Panic buying commodity transaction data processing method and system

Abstract

The invention provides a panic buying commodity transaction data processing method and system. The method comprises the steps: receiving commodity transaction data of a user in a reserved preset timeperiod; determining user information according to the commodity transaction data of the user, and determining a signature number range according to the user information; and after the reservation is finished, forming a reservation sequence according to the signature number ranges of all the users, randomly extracting a target user according to the reservation sequence, and sending commodity purchase success information to the target user to complete commodity transaction. The method can relieve system panic purchase pressure, prevent various cheating software from interfering the commodity transaction process, and improve user experience.

Description

technical field [0001] The invention relates to the technical field of electronic transactions, in particular to a method and system for processing transaction data of rush-buying commodities. Background technique [0002] At present, the marketing activities of shopping malls are various, and the number of participants in the activities is large. For some low-price activities, the model of rush buying is often adopted. However, on the one hand, the time of customer participation in the rush buying activities is too short, and a large number of visits in a short period of time may easily lead to rush buying software. Crash, reducing customer experience. On the other hand, there are all kinds of tools on the market that can cheat. The current replacement method cannot effectively rule out the behavior of snapping up products through cheating, and cannot guarantee the fairness of snapping up products. Contents of the invention [0003] An object of the present invention is t...

AI Technical Summary

Problems solved by technology

[0002] At present, the marketing activities of shopping malls are various, and the number of participants in the activities is large. For some low-price activities, the model of rush buying is often adopted. However, on the one hand, the time of customer participation in the rush buying activities is too short, and a large number of visits in a short period of time may easily lead to rush buying software. Crash, reducing customer experience. On the other hand, there are various tools on the market that can be used to cheat. The current replacement method cannot effectively eliminate the behavior of buying products through cheating, and cannot guarantee the fairness of buying products.

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