Coupon reissue method, device, storage medium and server

Abstract

The present application provides a coupon reissue method, device, storage medium, and server, relating to the field of e-commerce. The server receives a return operation from a target user; responds to the return operation and determines the discount amount required for the returned product; predicts the target product that the target user will purchase based on the target user's historical shopping behavior information; and reissues a coupon for the target product to the target user. The coupon has a discount amount. Thus, a coupon with an appropriate amount is reissued based on the total price of the returned product, and a coupon with a corresponding discount amount is selected for the target product that the target user will purchase, thereby improving the utilization rate of the coupon.

Description

Technical Field

[0001] The present application relates to the field of e-commerce, and more specifically, to a coupon reissue method, device, storage medium, and server. Background Art

[0002] When shopping on major e-commerce platforms, users receive numerous coupons, including those provided by merchants or the platforms themselves. These coupons vary in type, especially during major sales events like Singles' Day (Singles' Day) and Singles' Day (Double 11). When a user places an order using a coupon and discovers quality issues with the product upon receipt, they may need to request a partial refund. Currently, most e-commerce platforms offer either a full refund or no refund at all for coupons.

[0003] In the case of non-refundable coupons, users are often required to proactively contact customer service to request a replacement coupon. This cumbersome process creates a poor user experience, fails to increase repurchase rates, and may even lead to user churn. Furthermore, in the case of coupon refunds, coupons are not issued based on user shopping needs, making it difficult for users to use the returned coupons in a timely manner, resulting in wasted coupons. Summary of the Invention

[0004] To overcome at least one of the shortcomings of the prior art, the present application provides a coupon reissue method, device, storage medium, and server for reissuing coupons of appropriate amounts based on the returned goods and improving the utilization rate of the coupons. Specifically, the method includes:

[0005] In a first aspect, the present application provides a coupon reissue method, the method comprising:

[0006] Receive return operations from target users;

[0007] In response to the return operation, determine the discount amount to be refunded for the returned product;

[0008] Predicting target products that the target user will purchase based on the target user's historical shopping behavior information;

[0009] A coupon for the target product is reissued to the target user, wherein the coupon has the discount amount.

[0010] In a second aspect, the present application provides a coupon reissue device, the device comprising:

[0011] Return processing module, used to receive return operations from target users;

[0012] A credit determination module is used to respond to the return operation and determine the preferential credit amount that needs to be returned for the returned goods;

[0013] A commodity prediction module is used to predict the target commodity that the target user will purchase based on the historical shopping behavior information of the target user;

[0014] The discount reissue module is used to reissue the coupon of the target product to the target user, wherein the coupon has the discount amount.

[0015] In a third aspect, the present application provides a storage medium storing a computer program, which, when executed by a processor, implements the coupon reissue method.

[0016] In a fourth aspect, the present application provides a server comprising a processor and a memory, wherein the memory stores a computer program, and when the computer program is executed by the processor, the coupon reissue method described in the claims is implemented.

[0017] Compared with the prior art, this application has the following beneficial effects:

[0018] In the coupon reissue method, device, storage medium, and server provided in this application, the server receives a return request from a target user; responds to the return request by determining the discount amount required for the returned product; predicts the target product that the target user will purchase based on the target user's historical shopping behavior information; and reissues a coupon for the target product to the target user. The coupon has a discount amount. Thus, a coupon with an appropriate amount is reissued based on the total price of the returned product, and a coupon with a corresponding discount amount is selected for the target product that the target user will purchase, thereby improving the coupon's utilization rate. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without creative work.

[0020] Figure 1 A flowchart of a coupon reissue method provided in an embodiment of the present application;

[0021] Figure 2 A schematic diagram of the purchase expectation analysis dimensions provided in an embodiment of the present application;

[0022] Figure 3 A comparison table of purchase expectation calculation results provided in the embodiments of this application;

[0023] Figure 4A schematic diagram of the structure of a coupon reissue device provided in an embodiment of the present application;

[0024] Figure 5 A schematic diagram of the structure of the server provided in an embodiment of the present application.

[0025] Icons: 101 - return processing module; 102 - quota determination module; 103 - product prediction module; 104 - discount reissue module; 201 - memory; 202 - processor; 203 - communication unit; 204 - system bus. DETAILED DESCRIPTION

[0026] To make the objectives, technical solutions, and advantages of the embodiments of the present application more clear, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Generally, the components of the embodiments of the present application described and shown in the drawings herein can be arranged and designed in various different configurations.

[0027] Therefore, the following detailed description of the embodiments of the present application provided in the accompanying drawings is not intended to limit the scope of the present application for protection, but merely represents selected embodiments of the present application. All other embodiments obtained by persons of ordinary skill in the art based on the embodiments in the present application without creative work are within the scope of protection of the present application.

[0028] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, it does not require further definition or explanation in subsequent drawings.

[0029] In the description of this application, it should be noted that the terms "first", "second", "third", etc. are used only to distinguish descriptions and should not be understood as indicating or implying relative importance. In addition, the terms "comprises", "comprising" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article or device comprising the element.

[0030] As introduced in the background technology, when a user uses a coupon to place an order and finds quality problems when receiving the goods, he needs to apply for a refund for part of the goods. Currently, most e-commerce platforms handle coupon refunds in a way that either refunds the entire amount or does not refund the entire amount. Even if the coupon is refunded, it is often difficult for the user to use the refunded coupon in a timely manner, resulting in a waste of the coupon.

[0031] For example, assume that a target user purchased 1 product A for 20 yuan, 1 product B for 30 yuan, and 1 product C for a total of 40 yuan. When submitting the order, he used a coupon for 15 yuan off for purchases over 50 yuan, so the actual total price paid by the user is: 20+30+40-15=75 yuan.

[0032] After receiving the product, the target user is dissatisfied with Product C and initiates an online return request for Product C. This return request triggers the system to either return a 15-yuan coupon to Product C or no coupon at all. If the coupon is returned to Product C but the target user returns Product C, it means the target user is unlikely to purchase Product C again, resulting in the returned coupon remaining unused for an extended period of time.

[0033] If the coupon is not returned and the discount amount for unreturned items is not adjusted, the target user can use this loophole to place orders together to reach the threshold for using the coupon, and then return the goods, thereby harming the merchant's interests. If the coupon is not returned but the discount amount for unreturned items is appropriately adjusted, the target user's interests will be harmed.

[0034] It should be noted that the defects existing in the solutions in the above-mentioned prior art are the results obtained by the inventors after practice and careful research. Therefore, the discovery process of the above-mentioned problems and the solutions proposed in the embodiments of this application below for the above-mentioned problems should be the contributions made by the inventors to this application in the process of invention and creation, and should not be understood as technical contents known to technical personnel in this field.

[0035] In view of this, the present embodiment provides a coupon reissue method for reissuing coupons of appropriate amounts based on the circumstances of the returned goods and improving the utilization rate of the coupons. The server implementing the method may be a single server or a server group. The server group may be centralized or distributed (for example, the server may be a distributed system). In some embodiments, the server may be local or remote relative to the user terminal. In some embodiments, the server may be implemented on a cloud platform; as an example only, the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud (Community Cloud), a distributed cloud, an inter-cloud (Inter-Cloud), a multi-cloud (Multi-Cloud), etc., or any combination thereof. In some embodiments, the server may be implemented on an electronic device having one or more components.

[0036] Based on the above introduction, the following Figure 1 The coupon reissue method provided in this embodiment is described in detail. However, it should be understood that the operations in the flowchart can be implemented in a non-sequential manner, and steps that have no logical contextual relationship can be reversed or implemented simultaneously. In addition, those skilled in the art can add one or more other operations to the flowchart, or remove one or more operations from the flowchart, guided by the content of this application. Figure 1 As shown, the method includes:

[0037] S101, receiving a return operation from a target user.

[0038] S102, responding to the return operation, determining the preferential amount that needs to be returned for the returned product.

[0039] In an optional implementation manner, step S102 includes the following specific implementation manners:

[0040] S102-1, responding to the return operation and determining the shopping order to which the returned product belongs;

[0041] S102-2, obtaining the total discount amount enjoyed by the shopping order;

[0042] S102-3, based on the proportion of the total price of the returned goods in the total price of the shopping order, determine the discount amount that needs to be returned for the returned goods from the total discount amount, wherein the total price of the shopping order does not enjoy the total discount amount.

[0043] Among them, in the optional implementation method of step S102-3, the server first determines whether the remaining goods in the shopping order can continue to enjoy the total discount amount after the returned goods are returned; if so, the discount amount that needs to be returned for the returned goods is determined from the total discount amount based on the proportion of the total price of the returned goods in the corresponding total price of the shopping order.

[0044] For example, suppose a target user's shopping order includes one item A for 20 yuan, one item B for 30 yuan, and one item C for 40 yuan. The total price of the shopping order is 20 + 30 + 40 = 90 yuan. The target user uses a cash coupon (discount of 15 yuan, coupon code DM0000120115) when paying. The target user only needs to pay 20 + 30 + 40 - 15 = 75 yuan. If the target user selects item C as the returned item, the discount credit for the returned item is 40 / (20 + 30 + 40) * 15 = 6.67 yuan. After rounding up, the actual coupon amount required is 6 yuan.

[0045] For example, assume the target user's shopping order includes one item A for 20 yuan, one item B for 30 yuan, and two items C for a total of 40 yuan. The total price of the shopping order is 20 + 30 + 40 = 90 yuan. The target user used a cash coupon (discount of 15 yuan, coupon code DM0000120115) when paying. The target user only needs to pay 20 + 30 + 40 - 15 = 75 yuan. If the target user selects item C as the returned item, the discount amount to be refunded for the returned item is 40 / (20 + 30 + 40) * 15 / 2 = 3.34 yuan. After rounding up, the actual coupon amount to be reissued is 3 yuan.

[0046] For example, assuming the target user purchased one item A for 20 yuan, one item B for 30 yuan, and two items C for a total of 40 yuan, the total price of the shopping order is 20+30+40=90 yuan. The target user used a discount coupon (15 yuan off for purchases over 50 yuan, coupon code DM0000120604) when paying, so the target user only needs to pay 20+30+40-15=75 yuan. If the target user selects item C as the returned item, the discount amount to be refunded for the returned item is 40 / (20+30+40)*15 / 2=3.34 yuan, and the actual coupon amount to be reissued after rounding is 3 yuan. It is worth noting that if the target user returns one item B and two items C, and the total price of the remaining items in the shopping order is less than 50, the remaining item A cannot trigger the discount coupon, so the coupon will not be reissued.

[0047] For example, suppose a target user purchased one item A for 20 yuan, one item B for 30 yuan, and two items C for a total of 40 yuan. The total price of the shopping order is 20 + 30 + 40 = 90 yuan. The target user used a discount coupon (15 yuan off for purchases over 50 yuan, coupon code DM000040125) and a cash coupon (10 yuan off, coupon code DM000018201) when paying. The target user only needs to pay 20 + 30 + 40 - 15 - 10 = 65 yuan. If the target user later selects one item B and one item C as the returned items, the total price is 20 + 30 + 40 - 15 - 10 = 65 yuan.

[0048] For the discount coupons, the discount amount that needs to be returned for these two returned products is:

[0049] 30 / (20+30+40)*15=5

[0050] 40 / (20+30+40)*15=6.67

[0051] 5+1 / 2*6.67=8.34

[0052] For cash coupons, the discount amount that needs to be returned for these two returned products is:

[0053] 30 / (20+30+40)*10=3.33

[0054] 40 / (20+30+40)*10=4.44

[0055] 3.33+1 / 2*4.44=5

[0056] The above example describes how to calculate the amount of discount that needs to be returned for returned goods. Figure 1 , the method further comprises:

[0057] S103: predicting the target product that the target user will purchase based on the historical shopping behavior information of the target user.

[0058] The historical shopping behavior information includes the number of times the target user browsed and purchased multiple candidate products. Step S103 includes the following specific implementation methods:

[0059] S103 - 1 , obtaining purchase expectations of the plurality of candidate commodities according to the number of views and purchases of the plurality of candidate commodities.

[0060] In this embodiment, the server calculates the percentage of page views of each candidate product based on the page views of the candidate products. Specifically, the server performs a weighted summation of the page views of the candidate products to obtain the equivalent total page views. The server then calculates the equivalent page views of each candidate product based on the page views of each candidate product and its weight. Finally, the server calculates the percentage of page views of each candidate product based on the ratio of the equivalent page views of each candidate product to the equivalent total page views.

[0061] In this example, the server calculates the purchase frequency ratios for each candidate product based on the purchase frequency of each candidate product. Specifically, the server performs a weighted summation of the purchase frequency of each candidate product to obtain the equivalent total purchase frequency. The server then calculates the equivalent purchase frequency for each candidate product based on the purchase frequency of each candidate product and the candidate product's weight. The server then calculates the purchase frequency ratio for each candidate product based on the ratio of the equivalent purchase frequency of each candidate product to the equivalent total purchase frequency.

[0062] After calculating the browsing ratio and the purchase ratio of each candidate product, the server performs a weighted summation of the browsing ratio and the purchase ratio of each candidate product to obtain the purchase expectation of each candidate product.

[0063] S103-2, based on the purchase expectations of the plurality of candidate commodities, the candidate commodity with the greatest purchase expectation is selected as the target commodity.

[0064] It is worth noting that the multiple candidate products in this embodiment can refer to specific products, such as brand A's serums and creams, brand B's jackets and hiking boots, and brand C's diapers, milk powder, and toys. Of course, the multiple candidate products can also refer to specific product categories, such as beauty and skincare, outdoor sports, home goods, maternity and baby products, office supplies, clothing and shoes, food and beverages, and digital computers.

[0065] The following uses commodity categories as an example to provide specific examples to illustrate the purchase expectations of each candidate commodity. Figure 2 As shown, the target user's shopping behavior (browsing and purchasing) of candidate products is used as a horizontal analysis indicator, and corresponding weights are assigned to each. Then, the shopping preferences (number of views and number of purchases) are used as vertical analysis indicators, thereby analyzing the target user's purchasing expectations from both horizontal and vertical dimensions.

[0066] Among them, in the horizontal dimension, the weights of the number of views and the number of purchases are shown in the following table:

[0067] Shopping behavior Weight Browse 0.30 Buy 0.70

[0068] In the vertical dimension, the target user's preferences for various candidate products are correlated with their gender and age. This means that for the same candidate product, there are significant differences in preference among users of different age groups; similarly, there are differences in preference among users of different genders. For example, for target user ID 14112, the number of times they viewed and purchased various candidate products in the past three months is shown in the following table:

[0069] User ID Product categories Views Number of purchases 14112 Beauty and Skincare 30 2 14112 Outdoor Sports 20 0 14112 Home Furnishings 35 3 14112 Mother and baby 10 1 14112 Office 5 0 14112 Clothing and shoes 108 5 14112 Food and Beverages 20 1 14112 digital computer 5 0 ... ... ... ...

[0070] Assuming that the target user with ID 14112 is female and aged between 20 and 34, the target user's preference for multiple candidate products is represented by weights. The specific details are shown in the following table:

[0071]

[0072] The target user's purchase expectation for each candidate product is calculated according to the following mathematical expression:

[0073]

[0074] R i represents the purchase expectation of the i-th candidate product, for example, clothing and shoes;

[0075] B i represents the number of views of the i-th candidate product, for example, the number of views of clothing and shoes is 108;

[0076] B n Indicates the number of views of the nth candidate product;

[0077] W i represents the weight of the i-th candidate product, for example, the weight of clothing and shoes is 3;

[0078] W n Indicates the weight of the nth candidate product;

[0079] W bh Indicates the weight of the browsing behavior, for example, 0.3 in this embodiment;

[0080] P i represents the number of purchases of the i-th candidate product, for example, the number of purchases of clothing and shoes is 7;

[0081] P n Indicates the number of purchases of the nth candidate product;

[0082] W ph Indicates the weight of the shopping behavior, for example, in this embodiment, it is 0.7.

[0083] Based on the above expression, we continue to use clothing and footwear as an example and combine the parameters in the above table to provide a specific calculation process for the purchase expectation of clothing and footwear:

[0084] Percentage of views:

[0085] 108*3 / (3*30+0.5*20+2*35+1*10+0.3*5+3*108+0.1*20+0.1*5)=0.637795276.

[0086] Purchase frequency ratio:

[0087] 7*3 / (3*2+0.5*1+2*3+1*2+0.3*1+3*7+0.1*1+0.1*1)=0.583333333

[0088] Purchase expectations:

[0089] 0.637795276*0.3+0.583333333*0.7=0.599671916

[0090] For each candidate product, repeat the above calculation process to get the following Figure 3 The purchase expectation of each candidate product is shown, among which the clothing and footwear with the greatest purchase expectation are selected as the target product.

[0091] Based on the above introduction to purchase expectations, continue to see Figure 1 , the method further comprises:

[0092] S104: reissue the coupon for the target product to the target user.

[0093] The coupon has a discount amount. In this way, a coupon with an appropriate amount is reissued based on the total price of the returned goods, and a coupon with a corresponding discount amount is issued for the target goods that the target user is about to purchase, thereby improving the utilization rate of the coupon.

[0094] The above embodiment introduces a coupon reissue method. Based on the same inventive concept, this embodiment also provides a coupon reissue device. The coupon reissue device includes at least one software function module that can be stored in the memory 201 in software form or solidified in the operating system (OS) of the server. The processor 202 in the server is used to execute the executable module stored in the memory 201. For example, the software function modules and computer programs included in the coupon reissue device. Please refer to Figure 4 From a functional perspective, the coupon reissue device may include:

[0095] The return processing module 101 is used to receive a return operation from a target user.

[0096] In this embodiment, the return processing module 101 is used to implement Figure 1 For a detailed description of step S101, please refer to the detailed description of step S101.

[0097] The credit determination module 102 is used to respond to a return operation and determine the credit amount that needs to be refunded for the returned product.

[0098] In this embodiment, the credit limit determination module 102 is used to implement Figure 1 For a detailed description of the credit limit determination module 102, please refer to the detailed description of step S102.

[0099] The commodity prediction module 103 is used to predict the target commodity that the target user will purchase based on the historical shopping behavior information of the target user.

[0100] In this embodiment, the commodity prediction module 103 is used to implement Figure 1 For a detailed description of the commodity prediction module 103 , please refer to the detailed description of step S103 .

[0101] The discount reissue module 104 is configured to reissue a coupon for a target product to a target user, wherein the coupon has a discount amount.

[0102] In this embodiment, the preferential reissue module 104 is used to implement Figure 1 For a detailed description of the preferential reissue module 104, please refer to the detailed description of step S104.

[0103] It is worth noting that, since the invention concept is the same as that of the coupon reissue method, the return processing module 101, the amount determination module 102, the discount reissue module 104 and the product prediction module 103 included in the coupon reissue device can also be used to try other steps or sub-steps of the method, and this embodiment does not make specific limitations on this.

[0104] In addition, the functional modules in each embodiment of the present application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0105] It should also be understood that if the above embodiments are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application.

[0106] Therefore, this embodiment further provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, the coupon reissue method provided in this embodiment is implemented. The computer-readable storage medium can be any medium capable of storing program code, such as a USB flash drive, a mobile hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0107] Please refer to Figure 5 This embodiment further provides a server, which may include a processor 202 and a memory 201. Furthermore, the memory 201 stores a computer program, and the processor implements the coupon reissue method provided in this embodiment by reading and executing the computer program corresponding to the above embodiment in the memory 201.

[0108] Continue to see Figure 5 The server further includes a communication unit 203. The memory 201, the processor 202 and the communication unit 203 are electrically connected to each other directly or indirectly via a system bus 204 to achieve data transmission or interaction.

[0109] The memory 201 may be an information recording device based on any electronic, magnetic, optical or other physical principles, for recording execution instructions, data, etc. In some embodiments, the memory 201 may be, but is not limited to, a volatile memory, a non-volatile memory, a storage drive, etc.

[0110] In some embodiments, the volatile memory may be a random access memory (RAM); in some embodiments, the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable read-only memory (EEPROM), a flash memory, etc.; in some embodiments, the storage drive may be a magnetic disk drive, a solid-state drive, any type of storage disk (such as a CD, DVD, etc.), or a similar storage medium, or a combination thereof.

[0111] The communication unit 203 is used to send and receive data through a network. In some embodiments, the network may include a wired network, a wireless network, a fiber optic network, a telecommunications network, an intranet, the Internet, a local area network (LAN), a wide area network (WAN), a wireless local area network (WLAN), a metropolitan area network (MAN), a wide area network (WAN), a public switched telephone network (PSTN), a Bluetooth network, a ZigBee network, or a near field communication (NFC) network, or any combination thereof. In some embodiments, the network may include one or more network access points. For example, the network may include a wired or wireless network access point, such as a base station and / or a network switching node, through which one or more components of the service request processing system can connect to the network to exchange data and / or information.

[0112] The processor 202 may be an integrated circuit chip having signal processing capabilities, and the processor may include one or more processing cores (e.g., a single-core processor or a multi-core processor). By way of example only, the processor may include a central processing unit (CPU), an application-specific integrated circuit (ASIC), an application-specific instruction set processor (ASIP), a graphics processing unit (GPU), a physical processing unit (PPU), a digital signal processor (DSP), a field programmable gate array (FPGA), a programmable logic device (PLD), a controller, a microcontroller unit, a reduced instruction set computer (RISC), or a microprocessor, or any combination thereof.

[0113] It should be understood that the devices and methods disclosed in the above embodiments may also be implemented in other ways. The device embodiments described above are merely illustrative. For example, the flowcharts and block diagrams in the accompanying drawings show the possible architectures, functions, and operations of the devices, methods, and computer program products according to multiple embodiments of the present application. In this regard, each box in the flowchart or block diagram may represent a module, a program segment, or a portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box may also occur in an order different from that marked in the accompanying drawings. For example, two consecutive boxes may actually be executed substantially in parallel, or they may sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of boxes in the block diagram and / or flowchart, may be implemented using a dedicated hardware-based system that performs a specified function or action, or may be implemented using a combination of dedicated hardware and computer instructions.

[0114] The above descriptions are merely examples of various embodiments of the present application, but the scope of protection of the present application is not limited thereto. Any modifications or substitutions that can be readily conceived by a person skilled in the art within the technical scope disclosed in the present application should be included within the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

Claims

1. A coupon reissue method, characterized in that: The method comprises: Receive return operations from target users; In response to the return operation, determine the shopping order to which the returned product belongs; Obtain the total discount amount enjoyed by the shopping order; Determine whether the remaining products in the shopping order can continue to enjoy the total discount amount after the returned products are returned; If so, determining the amount of discount to be refunded for the returned goods from the total discount amount based on the proportion of the total price of the returned goods in the total price of the shopping order, wherein the total price of the shopping order does not enjoy the total discount amount; Predicting target products that the target user will purchase based on the target user's historical shopping behavior information; A coupon for the target product is reissued to the target user, wherein the coupon has the discount amount.

2. The coupon reissue method according to claim 1, characterized in that: The historical shopping behavior information includes the number of times the target user browsed and purchased a plurality of candidate commodities. The predicting of the target commodity that the target user will purchase based on the historical shopping behavior information of the target user includes: Obtaining purchase expectations for each of the multiple candidate commodities based on the number of views and purchases of the multiple candidate commodities; According to the purchase expectations of the plurality of candidate commodities, the candidate commodity with the greatest purchase expectation is selected as the target commodity.

3. The coupon reissue method according to claim 2, characterized in that: Obtaining the purchase expectations of each of the plurality of candidate commodities according to the number of views and the number of purchases of the plurality of candidate commodities includes: Obtaining a percentage of each of the plurality of candidate products based on the number of times the plurality of candidate products have been viewed; Obtaining a purchase frequency ratio of each of the multiple candidate commodities based on the purchase frequency of the multiple candidate commodities; The proportion of browsing times and purchase times of each candidate product are weighted and summed to obtain the purchase expectation of each candidate product.

4. The coupon reissue method according to claim 3, characterized in that: Obtaining a percentage of the number of views of each of the plurality of candidate products according to the number of views of the plurality of candidate products includes: Performing a weighted summation on the number of views of the multiple candidate products to obtain an equivalent total number of views; Obtaining the equivalent number of views for each candidate product based on the number of views for each candidate product and the weight of the candidate product; The ratio of the equivalent number of views of each candidate product to the equivalent total number of views is taken as the view count ratio of each candidate product.

5. The coupon reissue method according to claim 3, characterized in that: Obtaining a purchase frequency ratio of each of the multiple candidate commodities according to the purchase frequency of the multiple candidate commodities includes: Performing a weighted summation on the purchase counts of the multiple candidate products to obtain an equivalent total purchase count; Obtaining the equivalent number of purchases for each candidate product based on the number of purchases for each candidate product and the weight of the candidate product; The ratio of the equivalent purchase times of each candidate product to the equivalent total purchase times is respectively used as the purchase times ratio of each candidate product.

6. A coupon reissue device, characterized in that: The device comprises: Return processing module, used to receive return operations from target users; A credit determination module, configured to respond to the return operation and determine the shopping order to which the returned product belongs; Obtain the total discount amount enjoyed by the shopping order; Determine whether the remaining products in the shopping order can continue to enjoy the total discount amount after the returned products are returned; If so, determining the amount of discount to be refunded for the returned goods from the total discount amount based on the proportion of the total price of the returned goods in the total price of the shopping order, wherein the total price of the shopping order does not enjoy the total discount amount; A commodity prediction module is used to predict the target commodity that the target user will purchase based on the historical shopping behavior information of the target user; The discount reissue module is used to reissue the coupon of the target product to the target user, wherein the coupon has the discount amount.

7. A storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed by the processor, the coupon reissue method according to any one of claims 1 to 5 is implemented.

8. A server, characterized in that: The server includes a processor and a memory, wherein the memory stores a computer program. When the computer program is executed by the processor, the coupon reissue method according to any one of claims 1 to 5 is implemented.

Images