Predictive Analysis in E-commerce: Utilizing Data Mining Techniques to Forecast Customer Purchasing Behavior
Abstract views: 0
/ 
PDF downloads: 1
Keywords:
E-commerce, Data Mining, ForecastingAbstract
In the dynamic landscape of e-commerce, understanding and predicting customer purchasing
behavior is paramount for businesses striving to optimize their operations and enhance customer
satisfaction [2, 5]. This research paper delves into the realm of predictive analysis within e-commerce,
focusing on the utilization of data mining techniques to forecast and comprehend customer purchasing
patterns [1, 7]. The study investigates the application of various data mining methodologies, including but
not limited to machine learning algorithms, association rule mining [3, 18], and clustering techniques, to
extract valuable insights from vast datasets encompassing customer transactions, browsing history,
demographics, and other relevant variables. Through a comprehensive literature review and empirical
analysis [9 20], this paper aims to elucidate the significance of predictive analysis in e-commerce[15], its
methodologies, challenges, and the potential impact on enhancing marketing strategies, inventory
management, personalized recommendations [13,14], and overall business profitability. Furthermore [4,
6] this research endeavors to highlight the ethical considerations and privacy concerns associated with the
collection and utilization of customer data for predictive analysis in the e-commerce domain [10, 13]. The
findings and insights presented herein aim to provide a foundation for e-commerce entities to adopt and
implement advanced predictive analysis techniques effectively, thereby fostering a competitive edge in an
increasingly data-driven market environment [8, 17].
Downloads
References
Dirk Van den Poel, Wouter Buckinx: Predicting online
purchasing behavior, Eur. J. Oper. Res, 2005.
Orieb
Abu Alghanam, Sumaya N. Al
Khatib, Mohammad O. Hiari. Data Mining Model for
Predicting Customer Purchase Behavior in E-Commerce
Context: International Journal of Advanced Computer
Science and Applications, 2022.
Orieb Abu Alghanam, Sumaya N. Al-Khatib, Mohammad
O. Hiari. Data Mining Model for Predicting Customer
Purchase Behavior in E-Commerce Context : International
Journal
of
Advanced
Applications,2022.
Computer
Science
and
Douglas Cirqueira, Markus Hofer, Dietmar Nedbal,
Markus Helfert, Marija Bezbradic. Customer Purchase
Behavior Prediction in E-commerce: A Conceptual
Framework and Research Agenda: NFMCP@PKDD/ECML,
Qian Guo, Chun Yang, Shaoqing Tian, Prediction of
Purchase Intention among E-Commerce Platform Users
Based on Big Data Analysis: Rev. d'Intelligence Artif, 2020.
Jiangtao Qiu. A predictive Model for Customer Purchase
Behavior in E-Commerce Context: Pacific Asia Conference
on Information Systems, 2014.
Jiangtao Qiu, Zhangxi Lin, Yinghong Li.Predicting
customer purchase behavior in the e-commerce context:
Electronic Commerce Research, 1 December 2015.
Mohamed Chajri, M. Fakir: Application of Data Mining
in e-Commerce Journal of Information Technology
Research, 2014.
Han, J., Pei, J., & Kamber, M. (2011). Data mining:
concepts and techniques. Elsevier.
Loughin, T. M. (2019). An introduction to random forests
for classification and regression. Journal of Statistics
Education, 19(1), 1-17.
Pyle, D. (1999). Data preparation for data mining.
Morgan Kaufmann.
Witten, I. H., Frank, E., Hall, M. A., & Pal, C. J. (2016).
Data mining: practical machine learning tools and techniques.
Morgan Kaufmann.
Zhang, J., Wang, S., & Li, M. (2015). Data mining
techniques and applications—a decade review from 2000 to
Expert Systems with Applications, 38(1), 1-11.
Shuxiang Yao. Method and Research of E-commerce
Consumers' Purchasing Behavior Forecast and Analysis
Based on Machine Learning: International Conference on
Artificial Intelligence and Advanced Manufacturing, 2021.
Zerf Mohammed, Suhad M. Kadum. A Study about E
Commerce Based on Customer Behaviors: Engineering and
Technology Journal, 25 July 2021.
Hui Yuan, Wei Xu, Mingming Wang. Can online user
behavior improve the performance of sales prediction in
E-commerce?: IEEE International Conference on Systems,
Man and Cybernetics, 2014.
Jon Kepa Gerrikagoitia, Iñigo Castánder, Fidel
Rebón, Aurkene Alzua-Sorzabal. New Trends of Intelligent
E-marketing Based on Web Mining for E-shops,
ELSEVIER, 12 February 2015.
Ru Jia, Ru Li, Meiju Yu, Shanshan Wang. E-commerce
purchase prediction approach by user behavior data:
International Conference on Computer, Information and
Telecommunication Systems, 1 July 2017.
A. Dhond, Amarjeet R. Gupta, Sanjeev Vadhavkar. Data
mining techniques for optimizing inventories for electronic
commerce: Knowledge Discovery and Data Mining,2000.
.Chen, M., & Wei, L. Y. Y. (2016). Data mining
techniques in customer behavior analysis. Journal of Service
Science and Management, 9(03), 212.
