The significance of data mining applications in evaluating customer reviews in the context of e-commerce transactions
List of Authors
  • Pritam Kumar

Keyword
  • data mining, e-commerce, data science, consumer review

Abstract
  • In this age of digitalization, most people use their smartphones and the internet to shop for not just luxury and convenience items, but also for necessities such as food and medicine. In the wake of the Covid 19 pandemic, businesses embraced e-commerce platforms, and customers opted to make purchases in a secure setting. Feedback from customers is critical for a variety of reasons, including helping to improve marketing and manufacturing methods. The customer feedback or reviews are evaluated by the organisation with the use of data mining technique or applications. One of the primary goals of this study is to determine the impact of data mining applications in the assessment of customer reviews on e-commerce transactions. The researcher will examine different research papers on certain topics such as data mining applications, e-commerce, contemporary information technology for data science and data mining, and customer reviews in an e-commerce platform, among others. According to the findings of this research, most e-commerce organisations and websites offer information about their goods and services. In addition, they enable users to comment on and record their opinions on different goods and services on the site. Then, with the assistance of data mining tools and technologies, they analyse and summarise the data to make a variety of important decisions or choices regarding products and services.

Reference
  • 1. Chen, Y. (2017). The Application of Data Mining in Electronic Commerce. Advances In Computer Science Research (ACSR), 76, 1017-1020.

    2. Ciotti, G. (2021). Understanding Consumer Behavior to Convert More Customers. Retrieved 20 September 2021, from https://www.helpscout.com/consumer-behavior/

    3. Delamaire, L., Abdou, H., & Pointon, J. (2009). Credit card fraud and detection techniques: a review. Banks And Bank Systems, 4(2), 57-68.

    4. Dwivedi, Y., Ismagilova, E., Hughes, D., Carlson, J., Filieri, R., & Jacobson, J. et al. (2021). Setting the future of digital and social media marketing research: Perspectives and research propositions. International Journal of Information Management, 59, 102168. doi: 10.1016/j.ijinfomgt.2020.102168

    5. Estay, B. (2020). Identifying Customers with A Target Market Analysis (2020). Retrieved 19 September 2021, from https://www.bigcommerce.com/blog/target-market-analysis/

    6. Farruh, K. (2020). Consumer Life Cycle and Profiling: A Data Mining Perspective. In M. Reyes, Consumer Behavior and Marketing (1st ed.). London: Intech Open Limited. Retrieved from https://www.intechopen.com/chapters/66823

    7. Gupta, P., & Bhushan, B. (2012). Data mining Techniques in E - Business. The International Journal of Advances in Engineering Sciences (IJAES), 2(1), 12-15.

    8. Infotech, N. (2020). What Is Data Mining and Role of data mining in business processes. Retrieved 22 September 2021, from https://narolainfoetch.medium.com/what-is-data-mining-and-role-of-data-mining-in-business-processes-78a3c58d1af0

    9. Ismail, M., Mansur Ibrahim, M., Mahmoud Sanusi, Z., & Nat, M. (2015). Data Mining in Electronic Commerce: Benefits and Challenges. International Journal Of Communications, Network And System Sciences, 8(12), 501-509. doi: http://dx.doi.org/10.4236/ijcns.2015.812045

    10. Khan, N., Yaqoob, I., Hashem, I., Inayat, Z., Mahmoud Ali, W., & Alam, M. et al. (2014). Big Data: Survey, Technologies, Opportunities, and Challenges. The Scientific World Journal, 2014, 1-18. doi: 10.1155/2014/712826

    11. Liu, G., Fei, S., Yan, Z., Wu, C., Tsai, S., & Zhang, J. (2020). An Empirical Study on Response to Online Customer Reviews and E-Commerce Sales: From the Mobile Information System Perspective. Mobile Information Systems, 2020, 1-12. doi: 10.1155/2020/8864764

    12. Maria, G. (2020). Convert Data to Dollars: The Business of Mining Data. Retrieved 21 September 2021, from https://www.getapp.com/resources/what-is-data-mining-small-business/

    13. McCue, C. (2015). Process Models for Data Mining and Predictive Analysis. Data Mining And Predictive Analysis, 51-74. doi: 10.1016/b978-0-12-800229-2.00004-3

    14. Salehi, F., Abdollahbeigi, B., Langroudi, A., & Salehi, F. (2012). The Impact of Website Information Convenience on E-commerce Success of Companies. Procedia - Social and Behavioral Sciences, 57(9), 381-387. doi: 10.1016/j.sbspro.2012.09.1201

    15. Shreyashi, S. (2020). The Impact of Big Data Analytics on the E-commerce Industry. Retrieved 20 September 2021, from https://www.researchgate.net/publication/347443987_The_Impact_of_Big_Data_Analytics_on_the_E-commerce_Industry

    16. Soegaard, M. (2020). Usability: A part of the User Experience. Retrieved 20 September 2021, from https://www.interaction-design.org/literature/article/usability-a-part-of-the-user-experience

    17. Stedman, C. (2021). What is Data Mining? Retrieved 20 September 2021, from https://searchbusinessanalytics.techtarget.com/definition/data-mining

    18. Toorajipour, R., Sohrabpour, V., Nazarpour, A., Oghazi, P., & Fischl, M. (2021). Artificial intelligence in supply chain management: A systematic literature review. Journal Of Business Research, 122, 502-517. doi: 10.1016/j.jbusres.2020.09.009

    19. Vasic, N., Kilibarda, M., & Kaurin, T. (2019). The Influence of Online Shopping Determinants on Customer Satisfaction in the Serbian Market. Journal Of Theoretical and Applied Electronic Commerce Research, 14(2), 70-89. doi: 10.4067/s0718-18762019000200107

    20. Zhang, S. (2021). Application of Data Mining Technology in the Analysis of E-commerce Emotional Law. Journal Of Physics: Conference Series, 1852(2), 022044. doi: 10.1088/1742-6596/1852/2/022044