A Study on Sales Forecasting Through Social Media Trends Using Power Bi

Authors

  • Tharik Azeez R
  • K. Selvavinayaki
  • M Sheela Newsheeba
  • Suhas K S
  • Sandeep Kumar
  • Vimal Raj G
  • Shan Raymond B
  • Kailas

Keywords:

N\A

Abstract

In today’s fast-paced and data-driven world, consumers seek innovative tools to make informed purchasing decisions. This project introduces a Sales Forecasting Application that empowers users to predict sales trends, identify the best purchase opportunities, and make smarter shopping choices. By integrating Artificial Intelligence (AI), machine learning, and data analytics, the application offers consumers a personalized experience to optimize budgets and leverage market trends.

The application utilizes time-series forecasting models (e.g., ARIMA, Prophet) to analyse historical data and predict future sales patterns. It incorporates real-time social media trends and customer sentiment analysis using Natural Language Processing (NLP) to assess public perception and its impact on product demand. This enhances forecast accuracy and keeps users updated on trending products.

Another key feature of the application is its ability to perform price recognition using Optical Character Recognition (OCR) technology. This enables users to extract and analyse price data directly from product images, such as photos of labels, receipts, or promotional banners. The extracted data is seamlessly integrated into the application’s analysis, providing users with insights into pricing fluctuations and helping them identify the best deals available in the market. 

The application’s integration with Power BI takes its functionality to the next level by offering users highly interactive and visually appealing dashboards. These dashboards are designed to provide an intuitive experience, allowing consumers to:

  • Track and visualize historical sales data with future forecasts.
  • Correlate social media sentiment trends with product sales and pricing.
  • Identify seasonal patterns and trends for specific products or categories.
  • Customize analyses by time periods, brands, or product categories.
  • Access real-time, dynamically updated visualizations for accurate insights.

By delivering actionable insights in an easy-to-understand format, the Power BI integration ensures that even non-technical users can benefit from the application’s features. Additionally, the application provides options for users to export data and reports, enabling them to share insights or further analyse the results independently. 

This Sales Forecasting Application bridges the gap between AI-driven analytics and consumer decision-making. It empowers users to make smarter purchases, save money, and stay ahead of trends. With advanced forecasting, intuitive dashboards, and real-time insights, it is a vital tool for navigating today’s dynamic marketplace.

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References

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Published

2025-06-09

How to Cite

1.
Azeez R T, Selvavinayaki K, Newsheeba MS, K S S, Kumar S, Raj G V, Raymond B S, Kailas K. A Study on Sales Forecasting Through Social Media Trends Using Power Bi. J Neonatal Surg [Internet]. 2025Jun.9 [cited 2025Jun.20];14(31S):548-53. Available from: https://jneonatalsurg.com/index.php/jns/article/view/7211

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