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Usage Data for Predicting User Trends and Behavioral Analysis in E-Commerce Applications

Author

Listed:
  • Sathiyamoorthi V.

    (Sona College of Technology, India)

  • T. Nadana Ravishankar

    (Veltech Hightech Dr. Rangarajan Dr. Sakunthala Engineering College, India)

  • Ilavarasi A. K.

    (Centre for Healthcare Advancement, Innovation and Research, Vellore Institute of Technology, Chennai, India)

  • Sridhar Udayakumar

    (Mettu University, Ethiopia)

  • Karthikeyan Harimoorthy

    (CHRIST University (Deemed), India)

  • Jayapandian N.

    (Christ University (Deemed), India)

  • Saravanan V.

    (Dambi Dollo University, Ethiopia)

Abstract

Reviewing and buying the right goods from online websites is growing day by day in today's fast internet environment. Numerous goods in the same label are available to consumers. It is thus a difficult job for consumers to pick up the correct commodity at a decent price under different market conditions. Therefore, it is important for owners of online shopping websites to better understand their customers' needs and offer better services. For these reasons, the access log documented a vast amount of data related to user interactions with the websites. This access log therefore plays a key role in predicting user access trends and in recommending the best product to consumers. This research work therefore focuses on one such methodology for evaluating the pattern and behavioral analysis of users in e-commerce websites.

Suggested Citation

  • Sathiyamoorthi V. & T. Nadana Ravishankar & Ilavarasi A. K. & Sridhar Udayakumar & Karthikeyan Harimoorthy & Jayapandian N. & Saravanan V., 2021. "Usage Data for Predicting User Trends and Behavioral Analysis in E-Commerce Applications," International Journal of Information Systems in the Service Sector (IJISSS), IGI Global, vol. 13(4), pages 40-61, October.
    • Handle: RePEc:igg:jisss0:v:13:y:2021:i:4:p:40-61
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