2.3 Application of Big Data Technology
in User Consumption Preference
As the key technology of big data technology, data
prediction has been deeply and widely used in various
fields. Covering geological disasters, financial crisis,
economic growth, event prediction, etc. all reflect a
strong technical function (Li, 2014, Ren, 2014,
ZHENG, 2014). Users' consumption preferences in
cross-border e-commerce can also be realized by
using big data technology. These data information
can be counted, analyzed and calculated by analyzing
consumers' browsing habits, purchase frequency,
preference settings, click through rate, etc. through
these consumption preference information, users'
consumption portrait can be established for
consumers to enhance the recognition of target
groups (Yang, 2014, Zheng, 2014, Yang, 2014). In
the shopping platform, some goods that may be
purchased are recommended to users according to the
user's access interface, click times, search path and
residence time. Enterprises realize the marketing of
shopping websites according to this technology (Zuo,
2014, Wang, 2014, Fan, 2014).
3 CONCLUSION
The application of big data technology in cross-
border e-commerce can not only improve the
timeliness of cross-border logistics, but also help
enterprises further adjust their marketing plans and
distribution routes. The transportation and
distribution of products will affect users'
consumption experience. Some merchants' delivery
time is too long or logistics delivery is slow, which
will lead to poor purchasing experience for
users. Therefore, it is necessary to constantly
improve the distribution routes and marketing plans
of enterprises to improve the speed of logistics
distribution. Therefore, through big data technology,
enterprises can accurately analyze the fastest logistics
route of products, and greatly reduce logistics costs.
The fastest route in the cross-border e-commerce
industry is air transport, which can quickly transport
goods to the destination to save turnover time, but the
cost is also relatively high.
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