Prediction of Online Product Sales using Machine Learning

Authors

  • K. P. Aldrin Neal John Department of Computer Science Engineering, Albertian Institute of Science and Technology, Kalamassery, India
  • K. Adarsh Nag Department of Computer Science Engineering, Albertian Institute of Science and Technology, Kalamassery, India

Keywords:

Clustering, Machine Learning

Abstract

Product sales prediction is a major aspect of purchasing management. One of the key challenges faced nowadays by organizations the dynamic, international and unpredictable business environment in which they operate. With growing customer expectations for price and quality, manufacturers today can no longer rely only on cost advantage that they have over their rivals. Forecasting the sales are crucial in determining inventory stock levels and accurately estimating the future demand for goods has been an ongoing challenge in industries If goods are not readily available or if goods availability is more than demand overall profit can be compromised. As a result, sales prediction for goods can be significant to ensure that loss is minimized. Depending on this study, our project is creating a prediction model using machine learning algorithms for accurately predicting online product sales. Our project aims to use upto date data which includes online reviews, online ratings, online promotional strategies and sentiments and various other parameters for predicting product sales.

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Published

25-07-2022

How to Cite

[1]
K. P. A. N. John and K. A. Nag, “Prediction of Online Product Sales using Machine Learning”, IJRESM, vol. 5, no. 7, pp. 81–83, Jul. 2022.

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Section

Articles