarpour, Ali, 2021. "Export sales forecasting using artificial intelligence," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
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