Commodity reservation panic buying optimization method

An optimization method and commodity technology, applied in the direction of reservation, commerce, structured data retrieval, etc., can solve the problems of untargeted processing and inability to identify users, and achieve the effect of improving the success rate of panic buying and improving the enthusiasm for participation.

Inactive Publication Date: 2020-12-29
SICHUAN CHANGHONG ELECTRIC CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] Due to the lack of targeted processing, the system cannot identify users who have participated in multiple purchases but failed to snap up

Method used

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  • Commodity reservation panic buying optimization method
  • Commodity reservation panic buying optimization method

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Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0020] The method for optimizing commodity pre-order snap-buying in the present invention includes:

[0021] Step (1), add a table A in the database, and increase the chance value field Y in table A, and set the initial value for Y at the same time;

[0022] Step (2), save the data of users who have participated in one or more snap-up activities but failed to snap-up successfully in Table A, and the data includes the number of user participation and the number of events held;

[0023] Step (3), table A in the database is synchronized to the redis cache library;

[0024] Step (4), match the user information in the snap-up page and the redis cache library, if the match is successful, then enter step (5);

[0025] Step (5), according to the successfully matched user data, calculate the opportunity value of the unsuccessful snap-up user through the formula Y=aX+D, a is a fixed percentage and is a positive value, set by the system, X is the number of user participation, D is the ...

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PUM

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Abstract

The invention relates to the field of e-commerce system data processing, in particular to a commodity reservation panic buying optimization method, which can preferentially process an order placing panic buying request of a user who participates in panic buying activities for multiple times but is unsuccessful in panic buying, improves the panic buying success rate of the user, and further improves the participation enthusiasm of the user. The technical scheme is summarized as follows: adding a table A in a database, adding an opportunity value field Y in the table A, and storing user data participating in panic buying activities for one or more times but not successfully panic buying in the table A; synchronizing the table A in the database into a redis cache library, matching the panic buying page with the user information in the redis cache library successfully, calculating the opportunity value of the unsuccessful panic buying user through a formula Y = aX + D, and submitting ordering panic buying requests triggered by the successfully matched users in sequence from high to low according to the opportunity value of the successfully matched users. The method is suitable for commodity appointment panic buying.

Description

technical field [0001] The invention relates to the field of data processing of an e-commerce system, in particular to a method for optimizing commodity reservation and snap-up. Background technique [0002] Commodity pre-order rush is the most commonly used promotional activity on e-commerce platforms. For example, mainstream e-commerce platforms such as JD.com and Taobao use it as a functional entrance and hold activities regularly. At present, the basic process of pre-order snap-buying is: the user makes an appointment to register, and enters the snap-up page to participate in the activity on time after the registration is successful. The system feedback result is whether the snap-up is successful or failed, and the user's activity ends at this point. As for the pre-booking snap-up system, sufficient preparations are required to bear many technical pressures such as high concurrency, database load, network and server bandwidth, front-end, and back-end. The goal of the sys...

Claims

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Application Information

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IPC IPC(8): G06F16/2455G06F16/27G06Q10/02G06Q30/06
CPCG06F16/24552G06F16/27G06Q10/02G06Q30/0635
Inventor 彭媛媛
Owner SICHUAN CHANGHONG ELECTRIC CO LTD
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