Application of data mining in e-commerce

Because data mining can bring significant economic benefits, it is widely used in electronic commerce, especially in finance, retailing and telecom industry.

In the financial field, managers can classify and rank by analyzing the customer's ability to repay and credit. This can reduce the numbness of lending and improve the efficiency of the use of funds. It can also be found that the leading factor in the repayment of the decisive role, so as to develop corresponding financial policy. It is worth mentioning that the analysis of the data can also be found in money laundering and other criminal activities.

In retailing, data mining can help identify customer buying behavior, identify customer buying patterns and trends, improve service quality, achieve better customer retention and satisfaction, increase product sales ratios, design better commodity transport and distribution strategies, and reduce business costs.

The telecommunications industry has rapidly evolved from simply providing local and long-distance services to integrated telecommunications services such as voice, fax, paging, mobile phones, images, e-mail, computer and web data transmission, and other data communications services. The convergence of telecommunications, computer networks, the Internet and various other modes of communication and computing is the current trend. And with the opening of telecommunications and the development of new computing and communication technology in many countries, the telecom market is expanding rapidly and becoming more and more competitive. Therefore, it is necessary to use data mining technology to help understand business behavior, identify telecom patterns, capture embezzlement, better utilize resources and improve service quality. The analyst can analyze the information of the call source, call target, call volume and daily usage mode, and can also exploit the pattern analysis and abnormal pattern recognition, so as to find the embezzlement as early as possible and reduce the loss for the company.