E-commerce cost management method, device, equipment, medium and product

Abstract

The invention provides an e-commerce expense management method and device, equipment, a medium and a product, and relates to the technical field of data management, and the method comprises the steps: determining the business type of a sales subject; according to the business type, order data of the sales subject is monitored in real time, and the type of the order data corresponds to the business type; according to the currently monitored order data, carrying out statistics on the use condition of the depreciation cost from at least one dimension of a sales subject dimension, a business type dimension, an order dimension and a commodity category dimension; executing at least one of the following operations according to the use condition of the depreciation cost counted in a statistical period: performing automatic settlement processing on the depreciation cost in the statistical period through docking with a financial marketing cost system; a suggested transaction unit price for a product related to the order data is generated. Therefore, the low-cost, real-time and accurate statistics and management of the e-commerce cost are realized.

Description

Technical Field

[0001] This application relates to the field of data management technology, and in particular to an e-commerce fee management method, apparatus, equipment, medium and product. Background Technology

[0002] Currently, businesses manage product sales expenses by having shops on various e-commerce platforms report sales data, which is then manually compiled by staff for expense management. However, the inconsistent data formats across different platforms make manual data compilation difficult, and manual data collection suffers from inaccuracies, timeliness, and high costs. Summary of the Invention

[0003] This application provides an e-commerce expense management method, apparatus, equipment, medium, and product, which solves the problems of high difficulty, high cost, low accuracy, and low timeliness in the current manual management of e-commerce expenses.

[0004] Firstly, to achieve the above objectives, embodiments of this application provide an e-commerce fee management method, comprising: Determine the business type of the sales entity; Based on the business type, the order data of the sales entity is monitored in real time, wherein the type of the order data corresponds to the business type; Based on the currently monitored order data, the usage of price reduction fees is statistically analyzed from at least one of the following dimensions: sales entity, business type, order, and product category. Based on the usage of the price reduction fees as statistically analyzed within a statistical period, perform at least one of the following operations: By connecting with the financial and marketing expense system, the price reduction expenses within the statistical period are automatically closed. Generate a suggested transaction price for the product associated with the order data.

[0005] The business types include at least one of the following: direct supply type, direct supply dropshipping type, consignment type, direct operation type, and direct operation warehousing type; When the business type is the direct sales type, the direct sales warehousing type, the consignment type, or the direct supply and distribution type, the order data type includes sales orders and / or after-sales orders; When the business type is direct supply, the order data type includes purchase sales orders and / or after-sales orders.

[0006] Specifically, based on the currently monitored order data, the usage of price reduction fees is statistically analyzed from at least one of the following dimensions: sales entity, business type, order, and product category. Based on the product code field in the currently monitored order data, obtain the standard unit price corresponding to the order data; If the type of the currently monitored order data is a sales order, the amount of the price reduction fee corresponding to the order data is determined based on the standard unit price, the product quantity field and the actual payment price field in the order data. If the type of the currently monitored order data is a purchase and sales order, the amount of the price reduction fee corresponding to the order data is determined based on the standard unit price, the product quantity field and the actual payment amount field in the order data. If the type of the currently monitored order data is an after-sales order, the amount of the price reduction fee corresponding to the order data is determined based on the product quantity field in the after-sales order and the actual payment unit price corresponding to the sales order or purchase order associated with the after-sales order. Based on the amount of price reduction fees used corresponding to the order data, the usage of the price reduction fees is statistically analyzed from at least one of the following dimensions: the sales entity dimension, the business type dimension, the order dimension, and the product category dimension.

[0007] Specifically, based on the product code field in the currently monitored order data, the standard unit price corresponding to the order data is obtained, including: If the product corresponding to the product code field is a product other than the pre-set target product category, obtain the standard unit price.

[0008] The method further includes, after analyzing the usage of price reduction fees based on the currently monitored order data from at least one of the following dimensions: sales entity, business type, order, and product category, the method also includes: Obtain the commission information input by the first user; wherein, the first user is the user corresponding to the brand owner; Based on the commission information, a price adjustment order is generated; wherein, the price adjustment order includes price adjustment sales orders and price adjustment after-sales orders; Based on the amount field in the adjusted sales order and the amount field in the adjusted after-sales order, adjust the usage of the currently statistically analyzed price reduction fees.

[0009] The method further includes, after analyzing the usage of price reduction fees based on the currently monitored order data from at least one of the following dimensions: sales entity, business type, order, and product category, the method also includes: Based on the usage of the price reduction fees statistically analyzed from the perspective of the sales entity, obtain the amount of the price reduction fees already used by the sales entity; If the ratio of the amount of price reduction fees already used by the sales entity to the amount of price reduction fees applied for by the sales entity is greater than a first threshold, then a warning message will be sent to the user corresponding to the sales entity.

[0010] Specifically, based on the usage of the price reduction expenses statistically analyzed within a statistical period, and through integration with the financial marketing expense system, the price reduction expenses within the statistical period are automatically closed out, including: If the sales entity has not applied for a price reduction fee, perform any of the following operations: If the amount of price reduction expenses already used by the sales entity is greater than zero, a first request is sent to the financial marketing expense system. The first request is used to request an additional amount of price reduction expenses. If the amount of price reduction fees already used by the sales entity is less than zero, the amount of price reduction fees already used by the sales entity will be transferred back to the target sales entity. If the sales entity has already applied for a price reduction fee, perform any of the following operations: If the amount of price reduction fee already used by the sales entity is greater than zero, a second request is sent to the financial marketing expense system. The second request is used to request the closure of the application line for the price reduction fee amount. The second request is also used to request additional price reduction fee amount based on the amount of price reduction fee already used by the sales entity. If the amount of price reduction fee already used by the sales entity is zero, a third request is sent to the financial marketing expense system, wherein the third request is used to request the closure of the application line for the price reduction fee amount; If the amount of price reduction fees already used by the sales entity is less than zero, the third request is sent to the financial marketing expense system, and the amount of price reduction fees already used by the sales entity is transferred back to the target sales entity.

[0011] The method further includes, after analyzing the usage of price reduction fees based on the currently monitored order data from at least one of the following dimensions: sales entity, business type, order, and product category, the method also includes: At a preset time point within a statistical period, obtain the amount of price reduction fees currently used by the sales entity; Based on the amount of price reduction fees currently used, the amount of price reduction fees used in the previous statistical period adjacent to the current statistical period, and the amount of price reduction fees used in the Nth statistical period of the previous year adjacent to this year, the amount of price reduction fees for the next statistical period adjacent to the current statistical period is estimated; wherein, the current statistical period is the Nth statistical period of this year, and N is an integer; A fourth request is sent to the financial marketing expense system, the fourth request being used to apply for a price reduction expense limit for the next statistical period adjacent to the current statistical period.

[0012] Specifically, based on the usage of the price reduction fees statistically analyzed within a statistical period, a suggested transaction price for the product related to the order data is generated, including: Based on the usage of the price reduction expenses within a statistical period, summarize the amount of price reduction expenses used for the same type of product; Based on the standard unit price of the same type of products, the sales quantity of the same type of products in the statistical period, and the amount of price reduction expenses used for the same type of products, the transaction unit price of the same type of products in the statistical period is determined; Based on the transaction unit price, the suggested transaction unit price is generated, which is used to guide sales personnel in setting the actual transaction unit price for the sales entity.

[0013] Secondly, to achieve the above objectives, embodiments of this application provide an e-commerce fee management device, comprising: The determination module is used to determine the business type of the sales entity; The monitoring module is used to monitor the order data of the sales entity in real time according to the business type, wherein the type of the order data corresponds to the business type; The statistics module is used to analyze the usage of price reduction fees based on the currently monitored order data, from at least one of the following dimensions: sales entity, business type, order, and product category. The processing module is configured to perform at least one of the following operations based on the usage of the price reduction fees as statistically analyzed within a statistical period: By connecting with the financial and marketing expense system, the price reduction expenses within the statistical period are automatically closed. Generate a suggested transaction price for the product associated with the order data.

[0014] Thirdly, to achieve the above objectives, embodiments of this application provide an e-commerce fee management device, including a transceiver, a processor, a memory, and a program stored in the memory and executable on the processor; the transceiver sends and receives data under the control of the processor, and the processor executes the program to implement the e-commerce fee management method as described in the first aspect.

[0015] Fourthly, to achieve the above objectives, embodiments of this application provide a readable storage medium having a program or instructions stored thereon, which, when executed by a processor, implement the e-commerce fee management method as described in the first aspect.

[0016] Fifthly, to achieve the above objectives, embodiments of this application provide a computer program product, including computer instructions, which, when executed by a processor, implement the e-commerce fee management method as described in the first aspect.

[0017] The beneficial effects of the above technical solution in this application are as follows: In the embodiments of this application, firstly, the business type of the sales entity is determined; secondly, based on the business type, the order data of the sales entity is monitored in real time, wherein the type of the order data corresponds to the business type; thus, automated monitoring of different types of order data for different business types is achieved, solving the problem of inconsistent data reporting formats caused by different platform usage standards, which makes manual statistics difficult; thirdly, based on the currently monitored order data, the usage of price reduction fees is statistically analyzed from at least one dimension: sales entity, business type, order, and product category; thus, intelligent statistical analysis of the usage of price reduction fees for the sales entity is achieved from different dimensions, improving the accuracy and timeliness of data statistics and reducing statistical costs; finally, based on the usage of price reduction fees statistically analyzed within a statistical period, at least one of the following operations is performed: automatically closing the price reduction fees within the statistical period through integration with the financial marketing expense system; generating a suggested transaction price for products related to the order data. Thus, through interaction with the financial marketing expense system, automated management of the financial process is achieved, reducing data errors caused by manual operation. Attached Figure Description

[0018] Figure 1 This is a flowchart illustrating the e-commerce fee management method according to an embodiment of this application; Figure 2 This is a schematic diagram illustrating the usage of price reduction fees from the perspective of business type in an embodiment of this application; Figure 3 This is a schematic diagram illustrating the usage of price reduction fees from the perspective of the sales entity in this application embodiment; Figure 4 This is a schematic diagram of the e-commerce fee management device according to an embodiment of this application; Figure 5 This is a schematic diagram of the e-commerce fee management device according to an embodiment of this application. Detailed Implementation

[0019] To make the technical problems, technical solutions and advantages of this application clearer, a detailed description will be provided below in conjunction with the accompanying drawings and specific embodiments.

[0020] It should be understood that the phrase "one embodiment" or "an embodiment" throughout the specification means that a specific feature, structure, or characteristic related to the embodiment is included in at least one embodiment of this application. Therefore, "in one embodiment" or "in an embodiment" appearing throughout the specification does not necessarily refer to the same embodiment. Furthermore, these specific features, structures, or characteristics can be combined in any suitable manner in one or more embodiments.

[0021] In the various embodiments of this application, it should be understood that the sequence number of each process described below does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0022] In addition, the terms "system" and "network" are often used interchangeably in this article.

[0023] In the embodiments provided in this application, it should be understood that "B corresponding to A" means that B is associated with A, and B can be determined based on A. However, it should also be understood that determining B based on A does not mean that B is determined solely based on A, but can also be determined based on A and / or other information.

[0024] Embodiments of this application provide an e-commerce fee management method, such as... Figure 1 As shown, the method includes: Step 101: Determine the business type of the sales entity; for example, the sales entity includes entities that sell products (such as milk powder), such as stores and e-commerce platforms.

[0025] Step 102: Monitor the order data of the sales entity in real time according to the business type, wherein the type of the order data corresponds to the business type.

[0026] As a specific implementation method, the business type includes at least one of the following: direct supply type, direct supply dropshipping type, consignment type, direct operation type, and direct operation warehousing type. The following is a description of each of the above business types: Direct-operated type: The brand owner directly operates the stores, and the goods are shipped directly from the brand owner's own warehouse to consumers. The ownership of the warehouse belongs to the brand owner, and the brand owner and consumers settle accounts based on actual sales.

[0027] Direct-operated warehousing type: The brand directly operates the store, and the goods are sent to external warehouses (such as JD.com warehouses, Cainiao warehouses, etc.). The external warehouses handle the logistics and deliver the goods to consumers. The ownership of the goods in the external warehouses belongs to the brand, and the brand settles accounts with the consumers based on actual sales.

[0028] Direct supply type: Brands directly supply goods to e-commerce platforms, and the goods are delivered to the e-commerce platform's warehouse, from which the platform directly ships the goods to consumers. In this case, the ownership of the goods belongs to the platform, and the brand and the e-commerce platform settle accounts on a payment basis, which is a buyout model.

[0029] Direct supply and dropshipping type: The company directly supplies goods to the platform, and the company drops-ships the goods to consumers. In this case, the brand and the e-commerce platform settle accounts based on actual sales.

[0030] Consignment type: The brand stores the goods in the e-commerce platform's warehouse, and the e-commerce platform's warehouse ships the goods directly to the consumer. In this case, the brand owns the goods, and the brand settles the actual sales with the e-commerce platform.

[0031] Wherein, when the business type is the direct sales type, the direct sales warehousing type, the consignment type, or the direct supply and distribution type, the order data type includes sales orders and / or after-sales orders; for example, a sales order includes at least some of the following fields: order number, product code, purchase quantity, actual payment price, coupon code, coupon amount, commission type, commission amount, whether there is an invoice, etc.; wherein, the "whether there is an invoice" field is used to indicate whether an invoice is issued for the sales order.

[0032] Wherein, when the business type is direct supply, the order data type includes purchase sales orders and / or after-sales orders. For example, a purchase sales order may include at least some of the following fields: direct supply e-commerce platform, purchase order number, purchase amount, purchased product code, purchase quantity, actual payment amount, actual purchase quantity, etc. For example, an after-sales order may include at least some of the following fields: basic information (including subfields such as the original order number associated with the after-sales order, after-sales order number, after-sales order creator, store name, after-sales order status, store type / business type, original order source, and after-sales order submission time), member information (including subfields such as member code and member name), after-sales reason (including subfields such as after-sales type, receipt status, after-sales reason, remarks, uploaded after-sales pictures, and uploaded after-sales videos), and after-sales product (including the applied after-sales product code, applied after-sales product name, defect, original order quantity, original order actual points used, original order amount, physical product code, physical quantity, after-sales unit price, after-sales amount, applied after-sales quantity, platform actual refund amount, and platform actual refund amount). The data includes subfields such as quantity returned, after-sales product warehouse receipt scan details (including product number, product name, product batch, expiration date, logistics code, points status, issued sub-warehouse, issued font name, original order number, return receipt number, return receipt product amount, etc.), after-sales replacement / reissue products (including replacement / reissue product code, replacement / reissue product name, replacement / reissue product quantity, amount, replacement / reissue order number, replacement / reissue courier company, logistics tracking number, etc.), after-sales delivery address (including recipient name, recipient mobile phone number, detailed address, etc.), after-sales processing records (including return courier company, return courier tracking number, whether the entire order has been refunded points / amount / rights, whether the warehouse has received it, replacement / reissue order number, etc.), etc.

[0033] Step 103: Based on the currently monitored order data, statistically analyze the usage of price reduction fees from at least one of the following dimensions: sales entity, business type, order, and product category. For example, price reduction fees are incurred due to the difference between the standard unit price and the actual transaction price of a product. This enables the statistical analysis and real-time viewing of price reduction fee data for e-commerce business types, stores, product series, SKUs, and various fee scenarios. Product categories can include products of the same category, products of the same series within the same category, etc.

[0034] Step 104: Based on the usage of the price reduction fees as statistically analyzed within a statistical period, perform at least one of the following operations: By integrating with the financial and marketing expense system, the system automatically processes and closes out price reduction expenses within the statistical period. This automates the financial process, reducing manual operations and data entry, thereby minimizing data errors. For example, this step can generate a suggested transaction price based on the usage of price reduction expenses as statistically analyzed from the perspective of the sales entity.

[0035] Generate a suggested transaction price for the product related to the order data. For example, this step can generate a suggested transaction price based on the usage of price reduction fees statistically analyzed from the product category dimension; in this way, the efficiency of e-commerce sales pricing can be effectively improved.

[0036] In the embodiments of this application, firstly, the business type of the sales entity is determined; secondly, based on the business type, the order data of the sales entity is monitored in real time, wherein the type of the order data corresponds to the business type; thus, automated monitoring of different types of order data for different business types is achieved, solving the problem of inconsistent data reporting formats caused by different platform usage standards, making manual statistics difficult; thirdly, based on the currently monitored order data, the usage of price reduction fees is statistically analyzed from at least one dimension: sales entity, business type, order, and product category. This enables real-time and intelligent statistical analysis of the usage of price reduction fees for the sales entity from different dimensions, improving the accuracy and timeliness of data statistics and reducing statistical costs; finally, based on the usage of price reduction fees statistically analyzed within a statistical period, at least one of the following operations is performed: automatically closing the price reduction fees within the statistical period through integration with the financial marketing expense system; generating a suggested transaction price for products related to the order data. Thus, through interaction with the financial marketing expense system, automated management of the financial process is achieved, reducing data errors caused by manual operation.

[0037] As an optional implementation, step 103 involves, based on the currently monitored order data, statistically analyzing the usage of price reduction fees from at least one of the following dimensions: sales entity, business type, order, and product category. This includes: Based on the product code field in the currently monitored order data, obtain the standard unit price corresponding to the order data. For example, the standard unit price can be a pre-set price; for instance, a product standard price list can be configured according to the product category and specific SKU to define the product retail amount (standard unit price). For example, the standard unit price of brand A's B series milk powder is C yuan / can. This step can look up the product code field in a table to obtain the standard unit price of the product corresponding to the product code field.

[0038] When the currently monitored order data is a sales order, the amount of the price reduction fee corresponding to the order data is determined based on the standard unit price, the product quantity field, and the actual payment price field in the order data. For example, this step involves: first, calculating the first difference between the standard unit price and the actual payment price field; second, calculating the product of the first difference and the data in the product quantity field to obtain the amount of the price reduction fee corresponding to the sales order, where the price reduction fee amount is a positive value. When the currently monitored order data is a purchase order, the amount of the price reduction fee corresponding to the order data is determined based on the standard unit price, the product quantity field, and the actual payment amount field in the order data. For example, this step involves: first, calculating the product of the standard unit price and the data in the product quantity field; second, calculating the difference between the data in the purchase order amount field and the aforementioned product to obtain the amount of the price reduction fee corresponding to the purchase order, where the price reduction fee amount is a positive value.

[0039] If the currently monitored order data is an after-sales order, the amount of the price reduction fee corresponding to the order data is determined based on the product quantity field in the after-sales order and the actual payment unit price corresponding to the sales order or purchase order associated with the after-sales order. For example, if the after-sales order is associated with a sales order, this step is as follows: First, obtain the data in the actual payment price field of the sales order associated with the after-sales order; second, calculate the first product of this data and the data in the product quantity field of the after-sales order; third, calculate the second product of the data in the product quantity field of the after-sales order and the corresponding standard unit price; finally, calculate the difference between the second product and the first product to obtain the amount of the price reduction fee corresponding to the after-sales order, wherein the amount of the price reduction fee is negative. When the after-sales order is associated with a purchase and sales order, the steps are as follows: First, obtain the first data in the actual payment amount field of the purchase and sales order associated with the after-sales order. Second, calculate the first product of the data in the product quantity field of the after-sales order and the corresponding standard unit price. Finally, calculate the difference between the first product and the first data to obtain the amount of the price reduction fee corresponding to the after-sales order. The amount of the price reduction fee is negative.

[0040] It's important to clarify here that the after-sales order refers to the order corresponding to the returned goods. The return price reduction fee is the price reduction fee actually received by the brand for the returned goods. Therefore, the corresponding price reduction fee needs to be released based on the actual amount used in the original order from which the returned goods were received. In other words, in a return scenario, the system automatically traces the order back to its source based on the product's actual QR code, finds the original price reduction fee amount used in that order, and calculates the amount of fee to be released based on the actual number of returned goods.

[0041] Based on the amount of price reduction fees used corresponding to the order data, the usage of the price reduction fees is statistically analyzed from at least one of the following dimensions: the sales entity dimension, the business type dimension, the order dimension, and the product category dimension. For example, this step involves summing up the amount of price reduction fees used for all order data corresponding to any of the aforementioned dimensions.

[0042] As a specific implementation method, the step "obtaining the standard unit price corresponding to the order data based on the product code field in the currently monitored order data" in the aforementioned optional implementation method includes: If the product corresponding to the product code field is not a product of a pre-set target category, the standard unit price is obtained. For example, the target category includes promotional items or products from other brands, where the other brands' products are, for example, welfare items. Taking milk powder as an example, the other brands' products might be welfare items such as strollers and baby bottles.

[0043] It should be noted that when brands list products on e-commerce platforms, orders may include promotional items or other brands' products for sale. The costs of these items are not within the scope of the corresponding financial settlement entity's expenses. These products need to be excluded in advance, and the calculation of the expense amount will exclude the calculation of these products.

[0044] Further, as an optional implementation, step 103, after statistically analyzing the usage of price reduction fees from at least one of the following dimensions—sales entity, business type, order, and product category—based on the currently monitored order data, the method further includes: Obtain the commission information input by the first user; wherein, the first user is the user corresponding to the brand owner; for example, the commission information may be the commission provided by the brand owner for live streaming sales, the personal commission for community group buying, personal rebates, small compensation for consumer orders, etc.

[0045] Based on the commission information, an adjustment order is generated; wherein, the adjustment order includes adjustment sales orders and adjustment after-sales orders; wherein, the adjustment order is an order used to adjust the amount used for price reduction fees. The amount in the adjustment sales order or adjustment after-sales order is the same as the amount corresponding to the commission information, but the product quantity in the adjustment sales order or adjustment after-sales order is zero, that is: no products are shipped from the warehouse, nor are any products received into the warehouse.

[0046] Based on the amount fields in the adjusted sales orders and the adjusted after-sales orders, the usage of the currently statistically analyzed price reduction fees is adjusted. For example, when reducing the amount of price reduction fees used, the amount in the adjusted sales orders matches the amount corresponding to the commission information, and the amount in the adjusted after-sales orders is zero. When increasing the amount of price reduction fees used, the amount in the adjusted sales orders is zero, and the amount in the adjusted after-sales orders matches the amount corresponding to the commission information.

[0047] It's important to note that the price reduction fee for adjustment orders varies depending on the e-commerce platform. It may involve live-streaming sales rebates, group-buying commissions, or community commissions. These commissions don't have a formal invoicing process, but they represent actual company expenses. This fee is distributed across each SKU shipped that month in the form of an adjustment order (effectively adjusting the actual transaction price of the SKU). Adjustments can be made by increasing or decreasing the price.

[0048] Based on the above implementation methods, it can be seen that the calculation rule for the price reduction fee in this application embodiment is as follows: The final price reduction fee amount = actual price reduction fee amount - price reduction fee amount for after-sales returns + adjustment amount for this statistical period; where, actual price reduction fee amount = (standard unit price - actual transaction unit price) * actual sales quantity; price reduction fee amount for after-sales returns = (standard unit price - actual transaction unit price corresponding to the return) * actual return quantity; the adjustment amount for this statistical period is the amount corresponding to the aforementioned commission information; where, the adjustment amount for this statistical period is signed data; for each sales order / purchase order, the actual transaction unit price can be the same or different, therefore, the actual price reduction fee amount can be the sum of the price reduction fee amounts corresponding to each sales order / purchase order.

[0049] Furthermore, as another optional implementation, step 103, after statistically analyzing the usage of price reduction fees from at least one of the following dimensions—sales entity, business type, order, and product category—based on the currently monitored order data, the method further includes: Based on the usage of the price reduction fees statistically analyzed from the perspective of the sales entity, obtain the amount of the price reduction fees already used by the sales entity; If the ratio of the amount of price reduction fees already used by the sales entity to the price reduction fee amount applied for by the sales entity is greater than a first threshold, for example, the first threshold is 80%, then a warning message is sent to the users corresponding to the sales entity to remind them to add more price reduction fees or adjust their marketing plans.

[0050] In other words, the above-mentioned optional implementation method is to summarize the total amount of price reduction fees used in the current month at the sales entity level (such as the store level), compare it with the price reduction fee amount applied for in the current month, and support automatic push of usage warnings to the relevant store managers when the amount used exceeds a certain specific percentage.

[0051] As an optional implementation, in step 104 above, based on the usage of the price reduction expenses statistically analyzed within a statistical period, the price reduction expenses within the statistical period are automatically closed through integration with the financial marketing expense system, including: If the sales entity has not applied for a price reduction fee, perform any of the following operations: If the amount of price reduction expenses already used by the sales entity is greater than zero, a first request is sent to the financial marketing expense system. The first request is used to request an additional price reduction expense limit. The additional price reduction expense limit is the amount of price reduction expenses used within the statistical period.

[0052] If the amount of price reduction fees already used by the sales entity is less than zero, the amount of price reduction fees already used by the sales entity will be transferred to the target sales entity; here, "transferring" means, for example, transferring the amount of price reduction fees already used that is less than zero to a specific sales entity. Alternatively, for example, a situation where the amount of price reduction fees already used is less than zero may be when the amount of price reduction fees released by after-sales orders within the current statistical period is greater than the amount of price reduction fees used by sales orders / purchase sales orders.

[0053] If the sales entity has already applied for a price reduction fee, perform any of the following operations: If the amount of price reduction fees already used by the sales entity is greater than zero, a second request is sent to the financial marketing expense system. The second request is used to request the closure of the application line for the price reduction fee amount. The second request is also used to request additional price reduction fee amount based on the price reduction fee amount already used by the sales entity. That is, this step requires closing the price reduction fee amount applied for by the sales entity at the beginning of the statistical period, and re-applying for additional price reduction fee amount based on the actual price reduction fee amount used in the statistical period. In this way, the actual amount of price reduction fees used by the sales entity in the financial marketing expense system can be consistent with the amount of price reduction fees applied for.

[0054] If the sales entity has used zero amount of price reduction fees, a third request is sent to the financial marketing expense system, wherein the third request is used to request the closure of the application line for the price reduction fee amount.

[0055] If the amount of price reduction fees already used by the sales entity is less than zero, the third request is sent to the financial marketing expense system, and the amount of price reduction fees already used by the sales entity is transferred back to the target sales entity.

[0056] In the above-mentioned optional implementation methods, the executing entity of this application embodiment can automatically connect to the financial marketing expense system to achieve automated case closure based on the amount of price reduction expenses used by the sales entity. The case closure process requires comparing the price reduction expense application amount with the previous month's amount. If there are multiple situations such as no application amount, insufficient amount, or excessive amount, the system automatically executes processes such as requesting additional expense, closing excessive expense requests, and re-applying. Specific rules are as follows: 1) If the sales entity (such as a store) does not have an initial price reduction fee application form, but has a price reduction fee usage amount, a price reduction fee release amount corresponding to returns, and an adjustment amount, then the additional fee amount will be calculated according to the aforementioned formula: Final price reduction fee usage amount = Actual price reduction fee usage amount - Price reduction fee usage amount for after-sales returns + Adjustment amount for this statistical period, and the price reduction fee application will be automatically added. 2) If the sales entity (such as a store) has an initial price reduction fee application form, but no price reduction fee usage amount, price reduction fee release amount corresponding to the return, or adjustment amount, then when the fee is added or closed, the data row corresponding to the initial price reduction fee application form will be automatically closed. 3. When the sales entity (such as the distributor) has an initial price reduction fee application form, and has the amount of price reduction fee used, the amount of price reduction fee released for returned goods, and the adjustment amount, the original application form will be automatically closed when the fee is added or closed, and the price reduction fee application will be automatically added according to the aforementioned formula. 4) If the sales entity (such as a distributor) does not have an initial application for price reduction expenses, and there is no amount for price reduction expenses used, no amount for price reduction expenses released corresponding to returns, and no adjustment amount, then the settlement amount will be calculated according to the above formula. Where: ① After settlement according to the formula, if the actual cost amount is positive: the price reduction fee will be automatically applied for based on the positive amount, and the case will be closed according to the amount; ② After calculation according to the formula, the actual cost amount is negative: Scenario A (return amount is greater than the amount reduced this month) and Scenario B (there is a return amount and the distributor has an increase this month), then the stores will be merged according to the designated back-squeezing (all SKUs will be back-squeezed to the designated stores).

[0057] Further, as an optional implementation, step 103, after statistically analyzing the usage of price reduction fees from at least one of the following dimensions—sales entity, business type, order, and product category—based on the currently monitored order data, the method further includes: At a preset time point within a statistical period, obtain the amount of price reduction fees currently used by the sales entity; Based on the currently used price reduction amount, the price reduction amount used in the previous statistical period adjacent to the current statistical period, and the price reduction amount used in the Nth statistical period of the previous year adjacent to this year, the price reduction amount for the next statistical period adjacent to the current statistical period is estimated; where the current statistical period is the Nth statistical period of this year; N is an integer; for example, if the statistical period is one month, and the current statistical period is August 2025, then the price reduction amount used in the previous statistical period adjacent to the current statistical period is the price reduction amount used in July 2025, and the price reduction amount used in the Nth statistical period of the previous year adjacent to this year is the price reduction amount used in August 2024. The specific estimation method can be taking the average, or it can be linear or non-linear fitting.

[0058] A fourth request is sent to the financial marketing expense system, the fourth request being used to apply for a price reduction expense limit for the next statistical period adjacent to the current statistical period.

[0059] In other words, the above optional implementation is as follows: based on the progress of the price reduction expenses used this month and the reference actual price reduction expenses used in the same month last year, the price reduction expense application amount for the following month is automatically estimated at a preset time each month (such as the 25th of each month), and the expense application is automatically completed by connecting with the financial system.

[0060] As a specific implementation, in step 104 above, based on the usage of the price reduction fees statistically analyzed within a statistical period, a suggested transaction price for the product related to the order data is generated, including: Based on the usage of price reduction fees statistically analyzed from the product category dimension, the actual transaction unit price corresponding to the same product category is obtained. For example, this step can be: obtaining the amount of price reduction fees used for the same product category, and calculating the actual transaction unit price for the same product category based on the amount of price reduction fees used and the actual sales quantity corresponding to the same product category; wherein, the amount of price reduction fees used and the actual sales quantity corresponding to the same product category are, for example, the amount of price reduction fees used and the sales quantity corresponding to the sales orders / purchase sales orders within the statistical period.

[0061] Based on the actual transaction price, a suggested transaction price is generated. This suggested transaction price guides sales personnel in setting the actual transaction price for the sales entity. For example, sales personnel can use the suggested transaction price to set the actual transaction price of the product in different operational scenarios, such as discounts, coupons, and commissions, thereby effectively improving the efficiency of e-commerce sales pricing.

[0062] It should be noted here that the entity executing the e-commerce fee management method of this application embodiment can be an e-commerce fee management system / device. For example, the e-commerce fee management system / device may include: The business type configuration module is used to configure the business type of the sales entity. For example, the business type can be configured as described above: direct operation type, direct operation warehousing type, direct supply type, direct supply drop shipping type, and consignment type.

[0063] The rules configuration module is used to configure automatic cost calculation rules for various business types, including configuring the following rules: 1) Configure the statistical dimensions corresponding to each business type: E-commerce fees for direct-sales / direct-sales warehousing / consignment / direct-supply dropshipping business types are statistically analyzed based on sales orders. Specifically, sales order prices and fee-related data can be collected in real time. Specific statistical fields include: order number, product code, quantity purchased, actual payment price, coupon code, coupon amount, commission type, commission amount, and whether an invoice is available. The direct supply business type is statistically analyzed based on the purchase and sales order, and the statistics include relevant expense data related to the purchase price. Specific statistical fields include: direct supply e-commerce platform, purchase order number, purchase amount, purchase product code, purchase quantity, actual payment amount, actual purchase quantity, and other details.

[0064] 2) Standard price of the configured goods: For example, configure a standard price list for products based on product categories and specific SKUs, and define the product retail amount (i.e., standard price).

[0065] 3) Configure statistical rules for each document (sales order, purchase order, return order / after-sales order): The order price reduction fee calculation rule is: product standard price - actual transaction price of the product in the order. It records the usage of price reduction fees for each order and supports aggregation by SKU and store. The calculation rule for price reduction fees in purchase and sales orders is: product standard price - actual transaction amount of purchase order. It records the usage of price reduction fees for each purchase and sales order and supports aggregation by SKU and e-commerce platform. The price reduction fee for returned / after-sales orders is based on the actual amount of returned goods received by the brand. This fee needs to be released according to the actual amount used in the original order from which the returned goods were received. In a return scenario, the system automatically traces the order back to its source using the product's actual QR code, identifies the original price reduction fee amount used for that order, and calculates the amount to be released based on the actual number of returned goods.

[0066] Additionally, for specific product price reduction fees, when brands list their products on e-commerce platforms, orders may include promotional items or other brands' products for sale. These fees are not included in the corresponding financial settlement entity's expense calculations and must be configured in advance to exclude them from the fee statistics. In other words, it's necessary to configure the selection of products that will not be included in the price reduction fee statistics.

[0067] Price reduction fees for adjusted orders vary depending on the e-commerce platform and may include live-streaming sales rebates, group-buying commissions, and community commissions. These commissions lack a formal invoicing process but represent actual costs incurred by the brand. These fees are distributed across each SKU shipped that month in the form of adjusted orders (effectively adjusting the actual transaction price of the SKU). Both increases and decreases are supported.

[0068] The cost monitoring module is used for real-time automatic cost detection, such as... Figure 2 and Figure 3 As shown, specifically: based on the transaction amount and return status of orders from various platforms and e-commerce categories, real-time statistics on price reduction fees are generated, forming real-time statistics on price reduction fees at the business type, store, and order levels. The real-time statistics on price reduction fees by business type are as follows: Figure 2 As shown, the real-time statistics of price reduction costs at the store level are as follows: Figure 3 As shown.

[0069] The early warning module is used to summarize the total amount of price reduction fees for the current month at the store level and compare it with the fees applied for by stores in the current month. It supports automatically pushing usage warnings to the relevant store managers when the amount used exceeds a certain percentage.

[0070] The summary module is used to automatically summarize the amount of price reduction fees used for all shipped SKUs across various business scenarios and stores. The calculation rules are as follows: Final cost amount = Usage amount - Usage amount for after-sales returns (standard factory price - unit price of returned goods) + Adjustment amount for this month (reduction); Final cost amount = Usage amount - Usage amount for after-sales returns (standard factory price - unit price of returned goods) - Adjustment amount for this month (increase).

[0071] In the above-mentioned calculation rules, "the amount of the adjustment this month" is an unsigned number.

[0072] The settlement module is used to automatically add budgets and close accounts through the financial system. Specifically, the settlement module automatically closes accounts based on the amount of e-commerce price reduction expenses used, connecting with the financial marketing expense system. The closing process compares the amount applied for in the previous month. If the applied amount is insufficient, non-existent, or exceeds the limit, the module automatically executes processes such as adding expense requests, closing excess expenses, and reapplying. Specific rules are as follows: 1. If the store does not have an initial expense application form, but has usage amount, return amount, and adjustment amount related to price reduction expenses, then the additional expense amount will be calculated according to the aforementioned formula and the expense application will be automatically added. 2. If a store has an initial expense application form but no usage amount, return amount, or adjustment amount related to the price reduction expense, this application form will be automatically closed when the price reduction expense is added or closed. 3. If the dealer has an initial expense application form, and has the usage amount, return amount, and adjustment amount related to the price reduction expense, when the price reduction expense is added or closed, the original application form will be automatically closed, and the expense application will be automatically added according to the above formula; 4. The distributor did not submit an initial expense application form, nor did it have any usage amount related to the price reduction expenses. It only had the amount of returned goods and the amount of the adjustment. The settlement amount was calculated according to the aforementioned formula.

[0073] If the actual cost amount is positive after settlement according to the formula, the application for additional cost will be automatically added based on the positive amount, and the case will be closed based on the amount. If the actual cost amount is negative after calculation according to the formula, in scenario A (return amount is greater than the amount reduced this month) or scenario B (there is a return amount and the distributor has an increase this month), the SKUs will be merged by the designated store (all SKUs will be merged into the designated store).

[0074] The price reduction fee application module is used to automatically estimate the fee application amount for the following month on the 25th of each month based on the progress of e-commerce fees used this month and the reference actual fee usage amount for the same month last year, and automatically complete the fee application by connecting with the financial system.

[0075] The unit price recommendation module is used to automatically recommend the actual transaction price of products. Specifically, it can be adapted to e-commerce event time nodes. The system automatically recommends the actual transaction price of products based on the SKU dimension. Businesses can then set the actual transaction price of products in different scenarios such as discounts, coupons, and commissions, effectively improving the pricing efficiency of e-commerce sales.

[0076] In the e-commerce fee management method of this application embodiment, firstly, by integrating multi-source data from e-commerce platforms and suppliers, and by accurately analyzing and calculating various price reduction strategies, the price reduction fee for each order can be accurately calculated, avoiding statistical errors caused by incomplete data or misunderstanding of price reduction strategies. Compared with traditional statistical methods, this greatly improves the accuracy of price reduction fee statistics, providing merchants with reliable data. Secondly, by adopting an automated data collection and processing flow, massive amounts of e-commerce transaction data can be processed quickly. Even when facing a large number of orders during large-scale promotional events, the calculation of price reduction fees can still be completed in a short time, greatly improving statistical efficiency and saving manpower and time costs. Thirdly, it can adapt to various common e-commerce price reduction strategies, whether it is direct discounts, full-reduction offers, coupons, or limited-time special offers, and can accurately identify and calculate the fees. The method and system of this invention can be effectively applied to different types of goods and e-commerce businesses of different scales, and have wide applicability. Fourth, it can display the statistical results of price reduction expenses in intuitive reports or charts, making it easy for merchants to clearly understand the price reduction expenses from different dimensions, such as the price reduction costs of various products and the return on investment of various promotional activities. This helps merchants make quick business decisions, optimize promotional strategies, and improve economic efficiency. Fifth, it supports automatic application, automatic addition, automatic closure, and automatic settlement of expenses for various platform stores. This improves the accuracy of financial expense management, reduces manual operation, and improves operational efficiency.

[0077] Embodiments of this application also provide an e-commerce fee management device, such as... Figure 4 As shown, it includes: Module 401 is used to determine the business type of the sales entity; The monitoring module 402 is used to monitor the order data of the sales entity in real time according to the business type, wherein the type of the order data corresponds to the business type; The statistics module 403 is used to statistically analyze the usage of price reduction fees based on the currently monitored order data, from at least one of the following dimensions: sales entity, business type, order, and product category. Processing module 404 is configured to perform at least one of the following operations based on the usage of the price reduction fees as statistically analyzed within a statistical period: By connecting with the financial and marketing expense system, the price reduction expenses within the statistical period are automatically closed. Generate a suggested transaction price for the product associated with the order data.

[0078] The business types include at least one of the following: direct supply type, direct supply dropshipping type, consignment type, direct operation type, and direct operation warehousing type; When the business type is the direct sales type, the direct sales warehousing type, the consignment type, or the direct supply and distribution type, the order data type includes sales orders and / or after-sales orders; When the business type is direct supply, the order data type includes purchase sales orders and / or after-sales orders.

[0079] The statistics module 403 includes: The first acquisition submodule is used to obtain the standard unit price corresponding to the order data based on the product code field in the currently monitored order data; The first determining submodule is used to determine the amount of the price reduction fee corresponding to the order data based on the standard unit price, the product quantity field and the actual payment price field in the order data, when the type of the currently monitored order data is a sales order. The second determining submodule is used to determine the amount of the price reduction fee corresponding to the order data when the type of the currently monitored order data is a purchase and sales order, based on the standard unit price, the product quantity field and the actual payment amount field in the order data; The third determination submodule is used to determine the amount of the price reduction fee corresponding to the order data when the type of the currently monitored order data is an after-sales order, based on the product quantity field in the after-sales order and the actual payment unit price corresponding to the sales order or purchase order associated with the after-sales order. The statistics submodule is used to calculate the usage of the price reduction fee based on the amount of the price reduction fee corresponding to the order data, from at least one of the following dimensions: the sales entity dimension, the business type dimension, the order dimension, and the product category dimension.

[0080] Specifically, the first acquisition submodule is used to: acquire the standard unit price when the product corresponding to the product code field is a product other than a pre-set target product category.

[0081] The device further includes: The first acquisition module is used to acquire commission information input by the first user; wherein, the first user is the user corresponding to the brand owner; The generation module is used to generate adjustment orders based on the commission information; wherein, the adjustment orders include adjustment sales orders and adjustment after-sales orders; The adjustment module is used to adjust the usage of the currently statistically analyzed price reduction fees based on the amount field in the adjusted sales order and the amount field in the adjusted after-sales order.

[0082] The device further includes: The second acquisition module is used to acquire the amount of price reduction fees already used by the sales entity based on the usage of the price reduction fees statistically analyzed from the perspective of the sales entity. The first sending module is used to send a warning message to the user corresponding to the sales entity if the ratio of the amount of price reduction fee already used by the sales entity to the amount of price reduction fee applied for by the sales entity is greater than a first threshold.

[0083] Specifically, when the processing module is used to automatically close out price reduction expenses within the statistical period by interfacing with the financial marketing expense system, it is used for: If the sales entity has not applied for a price reduction fee, perform any of the following operations: If the amount of price reduction expenses already used by the sales entity is greater than zero, a first request is sent to the financial marketing expense system. The first request is used to request an additional amount of price reduction expenses. If the amount of price reduction fees already used by the sales entity is less than zero, the amount of price reduction fees already used by the sales entity will be transferred back to the target sales entity. If the sales entity has already applied for a price reduction fee, perform any of the following operations: If the amount of price reduction fee already used by the sales entity is greater than zero, a second request is sent to the financial marketing expense system. The second request is used to request the closure of the application line for the price reduction fee amount. The second request is also used to request additional price reduction fee amount based on the amount of price reduction fee already used by the sales entity. If the amount of price reduction fee already used by the sales entity is zero, a third request is sent to the financial marketing expense system, wherein the third request is used to request the closure of the application line for the price reduction fee amount; If the amount of price reduction fees already used by the sales entity is less than zero, the third request is sent to the financial marketing expense system, and the amount of price reduction fees already used by the sales entity is transferred back to the target sales entity.

[0084] The device further includes: The second acquisition module is used to acquire the amount of price reduction fees currently used by the sales entity at a preset time in a statistical period; The prediction module is used to predict the price reduction amount for the next statistical period adjacent to the current statistical period based on the price reduction amount already used, the price reduction amount used in the previous statistical period adjacent to the current statistical period, and the price reduction amount used in the Nth statistical period of the previous year adjacent to the current year; wherein the current statistical period is the Nth statistical period of the current year, and N is an integer; The second sending module is used to send a fourth request to the financial marketing expense system, the fourth request being used to apply for a price reduction fee amount for the next statistical period adjacent to the current statistical period.

[0085] Specifically, when generating a suggested transaction price for products related to the order data, the processing module 404 is used to: Based on the usage of price reduction fees statistically analyzed from the product category dimension, the actual transaction unit price corresponding to the same product category is obtained; Based on the actual transaction price, the suggested transaction price is generated. The suggested transaction price is used to guide sales personnel in setting the actual transaction price for the sales entity.

[0086] It should be noted that the e-commerce fee management device provided in this application embodiment can implement all the method steps implemented in the above e-commerce fee management method embodiment and can achieve the same technical effect. Here, the parts that are the same as those in the method embodiment and the beneficial effects will not be described in detail.

[0087] Another embodiment of the e-commerce fee management device of this application, such as Figure 5 As shown, it includes a transceiver 510, a processor 500, a memory 520, and a program or instructions stored in the memory 520 and executable on the processor 500; when the processor 500 executes the program or instructions, it implements the above-mentioned e-commerce fee management method.

[0088] The transceiver 510 is used to receive and send data under the control of the processor 500.

[0089] Among them, Figure 5In this context, the bus architecture may include any number of interconnected buses and bridges, specifically linking various circuits together, represented by one or more processors (processor 500) and memory (memory 520). The bus architecture may also link various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art and therefore will not be described further herein. The bus interface provides an interface. The transceiver 510 may be multiple elements, including transmitters and receivers, providing a unit for communicating with various other devices over a transmission medium. The processor 500 is responsible for managing the bus architecture and general processing, and the memory 520 may store data used by the processor 500 during operation.

[0090] This application provides a readable storage medium storing a program or instructions. When the program or instructions are executed by a processor, they implement the steps in the e-commerce fee management method described above and achieve the same technical effect. To avoid repetition, further details are omitted here.

[0091] The processor mentioned above is the processor in the electronic device described in the above embodiments. The readable storage medium includes computer-readable storage media, such as computer read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk.

[0092] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, disk, optical disk) and includes several instructions for executing the methods described in the various embodiments of this application.

[0093] Therefore, embodiments of this application also provide a computer program product, including computer instructions, which, when executed by a processor, implement the e-commerce fee management method described above and achieve the same technical effect. To avoid repetition, further details are omitted here.

[0094] In this embodiment, the module can be implemented in software so that it can be executed by various types of processors. For example, an identified executable code module may include one or more physical or logical blocks of computer instructions, which may be constructed as objects, procedures, or functions. Nevertheless, the executable code of the identified module does not need to be physically located together, but may include different instructions stored in different bits, which, when logically combined, constitute the module and achieve the module's intended purpose.

[0095] In practice, an executable code module can be a single instruction or many instructions, and can even be distributed across multiple different code segments, different programs, and across multiple memory devices. Similarly, operational data can be identified within the module and can be implemented in any suitable form and organized within any suitable data structure. This operational data can be collected as a single dataset or distributed across different locations (including different storage devices), and can exist, at least in part, solely as electronic signals within the system or network.

[0096] When a module can be implemented using software, considering the current level of hardware technology, modules that can be implemented in software can be implemented using hardware circuits by those skilled in the art to achieve the corresponding functions, without considering cost. These hardware circuits include conventional very-large-scale integrated circuits (VLSI) or gate arrays, as well as existing semiconductors such as logic chips and transistors, or other discrete components. Modules can also be implemented using programmable hardware devices, such as field-programmable gate arrays, programmable array logic, and programmable logic devices.

[0097] The exemplary embodiments described above are with reference to the accompanying drawings. Many different forms and embodiments are feasible without departing from the spirit and teachings of this application. Therefore, this application should not be construed as limiting the exemplary embodiments set forth herein. Rather, these exemplary embodiments are provided to make this application complete and convey the scope of this application to those skilled in the art. In these drawings, component dimensions and relative dimensions may be exaggerated for clarity. The terminology used herein is for the purpose of describing particular exemplary embodiments only and is not intended to be limiting. As used herein, unless clearly indicated otherwise, the singular forms “a,” “an,” and “the” are intended to include all such forms. It will be further understood that the terms “comprising” and / or “including”, when used in this specification, indicate the presence of the stated features, integers, steps, operations, components, and / or elements, but do not exclude the presence or addition of one or more other features, integers, steps, operations, components, and / or groups thereof. Unless otherwise indicated, when stated, a range of values ​​includes the upper and lower limits of the range and any subranges in between.

[0098] The above description is the preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principles described in this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for managing e-commerce expenses, characterized in that, include: Determine the business type of the sales entity; Based on the business type, the order data of the sales entity is monitored in real time, wherein the type of the order data corresponds to the business type; Based on the currently monitored order data, the usage of price reduction fees is statistically analyzed from at least one of the following dimensions: sales entity, business type, order, and product category. Based on the usage of the price reduction fees as statistically analyzed within a statistical period, perform at least one of the following operations: By connecting with the financial and marketing expense system, the price reduction expenses within the statistical period are automatically closed. Generate a suggested transaction price for the product associated with the order data.

2. The method according to claim 1, characterized in that, The business types include at least one of the following: direct supply type, direct supply dropshipping type, consignment type, direct operation type, and direct operation warehousing type; When the business type is the direct sales type, the direct sales warehousing type, the consignment type, or the direct supply and distribution type, the order data type includes sales orders and / or after-sales orders; When the business type is direct supply, the order data type includes purchase sales orders and / or after-sales orders.

3. The method according to claim 1 or 2, characterized in that, Based on the currently monitored order data, the usage of price reduction fees is statistically analyzed from at least one of the following dimensions: sales entity, business type, order, and product category. This includes: Based on the product code field in the currently monitored order data, obtain the standard unit price corresponding to the order data; If the type of the currently monitored order data is a sales order, the amount of the price reduction fee corresponding to the order data is determined based on the standard unit price, the product quantity field and the actual payment price field in the order data. If the type of the currently monitored order data is a purchase and sales order, the amount of the price reduction fee corresponding to the order data is determined based on the standard unit price, the product quantity field and the actual payment amount field in the order data; If the type of the currently monitored order data is an after-sales order, the amount of the price reduction fee corresponding to the order data is determined based on the product quantity field in the after-sales order and the actual payment unit price corresponding to the sales order or purchase order associated with the after-sales order. Based on the amount of price reduction fees used corresponding to the order data, the usage of the price reduction fees is statistically analyzed from at least one of the following dimensions: the sales entity dimension, the business type dimension, the order dimension, and the product category dimension.

4. The method according to claim 3, characterized in that, Based on the product code field in the currently monitored order data, obtain the standard unit price corresponding to the order data, including: If the product corresponding to the product code field is a product other than the pre-set target product category, obtain the standard unit price.

5. The method according to claim 1, characterized in that, Based on the currently monitored order data, after statistically analyzing the usage of price reduction fees from at least one of the following dimensions—sales entity, business type, order, and product category—the method further includes: Obtain the commission information input by the first user; wherein, the first user is the user corresponding to the brand owner; Based on the commission information, a price adjustment order is generated; wherein, the price adjustment order includes price adjustment sales orders and price adjustment after-sales orders; Based on the amount field in the adjusted sales order and the amount field in the adjusted after-sales order, adjust the usage of the currently statistically analyzed price reduction fees.

6. The method according to claim 1, characterized in that, Based on the currently monitored order data, after statistically analyzing the usage of price reduction fees from at least one of the following dimensions—sales entity, business type, order, and product category—the method further includes: Based on the usage of the price reduction fees statistically analyzed from the perspective of the sales entity, obtain the amount of the price reduction fees already used by the sales entity; If the ratio of the amount of price reduction fees already used by the sales entity to the amount of price reduction fees applied for by the sales entity is greater than a first threshold, then a warning message will be sent to the user corresponding to the sales entity.

7. The method according to claim 1 or 5, characterized in that, Based on the usage of the price reduction expenses within a statistical period, and through integration with the financial marketing expense system, the price reduction expenses within the statistical period are automatically closed, including: If the sales entity has not applied for a price reduction fee, perform any of the following operations: If the amount of price reduction expenses already used by the sales entity is greater than zero, a first request is sent to the financial marketing expense system. The first request is used to request an additional amount of price reduction expenses. If the amount of price reduction fees already used by the sales entity is less than zero, the amount of price reduction fees already used by the sales entity will be transferred back to the target sales entity. If the sales entity has already applied for a price reduction fee, perform any of the following operations: If the amount of price reduction fee already used by the sales entity is greater than zero, a second request is sent to the financial marketing expense system. The second request is used to request the closure of the application line for the price reduction fee amount. The second request is also used to request additional price reduction fee amount based on the amount of price reduction fee already used by the sales entity. If the amount of price reduction fee already used by the sales entity is zero, a third request is sent to the financial marketing expense system, wherein the third request is used to request the closure of the application line for the price reduction fee amount; If the amount of price reduction fees already used by the sales entity is less than zero, the third request is sent to the financial marketing expense system, and the amount of price reduction fees already used by the sales entity is transferred back to the target sales entity.

8. The method according to claim 1 or 5, characterized in that, Based on the currently monitored order data, after statistically analyzing the usage of price reduction fees from at least one of the following dimensions—sales entity, business type, order, and product category—the method further includes: At a preset time point within a statistical period, obtain the amount of price reduction fees currently used by the sales entity; Based on the amount of price reduction fees currently used, the amount of price reduction fees used in the previous statistical period adjacent to the current statistical period, and the amount of price reduction fees used in the Nth statistical period of the previous year adjacent to this year, the amount of price reduction fees for the next statistical period adjacent to the current statistical period is estimated; wherein, the current statistical period is the Nth statistical period of this year, and N is an integer; A fourth request is sent to the financial marketing expense system, the fourth request being used to apply for a price reduction expense limit for the next statistical period adjacent to the current statistical period.

9. The method according to claim 1 or 5, characterized in that, Based on the usage of the price reduction fees statistically analyzed within a statistical period, a suggested transaction price for the product related to the order data is generated, including: Based on the usage of price reduction fees statistically analyzed from the product category dimension, the actual transaction unit price corresponding to the same product category is obtained; Based on the actual transaction price, the suggested transaction price is generated. The suggested transaction price is used to guide sales personnel in setting the actual transaction price for the sales entity.

10. An e-commerce fee management device, characterized in that, include: The determination module is used to determine the business type of the sales entity; The monitoring module is used to monitor the order data of the sales entity in real time according to the business type, wherein the type of the order data corresponds to the business type; The statistics module is used to analyze the usage of price reduction fees based on the currently monitored order data, from at least one of the following dimensions: sales entity, business type, order, and product category. The processing module is configured to perform at least one of the following operations based on the usage of the price reduction fees as statistically analyzed within a statistical period: By connecting with the financial and marketing expense system, the price reduction expenses within the statistical period are automatically closed. Generate a suggested transaction price for the product associated with the order data.

11. An e-commerce expense management device, characterized in that, The transceiver includes a transceiver, a processor, a memory, and a program stored in the memory and executable on the processor; characterized in that the transceiver transmits and receives data under the control of the processor, and the processor executes the program to implement the e-commerce fee management method as described in any one of claims 1 to 9.

12. A readable storage medium having a program or instructions stored thereon, characterized in that, When the program or instructions are executed by the processor, they implement the e-commerce fee management method as described in any one of claims 1 to 9.

13. A computer program product, characterized in that, It includes computer instructions that, when executed by a processor, implement the e-commerce fee management method as described in any one of claims 1 to 9.

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