Method and device for pushing information

Abstract

The embodiment of the present application discloses a method and device for pushing information. A specific implementation of the method includes: obtaining historical transaction data and current inventory information of the commodity to be evaluated, judging whether the sales status of the commodity to be evaluated is a slow-selling state based on the historical transaction data and current inventory information of the commodity to be evaluated, in response to determining that the sales status of the commodity to be evaluated is a slow-selling state, calculating the cost sunk coefficient of the commodity to be evaluated based on the historical transaction data and current inventory information of the commodity to be evaluated, calculating the effective cost of the commodity to be evaluated based on the cost sunk coefficient and the actual cost of the commodity to be evaluated that has been obtained, determining the recommended price of the commodity to be evaluated by collaboratively optimizing the total transaction amount of the commodity to be evaluated and the profit of the commodity to be evaluated based on the effective cost of the commodity to be evaluated, and pushing price information indicating the recommended price of the commodity to be evaluated. This implementation realizes automated price evaluation and push, and improves the accuracy of price evaluation.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of computer technology, specifically to the field of Internet technology, and in particular to a method and device for pushing information. Background Art

[0002] With the development of e-commerce technology, more and more platforms provide online commodity trading services. The price of commodities usually changes with their popularity and market demand.

[0003] In the dynamic pricing management system of commodities, it is usually possible to find the price that maximizes sales targets such as transaction volume, transaction amount, and gross profit based on the relationship between commodity price and sales volume within a certain range of market fairness. However, since this method does not take inventory factors into consideration, it is easy to increase inventory pressure when commodities are unsalable, which is not conducive to improving warehouse utilization and converting commodity revenue. Summary of the invention

[0004] The embodiments of the present application provide a method and device for pushing information.

[0005] In a first aspect, an embodiment of the present application provides a method for pushing information, including: obtaining historical transaction data and current inventory information of a commodity to be evaluated; judging whether the sales status of the commodity to be evaluated is a slow-selling state based on the historical transaction data and current inventory information of the commodity to be evaluated; in response to determining that the sales status of the commodity to be evaluated is a slow-selling state, calculating the cost sunk coefficient of the commodity to be evaluated based on the historical transaction data and current inventory information of the commodity to be evaluated, wherein the cost sunk coefficient is used to characterize the proportion of the unsunk cost of the commodity to be evaluated to the actual cost of the commodity to be evaluated; calculating the effective cost of the commodity to be evaluated based on the cost sunk coefficient and the actual cost of the commodity to be evaluated that has been obtained, and determining the recommended price of the commodity to be evaluated by collaboratively optimizing the total transaction amount of the commodity to be evaluated and the profit of the commodity to be evaluated based on the effective cost of the commodity to be evaluated; and pushing price information indicating the recommended price of the commodity to be evaluated.

[0006] In some embodiments, the above-mentioned determination of whether the sales status of the commodity to be evaluated is a slow-selling state based on the historical transaction data and current inventory information of the commodity to be evaluated includes: calculating the safety inventory of the commodity to be evaluated based on the historical transaction data of the commodity to be evaluated; calculating the ratio of the current inventory indicated by the current inventory information of the commodity to be evaluated to the safety inventory to obtain the slow-selling index of the commodity to be evaluated; in response to determining that the slow-selling index of the commodity to be evaluated is greater than a preset slow-selling index threshold, and the current inventory indicated by the current inventory information of the commodity to be evaluated is greater than the preset inventory threshold, determining that the sales status of the commodity to be evaluated is a slow-selling state.

[0007] In some embodiments, the historical transaction data of the commodity to be evaluated includes the historical transaction data of each warehouse storing the commodity to be evaluated, and the current inventory information of the commodity to be evaluated includes the current inventory information of each warehouse storing the commodity to be evaluated; the above-mentioned calculation of the safety stock of the commodity to be evaluated based on the historical transaction data of the commodity to be evaluated includes: calculating the safety stock of each warehouse based on the historical transaction data of the commodity to be evaluated; and the above-mentioned calculation of the ratio of the current inventory indicated by the current inventory information of the commodity to be evaluated to the safety stock, so as to obtain the unsalable index of the commodity to be evaluated, includes: calculating the ratio of the current inventory indicated by the current inventory information of each warehouse to the safety stock of the warehouse, to obtain the unsalable index of each warehouse; determining the weight of each warehouse according to the safety stock of each warehouse, and weighted summing the unsalable indexes of each warehouse to obtain the unsalable index of the commodity to be evaluated.

[0008] In some embodiments, the above-mentioned determination of whether the sales status of the commodity to be evaluated is a slow-selling state based on the historical transaction data and current inventory information of the commodity to be evaluated also includes: determining whether the sales status of the commodity to be evaluated is a preset non-slow-selling state; and the above-mentioned determination that the sales status of the commodity to be evaluated is a slow-selling state in response to determining that the slow-selling index of the commodity to be evaluated is greater than a preset slow-selling index threshold, and the current inventory indicated by the current inventory information of the commodity to be evaluated is greater than the preset inventory threshold, includes: in response to determining that the sales status of the commodity to be evaluated is not a preset non-slow-selling state, the slow-selling index of the commodity to be evaluated is greater than the preset slow-selling index threshold, and the current inventory indicated by the current inventory information of the commodity to be evaluated is greater than the preset inventory threshold, determining that the sales status of the commodity to be evaluated is a slow-selling state.

[0009] In some embodiments, the above-mentioned calculation of the sunk cost coefficient of the commodity to be evaluated based on the historical transaction data and current inventory information of the commodity to be evaluated includes: taking the ratio of the safety inventory of the commodity to be evaluated calculated based on the historical transaction data of the commodity to be evaluated to the current inventory of the commodity to be evaluated as the sunk cost coefficient of the commodity to be evaluated.

[0010] In some embodiments, the effective cost c* of the commodity to be evaluated is calculated as follows:

[0011] c * =α·c

[0012] Among them, α is the cost sunk coefficient, c is the actual cost;

[0013] The GMV of the product to be evaluated at price p is calculated as follows:

[0014] GMV=p·Q(p),

[0015] Q(p)=ε(Q0 / p0)p+(1-ε)Q0;

[0016] Among them, ε represents the price elasticity of the commodity to be evaluated, Q0 represents the initial transaction quantity of the commodity to be evaluated, p0 represents the initial price of the commodity to be evaluated, and Q(p) represents the transaction quantity of the commodity to be evaluated at price p;

[0017] The profit GP of the commodity to be evaluated at price p is calculated as follows:

[0018] GP=(pc * )·Q(p);

[0019] The above method of determining the recommended price of the commodity to be evaluated by collaboratively optimizing the total transaction amount and the profit of the commodity to be evaluated based on the effective cost of the commodity to be evaluated includes: constructing a collaborative optimization function G(p) based on the total transaction amount GMV and the profit GP of the commodity to be evaluated at price p; determining the recommended price of the commodity to be evaluated by maximizing the collaborative optimization function; wherein,

[0020]

[0021] GP0 and GMV0 represent the total transaction volume and profit of the commodity to be evaluated at the initial price p0, respectively, and β is the synergy coefficient.

[0022] In a second aspect, an embodiment of the present application provides a device for pushing information, including: an acquisition unit, used to acquire historical transaction data and current inventory information of the commodity to be evaluated; a judgment unit, used to judge whether the sales status of the commodity to be evaluated is a slow-selling state based on the historical transaction data and current inventory information of the commodity to be evaluated; a calculation unit, used to calculate the cost sunk coefficient of the commodity to be evaluated based on the historical transaction data and current inventory information of the commodity to be evaluated in response to determining that the sales status of the commodity to be evaluated is a slow-selling state, wherein the cost sunk coefficient is used to characterize the proportion of the unsunk cost of the commodity to be evaluated to the actual cost of the commodity to be evaluated; a determination unit, used to calculate the effective cost of the commodity to be evaluated based on the cost sunk coefficient and the actual cost of the commodity to be evaluated that has been acquired, and determine the recommended price of the commodity to be evaluated by collaboratively optimizing the total transaction amount of the commodity to be evaluated and the profit of the commodity to be evaluated based on the effective cost of the commodity to be evaluated; a pushing unit, used to push price information indicating the recommended price of the commodity to be evaluated.

[0023] In some embodiments, the above-mentioned judgment unit is further used to judge whether the sales status of the commodity to be evaluated is a slow-selling state in the following manner: calculating the safety stock of the commodity to be evaluated based on the historical transaction data of the commodity to be evaluated; calculating the ratio of the current inventory indicated by the current inventory information of the commodity to be evaluated to the safety stock to obtain the slow-selling index of the commodity to be evaluated; in response to determining that the slow-selling index of the commodity to be evaluated is greater than a preset slow-selling index threshold, and the current inventory indicated by the current inventory information of the commodity to be evaluated is greater than the preset inventory threshold, determining that the sales status of the commodity to be evaluated is a slow-selling state.

[0024] In some embodiments, the historical transaction data of the above-mentioned goods to be evaluated include the historical transaction data of each warehouse storing the goods to be evaluated, and the current inventory information of the goods to be evaluated includes the current inventory information of each warehouse storing the goods to be evaluated; the judgment unit is further used to calculate the safety stock of the goods to be evaluated in the following manner: based on the historical transaction data of each warehouse storing the goods to be evaluated, calculate the safety stock of each warehouse; and the judgment unit is further used to obtain the unsalable index of the goods to be evaluated in the following manner: calculate the ratio of the current inventory indicated by the current inventory information of each warehouse to the safety stock of the warehouse, and obtain the unsalable index of each warehouse; determine the weight of each warehouse according to the safety stock of each warehouse, and perform weighted summation on the unsalable index of each warehouse to obtain the unsalable index of the goods to be evaluated.

[0025] In some embodiments, the above-mentioned judgment unit is also used to: judge whether the sales status of the commodity to be evaluated is a preset non-slow-selling status; and the above-mentioned judgment unit is used to judge whether the sales status of the commodity to be evaluated is a slow-selling status in the following manner: in response to determining that the sales status of the commodity to be evaluated is not a preset non-slow-selling status, the slow-selling index of the commodity to be evaluated is greater than a preset slow-selling index threshold, and the current inventory indicated by the current inventory information of the commodity to be evaluated is greater than the preset inventory threshold, it is determined that the sales status of the commodity to be evaluated is a slow-selling status.

[0026] In some embodiments, the above-mentioned calculation unit is further used to calculate the cost sunk coefficient of the commodity to be evaluated in the following manner: the ratio of the safety inventory of the commodity to be evaluated calculated based on the historical transaction data of the commodity to be evaluated to the current inventory of the commodity to be evaluated is used as the cost sunk coefficient of the commodity to be evaluated.

[0027] In some embodiments, the effective cost c* of the commodity to be evaluated is calculated as follows:

[0028] c * =α·c

[0029] Among them, α is the cost sunk coefficient, c is the actual cost;

[0030] The GMV of the product to be evaluated at price p is calculated as follows:

[0031] GMV=p·Q(p),

[0032] Q(p)=ε(Q0 / p0)p+(1-ε)Q0;

[0033] Among them, ε represents the price elasticity of the commodity to be evaluated, Q0 represents the initial transaction quantity of the commodity to be evaluated, p0 represents the initial price of the commodity to be evaluated, and Q(p) represents the transaction quantity of the commodity to be evaluated at price p;

[0034] The profit GP of the commodity to be evaluated at price p is calculated as follows:

[0035] GP=(pc * )·Q(p);

[0036] The determination unit is further used to determine the recommended price of the commodity to be evaluated in the following manner: construct a collaborative optimization function G(p) based on the total transaction amount GMV and profit GP of the commodity to be evaluated at price p; determine the recommended price of the commodity to be evaluated by maximizing the collaborative optimization function; wherein,

[0037]

[0038] GP0 and GMV0 represent the total transaction volume and profit of the commodity to be evaluated at the initial price p0, respectively, and β is the synergy coefficient.

[0039] In a third aspect, an embodiment of the present application provides an electronic device, comprising: one or more processors; a storage device for storing one or more programs, when the one or more programs are executed by one or more processors, the one or more processors implement the method for pushing information provided in the first aspect of the present application.

[0040] In a fourth aspect, an embodiment of the present application provides a computer storage medium on which a computer program is stored, wherein when the program is executed by a processor, the method for pushing information provided in the first aspect of the present application is implemented.

[0041] The method and device for pushing information provided by the embodiment of the present application obtains the historical transaction data and current inventory information of the commodity to be evaluated, and then determines whether the sales status of the commodity to be evaluated is a slow-selling state based on the historical transaction data and current inventory information of the commodity to be evaluated, and then in response to determining that the sales status of the commodity to be evaluated is a slow-selling state, calculates the cost sunk coefficient of the commodity to be evaluated based on the historical transaction data and current inventory information of the commodity to be evaluated, wherein the cost sunk coefficient is used to characterize the proportion of the unsunk cost of the commodity to be evaluated to the actual cost of the commodity to be evaluated, and then calculates the effective cost of the commodity to be evaluated based on the cost sunk coefficient and the actual cost of the commodity to be evaluated that has been obtained, and determines the recommended price of the commodity to be evaluated by collaboratively optimizing the total transaction amount of the commodity to be evaluated and the profit of the commodity to be evaluated according to the effective cost of the commodity to be evaluated, and finally pushes the price information indicating the recommended price of the commodity to be evaluated, thereby realizing automatic commodity price evaluation and push. Since the impact of the inventory pressure caused by the slow-selling state of the commodity on the effective cost used in calculating the profit is fully considered when performing price evaluation, a more accurate recommended price can be provided. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Other features, objects and advantages of the present application will become more apparent by reading the detailed description of non-limiting embodiments made with reference to the following drawings:

[0043] Figure 1 is an exemplary system architecture diagram to which the present application may be applied;

[0044] Figure 2 is a flow chart of an embodiment of a method for pushing information according to the present application;

[0045] Figure 3 It is a flowchart of an implementation method of a method for determining whether the sales status of a commodity to be evaluated is a slow-selling state in the method for pushing information according to the present application;

[0046] Figure 4 It is a schematic diagram of the relationship between the cost of the goods to be evaluated and the profit of the goods to be evaluated;

[0047] Figure 5 is a structural diagram of an embodiment of a device for pushing information according to the present application;

[0048] Figure 6 It is a structural diagram of a computer system suitable for implementing an electronic device of an embodiment of the present application. DETAILED DESCRIPTION

[0049] The present application will be further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the relevant invention, rather than to limit the invention. It should also be noted that, for ease of description, only the parts related to the relevant invention are shown in the accompanying drawings.

[0050] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0051] Figure 1 An exemplary system architecture 100 is shown to which the webpage generation method or webpage generation device according to the embodiment of the present application can be applied.

[0052] like Figure 1 As shown, the system architecture 100 may include terminal devices 101, 102, 103, a network 104 and a server 105. The network 104 is used to provide a medium for communication links between the terminal devices 101, 102, 103 and the server 105. The network 104 may include various connection types, such as wired, wireless communication links or optical fiber cables, etc.

[0053] The user 110 can use the terminal devices 101, 102, 103 to interact with the server 105 through the network 104 to receive or send messages, etc. Various communication client applications can be installed on the terminal devices 101, 102, 103, such as web browser applications, shopping applications, search applications, etc. In the scenario of the present application, the user 110 can be an online store user.

[0054] Terminal devices 101, 102, 103 can be hardware or software. When terminal devices 101, 102, 103 are hardware, they can be various electronic devices with display screens and supporting data processing, including but not limited to smart phones, tablet computers, e-book readers, laptop portable computers, desktop computers, etc. When terminal devices 101, 102, 103 are software, they can be installed in the electronic devices listed above. It can be implemented as multiple software or software modules (for example, multiple software and multiple software modules for providing distributed services), or it can be implemented as a single software or software module. No specific limitation is made here.

[0055] The server 105 may be a server that provides various services, such as a background commodity information processing server that supports commodity price information displayed on the terminal devices 101, 102, and 103. The background commodity information processing server may process the received price recommendation request, for example, it may analyze and evaluate the transaction quantity and demand data of the commodity on each platform, and feed back the processing result (such as price evaluation result) to the terminal device.

[0056] It should be noted that the method for pushing information provided in the embodiment of the present application is generally executed by the server 105 , and accordingly, the device for pushing information is generally set in the server 105 .

[0057] It should be noted that the server can be hardware or software. When the server is hardware, it can be implemented as a distributed server cluster consisting of multiple servers, or it can be implemented as a single server. When the server is software, it can be implemented as multiple software or software modules (for example, used to provide distributed services), or it can be implemented as a single software or software module. No specific limitation is made here.

[0058] It should be understood that Figure 1 The number of terminal devices, networks and servers in the embodiment is only for illustration. Any number of terminal devices, networks and servers may be provided according to implementation requirements.

[0059] Continue to refer Figure 2 , which shows a process 200 of an embodiment of a method for pushing information according to the present application. The method for pushing information includes the following steps:

[0060] Step 201, obtaining historical transaction data and current inventory information of the commodity to be evaluated.

[0061] In this embodiment, the execution subject of the above method for pushing information (for example Figure 1 The server 105 shown in the figure can first obtain the transaction data and current inventory information of the commodity to be evaluated. Here, the commodity to be evaluated can be a commodity provided by a store on the online platform. In actual scenarios, the item to be evaluated can be a commodity specified by the merchant or any valid commodity on the online platform.

[0062] The historical transaction data may include transaction data within a period of time from the current time as the end point. The historical transaction data of the commodity to be evaluated may include the transaction volume, order generation time, order price, transaction payment method, shipping warehouse, delivery time, commodity evaluation data, etc. of the commodity to be evaluated within a period of time before the current time.

[0063] The current inventory information of the commodity to be evaluated can represent the inventory of the commodity to be evaluated at the current moment. In the actual scenario of this embodiment, the online platform can be associated with multiple warehouses, that is, the commodities of the online platform can be supplied by multiple warehouses, and these warehouses can be distributed in different geographical locations. The current inventory information of the commodity to be evaluated can include the inventory information of the commodity to be evaluated in each warehouse.

[0064] In this embodiment, the execution subject of the above-mentioned method for pushing information can record transaction data when a transaction occurs and save the transaction data according to the commodity identification. When obtaining the historical transaction data of the commodity to be evaluated, the corresponding transaction data can be found according to the commodity identification of the commodity to be evaluated. The current inventory information can be calculated based on the storage capacity reported by the warehouse and the data of the completed transactions. For example, if the initial inventory of the commodity to be evaluated in the warehouse is 1,000 pieces, and the transaction quantity of the commodity to be evaluated in the completed transaction is 200 pieces, then the current inventory of the commodity to be evaluated is 800 pieces.

[0065] Step 202: determine whether the sales status of the commodity to be evaluated is a slow-moving state based on the historical transaction data and current inventory information of the commodity to be evaluated.

[0066] After obtaining the historical transaction data and current inventory information of the commodity to be evaluated, the sales status of the commodity to be evaluated can be evaluated. The sales status may include a slow-selling state, an out-of-stock state, and a normal sales state. In this embodiment, it can be determined whether the sales status of the commodity to be evaluated is a slow-selling state. The slow-selling state refers to a state in which the inventory of the commodity is overstocked due to a slow sales speed. In the slow-selling state, the inventory of the commodity exceeds the demand estimated according to the current sales speed.

[0067] Specifically, when judging whether the sales status of the commodity to be evaluated is a slow-selling state, it can be judged whether the historical transaction volume, current inventory and / or the relative relationship between the historical transaction volume and the current inventory of the commodity to be evaluated meet the preset transaction volume conditions, inventory conditions and / or the relative relationship conditions between the transaction volume and the inventory under the slow-selling state. If so, it can be determined that the sales status of the commodity to be evaluated is a slow-selling state; otherwise, it can be determined that the sales status of the commodity to be evaluated is not a slow-selling state.

[0068] In some optional implementations of this embodiment, the safety inventory of the commodity to be evaluated may be determined, and whether the sales status of the commodity to be evaluated is a slow-moving state may be determined based on the safety inventory. Figure 3 The flowchart of one implementation method of the method for determining whether the sales status of the commodity to be evaluated is a slow-selling state is shown. Figure 3 As shown, the process 300 of the method for determining whether the sales status of the commodity to be evaluated is a slow-selling state includes the following steps:

[0069] Step 301: Calculate the safety stock of the commodity to be evaluated based on the historical transaction data of the commodity to be evaluated.

[0070] The safety stock can be an estimated insurance reserve to prevent insufficient supply caused by uncertain factors such as a large number of sudden orders and sudden advance of delivery dates. Usually, the safety stock is an insurance and high stock estimate, which needs to be greater than the average transaction volume per unit time. In this embodiment, the average transaction volume of the commodity to be evaluated in a unit time can be calculated based on the historical transaction data of the commodity to be evaluated. The unit time can be one day, one week, one month, or one quarter. Then, the safety stock of the commodity to be evaluated is calculated according to the numerical relationship between the pre-set safety stock and the average transaction volume per unit time.

[0071] For example, the safety stock can be pre-set to three times the monthly transaction volume. If the transaction volume in the 30 days before the current time in the historical transaction data of the commodity to be evaluated is V, then the safety stock amount is 3×V.

[0072] Step 302, calculating the ratio of the current inventory quantity indicated by the current inventory quantity information of the commodity to be evaluated to the safety inventory quantity, so as to obtain the unsalable index of the commodity to be evaluated.

[0073] The current inventory information of the commodity to be evaluated may be information used to characterize the current inventory of the commodity to be evaluated. The ratio between the current inventory of the commodity to be evaluated and the safety inventory obtained in step 301 may be calculated, and the unsalable index of the commodity to be evaluated may be determined based on the ratio.

[0074] In some optional implementations of this embodiment, the ratio of the inventory of the commodity to be evaluated to the safety inventory can be used as the unsalable index of the commodity to be evaluated. The inventory here can be the sum of the inventory of multiple warehouses storing the commodity to be evaluated, or the safety inventory can also be calculated based on the transaction data corresponding to the above-mentioned multiple warehouses.

[0075] In some other optional implementations of this embodiment, the historical transaction data of the commodity to be evaluated may include the historical transaction data of each warehouse storing the commodity to be evaluated, and the current inventory information of the commodity to be evaluated may include the current inventory information of each warehouse storing the commodity to be evaluated. In this case, the step of calculating the safety inventory of the commodity to be evaluated based on the historical transaction data of the commodity to be evaluated may include: calculating the safety inventory of each warehouse based on the historical transaction data of each warehouse storing the commodity to be evaluated. That is, the safety inventory of each warehouse may be calculated separately according to the historical transaction data of each warehouse.

[0076] At the same time, the unsalable index of the above-mentioned goods to be evaluated can be obtained in the following manner: calculate the ratio of the current inventory indicated by the current inventory information of each warehouse to the safety inventory of the warehouse to obtain the unsalable index of each warehouse; determine the weight of each warehouse according to the safety inventory of each warehouse, and perform weighted summation on the unsalable index of each warehouse to obtain the unsalable index of the goods to be evaluated. In other words, the unsalable index of the goods to be evaluated in each warehouse can be calculated separately, and then the weighted summation of the unsalable index of each warehouse can be performed to obtain the unsalable index of the goods to be evaluated. Here, the weight can be determined according to the safety inventory of each warehouse, that is, it can be determined according to the number of transactions per unit time of each warehouse.

[0077] Table 1 shows an example of sales and inventory data of the goods to be evaluated in multiple warehouses. As shown in Table 1, the goods to be evaluated are stored in warehouses A and B. The average daily sales of warehouse A is 1, the safety stock is 90 times the average daily sales, that is, 90, and the current inventory is 150. The unsalable index of warehouse A is 150 / 90=1.67. The average daily sales of warehouse B is 2, the safety stock is 180, and the current inventory is 150. The unsalable index of warehouse B is 150 / 180=0.83. The weights of warehouses A and B can be determined according to the proportion of the average daily sales of each warehouse in the total average daily sales of all warehouses, that is, the weight of warehouse A is 90 / (90+180)=0.33, and the weight of warehouse B is 180 / (90+180)=0.67. Then, the unsalable index of the commodity to be evaluated can be calculated to be 1.67×0.33+0.83×0.33=1.12.

[0078] Table 1 Sales volume and inventory data of the products to be evaluated

[0079] storehouse Average daily sales Safety Stock Current inventory Unsalable Index Warehouse Weight A 1 90 150 1.67 0.33 B 2 180 150 0.83 0.66

[0080] It can be seen from the example described in combination with Table 1 that by performing statistical analysis on the inventory data and transaction data of each warehouse respectively, the safety inventory of different warehouses is taken into account when calculating the unsalable index of the commodity to be evaluated, and the weight of each warehouse is determined accordingly, thereby introducing the differences in transaction data and inventory of warehouses located in different regions into the process of determining the unsalable index, so that a more accurate unsalable index can be obtained.

[0081] Step 303, in response to determining that the unsalable index of the commodity to be evaluated is greater than a preset unsalable index threshold, and the current inventory indicated by the current inventory information of the commodity to be evaluated is greater than the preset inventory threshold, determine that the sales status of the commodity to be evaluated is a unsalable status.

[0082] Then, it can be determined whether the unsalable index of the commodity to be evaluated is greater than the preset unsalable index threshold, and whether the current inventory of the commodity to be evaluated is greater than the preset inventory threshold. If the unsalable index of the commodity to be evaluated is greater than the preset unsalable index threshold, and the current inventory of the commodity to be evaluated is greater than the preset inventory threshold, it can be determined that the sales status of the commodity to be evaluated is an unsalable state. Here, the preset unsalable index threshold can be 1. When the unsalable index exceeds the threshold, it means that the current inventory exceeds the safety stock and there is a risk of inventory backlog. The above-mentioned preset inventory threshold is a value set to avoid commodities with a small actual inventory from being determined as unsalable commodities. In actual scenarios, for example, the safety stock of a commodity to be evaluated is 3, the current inventory is 5, and its unsalable index is 1.67, but the actual inventory of the commodity (i.e., the current inventory) has a negligible effect on the inventory pressure, so it should not be regarded as an unsalable commodity. Therefore, by setting the above-mentioned preset inventory threshold, it can be avoided that the sales status of the commodity to be evaluated is misjudged as an unsalable state due to a small absolute inventory.

[0083] Further optionally, the above method for determining whether the sales status of the commodity to be evaluated is a slow-selling state may also include: determining whether the sales status of the commodity to be evaluated is a preset non-slow-selling state. In this case, the above step 303 may include: in response to determining that the sales status of the commodity to be evaluated is not a preset non-slow-selling state, the slow-selling index of the commodity to be evaluated is greater than a preset slow-selling index threshold, and the current inventory indicated by the current inventory information of the commodity to be evaluated is greater than a preset inventory threshold, determining that the sales status of the commodity to be evaluated is a slow-selling state. Here, the preset non-slow-selling state may be other states pre-set by the merchant providing the commodity to be evaluated according to demand, such as a clearance promotion state. When the sales status of the commodity to be evaluated is a preset non-slow-selling state, the target price of the commodity to be evaluated may be determined according to the price adjustment strategy corresponding to the non-slow-selling state.

[0084] return Figure 2 Then, in step 203, in response to determining that the sales status of the commodity to be evaluated is a slow-selling state, the cost sunk coefficient of the commodity to be evaluated is calculated based on the historical transaction data and current inventory information of the commodity to be evaluated.

[0085] Sunk costs are costs that have been sunk, and are usually used to represent past expenses that are irrelevant to the current decision, and may include, for example, storage costs and transportation costs that have been incurred. Unsunk costs are the remaining costs after deducting sunk costs from the actual costs. In this embodiment, the cost sunk coefficient is used to represent the ratio of the unsunk costs of the commodity to be evaluated to the actual costs of the commodity to be evaluated.

[0086] Generally, sunk costs decrease as transaction volume increases and inventory decreases, and increase as transaction volume decreases and inventory increases. In this embodiment, the cost sunk coefficient can be calculated based on the negative correlation between sunk costs and transaction volume, and the positive correlation between sunk costs and inventory. For example, the ratio of the number of goods that need to be sold per unit time indicated by the current inventory to the average number of transactions per unit time indicated by the historical transaction data can be used as the ratio of sunk costs to actual costs, and then the ratio of unsunk costs to actual costs is calculated, that is, the cost sunk coefficient is obtained.

[0087] In some optional implementations of this embodiment, when determining whether the sales status of the commodity to be evaluated is a slow-moving state, the safety inventory of the commodity to be evaluated can be first calculated based on the historical transaction data of the commodity to be evaluated, and then the ratio of the current inventory indicated by the current inventory information of the commodity to be evaluated to the safety inventory can be calculated to obtain the slow-moving index of the commodity to be evaluated. At this time, the ratio of the safety inventory of the commodity to be evaluated calculated based on the historical transaction data of the commodity to be evaluated to the current inventory of the commodity to be evaluated can be used as the cost sunk coefficient of the commodity to be evaluated, that is, the inverse of the slow-moving index can be used as the cost sunk coefficient. In this way, the slow-moving index used to characterize the slow-moving pressure can be used to calculate the proportion of unsunk costs, so that the impact of the slow-moving pressure on the cost can be considered when determining the price of the commodity to be evaluated, which is conducive to determining a more reasonable and accurate price.

[0088] Step 204, the effective cost of the commodity to be evaluated is calculated based on the sunk cost coefficient and the actual cost of the commodity to be evaluated that has been obtained, and the recommended price of the commodity to be evaluated is determined by collaboratively optimizing the total transaction amount of the commodity to be evaluated and the profit of the commodity to be evaluated based on the effective cost of the commodity to be evaluated.

[0089] The actual cost of the commodity to be evaluated is the cost of the basic expenditures of production, transit, storage, maintenance, etc. of the commodity to be evaluated. The actual cost can be calculated in advance and saved in the above-mentioned execution entity. The effective cost is the unsunk cost.

[0090] Assuming that the above cost sunk coefficient is α, 0<α<1, and the actual cost of the product to be evaluated is c, then the effective cost of the product to be evaluated is c * Calculate according to the following formula (1):

[0091] c * =α·c (1)

[0092] The price of the commodity to be evaluated can be determined by co-optimizing the total transaction amount and profit. Here, the total transaction amount is the total transaction amount within a period of time, which can be the product of the transaction volume and the average transaction price within a period of time, or the cumulative value of each transaction price and the corresponding transaction volume. Profit can be the total transaction amount minus the transaction volume and effective cost c * The remaining part other than the product of . When optimizing the price of a product, it is necessary to maximize the total transaction amount and profit at the recommended price. Alternatively, a price that satisfies the preset conditions for the total transaction amount and profit can be found as the recommended price. For example, a percentage threshold of the profit to the total transaction amount can be set. When optimizing the price of a product, a price that satisfies the percentage threshold of the profit to the total transaction amount is calculated as the recommended price. Or, for example, the total transaction amount and the profit that can be obtained for the current inventory of the product at the current price can be estimated according to the current price of the product to be evaluated, and a preset percentage (for example, 50%) of the estimated total transaction amount and profit is used as the minimum total transaction amount and the minimum profit. When optimizing the price of a product, a price that satisfies the preset percentage of the estimated total transaction amount and the preset percentage of the estimated profit is calculated as the recommended price.

[0093] In some optional implementations of this embodiment, the total transaction amount GMV of the commodity to be evaluated at price p can be calculated as follows:

[0094] GMV=p·Q(p) (2)

[0095] Q(p)=ε(Q0 / p0)p+(1-ε)Q0 (3)

[0096] Among them, ε represents the price elasticity of the commodity to be evaluated, Q0 represents the initial transaction quantity of the commodity to be evaluated, p0 represents the initial price of the commodity to be evaluated, and Q(p) represents the transaction quantity of the commodity to be evaluated at price p;

[0097] The profit GP of the commodity to be evaluated at price p is calculated as follows:

[0098] GP=(pc * )·Q(p) (4)

[0099] According to the effective cost of the commodity to be evaluated, the recommended price of the commodity to be evaluated is determined by collaboratively optimizing the total transaction amount of the commodity to be evaluated and the profit of the commodity to be evaluated. The method may include: firstly constructing a collaborative optimization function G(p) based on the total transaction amount GMV and the profit GP of the commodity to be evaluated at price p:

[0100]

[0101] GP0 and GMV0 represent the total transaction volume and profit of the commodity to be evaluated at the initial price p0, respectively. β is the synergy coefficient, β>0.

[0102] Then, the recommended price of the commodity to be evaluated is determined by maximizing the collaborative optimization function, that is, the price p that maximizes G(p) of formula (5) is found as the recommended price.

[0103] The above synergy coefficient β is used to characterize the relative size of the ability of the evaluated commodity to increase the total transaction amount and the ability to increase the profit. When the ability of the evaluated commodity to increase the total transaction amount is stronger than the ability to increase the profit, β < 1; when the ability of the evaluated commodity to increase the total transaction amount is weaker than the ability to increase the profit, β > 1; when the ability of the evaluated commodity to increase the total transaction amount and the ability to increase the profit are equal, β = 1. In some optional implementations, the synergy coefficient can be a preset value.

[0104] Here, the ability of the commodity to be evaluated to increase the total transaction amount and the ability to increase profits are based on the statistical analysis of historical transaction data. For example, when the total transaction amount changes by 1% by adjusting the price near the original price p0, the profit changes by more than 1%, then the ability of the commodity to be evaluated to increase profits is considered to be stronger than its ability to increase the total transaction amount; when the total transaction amount changes by 1% by adjusting the price near the original price p0, the profit changes by less than 1%, then the ability of the commodity to be evaluated to increase profits is considered to be weaker than its ability to increase the total transaction amount; when the total transaction amount changes by 1% by adjusting the price near the original price p0, the profit changes by 1%, then the ability of the commodity to be evaluated to increase profits is equal to its ability to increase the total transaction amount.

[0105] In some other optional implementations, the synergy coefficient can be determined by combining the ability of the above-mentioned commodity to be evaluated to increase the total transaction amount and the ability to increase profits with the merchant's expectations for the total transaction amount and profits. For example, the merchant sets the price to be adjusted only if the profit can be increased by more than 2% when the total transaction amount is lost by 1%, or the price to be adjusted only if the total transaction amount can be increased by more than 2% when the profit is lost by 1%. If the ability of the commodity to be evaluated to increase profits is stronger than its ability to increase the total transaction amount, the synergy coefficient β can be set to 2. If the ability of the commodity to be evaluated to increase profits is weaker than its ability to increase the total transaction amount, the synergy coefficient β can be set to 0.5.

[0106] Please refer to Figure 4 , which shows a schematic diagram of the relationship between the cost of the commodity to be evaluated and the profit of the commodity to be evaluated.

[0107] exist Figure 4 In the example, the horizontal axis represents the price p, and the vertical axis represents the transaction quantity Q(p). The transaction quantity decreases as the price increases. c represents the cost, α×c represents the effective cost, and p1* , p2 * They represent the price without considering sunk costs and the recommended price after considering sunk costs respectively.

[0108] from Figure 4 It can be seen that the area of ​​region L1 is (p1 * -c)×Q(p1 * ), the area of ​​region L2 is (p2 * -α×c)×Q(p2 * ), the area of ​​region L2 is larger than that of region L1. When the sales status of the commodity to be evaluated is a slow-moving state, it is necessary to consider the recovery of sunk costs. (c-α×c)×Q(p) represents the total sunk costs. In the slow-moving state, the total sunk costs that need to be recovered can also be regarded as part of the profit. In the slow-moving state (price p is p2 * When the equivalent profit is the area of ​​L2, the cost is not sunk under normal sales conditions, and the profit is the area of ​​L1, which means that the price is increased from p1 to p2. * Reduced to p2 * Then the equivalent profit can be obtained by (p1 * -c)×Q(p1 * ) increases to (p2 * -α×c)×Q(p2 * ). In other words, in the state of slow sales, it is necessary to maximize the recoverable total sunk cost (c-α×c)×Q(p), so it is necessary to increase the transaction quantity Q(p). According to the negative correlation between the transaction quantity Q(p) and the price p, it can be known that the recoverable total sunk cost can be increased by lowering the price p.

[0109] In the above optional implementation, when calculating the recommended price, the price p can be derived according to formula (5) to obtain:

[0110] G'(p)=2(1+β')εp+(1+β')(1-ε)p0-α·c·ε (6)

[0111]

[0112] Among them, ε is the price elasticity, which is usually negative, so 2εp<0, (1-ε)p0>0,

[0113] Let G'(p) = 0 and we get:

[0114]

[0115] If p<p * When G'(p)>0, then p calculated by equation (8) is *The recommended price to maximize the collaborative optimization function G(p).

[0116] Step 205: Push price information indicating a recommended price for the commodity to be evaluated.

[0117] In this embodiment, price information of the commodity to be evaluated can be generated and pushed according to the determined recommended price. Specifically, the price information can be pushed in response to the merchant's price recommendation request for the commodity to be evaluated, or the price information can be actively pushed to the merchant. After receiving the price information, the merchant can make a price adjustment decision.

[0118] The method for pushing information in the above embodiment of the present application obtains the historical transaction data and current inventory information of the commodity to be evaluated, and then determines whether the sales status of the commodity to be evaluated is a slow-selling state based on the historical transaction data and current inventory information of the commodity to be evaluated, and then in response to determining that the sales status of the commodity to be evaluated is a slow-selling state, calculates the cost sunk coefficient of the commodity to be evaluated based on the historical transaction data and current inventory information of the commodity to be evaluated, wherein the cost sunk coefficient is used to characterize the proportion of the unsunk cost of the commodity to be evaluated to the actual cost of the commodity to be evaluated, and then calculates the effective cost of the commodity to be evaluated based on the cost sunk coefficient and the actual cost of the commodity to be evaluated that has been obtained, and determines the recommended price of the commodity to be evaluated by collaboratively optimizing the total transaction amount of the commodity to be evaluated and the profit of the commodity to be evaluated based on the effective cost of the commodity to be evaluated, and finally pushes the price information indicating the recommended price of the commodity to be evaluated, thereby realizing automated commodity price evaluation and push. Since the impact of the inventory pressure caused by the slow-selling state of the commodity on the effective cost used in calculating the profit is fully considered when performing price evaluation, a more accurate recommended price can be provided.

[0119] Further references Figure 5 As an implementation of the methods shown in the above figures, the present application provides an embodiment of a device for pushing information, and the device embodiment is similar to Figure 2 Corresponding to the method embodiment shown, the device can be specifically applied to various electronic devices.

[0120] like Figure 5As shown, the device 500 for pushing information in this embodiment includes: an acquisition unit 501, a judgment unit 502, a calculation unit 503, a determination unit 504 and a push unit 505. The acquisition unit 501 is used to acquire the historical transaction data and current inventory information of the commodity to be evaluated; the judgment unit 502 is used to determine whether the sales status of the commodity to be evaluated is a slow-selling state based on the historical transaction data and current inventory information of the commodity to be evaluated; the calculation unit 503 is used to calculate the cost sunk coefficient of the commodity to be evaluated based on the historical transaction data and current inventory information of the commodity to be evaluated in response to determining that the sales status of the commodity to be evaluated is a slow-selling state, wherein the cost sunk coefficient is used to characterize the proportion of the unsunk cost of the commodity to be evaluated to the actual cost of the commodity to be evaluated; the determination unit 504 is used to calculate the effective cost of the commodity to be evaluated based on the cost sunk coefficient and the actual cost of the commodity to be evaluated that has been acquired, and determine the recommended price of the commodity to be evaluated by collaboratively optimizing the total transaction amount of the commodity to be evaluated and the profit of the commodity to be evaluated based on the effective cost of the commodity to be evaluated; the push unit 505 is used to push price information indicating the recommended price of the commodity to be evaluated.

[0121] In some embodiments, the judgment unit 502 can be further used to judge whether the sales status of the commodity to be evaluated is a slow-selling state in the following manner: calculating the safety stock of the commodity to be evaluated based on the historical transaction data of the commodity to be evaluated; calculating the ratio of the current inventory indicated by the current inventory information of the commodity to be evaluated to the safety stock to obtain the slow-selling index of the commodity to be evaluated; in response to determining that the slow-selling index of the commodity to be evaluated is greater than a preset slow-selling index threshold, and the current inventory indicated by the current inventory information of the commodity to be evaluated is greater than the preset inventory threshold, determining that the sales status of the commodity to be evaluated is a slow-selling state.

[0122] In some embodiments, the historical transaction data of the commodity to be evaluated includes the historical transaction data of each warehouse storing the commodity to be evaluated, and the current inventory information of the commodity to be evaluated includes the current inventory information of each warehouse storing the commodity to be evaluated. At this time, the judgment unit 502 can be further used to calculate the safety inventory of the commodity to be evaluated in the following manner: based on the historical transaction data of each warehouse storing the commodity to be evaluated, calculate the safety inventory of each warehouse; and the judgment unit 502 can be further used to obtain the unsalable index of the commodity to be evaluated in the following manner: calculate the ratio of the current inventory indicated by the current inventory information of each warehouse to the safety inventory of the warehouse, and obtain the unsalable index of each warehouse; determine the weight of each warehouse according to the safety inventory of each warehouse, and perform weighted summation on the unsalable index of each warehouse to obtain the unsalable index of the commodity to be evaluated.

[0123] In some embodiments, the judgment unit 502 can also be used to: judge whether the sales status of the commodity to be evaluated is a preset non-slow-selling status; and the judgment unit 502 can be used to judge whether the sales status of the commodity to be evaluated is a slow-selling status in the following manner: in response to determining that the sales status of the commodity to be evaluated is not a preset non-slow-selling status, the slow-selling index of the commodity to be evaluated is greater than a preset slow-selling index threshold, and the current inventory indicated by the current inventory information of the commodity to be evaluated is greater than the preset inventory threshold, it is determined that the sales status of the commodity to be evaluated is a slow-selling status.

[0124] In some embodiments, the calculation unit 503 can be further used to calculate the sunk cost coefficient of the commodity to be evaluated in the following manner: the ratio of the safety inventory of the commodity to be evaluated calculated based on the historical transaction data of the commodity to be evaluated to the current inventory of the commodity to be evaluated is used as the sunk cost coefficient of the commodity to be evaluated.

[0125] In some embodiments, the effective cost c* of the commodity to be evaluated is calculated as follows:

[0126] c * =α·c,

[0127] Among them, α is the cost sunk coefficient and c is the actual cost.

[0128] The GMV of the product to be evaluated at price p is calculated as follows:

[0129] GMV=p·Q(p),

[0130] Q(p)=ε(Q0 / p0)p+(1-ε)Q0;

[0131] Among them, ε represents the price elasticity of the commodity to be evaluated, Q0 represents the initial transaction quantity of the commodity to be evaluated, p0 represents the initial price of the commodity to be evaluated, and Q(p) represents the transaction quantity of the commodity to be evaluated at price p.

[0132] The profit GP of the commodity to be evaluated at price p is calculated as follows:

[0133] GP=(pc * )·Q(p),

[0134] The determination unit 504 can be further used to determine the recommended price of the commodity to be evaluated in the following manner: construct a collaborative optimization function G(p) based on the total transaction amount GMV and profit GP of the commodity to be evaluated at price p; determine the recommended price of the commodity to be evaluated by maximizing the collaborative optimization function; wherein,

[0135]

[0136] GP0 and GMV0 represent the total transaction volume and profit of the commodity to be evaluated at the initial price p0, respectively, and β is the synergy coefficient.

[0137] It should be understood that the units described in the apparatus 500 are similar to those described in the reference Figure 2 Therefore, the operations and features described above for the method are also applicable to the device 500 and the units included therein, and will not be described in detail here.

[0138] The device 500 for pushing information in the above embodiment of the present application obtains the historical transaction data and current inventory information of the commodity to be evaluated through the acquisition unit, and then the judgment unit judges whether the sales status of the commodity to be evaluated is a slow-selling state based on the historical transaction data and current inventory information of the commodity to be evaluated. Then, in response to determining that the sales status of the commodity to be evaluated is a slow-selling state, the calculation unit calculates the cost sunk coefficient of the commodity to be evaluated based on the historical transaction data and current inventory information of the commodity to be evaluated, wherein the cost sunk coefficient is used to characterize the proportion of the unsunk cost of the commodity to be evaluated to the actual cost of the commodity to be evaluated, and then the determination unit calculates the effective cost of the commodity to be evaluated based on the cost sunk coefficient and the actual cost of the commodity to be evaluated that has been obtained, and determines the recommended price of the commodity to be evaluated by collaboratively optimizing the total transaction amount of the commodity to be evaluated and the profit of the commodity to be evaluated according to the effective cost of the commodity to be evaluated, and finally the push unit pushes the price information indicating the recommended price of the commodity to be evaluated, thereby realizing automatic commodity price evaluation and push. Since the impact of the inventory pressure caused by the slow-selling state of the commodity on the effective cost used in calculating the profit is fully considered when performing price evaluation, a more accurate recommended price can be provided.

[0139] Reference below Figure 6 , which shows a schematic diagram of the structure of a computer system 600 suitable for implementing a server of an embodiment of the present application. Figure 6 The server shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0140] like Figure 6 As shown, the computer system 600 includes a central processing unit (CPU) 601, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 602 or a program loaded from a storage part 608 into a random access memory (RAM) 603. In the RAM 603, various programs and data required for the operation of the system 600 are also stored. The CPU 601, the ROM 602, and the RAM 603 are connected to each other via a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0141] The following components are connected to the I / O interface 605: an input section 606 including a keyboard, a mouse, etc.; an output section 607 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 608 including a hard disk, etc.; and a communication section 609 including a network interface card such as a LAN card, a modem, etc. The communication section 609 performs communication processing via a network such as the Internet. A drive 610 is also connected to the I / O interface 605 as needed. A removable medium 611, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 610 as needed, so that a computer program read therefrom is installed into the storage section 608 as needed.

[0142] In particular, according to an embodiment of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 609, and / or installed from the removable medium 611. When the computer program is executed by the central processing unit (CPU) 601, the above functions defined in the method of the present application are executed. It should be noted that the computer-readable medium described in the present application can be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium can be, for example, - but not limited to - an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to, an electrical connection with one or more conductors, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, an apparatus or a device. In the present application, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in combination with an instruction execution system, an apparatus or a device. The program code contained on the computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, optical cable, RF, etc., or any suitable combination of the above.

[0143] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0144] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0145] The units involved in the embodiments described in the present application may be implemented by software or by hardware. The units described may also be set in a processor, for example, it may be described as: a processor includes an acquisition unit, a judgment unit, a calculation unit, a determination unit, and a push unit. Among them, the names of these units do not constitute a limitation on the unit itself under certain circumstances. For example, the acquisition unit may also be described as "a unit for acquiring historical transaction data and current inventory information of the commodity to be evaluated."

[0146] As another aspect, the present application also provides a computer-readable medium, which may be included in the device described in the above embodiment; or may exist independently without being assembled into the device. The above computer-readable medium carries one or more programs, and when the above one or more programs are executed by the device, the device: obtains historical transaction data and current inventory information of the commodity to be evaluated; determines whether the sales status of the commodity to be evaluated is a slow-selling state based on the historical transaction data and current inventory information of the commodity to be evaluated; in response to determining that the sales status of the commodity to be evaluated is a slow-selling state, calculates the cost sunk coefficient of the commodity to be evaluated based on the historical transaction data and current inventory information of the commodity to be evaluated, wherein the cost sunk coefficient is used to characterize the proportion of the unsunk cost of the commodity to be evaluated to the actual cost of the commodity to be evaluated; calculates the effective cost of the commodity to be evaluated based on the cost sunk coefficient and the actual cost of the commodity to be evaluated that has been obtained, and determines the recommended price of the commodity to be evaluated by collaboratively optimizing the total transaction amount of the commodity to be evaluated and the profit of the commodity to be evaluated based on the effective cost of the commodity to be evaluated; pushes price information indicating the recommended price of the commodity to be evaluated.

[0147] The above description is only a preferred embodiment of the present application and an explanation of the technical principles used. Those skilled in the art should understand that the scope of the invention involved in the present application is not limited to the technical solution formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the above invention concept. For example, the above features are replaced with the technical features with similar functions disclosed in this application (but not limited to) by each other to form a technical solution.

Claims

1. A method for pushing information, include: Obtaining historical transaction data and current inventory information of the commodity to be evaluated, wherein the historical transaction data of the commodity to be evaluated includes: transaction volume, order generation time, order price, transaction payment method, shipping warehouse, delivery time, and commodity evaluation data of the commodity to be evaluated in a historical period before the current time; Determining whether the sales status of the commodity to be evaluated is a slow-selling status based on the historical transaction data and current inventory information of the commodity to be evaluated, wherein the historical transaction data of the commodity to be evaluated includes the historical transaction data of each warehouse storing the commodity to be evaluated, and the current inventory information of the commodity to be evaluated includes the current inventory information of each warehouse storing the commodity to be evaluated; In response to determining that the sales status of the commodity to be evaluated is a slow-selling status, calculating the cost sunk factor of the commodity to be evaluated based on the historical transaction data and current inventory information of the commodity to be evaluated, wherein the cost sunk factor is used to represent the ratio of the unsunk cost of the commodity to be evaluated to the actual cost of the commodity to be evaluated; Calculating the effective cost of the commodity to be evaluated based on the sunk cost coefficient and the actual cost of the commodity to be evaluated that has been obtained, and determining the recommended price of the commodity to be evaluated by collaboratively optimizing the total transaction amount of the commodity to be evaluated and the profit of the commodity to be evaluated based on the effective cost of the commodity to be evaluated; Push price information indicating a recommended price for the commodity to be evaluated.

2. The method according to claim 1, in, The determining whether the sales status of the commodity to be evaluated is a slow-selling status based on the historical transaction data and current inventory information of the commodity to be evaluated includes: Calculate the safety inventory of the commodity to be evaluated based on the historical transaction data of the commodity to be evaluated; Calculating the ratio of the current inventory quantity indicated by the current inventory quantity information of the commodity to be evaluated to the safety inventory quantity to obtain the unsalable index of the commodity to be evaluated; In response to determining that the unsalable index of the commodity to be evaluated is greater than a preset unsalable index threshold, and the current inventory indicated by the current inventory information of the commodity to be evaluated is greater than the preset inventory threshold, it is determined that the sales status of the commodity to be evaluated is a unsalable status.

3. The method according to claim 2, in, The calculating the safety inventory of the commodity to be evaluated based on the historical transaction data of the commodity to be evaluated includes: Calculating the safety inventory of each warehouse based on the historical transaction data of each warehouse storing the commodity to be evaluated; and The calculating the ratio of the current inventory quantity indicated by the current inventory quantity information of the commodity to be evaluated to the safety inventory quantity to obtain the unsalable index of the commodity to be evaluated includes: Calculate the ratio of the current inventory quantity indicated by the current inventory quantity information of each warehouse to the safety inventory quantity of the warehouse to obtain the unsalable index of each warehouse; The weight of each warehouse is determined according to the safety inventory of each warehouse, and the unsalable index of each warehouse is weighted and summed to obtain the unsalable index of the commodity to be evaluated.

4. The method according to claim 2, in, The determining whether the sales status of the commodity to be evaluated is a slow-selling status based on the historical transaction data and current inventory information of the commodity to be evaluated further includes: Determining whether the sales status of the commodity to be evaluated is a preset non-unsalable status; and In response to determining that the unsalable index of the commodity to be evaluated is greater than a preset unsalable index threshold, and the current inventory quantity indicated by the current inventory quantity information of the commodity to be evaluated is greater than the preset inventory quantity threshold, determining that the sales status of the commodity to be evaluated is an unsalable status includes: In response to determining that the sales status of the commodity to be evaluated is not a preset non-slow-selling status, the slow-selling index of the commodity to be evaluated is greater than a preset slow-selling index threshold, and the current inventory indicated by the current inventory information of the commodity to be evaluated is greater than the preset inventory threshold, it is determined that the sales status of the commodity to be evaluated is a slow-selling status.

5. The method according to claim 2, in, The calculating the sunk cost coefficient of the commodity to be evaluated based on the historical transaction data and current inventory information of the commodity to be evaluated includes: The ratio of the safety inventory of the commodity to be evaluated calculated based on the historical transaction data of the commodity to be evaluated to the current inventory of the commodity to be evaluated is used as the cost sunk coefficient of the commodity to be evaluated.

6. The method according to any one of claims 1 to 5, in, The effective cost c of the commodity to be evaluated * It is calculated as follows: c * =αc Among them, α is the cost sunk coefficient, c is the actual cost; The total transaction volume GMV of the commodity to be evaluated at price p is calculated as follows: GMV=pQ(p), Q(p)=ε(Q 0 / p 0 )p+(1-ε)Q 0 ; Among them, ε represents the price elasticity of the commodity to be evaluated, Q 0 represents the initial transaction quantity of the commodity to be evaluated, p 0 represents the initial price of the commodity to be evaluated, Q(p) represents the transaction quantity of the commodity to be evaluated at price p; The profit GP of the commodity to be evaluated at price p is calculated as follows: GP=(pc * )Q(p); The determining the recommended price of the commodity to be evaluated by collaboratively optimizing the total transaction amount of the commodity to be evaluated and the profit of the commodity to be evaluated according to the effective cost of the commodity to be evaluated includes: Construct a collaborative optimization function G(p) based on the total transaction amount GMV and profit GP of the commodity to be evaluated at price p; Determine the recommended price of the commodity to be evaluated by maximizing the collaborative optimization function; in, GP 0 and GMV 0 They represent the initial price p 0 The total transaction volume and profit of the commodity to be evaluated are as follows, and β is the synergy coefficient.

7. A device for pushing information, include: An acquisition unit is used to acquire historical transaction data and current inventory information of the commodity to be evaluated, wherein the historical transaction data of the commodity to be evaluated includes: transaction volume, order generation time, order price, transaction payment method, shipping warehouse, delivery time, and commodity evaluation data of the commodity to be evaluated within a historical period before the current time; A judging unit, configured to judge whether the sales status of the commodity to be evaluated is a slow-selling status based on the historical transaction data and current inventory information of the commodity to be evaluated, wherein the historical transaction data of the commodity to be evaluated includes the historical transaction data of each warehouse storing the commodity to be evaluated, and the current inventory information of the commodity to be evaluated includes the current inventory information of each warehouse storing the commodity to be evaluated; A calculation unit, configured to calculate, in response to determining that the sales status of the commodity to be evaluated is a slow-selling status, a cost sunk coefficient of the commodity to be evaluated based on historical transaction data and current inventory information of the commodity to be evaluated, wherein the cost sunk coefficient is used to represent the ratio of the unsunk cost of the commodity to be evaluated to the actual cost of the commodity to be evaluated; a determination unit, configured to calculate the effective cost of the commodity to be evaluated according to the sunk cost coefficient and the acquired actual cost of the commodity to be evaluated, and determine the recommended price of the commodity to be evaluated by collaboratively optimizing the total transaction amount of the commodity to be evaluated and the profit of the commodity to be evaluated according to the effective cost of the commodity to be evaluated; The push unit is used to push price information indicating a recommended price of the commodity to be evaluated.

8. The device according to claim 7, in, The judging unit is further used to judge whether the sales status of the commodity to be evaluated is a slow-selling status in the following manner: Calculate the safety inventory of the commodity to be evaluated based on the historical transaction data of the commodity to be evaluated; Calculating the ratio of the current inventory quantity indicated by the current inventory quantity information of the commodity to be evaluated to the safety inventory quantity to obtain the unsalable index of the commodity to be evaluated; In response to determining that the unsalable index of the commodity to be evaluated is greater than a preset unsalable index threshold, and the current inventory indicated by the current inventory information of the commodity to be evaluated is greater than the preset inventory threshold, it is determined that the sales status of the commodity to be evaluated is a unsalable status.

9. The device according to claim 8, in, The judgment unit is further configured to calculate the safety inventory of the commodity to be evaluated in the following manner: Calculating the safety inventory of each warehouse based on the historical transaction data of each warehouse storing the commodity to be evaluated; and The judgment unit is further used to obtain the unsalable index of the commodity to be evaluated in the following manner: Calculate the ratio of the current inventory quantity indicated by the current inventory quantity information of each warehouse to the safety inventory quantity of the warehouse to obtain the unsalable index of each warehouse; The weight of each warehouse is determined according to the safety inventory of each warehouse, and the unsalable index of each warehouse is weighted and summed to obtain the unsalable index of the commodity to be evaluated.

10. The device according to claim 8, in, The judging unit is also used for: Determining whether the sales status of the commodity to be evaluated is a preset non-unsalable status; and The judging unit is used to judge whether the sales status of the commodity to be evaluated is a slow-selling status in the following manner: In response to determining that the sales status of the commodity to be evaluated is not a preset non-slow-selling status, the slow-selling index of the commodity to be evaluated is greater than a preset slow-selling index threshold, and the current inventory indicated by the current inventory information of the commodity to be evaluated is greater than the preset inventory threshold, it is determined that the sales status of the commodity to be evaluated is a slow-selling status.

11. The device according to claim 8, in, The calculation unit is further used to calculate the cost sunk coefficient of the commodity to be evaluated in the following manner: The ratio of the safety inventory of the commodity to be evaluated calculated based on the historical transaction data of the commodity to be evaluated to the current inventory of the commodity to be evaluated is used as the cost sunk coefficient of the commodity to be evaluated.

12. The device according to any one of claims 7 to 11, in, The effective cost c of the commodity to be evaluated * It is calculated as follows: c * =αc Among them, α is the cost sunk coefficient, c is the actual cost; The total transaction volume GMV of the commodity to be evaluated at price p is calculated as follows: GMV=pQ(p), Q(p)=ε(Q 0 / p 0 )p+(1-ε)Q 0 ; Among them, ε represents the price elasticity of the commodity to be evaluated, Q 0 represents the initial transaction quantity of the commodity to be evaluated, p 0 represents the initial price of the commodity to be evaluated, Q(p) represents the transaction quantity of the commodity to be evaluated at price p; The profit GP of the commodity to be evaluated at price p is calculated as follows: GP=(pc * )Q(p); The determining unit is further configured to determine the recommended price of the commodity to be evaluated in the following manner: Construct a collaborative optimization function G(p) based on the total transaction amount GMV and profit GP of the commodity to be evaluated at price p; Determine the recommended price of the commodity to be evaluated by maximizing the collaborative optimization function; in, GP 0 and GMV 0 They represent the initial price p 0 The total transaction volume and profit of the commodity to be evaluated are as follows, and β is the synergy coefficient.

13. An electronic device, include: one or more processors; a storage device for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 6.

14. A computer storage medium having a computer program stored thereon, in, When the program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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