Fresh commodity pricing method and system
Through an automated fresh product pricing system, numerical adjustment of pricing based on product types and consumer preferences, the pricing inaccurate problem caused by manual judgment is solved, pricing efficiency and accuracy are improved, and sales are improved.
Patent Information
- Application Number
- CN202411519812.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-10-29
- Publication Date
- 2025-01-14
- Estimated Expiration
- Not applicable · inactive patent
AI Technical Summary
The existing fresh product pricing strategy relies too much on manual judgment, resulting in inaccurate pricing and affecting sales.
By receiving target pricing requests, the initial pricing is automatically calculated based on the target product type and cost price, and adjusted in combination with the consumer preference values, reducing manual intervention and achieving pricing automation and accuracy.
It improves the efficiency and accuracy of pricing, improves sales, and ensures that pricing matches market demand.
Smart Images
Figure CN119313414A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the technical field of fresh commodity supply chain management, and specifically to a pricing method and system for fresh commodities. Background Art
[0002] Fresh products refer to primary products that have not been deeply processed (such as cooking, making, etc.), but have only undergone necessary preservation treatment and simple arrangement before being put on the shelves for sale, as well as a collection of products including on-site processed categories such as bread and cooked food. This category covers multiple categories such as fruits, vegetables, meat, aquatic products, dry goods and daily necessities, cooked food and cakes. Fresh products are classified into one category because of their common characteristics and storage conditions - that is, they need to be preserved, refrigerated or frozen, are usually sold in bulk and need to be sold by weighing and printing barcodes. In addition, this type of product has a relatively short shelf life and shows a strong correlation in consumer purchasing habits.
[0003] In the current supply chain management of fresh products, the formulation of pricing strategies is often limited to the fixed cost plus method or a static method based on a simplified market demand forecasting model. Specifically, the traditional fresh product pricing process often relies too much on manual judgment or preset pricing rules. Manual judgment is prone to inaccurate pricing, which can affect the sales of products.
[0004] Therefore, there is an urgent need for a pricing method and system for fresh products that can solve the above technical problems. Summary of the invention
[0005] The present application provides a pricing method and system for fresh goods. The method receives a target pricing request, automatically determines a target type according to the target product, and then uses a preset pricing model to calculate a first price for the target type and the target cost price, and then obtains a preference value for the target product, and adjusts the first price to obtain a second price, which reflects the differences in preferences of different consumers for different products. The entire pricing process reduces human intervention, thereby reducing the risk of inaccurate pricing due to personal factors.
[0006] In a first aspect, the present application provides a pricing method for fresh goods, which is applied to a server, and the method includes: receiving a target pricing request sent by a user, the target pricing request being a request for pricing a target commodity, and the target commodity being any fresh commodity to be priced; determining a target type according to the target commodity, the target types including fruit type, vegetable type, meat type, aquatic product type, dry goods type, and cooked food and pastry type; determining a first factor according to the target type, inputting the first factor and a target cost price into a preset pricing model for processing to obtain a first price, and the target cost price is the cost price corresponding to the target commodity; obtaining a target preference value corresponding to the target commodity, calculating the first price according to the target preference value to obtain a second price; and sending the second price to the user so that the user processes the target commodity according to the second price.
[0007] By adopting the above technical solution, the target pricing request sent by the user is received, and the target type corresponding to the target product is determined according to the target pricing request, so as to realize automatic classification of products and reduce the tediousness and errors of manual classification. Then, the preset pricing model is used for processing according to the target type and target cost price to obtain the first pricing, and then the target preference value corresponding to the target product is introduced. The target preference value is combined with the first pricing, and the second pricing is further calculated, so that the pricing is closer to the market demand, the whole pricing process is automated, and the situation of manual intervention is reduced, which not only improves the efficiency of pricing, but also improves the accuracy of pricing, which in turn helps to improve sales.
[0008] Optionally, a target preference value corresponding to the target product is obtained, and the first price is calculated according to the target preference value to obtain a second price, specifically including: obtaining target analysis information corresponding to the target product, the target analysis information including survey information, social media analysis information and sales data information; processing the target analysis information to obtain a target preference value; determining whether the target preference value is greater than a preset preference threshold; when the target preference value is greater than the preset preference threshold, obtaining a first value, which is the difference between the target preference value and the preset preference threshold; and calculating the first value and the first price to obtain a second price.
[0009] By adopting the above technical solution, the target analysis information corresponding to the target product is obtained. Based on the target analysis information, the consumer's demand and preference for the target product can be fully understood. The target analysis information is processed to obtain a target preference value. The target preference value can accurately reflect the consumer's preference for the target product. The target preference value is compared with the preset preference threshold. When the target preference value is greater than the preset preference threshold, it means that the consumer has a high preference for the target product and the market demand is strong. The first value can be calculated with the first price to obtain a higher second price. This dynamic adjustment method can ensure that the pricing matches the market demand.
[0010] Optionally, after determining whether the target preference value is greater than a preset preference threshold, the method also includes: when the target preference value is equal to the preset preference threshold, confirming to output the first price as the second price; when the target preference value is less than the preset preference threshold, confirming to obtain the second value; and calculating the second value with the first price to obtain the second price.
[0011] By adopting the above technical solution, the pricing strategy can be flexibly adjusted according to the comparison between the target preference value and the preset preference threshold. When the target preference value is equal to the preset preference value, it means that the consumer's preference for the target product is consistent with market expectations. At this time, directly using the first price as the second price can ensure that the pricing is consistent with market demand; when the target preference value is less than the preset preference threshold, it means that the consumer's preference for the target product is low and the market demand is not strong. By calculating the relationship between the second value and the first price, a lower second price can be obtained to improve sales efficiency.
[0012] Optionally, after sending the second price to the user so that the user can process the target product according to the second price, the method also includes: obtaining a target time point, the target time point being the time point for determining that the target product is corresponding to the second price; determining a target time period based on the target time point, the target time period being any time period after the target time point; determining a second factor corresponding to the target type, the second factor being a time factor and a shelf life factor; inputting the second factor and the second price into a preset pricing model for processing to obtain a third price; and sending a prompt message to the user so that the user can adjust the second price according to the prompt message, the prompt message being information about the target product corresponding to the third price in the target time period.
[0013] By adopting the above technical solution, the target time point is obtained, and the target time period is determined based on the target time point. Different pricing strategies can be formulated for different time periods. The second factor is introduced, and the second factor and the second price are input into the preset pricing model for processing to obtain a third price that meets market demand, so that merchants can make corresponding adjustments in a timely manner based on the third price.
[0014] Optionally, after sending the second price to the user so that the user can process the target product according to the second price, the method also includes: obtaining a target inventory corresponding to the target product at preset time intervals; if the target inventory is in an abnormal sales state, confirming the acquisition of the second price, the second price being the price corresponding to the currently sold target product; obtaining a target number of days corresponding to the target product, the target number of days being the number of days remaining in the shelf life of the target product; determining whether the target number of days is less than or equal to the preset number of days; when the target number of days is less than or equal to the preset number of days, confirming that the target product corresponds to a first processing plan, the first processing plan includes a discount pricing processing plan, a combination sales processing plan, and a member discount processing plan; when the target number of days is greater than the preset number of days, confirming that the target product corresponds to a second processing plan, the second processing plan includes a promotion processing plan, a differentiated pricing processing plan, and an additional service processing plan.
[0015] By adopting the above technical solution, the inventory quantity corresponding to the target product is obtained at preset intervals. When the inventory quantity is in an abnormal sales state, the second price corresponding to the target product can be obtained, and then the target number of days can be obtained. Differentiated sales can be formulated for products with different shelf lives. The target number of days is compared with the preset number of days. When the target number of days is less than or equal to the preset number of days, the first processing solution can be adopted. The first processing solution helps to quickly reduce inventory and improve sales efficiency. When the target number of days is greater than the preset number of days, the second processing solution can be adopted to increase sales attractiveness and extend the sales cycle.
[0016] Optionally, the first factor is determined according to the target type, specifically including: when the target type is a fruit type or a vegetable type, the first factor is confirmed as a first set, and the first set includes weather factors, competitive price factors and seasonal planting factors; when the target type is a meat type, the first factor is confirmed as a second set, and the second set includes shelf life factors, competitive price factors and time factors; when the target type is aquatic product type or a dry product type, the first factor is confirmed as a third set, and the third set includes time factors and weather factors; when the target type is a cooked food and pastry type, the first factor is confirmed as a fourth set, and the fourth set includes shelf life factors and time factors.
[0017] By adopting the above technical solutions, different types of goods determine different sets of target factors, and then accurately formulate pricing strategies and inventory management plans, which helps merchants respond to market changes in a timely manner and adjust sales strategies.
[0018] Optionally, after receiving the target pricing request sent by the user, the method also includes: determining a target store based on the target product, the target store being an offline store that sells fresh products; inputting the target product into a preset intelligent big model for processing to obtain a target prediction result; determining a fourth price based on the target prediction result, and sending the fourth price to the target store so that the target store can optimize the selling price of the target product.
[0019] By adopting the above technical solution, the target product is input into the preset intelligent big model for processing, and the target prediction result can be obtained. The target prediction result is a comprehensive consideration of multiple factors to provide a more accurate pricing suggestion for the target product. The target store can dynamically adjust the selling price of the target product according to the target prediction result to adapt to market changes, thereby improving operational efficiency.
[0020] In a second aspect of the present application, a pricing system for fresh goods is provided, the system is a server, the server includes a receiving unit, a processing unit and a sending unit; the receiving unit receives a target pricing request sent by a user, the target pricing request is a request for pricing a target commodity, and the target commodity is any fresh commodity to be priced; the target preference value corresponding to the target commodity is obtained, the processing unit determines the target type according to the target commodity, the target type includes fruit type, vegetable type, meat type, aquatic product type, dry goods type and cooked pastry type; a first factor is determined according to the target type, the first factor and the target cost price are input into a preset pricing model for processing, and a first price is obtained, and the target cost price is the cost price corresponding to the target commodity; the first price is calculated according to the target preference value to obtain a second price; the sending unit sends the second price to the user, so that the user processes the target commodity according to the second price.
[0021] Optionally, the receiving unit is used to obtain target analysis information corresponding to the target product, the target analysis information including survey information, social media analysis information and sales data information; the processing unit is used to process the target analysis information to obtain a target preference value; determine whether the target preference value is greater than a preset preference threshold; when the target preference value is greater than the preset preference threshold, obtain a first value, the first value being the difference between the target preference value and the preset preference threshold; and compare the first value with the first price to obtain a second price.
[0022] Optionally, the processing unit is used to confirm that the first price is output as the second price when the target preference value is equal to a preset preference threshold; confirm that the second value is obtained when the target preference value is less than the preset preference threshold; and calculate the second value with the first price to obtain the second price.
[0023] Optionally, the receiving unit is used to obtain a target time point, which is a time point for determining that the target product is corresponding to the second price; the processing unit is used to determine a target time period based on the target time point, which is any time period after the target time point; determine a second factor corresponding to the target type, which is a time factor and a shelf life factor; input the second factor and the second price into a preset pricing model for processing to obtain a third price; and the sending unit is used to send a prompt message to the user so that the user can adjust the second price according to the prompt message, and the prompt message is information about the third price corresponding to the target product in the target time period.
[0024] Optionally, the receiving unit is used to obtain a target inventory corresponding to the target product at preset time intervals; the processing unit is used to confirm the acquisition of a second price if the target inventory is in an abnormal sales state, and the second price is the price corresponding to the target product currently on sale; the receiving unit is used to obtain a target number of days corresponding to the target product, and the target number of days is the number of days remaining in the shelf life of the target product; the processing unit is used to determine whether the target number of days is less than or equal to the preset number of days; when the target number of days is less than or equal to the preset number of days, it is confirmed that the target product corresponds to a first processing plan, and the first processing plan includes a discount pricing processing plan, a combination sales processing plan, and a member discount processing plan; when the target number of days is greater than the preset number of days, it is confirmed that the target product corresponds to a second processing plan, and the second processing plan includes a promotion processing plan, a differentiated pricing processing plan, and an additional service processing plan.
[0025] Optionally, the processing unit is used to, when the target type is a fruit type or a vegetable type, confirm the first factor as a first set, the first set including weather factors, competitive price factors and seasonal planting factors; when the target type is a meat type, confirm the first factor as a second set, the second set including shelf life factors, competitive price factors and time factors; when the target type is aquatic product type or dry goods type, confirm the first factor as a third set, the third set including time factors and weather factors; when the target type is a cooked food and pastry type, confirm the first factor as a fourth set, the fourth set including shelf life factors and time factors.
[0026] Optionally, the processing unit is used to determine the target store based on the target product, and the target store is an offline store that sells fresh products; the target product is input into a preset intelligent big model for processing to obtain a target prediction result; the sending unit is used to determine a fourth price based on the target prediction result, and send the fourth price to the target store, so that the target store can optimize the selling price of the target product.
[0027] In a third aspect of the present application, an electronic device is provided, which includes a processor, a memory, a user interface and a network interface, the memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory, so that an electronic device executes any one of the methods described above in the present application.
[0028] In a fourth aspect of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores instructions, and when the instructions are executed, any one of the above methods of the present application is executed.
[0029] In summary, one or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: 1. Receive the target pricing request sent by the user, determine the target type corresponding to the target product according to the target pricing request, realize automatic classification of products, reduce the tediousness and errors of manual classification, and then use the preset pricing model to process according to the target type and target cost price to obtain the first pricing, and then introduce the target preference value corresponding to the target product, combine the target preference value with the first pricing, and further calculate the second pricing, so that the pricing is closer to market demand, the entire pricing process is automated, and manual intervention is reduced, which not only improves the efficiency of pricing, but also improves the accuracy of pricing, which in turn helps to improve sales.
[0030] 2. Input the target product into the preset intelligent big model for processing to obtain the target prediction result. The target prediction result comprehensively considers multiple factors to provide a more accurate pricing suggestion for the target product. The target store can dynamically adjust the selling price of the target product according to the target prediction result to adapt to market changes and thus improve operational efficiency. BRIEF DESCRIPTION OF THE DRAWINGS
[0031] Figure 1 It is a flowchart of a pricing method for fresh goods provided in an embodiment of the present application; Figure 2 It is a structural schematic diagram of a pricing system for fresh goods provided in an embodiment of the present application; Figure 3 It is a structural schematic diagram of an electronic device disclosed in an embodiment of the present application.
[0032] Explanation of the reference numerals: 201, receiving unit; 202, processing unit; 203, sending unit; 300, electronic device; 301, processor; 302, communication bus; 303, user interface; 304, network interface; 305, memory. DETAILED DESCRIPTION
[0033] In order to enable technicians in this field to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.
[0034] In the description of the embodiments of the present application, words such as "for example" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "for example" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "for example" or "for example" is intended to present related concepts in a specific way.
[0035] In the description of the embodiments of the present application, the meaning of the term "multiple" refers to two or more. For example, multiple systems refer to two or more systems, and multiple screen terminals refer to two or more screen terminals. In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance or implicitly indicating the indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. The terms "include", "comprise", "have" and their variations all mean "including but not limited to", unless otherwise specifically emphasized.
[0036] Fresh products refer to primary products that have not been deeply processed (such as cooking, making, etc.), but have only undergone necessary preservation treatment and simple arrangement before being put on the shelves for sale, as well as a collection of products including on-site processed categories such as bread and cooked food. This category covers multiple categories such as fruits, vegetables, meat, aquatic products, dry goods and daily necessities, cooked food and cakes. Fresh products are classified into one category because of their common characteristics and storage conditions - that is, they need to be preserved, refrigerated or frozen, are usually sold in bulk and need to be sold by weighing and printing barcodes. In addition, this type of product has a relatively short shelf life and shows a strong correlation in consumer purchasing habits.
[0037] In the current supply chain management of fresh products, the formulation of pricing strategies is often limited to the fixed cost plus method or a static method based on a simplified market demand forecasting model. Specifically, the traditional fresh product pricing process often relies too much on manual judgment or preset pricing rules. Manual judgment is prone to inaccurate pricing, which can affect the sales of products.
[0038] Therefore, how to solve the problem of excessive reliance on manual judgment and inaccurate pricing of fresh goods. A pricing method for fresh goods provided in an embodiment of the present application is applied to a server. The server of the present application can be a platform that provides pricing services for fresh goods. Figure 1 This is a flowchart of a pricing method for fresh products provided in an embodiment of the present application, with reference to Figure 1 The method includes the following steps S101-S105.
[0039] S101: receiving a target pricing request sent by a user, where the target pricing request is a request for pricing a target commodity, and the target commodity is any fresh commodity to be priced.
[0040] In the above S101, the user refers to the staff who performs pricing operations on fresh goods. After purchasing the corresponding fresh goods from the supplier, the staff needs to determine the corresponding price of the fresh goods, that is, the price, and then assign the price to the fresh goods so that consumers can choose whether to buy them after determining the selling price of the fresh goods. After purchasing fresh goods, users need to set prices for the fresh goods, that is, there is currently a demand for pricing settings. Users can input or select target goods on the front-end interface (such as web pages, APPs, etc.) and request the server to price them. At this time, the target product is any fresh product that the user wants to price. After receiving the target pricing request, the server parses the target pricing request and parses out the target product information that needs to be priced. The target product information includes information such as product name, type and specification.
[0041] S102: Determine a target type according to the target commodity, the target type including fruit type, vegetable type, meat type, aquatic product type, dry goods type, and cooked food and pastry type.
[0042] In the above S102, after receiving the pricing request corresponding to the target commodity, the server classifies the target commodity into a predefined commodity type according to the name or classification label of the target commodity. The predefined commodity types include fruit type, vegetable type, meat type, aquatic product type, dry goods type, and cooked food and pastry type. For example, if the target commodity is an apple, the apple is classified as a fruit type. If the target commodity is pork, the pork is classified as a meat type.
[0043] S103: Determine a first factor according to the target type, input the first factor and the target cost price into a preset pricing model for processing, and obtain a first price, where the target cost price is the cost price corresponding to the target product.
[0044] In the above S103, after determining the target type corresponding to the target commodity, the first factor needs to be determined according to the target type, and the first factor is various factors that affect the pricing of the target commodity. Different factors will vary according to different target types. Determine the first factor according to the target type, specifically including: when the target type is a fruit type or a vegetable type, confirm that the first factor is a first set, and the first set includes weather factors, competitive price factors, and seasonal planting factors; when the target type is a meat type, confirm that the first factor is a second set, and the second set includes shelf life factors, competitive price factors, and time factors; when the target type is aquatic type or dry goods type, confirm that the first factor is a third set, and the third set includes time factors and weather factors; when the target type is a cooked pastry type, confirm that the first factor is a fourth set, and the fourth set includes shelf life factors and time factors. Specifically, according to the characteristics of different types of commodities, confirm the first factor set that affects their pricing, and these sets contain key factors that affect commodity pricing. First, clarify the type of the target commodity, which can be achieved through commodity classification or commodity labeling. According to the type of target product, select the corresponding first factor set from the preset set, which includes the first set, the second set, the third set and the fourth set. The first set is applicable to fruit or vegetable types, including weather factors, competitive price factors and seasonal planting factors. The second set is applicable to meat types, including shelf life factors, competitive price factors and time factors. The third set is applicable to aquatic products or dry goods types, including time factors and weather factors. The fourth set is applicable to cooked pastry types, including shelf life factors and time factors. Conduct in-depth analysis on the selected first factor set to understand the specific impact of each factor on pricing. For example, for fruit types, weather factors may affect yield and quality, and thus affect pricing; competitive price factors reflect the price level of similar products on the market; seasonal planting factors are related to the supply and seasonal demand of the product.
[0045] In addition, after determining the first factor according to the target type, the first factor data and the target cost price are input into the preset pricing model for processing to obtain the first price. At this time, the target cost price refers to the total cost corresponding to the target product, which is obtained by adding the supplier's supply price, packaging cost and transportation cost. The preset pricing model is an algorithm based on machine learning or statistics, which is used to calculate based on the input target cost price and the first factor to obtain the first price. The construction process of the preset pricing model is as follows: first collect relevant information about the target product, including historical selling prices, market demand, competitive prices, weather conditions, seasonal planting characteristics, etc. Clean and organize the collected data, remove invalid or erroneous data, and ensure the accuracy and completeness of the data. According to the product type and pricing target, select the key factors that have an important impact on pricing as features. Extract the specific values or indicators of these features for subsequent model training. Select a machine learning model that is suitable for handling pricing problems, such as a regression model, a classification model, etc. Use the preprocessed data and the extracted features to train the model so that it can learn the complex relationship between features and pricing. Adjust and optimize the parameters of the trained model to improve its prediction performance. The model is validated using the validation data set to evaluate the accuracy and reliability of its prediction results. The built preset pricing model is applied to the pricing of fresh products, and then the first price is determined based on the first factor and the target cost price. At this time, the first price refers to the price at which the target product can be sold after initial evaluation.
[0046] S104: Obtain a target preference value corresponding to the target product, and calculate the first pricing according to the target preference value to obtain a second pricing.
[0047] In the above S104, in order to ensure that the first pricing set for the target product meets the market demand, the target preference value corresponding to the target product can be obtained. The target preference value refers to the degree of preference of consumers for the target product. Obtaining the target preference value corresponding to the target product, calculating the first pricing according to the target preference value, and obtaining the second pricing specifically includes: obtaining the target analysis information corresponding to the target product, the target analysis information includes survey information, social media analysis information and sales data information; processing the target analysis information to obtain the target preference value; judging whether the target preference value is greater than the preset preference threshold; when the target preference value is greater than the preset preference threshold, obtaining the first value, the first value is the difference between the target preference value and the preset preference threshold; and performing the first value and the first pricing to obtain the second pricing. Specifically, information on consumer demand, purchasing behavior, satisfaction, etc. of the target product can be collected through market research, questionnaire surveys, consumer interviews, etc. This information can reflect consumers' preferences and expectations for the target product. Using user comments, likes, reposts and other data on social media platforms (such as Weibo, WeChat, Douyin, etc.), analyze consumers' emotional tendencies and word-of-mouth for the target product. User feedback on social media is often more direct and real, which helps to gain a deeper understanding of consumer preferences. Extract indicators such as sales volume, sales revenue, and return rate of target products from sales data to analyze sales trends and consumer behavior patterns. Sales data can reflect the market acceptance of target products and the degree of consumer recognition of their value. Clean the collected target analysis information to remove duplicate, invalid or abnormal data. Use statistical analysis, text mining, machine learning and other technical means to conduct in-depth analysis of the cleaned data to extract key information about the preferences of target products. Based on the analysis results, calculate a quantitative target preference value. This value can be a score, index or ranking to reflect the degree of consumer preference for the target product. After determining the target preference value corresponding to the target product, compare the target preference value with the preset preference threshold. The preset preference threshold is a reasonable preference threshold set based on industry standards, market conditions, corporate strategies and other factors. This threshold is used to determine whether the preference for the target product meets or exceeds expectations. If the target preference value is greater than the preset preference threshold, calculate the difference between the two, that is, the first value. This difference reflects the degree to which the preference for the target product exceeds expectations. According to the pricing strategy and market conditions, determine a reasonable calculation rule or formula to convert the first value into a price adjustment. Substitute the calculated first value into the calculation rule or formula to obtain the price adjustment. Then add this price adjustment to the first price to obtain the second price, which is an increase on the basis of the first price.For example, if the target product is beef, the first factor is determined according to the target type corresponding to the target product, and then the first pricing a is determined according to the first factor and the target cost price, and the target preference value corresponding to the target product is obtained. If the target preference value is 0.6, the preset preference threshold is set to 0.5. At this time, the target preference value is greater than the preset preference threshold, and the first pricing can be adjusted upward. The first pricing can be calculated with the first value to obtain the second pricing b.
[0048] Further, when the target preference value is equal to the preset preference threshold, it is confirmed that the first pricing is output as the second pricing; when the target preference value is less than the preset preference threshold, it is confirmed to obtain the second value; the second value is calculated with the first pricing to obtain the second pricing. Specifically, the target preference value is compared with the preset preference threshold. If the two are completely equal, it means that the preference degree of the target product is consistent with the expectations of the enterprise. In this case, no adjustment is required to the first pricing. It is directly confirmed that the first pricing is output as the second pricing. This means that the pricing strategy of the target product is consistent with the market positioning and consumer expectations of the enterprise. If the target preference value is less than the preset preference threshold, it means that the preference degree of the target product is lower than the market expectations. In order to reflect this difference in preference degree, an adjustment amount, namely the second value, needs to be calculated. This value can be a ratio, percentage or other suitable measurement method based on the gap between the target preference value and the preset preference threshold. The specific calculation method may depend on the pricing strategy and market conditions. After obtaining the second value, it is calculated with the first pricing. This operation can be a simple addition and subtraction operation, a multiplication operation or a more complex functional relationship. The result of the operation is the second price, which is a reduction from the first price. It reflects the reasonable pricing level of the target product in the current market environment.
[0049] S105: Send the second price to the user so that the user can process the target product according to the second price.
[0050] In the above S105, after the second price is obtained, the second price is displayed to the user through the front-end interface, or the user is notified through email, SMS, etc. After the server outputs the corresponding second price according to the target product, the user can use the second price as the selling price of the target product according to the actual situation, or use the second price as a reference price, and then adjust the second price.
[0051] In a possible implementation, after determining the current selling price corresponding to the target product, how to predict the pricing of the target product in other time periods, and then output the pricing corresponding to different time periods, so that the user can adjust the sales strategy in time according to the pricing, specifically including: obtaining the target time point, the target time point is the time point corresponding to the second pricing of the target product; determining the target time period according to the target time point, the target time period is any time period after the target time point; determining the second factor corresponding to the target type, the second factor is the time factor and the shelf life factor; inputting the second factor and the second pricing into the preset pricing model for processing to obtain the third pricing; sending the prompt information to the user, so that the user can adjust the second pricing according to the prompt information, the prompt information is the information of the target product corresponding to the third pricing in the target time period. Specifically, after determining that the target product has started to be sold, if the selling price of the target product is set to the second pricing, the time point of the target product being the second pricing, that is, the target time point, is obtained. This time point can be the product listing date, the promotion start date, the inventory adjustment date, etc., depending on the company's pricing strategy and market strategy. After determining the target time point, obtain any time period after the target time point, i.e., the target time period. This time period can be a week, a month, a quarter, etc. The specific length depends on the pricing cycle and market conditions. The start date and end date of the target time period can be set so that the time range can be provided later. Then determine the second factor according to the target type corresponding to the target product. At this time, the target product is predicted and priced. Therefore, the second factor is the factor affecting the predicted pricing. At this time, the second factor includes the time factor and the shelf life factor. Specific evaluation is performed on the time factor and the shelf life factor. For example, the demand changes, inventory status, and remaining shelf life of the product in different time periods are considered. The second factor and the second pricing are input into the preset pricing model for processing to obtain the third pricing. The preset pricing model is an algorithm based on machine learning, statistics, or economics principles, which is used to calculate a reasonable pricing (i.e., the third pricing) based on the input data. Input the input data into the model for calculation and processing. The third pricing reflects the reasonable pricing level of the target product in the target time period after considering the time factor and the shelf life factor. A prompt message is generated based on the information of the third pricing and the target time period. This information may include the third pricing, price change trend, and recommended sales strategy of the target product within the target time period. The prompt information is sent to the user through email, SMS, APP push, etc. Ensure that the user can receive and understand this information in a timely manner so that the second pricing can be adjusted according to the prompt. For example, the target time point is February 4, 202x, and the second pricing d corresponding to the target product sold at the target time point is obtained, and the pricing of the target product in the next week is predicted, that is, the target time period is the time period from February 5, 202x to February 11, 202x.Since the factors that affect pricing are time and shelf life, time refers to holidays, and shelf life refers to the remaining days of the product's shelf life. The fewer the remaining days, the more it affects the sales of the product. Therefore, the second price and the second factor are input into the preset pricing model for processing to obtain the third price. At this time, the third price is the predicted price of the target product in the target time period based on the second factor. That is, after February 11, 202x, the selling price of the target product can be adjusted to the third price.
[0052] In a possible implementation, by monitoring the inventory and remaining shelf life of the target product, the sales efficiency of the product is improved based on a reasonable processing scheme, which specifically includes: obtaining the target inventory corresponding to the target product at a preset interval; if the target inventory is in an abnormal sales state, confirming to obtain the second price, the second price is the price corresponding to the current target product; obtaining the target number of days corresponding to the target product, the target number of days is the number of days remaining in the shelf life of the target product; judging whether the target number of days is less than or equal to the preset number of days; when the target number of days is less than or equal to the preset number of days, confirming that the target product corresponds to the first processing scheme, the first processing scheme includes a discount pricing processing scheme, a combination sales processing scheme, and a member discount processing scheme. Specifically, a reasonable inventory monitoring cycle can be set according to factors such as the characteristics of the product, sales speed, and inventory capacity. This cycle can be daily, weekly, or monthly, etc. Within the set monitoring cycle, the inventory management system or Internet of Things technology is used to automatically obtain the inventory data of the target product. These data can be updated to the enterprise's database system in real time or regularly. The acquired inventory data is preliminarily analyzed to determine whether it is in a normal sales state or an abnormal sales state. Abnormal sales may include unsalable goods due to excessive inventory, out-of-stock due to insufficient inventory, etc. When the inventory data indicates that the product is in an abnormal sales state, it is necessary to further analyze the reasons and confirm whether the pricing strategy needs to be adjusted. Obtain the price corresponding to the current target product, i.e., the second price, through the price management system or database. Query the shelf life information of the target product through the product management system or database. Calculate the remaining saleable days of the target product, i.e., the target days, based on the current date and the expiration date of the product. Set a reasonable warning day based on the characteristics and sales strategy of the product. This number of days is usually used to determine whether the product is about to expire or needs to take emergency measures. Compare the calculated target days with the preset warning days. If the target days are less than or equal to the warning days, emergency measures need to be taken; if the target days are greater than the warning days, you can continue to observe or adopt other strategies. When the target days are less than or equal to the preset days, select one or more appropriate processing solutions from the discount pricing processing solution, the combined sales processing solution, and the member discount processing solution based on the characteristics and sales strategy of the product. Discount pricing solutions reduce inventory backlogs by lowering product prices. Combination sales solutions combine target products with other products to increase overall sales and profits. Member discount solutions provide additional discounts or benefits to members to increase their willingness to buy and loyalty. Communicate the selected solution to the sales department, inventory management department and other relevant departments, and ensure that the solution is implemented correctly.
[0053] In addition, when the target number of days is greater than the preset number of days, the second processing plan corresponding to the target product is confirmed, and the second processing plan includes a promotion processing plan, a differentiated pricing processing plan, and an additional service processing plan. Specifically, when the target number of days is greater than the preset number of days, one or more suitable processing plans are selected from the promotion processing plan, the differentiated pricing processing plan, and the additional service processing plan according to the characteristics and sales strategy of the product. The promotion processing plan increases the sales volume of the product through promotional activities (such as limited-time discounts, full-reduction discounts, etc.). The differentiated pricing processing plan formulates different pricing strategies according to the different characteristics, quality or consumer groups of the product. The additional service processing plan provides additional services (such as free delivery, extended warranty period, etc.) to attract consumers to buy. Similarly, the selected processing plan is communicated to the relevant departments and ensures that the plan is implemented correctly.
[0054] In a possible implementation, for offline stores selling fresh goods, the target goods can be analyzed according to the intelligent big model, the latest selling price corresponding to the target goods can be output, and the latest selling price can be sent to the target store, so that the target store can adjust the selling price of the target goods according to the latest selling price in time. Specifically, it includes: determining the target store according to the target goods, the target store is the offline store corresponding to the sale of fresh goods; inputting the target goods into the preset intelligent big model for processing to obtain the target prediction result; determining the fourth pricing according to the target prediction result, and sending the fourth pricing to the target store, so that the target store can optimize the selling price of the target goods. Specifically, it is necessary to determine the target goods to be optimized for pricing, which are usually fresh goods, such as vegetables, fruits, meat, seafood, etc. According to the type and sales characteristics of the target goods, offline stores that sell these goods are selected as target stores. The screening process may involve consideration of factors such as the business scope, geographical location, and customer groups of the store. The selected target stores are sorted to form a list of target stores for subsequent operations. Then collect relevant information about the target product, such as type, origin, quality, shelf life, historical selling price, market demand, etc. Organize this information into a data format suitable for input into the intelligent big model. Select a model suitable for handling fresh product pricing from the available intelligent big models. The intelligent big model has been specially trained and optimized for fresh product pricing. Input the prepared target product data into the preset intelligent big model. The intelligent big model outputs the target prediction results, which may include the recommended selling price range, price trend, competitor pricing strategy, etc. Based on the target prediction results, combined with the store's pricing strategy and actual market conditions, determine a reasonable fourth price. The fourth price should be able to reflect the value of the product while meeting the store's profit goals. Organize the fourth pricing information into a format suitable for sending to the target store, which may include the product name, new selling price, effective time, etc. According to the actual situation of the target store, select a suitable sending method, such as email, SMS, in-store notification system, etc. After receiving the fourth pricing information, the target store adjusts the selling price of the target product as required. Make sure that the price tags in the store have been updated to the new selling price so that customers can accurately understand the product price. Through the above method, the selling price of the target product can be determined more accurately and the pricing strategy of the target store can be optimized, thereby improving the competitiveness of the product and the profitability of the enterprise.
[0055] Through the above method, a target pricing request is received, and the product type is automatically determined according to the target product, reducing the error and time cost of manual classification. Then, the preset pricing model is used to calculate the first price for the target type and target cost price. The preset pricing model can objectively reflect the true value of the product and reduce the subjectivity and uncertainty of manual judgment. Then, the preference value of the target product is obtained, and the first price is adjusted to obtain the second price, which reflects the differences in preferences of different consumers for different products. This helps to formulate a pricing strategy that is more in line with market demand. The entire pricing process reduces human intervention, thereby reducing the risk of inaccurate personal pricing.
[0056] The present application also provides a pricing system for fresh products. Figure 2 This is a schematic diagram of a pricing system for fresh products provided in an embodiment of the present application. Figure 2 , the system is a server, and the server includes a receiving unit 201, a processing unit 202 and a sending unit 203.
[0057] The receiving unit 201 receives a target pricing request sent by a user, where the target pricing request is a request for pricing a target commodity, where the target commodity is any fresh commodity to be priced; and obtains a target preference value corresponding to the target commodity.
[0058] Processing unit 202 determines a target type according to the target commodity, where the target types include fruit type, vegetable type, meat type, seafood type, dry goods type, and cooked food and pastry type; determines a first factor according to the target type, inputs the first factor and the target cost price into a preset pricing model for processing, and obtains a first pricing, where the target cost price is the cost price corresponding to the target commodity; calculates the first pricing according to the target preference value to obtain a second pricing.
[0059] The sending unit 203 sends the second price to the user so that the user can process the target product according to the second price.
[0060] In a possible implementation, the receiving unit 201 is used to obtain target analysis information corresponding to the target product, the target analysis information including survey information, social media analysis information and sales data information; the processing unit 202 is used to process the target analysis information to obtain a target preference value; determine whether the target preference value is greater than a preset preference threshold; when the target preference value is greater than the preset preference threshold, obtain a first value, the first value being the difference between the target preference value and the preset preference threshold; and compare the first value with the first price to obtain a second price.
[0061] In one possible implementation, the processing unit 202 is used to confirm that the first price is output as the second price when the target preference value is equal to a preset preference threshold; confirm that the second value is obtained when the target preference value is less than the preset preference threshold; and calculate the second value and the first price to obtain the second price.
[0062] In a possible implementation, the receiving unit 201 is used to obtain a target time point, which is a time point for determining that the target product corresponds to the second price; the processing unit 202 is used to determine a target time period based on the target time point, which is any time period after the target time point; determine a second factor corresponding to the target type, which is a time factor and a shelf life factor; input the second factor and the second price into a preset pricing model for processing to obtain a third price; and the sending unit 203 is used to send a prompt message to the user so that the user can adjust the second price according to the prompt message, and the prompt message is information about the third price corresponding to the target product in the target time period.
[0063] In a possible implementation, the receiving unit 201 is used to obtain the target inventory corresponding to the target product at preset time intervals; the processing unit 202 is used to confirm the acquisition of a second price if the target inventory is in an abnormal sales state, and the second price is the price corresponding to the target product currently being sold; the receiving unit 201 is used to obtain the target number of days corresponding to the target product, and the target number of days is the number of days remaining in the shelf life of the target product; the processing unit 202 is used to determine whether the target number of days is less than or equal to the preset number of days; when the target number of days is less than or equal to the preset number of days, it is confirmed that the target product corresponds to a first processing plan, and the first processing plan includes a discount pricing processing plan, a combination sales processing plan, and a member discount processing plan; when the target number of days is greater than the preset number of days, it is confirmed that the target product corresponds to a second processing plan, and the second processing plan includes a promotion processing plan, a differentiated pricing processing plan, and an additional service processing plan.
[0064] In one possible embodiment, the processing unit 202 is used to, when the target type is a fruit type or a vegetable type, confirm that the first factor is a first set, and the first set includes weather factors, competitive price factors, and seasonal planting factors; when the target type is a meat type, confirm that the first factor is a second set, and the second set includes shelf life factors, competitive price factors, and time factors; when the target type is aquatic product type or dry goods type, confirm that the first factor is a third set, and the third set includes time factors and weather factors; when the target type is a cooked food and pastry type, confirm that the first factor is a fourth set, and the fourth set includes shelf life factors and time factors.
[0065] In a possible implementation, the processing unit 202 is used to determine a target store based on the target product, where the target store is an offline store that sells fresh products; the target product is input into a preset intelligent big model for processing to obtain a target prediction result; the sending unit 203 is used to determine a fourth price based on the target prediction result, and send the fourth price to the target store so that the target store can optimize the selling price of the target product.
[0066] It should be noted that: when the system provided in the above embodiment realizes its functions, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the system and method embodiments provided in the above embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be repeated here.
[0067] The present application also discloses an electronic device. Figure 3 , Figure 3 The electronic device 300 may include: at least one processor 301 , at least one network interface 304 , a user interface 303 , a memory 305 , and at least one communication bus 302 .
[0068] The communication bus 302 is used to realize the connection and communication between these components.
[0069] The user interface 303 may include a display screen (Display) and a camera (Camera). Optionally, the user interface 303 may also include a standard wired interface and a wireless interface.
[0070] The network interface 304 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).
[0071] Among them, the processor 301 may include one or more processing cores. The processor 301 uses various interfaces and lines to connect various parts in the entire server, and executes various functions of the server and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory 305, and calling data stored in the memory 305. Optionally, the processor 301 can be implemented in at least one hardware form of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), and programmable logic array (Programmable Logic Array, PLA). The processor 301 can integrate one or a combination of a central processing unit (Central Processing Unit, CPU), a graphics processing unit (Graphics Processing Unit, GPU) and a modem. Among them, the CPU mainly processes the operating system, user interface and application requests; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; the modem is used to process wireless communications. It can be understood that the above-mentioned modem may not be integrated into the processor 301, and it can be implemented separately through a chip.
[0072] Among them, the memory 305 may include a random access memory (RAM) or a read-only memory (Read-Only Memory). Optionally, the memory 305 includes a non-transitory computer-readable storage medium. The memory 305 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 305 may include a program storage area and a data storage area, wherein the program storage area. Instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc. can be stored; the data storage area can store data involved in the above-mentioned various method embodiments, etc. The memory 305 can also be optionally at least one storage device located away from the aforementioned processor 301.
[0073] like Figure 3 As shown, the memory 305 as a computer storage medium may include an operating system, a network communication module, a user interface module, and an application program for pricing fresh goods.
[0074] exist Figure 3In the electronic device 300 shown, the user interface 303 is mainly used to provide an input interface for the user and obtain data input by the user; and the processor 301 can be used to call the application for pricing fresh goods stored in the memory 305. When executed by one or more processors, the electronic device executes one or more of the methods described in the above embodiments.
[0075] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all described as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the order of the actions described, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required for the present application.
[0076] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.
[0077] In the several embodiments provided in the present application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of the units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some service interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.
[0078] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
[0079] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.
[0080] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a memory and includes several instructions for a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned memory includes: various media that can store program codes, such as USB flash drives, mobile hard drives, magnetic disks or optical disks.
[0081] The above is only an exemplary embodiment of the present disclosure and cannot be used to limit the scope of the present disclosure. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure. After considering the disclosure of the specification and the truth of practice, it will be easy for those skilled in the art to think of other embodiments of the present disclosure. This application is intended to cover any variation, use or adaptive change of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary technical means in the technical field that are not recorded in the present disclosure.
Claims
1. A pricing method for fresh products, characterized in that: Applied in a server, the method comprises: Receiving a target pricing request sent by a user, wherein the target pricing request is a request for pricing a target commodity, and the target commodity is any fresh commodity to be priced; Determine a target type according to the target commodity, wherein the target type includes a fruit type, a vegetable type, a meat type, a seafood type, a dry food type, and a cooked food and pastry type; Determine a first factor according to the target type, input the first factor and the target cost price into a preset pricing model for processing, and obtain a first price, wherein the target cost price is the cost price corresponding to the target commodity; Obtaining a target preference value corresponding to the target product, and calculating the first pricing according to the target preference value to obtain a second pricing; The second price is sent to the user so that the user processes the target product according to the second price.
2. The method according to claim 1, characterized in that The obtaining of the target preference value corresponding to the target product and calculating the first pricing according to the target preference value to obtain the second pricing specifically includes: Acquire target analysis information corresponding to the target product, wherein the target analysis information includes research information, social media analysis information, and sales data information; Processing the target analysis information to obtain the target preference value; Determining whether the target preference value is greater than a preset preference threshold; When the target preference value is greater than the preset preference threshold, a first value is obtained, where the first value is the difference between the target preference value and the preset preference threshold; The first value is added to the first price to obtain the second price.
3. The method according to claim 2, characterized in that After determining whether the target preference value is greater than a preset preference threshold, the method further includes: When the target preference value is equal to the preset preference threshold, confirming to output the first pricing as the second pricing; When the target preference value is less than the preset preference threshold, confirming to obtain the second value; The second value is calculated with the first pricing to obtain the second pricing.
4. The method according to claim 1, characterized in that: After sending the second price to the user so that the user processes the target product according to the second price, the method further includes: Obtaining a target time point, where the target time point is a time point corresponding to the second price for determining the target commodity; Determine a target time period according to the target time point, where the target time period is any time period after the target time point; Determine a second factor corresponding to the target type, where the second factor is a time factor and a shelf life factor; Inputting the second factor and the second price into the preset pricing model for processing to obtain a third price; Prompt information is sent to the user so that the user can adjust the second price according to the prompt information, wherein the prompt information is information about the third price corresponding to the target product in the target time period.
5. The method according to claim 1, characterized in that After sending the second price to the user so that the user processes the target product according to the second price, the method further includes: At preset time intervals, obtaining a target inventory quantity corresponding to the target product; If the target inventory is in an abnormal sales state, confirming to obtain the second price, where the second price is the price corresponding to the current sale of the target product; Obtain the target number of days corresponding to the target product, where the target number of days is the number of days remaining in the shelf life of the target product; Determine whether the target number of days is less than or equal to a preset number of days; When the target number of days is less than or equal to the preset number of days, it is confirmed that the target product corresponds to a first processing solution, wherein the first processing solution includes a discount pricing processing solution, a combination sales processing solution, and a member discount processing solution; When the target number of days is greater than the preset number of days, it is confirmed that the target product corresponds to a second processing solution, where the second processing solution includes a sales promotion processing solution, a differentiated pricing processing solution, and an additional service processing solution.
6. The method according to claim 1, characterized in that The determining of the first factor according to the target type specifically includes: When the target type is the fruit type or the vegetable type, it is confirmed that the first factor is a first set, and the first set includes weather factors, competitive price factors, and seasonal planting factors; When the target type is the meat type, the first factor is confirmed to be a second set, and the second set includes a shelf life factor, the competitive price factor, and a time factor; When the target type is the aquatic product type or the dry goods type, it is confirmed that the first factor is a third set, and the third set includes the time factor and the weather factor; When the target type is the cooked pastry type, it is confirmed that the first factor is a fourth set, and the fourth set includes the shelf life factor and the time factor.
7. The method according to claim 1, characterized in that After receiving the target pricing request sent by the user, the method further includes: Determine a target store according to the target product, where the target store is an offline store that sells fresh products; Input the target commodity into a preset intelligent big model for processing to obtain a target prediction result; A fourth pricing is determined according to the target prediction result, and the fourth pricing is sent to the target store so that the target store can optimize the selling price of the target product.
8. A pricing system for fresh goods, characterized in that: The system is a server, and the server comprises a receiving unit (201), a processing unit (202) and a sending unit (203); The receiving unit (201) receives a target pricing request sent by a user, wherein the target pricing request is a request for pricing a target commodity, wherein the target commodity is any one of the fresh commodities to be priced; obtains a target preference value corresponding to the target commodity, The processing unit (202) determines a target type according to the target commodity, wherein the target type includes a fruit type, a vegetable type, a meat type, a seafood type, a dry food type, and a cooked food and pastry type; Determine a first factor according to the target type, input the first factor and the target cost price into a preset pricing model for processing, and obtain a first price, wherein the target cost price is the cost price corresponding to the target commodity; Calculating the first pricing according to the target preference value to obtain a second pricing; The sending unit (203) sends the second price to the user so that the user processes the target product according to the second price.
9. An electronic device, characterized in that: The electronic device (300) comprises a processor (301), a memory (305), a user interface (303) and a network interface (304), wherein the memory (305) is used to store instructions, the user interface (303) and the network interface (304) are used to communicate with other devices, and the processor (301) is used to execute the instructions stored in the memory (305) so that the electronic device (300) executes the method according to any one of claims 1 to 7.
10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions, and when the instructions are executed, the method according to any one of claims 1 to 7 is executed.