Customer Behavior Analysis in E-Commerce using Machine Learning Approach : A Survey

Authors

  • Siddhant Sharma  AKS University, SATNA, MP, India
  • Akhilesh A. Waoo  AKS University, SATNA, MP, India

DOI:

https://doi.org//10.32628/CSEIT239028

Keywords:

Customer, Machine Learning, Prediction, Accuracy, Error, Data Mining.

Abstract

These days, consumer behavior models are often founded on machine learning and the data mining of customer data. Forecasting client behavior is an unclear and tough endeavor. Thus, one has to use the appropriate strategy and strategy while constructing consumer behavior models. Once a prediction model has been built, it is difficult to manipulate it for the marketer to determine exactly what marketing actions to take for each customer or group of customers. This is because once the model has been built, it is impossible to change the variables that make up the model. While this formulation is very complicated, the majority of customer models are, in practice, rather straightforward. Because of this requirement, most customer behavior models neglect so many essential elements that the forecasts they provide are often not particularly trustworthy. The purpose of this study is to present different research work that has been done on the analysis of consumer behavior using various machine learning and data mining approaches.

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2023-04-30

Issue

Volume 9, Issue 2, March-April-2023

Section

Research Articles

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Siddhant Sharma, Akhilesh A. Waoo, " Customer Behavior Analysis in E-Commerce using Machine Learning Approach : A Survey, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 9, Issue 2, pp.163-170, March-April-2023. Available at doi : https://doi.org/10.32628/CSEIT239028