Price verification method and device, electronic equipment and storage medium

Abstract

The invention relates to the technical field of computers, and provides a price verification method and device, electronic equipment and a storage medium. The method comprises the steps of obtaining a target attribute, an initial unit price and a standard unit price corresponding to each target in a preset area, and determining a predicted unit price corresponding to the target according to the standard unit price and the target attribute; verifying the initial unit price according to a predicted unit price to obtain a first verification result; classifying the targets according to a preset rule, and verifying the initial unit price of the target in each classification to obtain a second verification result; and determining a target verification result according to the first verification result and the second verification result, and displaying the target verification result through the interactive interface. The problem that the accuracy of the final commodity pricing result is low is solved.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a price verification method, device, electronic device and storage medium. Background Art

[0002] In a market economy, trading of various commodities promotes economic development and meets one's own needs. The transaction price of commodities will be determined before the transaction. However, the pricing of most commodities is based on manual experience or the financial situation of the seller, and there is no intelligent verification of commodity pricing, resulting in low accuracy of commodity pricing. Summary of the invention

[0003] In view of this, the present application provides a price verification method, device, electronic device and storage medium to solve the problem of low commodity pricing accuracy in the prior art.

[0004] In a first aspect of the present application, a price verification method is provided, including: obtaining target attributes, initial unit prices, and standard unit prices corresponding to each target in a preset area, and determining a predicted unit price corresponding to the target based on the standard unit price and the target attributes; verifying the initial unit price based on the predicted unit price to obtain a first verification result; classifying the targets according to preset rules, verifying the initial unit prices of the targets in each category to obtain a second verification result; determining a target verification result based on the first verification result and the second verification result, and displaying the target verification result through an interactive interface.

[0005] According to a second aspect of the present application, a price verification device is provided, including: an acquisition module, configured to obtain target attributes, an initial unit price and a standard unit price corresponding to each target in a preset area, and determine a predicted unit price corresponding to the target based on the standard unit price and the target attributes; a first verification module, configured to verify the initial unit price based on the predicted unit price to obtain a first verification result; a second verification module, configured to classify the targets according to preset rules, verify the initial unit price of the targets in each classification, and obtain a second verification result; a third verification module, configured to determine a target verification result based on the first verification result and the second verification result, and display the target verification result through an interactive interface.

[0006] According to a third aspect of the present application, an electronic device is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above method when executing the computer program.

[0007] According to a fourth aspect of the present application, a storage medium is provided, which stores a computer program, and when the computer program is executed by a processor, the steps of the above method are implemented.

[0008] At least one of the above technical solutions adopted in this application can achieve the following beneficial effects:

[0009] By obtaining the target attributes, initial unit price and standard unit price corresponding to each target in the preset area, and determining the predicted unit price corresponding to the target according to the standard unit price and the target attributes, the initial unit price is then verified according to the predicted unit price to determine whether the initial unit price of the target is reasonable, and a first verification result of the initial unit price is obtained. The targets are classified using preset rules, and the pricing verification is performed again on the targets in each category globally to obtain a second verification result. In this way, it can be determined whether the target pricing is reasonable in each category. Combined with the first verification result and the second verification result, the judgment result of whether the pricing of the target is reasonable is finally determined, that is, the target verification result. The target verification result is displayed for the staff to determine whether the initial unit price of the corresponding target needs to be adjusted according to the verification result. In this way, after obtaining the initial unit price of the target, the staff can efficiently understand whether the initial unit price is reasonable through an intelligent verification method, and clearly understand the pricing of the target in the case of an unreasonable initial unit price, and make targeted adjustments, so as to obtain a more accurate target pricing result. This not only improves the rationality of target pricing, but also reduces the workload of manual verification and improves the accuracy of target pricing results. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0011] Figure 1 It is a flowchart of a price verification method provided in an embodiment of the present application;

[0012] Figure 2 It is a flowchart of another price verification method provided in an embodiment of the present application;

[0013] Figure 3 It is a structural schematic diagram of a price verification device provided in an embodiment of the present application;

[0014] Figure 4 It is a structural schematic diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0015] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present application. However, it should be clear to those skilled in the art that the present application may also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present application.

[0016] The terms "first", "second", etc. in the specification and claims of the present application are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable under appropriate circumstances, so that the embodiments of the present application can be implemented in an order other than those illustrated or described here, and the objects distinguished by "first", "second", etc. are generally of one type, and the number of objects is not limited. For example, the first object can be one or more. In addition, "and / or" in the specification and claims represents at least one of the connected objects, and the character " / " generally indicates that the objects associated with each other are in an "or" relationship.

[0017] In addition, it should be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "includes..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0018] Commodities are usually priced before they are traded. Nowadays, it is common to price them based on manual experience or budget, which is divorced from the intrinsic value of the goods and lacks verification of commodity pricing and intelligence in commodity pricing.

[0019] For example, in the commercial real estate industry, a common pricing method is to formulate the contract control price of shops based on the company budget. The core logic of this is to convert the company's overall business objectives into specific shop contract pricing indicators to ensure that the company's revenue from shop leasing or sales meets the annual target. Although company budget pricing helps achieve the company's overall business objectives, there are also some problems. For example, pricing is divorced from the actual value of the shop and the market environment. Shop pricing may not be reasonable and is easily interfered with by human factors. There is no effective price verification method to verify shop pricing. Therefore, the existing shop pricing method is difficult to achieve accurate pricing.

[0020] Therefore, based on the commercial real estate embodiment, this application provides a price verification method to ensure the rationality of shop pricing, and avoid excessive intervention of human factors, so that commodity pricing is more transparent, scientific, and accurate, and can accurately reflect the true value of the shop.

[0021] A price verification method and device according to an embodiment of the present application will be described in detail below with reference to the accompanying drawings.

[0022] Figure 1 : is a flow chart of a price verification method provided by an embodiment of the present application. Figure 1 As shown, the price verification method includes:

[0023] S101, obtaining target attributes, initial unit prices, and standard unit prices corresponding to each target in a preset area, and determining a predicted unit price corresponding to the target according to the standard unit price and the target attributes.

[0024] Specifically, the target attributes, initial unit price, and standard unit price can all be entered into the system by the staff after collecting relevant information, so that the subsequent system can obtain relevant data to verify the target price.

[0025] Among them, the preset area can represent a shopping mall where you want to check the shop prices, or a specific commercial area; the target can represent each shop or specific rental unit in the shopping mall; the target attributes can represent various factors related to the value of the shop, such as the shop's area segment, floor, orientation, customer flow, physical factors (such as light, location), engineering properties (such as infrastructure, decoration quality, etc.); the initial unit price can represent the shop price initially determined by humans; the standard unit price can be the standard price of the business format determined based on market research, industry level, shopping mall positioning and other factors; the predicted unit price can represent the price calculated by the system based on the standard unit price and the specific target attributes of each target, reflecting the reasonable market price of the target.

[0026] In this way, the system can generate a predicted unit price for each target, which can be used as a reference standard in the subsequent price verification process.

[0027] S102, verifying the initial unit price according to the predicted unit price to obtain a first verification result.

[0028] Specifically, the initial unit price of each target can be verified by using the predicted unit price as a reference standard, and the difference between the initial unit price of each target and the predicted unit price generated by the system can be compared to obtain a first verification result. If the first verification result indicates that the initial unit price is close to or equal to the predicted unit price, it indicates that the initial pricing is reasonable. If the initial unit price is much higher or lower than the predicted unit price, there may be unreasonable aspects. Therefore, the first verification result can be used to reflect the specific difference information between the initial unit price and the predicted unit price of the target, which will not be expanded here.

[0029] S103, classifying the targets according to preset rules, verifying the initial unit price of the targets in each category, and obtaining a second verification result.

[0030] Specifically, the targets may be classified according to preset rules, and a global pricing analysis may be performed on the targets of each classification to obtain a verification result of each category, namely, a second verification result.

[0031] Among them, the preset rules may be based on the nature of the shops for classification, and may be based on factors such as floors, business formats, and area segments to divide shops into different categories, such as classification of shops on the same floor, classification of shops in the same business format (such as catering, retail, etc.), classification of area segments, etc. Of course, the same is true in areas other than commercial real estate. For example, when pricing dolls, they can be classified based on the type, material, etc. of the dolls for further price verification, and there is no restriction here.

[0032] Furthermore, after the targets are classified, each category can be checked as a whole, for example, the proportion of the number of targets in the corresponding category whose initial unit price reaches the standard unit price and the proportion of all targets can be used to reflect the balance and rationality of the target pricing in the corresponding category. Then, the target price can be adjusted in combination with the first check result.

[0033] S104, determining a target verification result according to the first verification result and the second verification result, and displaying the target verification result through an interactive interface.

[0034] Specifically, after obtaining the first verification result and the second verification result, the two can be combined to obtain a target verification result, so that the target verification result can fully demonstrate the pricing situation of the target.

[0035] Among them, the first verification result can be used to reflect the difference between the initial unit price and the predicted unit price of the specific target, and the second verification result can be used to evaluate the pricing balance in the corresponding category. Combining the two, it can be determined whether the pricing of each target is reasonable and which targets need pricing adjustments.

[0036] Furthermore, after obtaining the target verification results, the verification results can be displayed to the staff through an interactive interface, so that the staff can make adjustments to the store pricing. The target verification results displayed on the interface can specifically include: the initial unit price of the target, the predicted unit price, the verification results (such as whether the initial unit price is too high, too low, or reasonable, etc.), specific difference analysis (such as target attribute differences) and the balance judgment in the corresponding classification, as well as prompts for which targets may need to be adjusted in pricing.

[0037] According to the solution provided by the above embodiment, the unit price of each target in the preset area can be predicted to obtain the predicted unit price, and the initial pricing can be verified based on the predicted unit price to obtain a first verification result. The targets can be classified according to preset rules, and the initial unit prices of the targets in each classification can be verified to obtain a second verification result. The first verification result and the second verification result can be combined to fully demonstrate the pricing situation of the target, analyze the specific target, and obtain specific pricing adjustment suggestions, which can enable staff to refer to and quickly adjust the target pricing to ensure the rationality and accuracy of the final pricing.

[0038] In some embodiments, the target attribute includes a first attribute and a second attribute, and the predicted unit price corresponding to the target is determined according to the standard unit price and the target attributes, including: obtaining the standard coefficient of the first attribute and the standard coefficient of the second attribute, the first attribute representing the first consideration for pricing the target, the second attribute representing the second consideration for pricing the target, and the standard coefficient representing the degree of influence of the standard on pricing the target; multiplying the standard coefficient of the first attribute, the standard coefficient of the second attribute, and the standard unit price to obtain the predicted unit price.

[0039] Specifically, the standard coefficient of the first attribute and the standard coefficient of the second attribute can be obtained, and then the standard coefficient of the first attribute, the standard coefficient of the second attribute and the standard unit price corresponding to the target are multiplied to obtain the system's predicted unit price for the target.

[0040] Among them, the first attribute and the second attribute represent the first consideration factor and the second consideration factor for pricing the target, respectively. The standard coefficient can represent the standardized influencing factor used to measure the pricing of the corresponding attribute corresponding to the target, and can represent the degree of influence of each attribute on the target price. The standard coefficient of the first attribute can represent the number obtained by converting the influencing factor of the first attribute, which is used to quantify the contribution of the first attribute to the price after standardization. Similarly, the standard coefficient of the second attribute can represent the value converted from the influencing factor of the second attribute, which is used to quantify its contribution to the price after standardization. The standard coefficient of the corresponding attribute can be pre-set or obtained by the system analyzing market data, which is not limited here.

[0041] Among them, in this embodiment, the first attribute represents the first consideration factor affecting the target price, and the first consideration factor may be the area of ​​the target. The standard coefficient of the first attribute may represent the area segment coefficient of the corresponding target. The second attribute represents the second consideration factor affecting the target price. The second consideration factor may be the floor of the target. The standard coefficient of the second attribute may represent the floor coefficient of the corresponding target. Of course, when the target is not limited to shops, the corresponding first attribute and second attribute may be other factors.

[0042] According to the solution provided in the above embodiment, by obtaining the standard coefficient of the first attribute and the standard coefficient of the second attribute that have a greater impact on the target pricing, and calculating the predicted unit price of each target, the predicted unit price after considering the influencing factors can be obtained, and used in the subsequent price verification step to determine whether the initial pricing of the target is reasonable. This can help quantify the subjective influencing factors in the pricing process, making price verification more scientific and intelligent.

[0043] In some embodiments, the targets include targets corresponding to at least two different standard unit prices and targets corresponding to at least two standard coefficients of a second attribute, and the targets are classified according to preset rules, including: classifying the targets according to preset dimensions, the preset dimensions including the standard unit price and the second attribute; wherein the targets are classified based on the standard unit price to obtain a first classification corresponding to the standard unit price, and each first classification corresponds to the same standard unit price; and the targets are classified based on the second attribute to obtain a second classification corresponding to the standard coefficient of the second attribute, and each second classification corresponds to the same standard coefficient of the second attribute.

[0044] Specifically, the targets that need to be price-checked can be classified based on preset rules to obtain multiple categories with similar characteristics. The preset rules for classification can be based on the categories of the corresponding targets by machine learning and select appropriate classification rules based on the learning results, or can be based on artificial pre-set rules to classify the corresponding targets. For example, in this embodiment, shops can be classified according to different dimensions based on artificially set rules. The targets can be classified based on the two dimensions of the standard unit price and the second attribute of the target. The targets can be classified based on the same standard unit price to obtain multiple first categories corresponding to multiple standard unit prices. Of course, for the sake of classification flexibility, the standard unit price of the target can be classified based on different price ranges. For example, shops with a standard unit price of less than 1,000 yuan / square meter are classified as the first sub-category, and shops with a standard unit price of 1,000-1,500 yuan / square meter are classified as another first sub-category. The targets can be classified based on the standard coefficient of the same second attribute, and multiple second categories corresponding to the standard coefficients of multiple second attributes can be obtained. The second attribute can indicate that the shop is located on a floor, that is, the shops can be classified based on the same floor, and the shops corresponding to each second category represent shops on the same floor.

[0045] It should be noted that the target can also be classified based on the first attribute as a classification dimension, for example, shops of different area segments can be classified into different categories to obtain a third classification, which is not limited here.

[0046] It should also be noted that a target can belong to multiple categories at the same time. For example, a shop can belong to the category with high standard unit price (first category), the category with low floors (second category), and the category with large area (third category). There is no restriction here.

[0047] In this way, through classification, the target price verification can be made more targeted, ensuring that different categories of shops are evaluated rationally under their respective standard conditions.

[0048] According to the solution provided in the above embodiment, the target can be classified according to different dimensions, so as to be analyzed and processed more accurately in the subsequent price verification. The classification can help identify which shops are unreasonable under similar conditions and serve as a reference for price adjustment. This can avoid simple one-size-fits-all pricing for all shops, but instead reasonably classify and adjust according to the multi-dimensional characteristics of the target, which can help the system obtain more accurate verification results and help staff provide more detailed verification results.

[0049] In some embodiments, the initial unit price of the target in each category is verified to obtain a second verification result, including: verifying each first category separately based on a first verification rule, the first verification rule represents obtaining the first target quantity in each first category whose initial unit price is lower than the predicted unit price, and calculating the pricing matching rate of each first category based on the first target quantity and all target quantities of the corresponding first category; verifying the second category based on a second verification rule, the second verification rule represents obtaining a second attribute verification result by calculating an actual coefficient of the second attribute, and comparing the actual coefficient of the second attribute with the standard coefficient of the second attribute, the actual coefficient of the second attribute represents the actual influence of the second attribute on the pricing of the target; wherein the second verification result includes the pricing matching rate and the second attribute verification result.

[0050] Specifically, after the targets are classified based on different dimensions, the initial unit price can be verified based on each classification.

[0051] First, the first category can be verified based on the first verification rule, that is, it can be understood that the group of shops with the same standard unit price is verified as a whole, that is, the initial unit price is verified for shops of the same business format. The system screens out the number of shops (i.e. the first target number) in each first category whose initial unit price is lower than the predicted unit price. The initial pricing of these shops may be too low, indicating that the initial unit price is lower than the predicted unit price given by the system, and manual remarks are required to explain, or the initial unit price is adjusted.

[0052] After obtaining the number of shops whose initial unit price is lower than the predicted unit price, obtain the total number of all shops in the corresponding first category, that is, the total number of shops in the same business format, and calculate the pricing match rate based on the total number of corresponding business formats and the number of shops whose initial unit price is lower than the predicted unit price. Pricing match rate = (number of shops in the first category whose initial unit price is lower than the predicted unit price) / (number of all shops in the first category). If the pricing match rate is low, it means that the initial unit price of most shops matches the predicted unit price well. If the pricing match rate is high, it means that the initial unit price of more shops deviates from reasonable pricing and may need to be adjusted.

[0053] Furthermore, based on the second verification rule, the second classification is verified, and the system can calculate the actual coefficient of the second attribute, and compare the actual coefficient of the second attribute with the standard coefficient of the second attribute to obtain a second verification result. The second attribute can indicate the floor where the shop is located, and the actual coefficient of the second attribute can be calculated based on the area of ​​all shops on the floor and the predicted unit price of all shops, that is, the actual coefficient = average floor price ÷ standard unit price of the business format, where the average floor price = (∑ the pricing of all resources on this floor in this business format × area) ÷ ∑ the area of ​​all resources on this floor in this business format.

[0054] Based on this, if the actual coefficient of the second attribute is greater than the standard coefficient of the second attribute, it means that there are shops with unreasonable initial unit prices on the corresponding floor, and it is necessary to adjust the unit prices of the unreasonable shops. The final comparison result of the actual coefficient of the second attribute and the standard coefficient of the second attribute represents the second attribute verification result.

[0055] According to the solution provided in the above embodiment, the initial unit price and the predicted unit price of the same business format shops are matched and verified through the first verification rule, and the rationality of the pricing is measured by the pricing matching rate. The second verification rule is based on the second attribute of the shop. By comparing the actual coefficient of the second attribute with the standard coefficient of the second attribute, the rationality of the initial unit price under the second attribute category is obtained. Finally, the second attribute verification result and the pricing matching rate are combined to obtain the second verification result, which shows a multi-faceted evaluation of the shop pricing, which helps the staff to further adjust the initial unit price of the shop according to these results to ensure the scientificity and rationality of the pricing.

[0056] In some embodiments, calculating the actual coefficient of the second attribute includes: obtaining targets corresponding to the standard coefficients of the same second attribute, and obtaining the predicted unit prices of each corresponding target, and calculating the average predicted unit prices corresponding to the standard coefficients of the same second attribute; and calculating the actual coefficient of the second attribute based on the average predicted unit prices and the standard unit prices.

[0057] Specifically, the second attribute may represent different floors of shops, and the rationality of the initial unit prices of shops on the same floor may be evaluated by calculating the actual coefficient of the floor.

[0058] The system can classify shops according to floors, and group shops on the same floor (i.e., targets corresponding to the same standard coefficient of the second attribute) together. These shops have the same floor attributes and the same standard coefficient of the second attribute. It should be understood that shops grouped together should belong to the same business format, that is, shops of the same business format on the same floor are grouped together. As an example, the preset area represents a shopping mall with three floors. The standard coefficient of each floor can be determined in advance through manual experience, such as 1.2 for the first floor, 1.0 for the second floor, and 0.8 for the third floor. After the system identifies the corresponding standard coefficients, shops with the same standard unit price with the same standard coefficients can be grouped together.

[0059] Furthermore, the system can calculate the average predicted unit price of the corresponding floor based on the predicted unit price of each shop in the same category, that is, the average floor price mentioned above. After obtaining the average predicted unit price, it is divided by the standard unit price of the corresponding business format to obtain the actual coefficient of the second attribute, that is, the actual coefficient of the corresponding floor. As an example, there are 5 shops of the same business format on the second floor, and the standard unit price is 500 yuan / square meter. The predicted unit prices are: 500 yuan / square meter, 550 yuan / square meter, 520 yuan / square meter, 530 yuan / square meter and 540 yuan / square meter, respectively. The predicted unit price average = (500+550+520+530+540) / 5 = 528 yuan / square meter, then the actual coefficient of the second floor = 528 / 500 = 1.056, this actual coefficient is slightly higher than the standard coefficient, which means that the market demand or other factors of the shops on the second floor make it more valuable than expected, then the initial unit price of the second floor can be targetedly increased based on the first verification result, and there is no restriction here.

[0060] According to the solution provided in the above embodiment, by classifying the standard coefficients of different second attributes and calculating the actual coefficients of the second attributes, the real impact of the second attributes on the target pricing can be evaluated, and whether the pricing of the corresponding target is reasonable can be judged in combination with the standard coefficients of the second attributes.

[0061] In some embodiments, a target verification result is determined based on the first verification result and the second verification result, including: if the pricing match rate is lower than a preset value, and the second attribute verification result represents that the actual coefficient of the second attribute is lower than the standard coefficient of the second attribute, then a first price adjustment signal is issued based on the first verification result, and the target verification result represents the information indicated by the first price adjustment signal; if the pricing match rate is lower than a preset value, and the second attribute verification result represents that the actual coefficient of the second attribute is not lower than the standard coefficient of the second attribute, then a second price adjustment signal is issued based on the first verification result, and the target verification result represents the information indicated by the second price adjustment signal.

[0062] Specifically, the first verification result can be understood as the comparison result between the initial unit price and the predicted unit price of each target, and the second verification result can include the pricing matching rate and the second attribute verification result, wherein the pricing matching rate can indicate the degree of consistency between the initial unit price of the target and the predicted unit price, that is, it can be understood as the extent to which the initial unit price of the target conforms to the reasonable pricing calculated by the system based on the standard unit price and attributes (first attribute, second attribute). The second attribute verification result can indicate whether the actual market impact of the second attribute meets expectations.

[0063] After obtaining the above-mentioned first verification result and second verification result, the system can comprehensively consider the verification results to determine whether the initial unit price needs to be adjusted, and send out different price adjustment signals.

[0064] The first possible situation is: the pricing matching rate is lower than the preset value (for example, 50%), which means that the initial unit price of the target deviates greatly from the predicted unit price and does not meet the standard of reasonable pricing. The actual coefficient of the second attribute is lower than the standard coefficient, which means that the actual impact of the second attribute is lower than expected. For example, the floor where the shop is located does not have the impact on the shop pricing that it should actually have in the market. In this way, it means that the initial unit price of the shop on the corresponding floor does not match the predicted unit price, and the market performance of the second attribute is not as expected. Therefore, the initial unit price of the target can be adjusted to adapt to the actual market situation, that is, a first price adjustment signal is issued. The first adjustment signal can display all analysis results, such as the first verification result and the second verification result, and indicate the target that needs to be adjusted in pricing. Of course, there is no limitation here, and the content displayed by the first price adjustment signal can be set based on the specific situation.

[0065] The second possible situation is that the pricing match rate is lower than the preset value, and the actual coefficient of the second attribute is not lower than the standard coefficient, which means that the market performance of the second attribute meets or even exceeds expectations. For example, the market influence of the floor meets the preset standard. In this case, the system sends a second price adjustment signal. At this time, there is a mismatch between the initial unit price and the predicted unit price. However, due to the good market performance of the second attribute, it may not be necessary to adjust the price significantly. Therefore, the second price adjustment signal can be used to prompt the staff to make slight adjustments as appropriate based on market performance and other factors, or keep the price unchanged. Of course, if the price remains unchanged, the staff can enter the reason for the unchanged price to avoid the system from repeatedly verifying the target.

[0066] It should be noted that since the first verification result represents the comparison result between the initial unit price and the predicted unit price of the corresponding target, the first verification result can be used as auxiliary information for the second verification result to issue a corresponding price adjustment signal. That is, after determining to issue a corresponding price adjustment signal based on the second verification result, the corresponding first verification result (the specific target whose initial unit price does not match the predicted unit price) is extracted so that the staff can clearly understand which target or targets have an initial unit price that does not match the predicted unit price. It should also be understood that when no price adjustment is required, the target verification result can also be returned to the user to display the target verification result. At this time, the target verification result can be a display information with reasonable pricing, which is not restricted here.

[0067] According to the solution provided in the above embodiment, by combining the pricing matching rate and the second attribute verification result, the system can intelligently determine whether the target pricing is reasonable, and send different price adjustment signals according to the situation, which can help the target make more reasonable pricing decisions based on actual conditions.

[0068] In some embodiments, after displaying the target verification result through an interactive interface, it also includes: obtaining a target unit price in response to manual adjustment; obtaining a budget unit price, comparing the target unit price with the budget unit price, obtaining a comparison result, and determining the final unit price of the target based on the comparison result.

[0069] Specifically, after displaying the target verification results, if price adjustment is required, the staff can adjust the pricing of the corresponding target based on the corresponding price adjustment signal, obtain the target unit price, and obtain the budget unit price corresponding to the target. The budget unit price can be the budget unit price pre-set by the company or seller for managing the target contract price. The budget unit price may be determined based on the annual company budget, operating goals or other financial indicators.

[0070] Furthermore, by comparing the target unit price with the budget unit price, we can check again whether the target unit price meets the budget requirements. This re-comparison can ensure that the target unit price not only reflects the market situation but also does not deviate from the company's strategic goals, and then determine the final unit price of the target based on the comparison results.

[0071] It should be noted that the comparison results may be 1: the target unit price is higher than the budgeted unit price; 2: the target unit price is lower than the budgeted unit price; 3: the target unit price is equal to or close to the budgeted unit price. Therefore, if there is a large gap between the target unit price and the budgeted unit price, the target unit price can be further adjusted based on the comparison results to reach the final unit price. For example, when the target unit price is 5% higher than the budgeted unit price, the staff can appropriately lower the target unit price to obtain the final unit price. The price adjustment process can be adjusted by the staff taking into account the market situation and the comparison results, and no specific restrictions are made here.

[0072] According to the solution provided in the above embodiment, the target unit price can be determined again by the budget unit price to obtain the final unit price. This can ensure that the target pricing not only meets market demand but also does not deviate from the company's strategic goals. The final pricing is verified through multiple checks, providing a more scientific and reasonable price management process.

[0073] It should also be noted that after obtaining the final unit price, you can also predict the target unit price for the next year. For example: next year's target price = current year's target price × (1 + increase rate). In this way, you can pre-calculate the target price for next year or even the year after that as a forecast for revenue calculation, which can assist in formulating the company's business plan and target unit prices.

[0074] Figure 2 This is a flow chart of another price verification method provided by the embodiment of the present application. Figure 2 The embodiments of the present application are further described.

[0075] First, the physical property library of the shops is constructed. The staff enters the physical factors and engineering properties of the shops (i.e., the lighting effect of the shops, whether they are at the elevator entrance, etc.), and sets the standard parameter configuration (i.e., manually set the standard unit price of the business format, the floor coefficient corresponding to different floors, the area segment coefficient corresponding to different areas, the physical factor coefficient, and the standard value of property management promotion, etc.), and further enters the resource data of all shops (i.e., the target) in the mall, i.e., the floor, area, business format, physical factor, and FMR decomposition coefficient of each shop. The initial unit price corresponding to each shop is entered for system verification. The initial unit price can be determined based on manual experience and comprehensive consideration of the standard parameters of the corresponding shops. FMR can represent financial indicators. In the real estate or investment field, it can be used to evaluate the economic performance of properties or projects, such as the annual income increase ratio, the standard value of property fees, and the standard value of promotion fees. These coefficients can be used for financial analysis and investment decisions to help evaluate the long-term value and potential benefits of real estate.

[0076] Furthermore, the overall resources of the system are verified, and the verification process may include: selection of measurement data, verification of the same business type, verification of the same area segment, and verification of the same floor, which will not be expanded here, and the verification result details will be displayed to facilitate the staff to adjust the prices of shops in a targeted manner.

[0077] Furthermore, by comprehensively analyzing the financial situation of shop leasing or sales through comparison of unit prices, revenues, areas of the same floor in the same business format, and unit price change ratios, targeted adjustments are made (it should be understood that shop prices can be adjusted based on manual responses to price adjustment signals, and the system can also automatically adjust unreasonable shop pricing after sufficient training, which is not limited here), the target unit price mentioned above is obtained.

[0078] Further budget control of shops is carried out through shop planning, rental change analysis, total revenue achievement, and business indicator achievement to obtain the budget unit price of shops. The target unit price is adjusted in combination with the budget unit price to obtain the final unit price, which is set as the contract price of the shop. After the contract is signed, the system automatically calculates the value of the shop (such as the predicted unit price) and the budget unit price achievement, and reversely guides the update of the shop intelligent pricing model, analyzes the system data, and implements FMR achievement analysis to evaluate the gap between actual financial performance and expected finance, achieves budget unit price achievement to compare the difference between the final unit price and the budget unit price, analyzes the factors affecting price achievement, and conducts financial anomaly warnings to help the system formulate more accurate forecast unit prices and achieve more accurate shop pricing strategies.

[0079] All the above optional technical solutions can be arbitrarily combined to form optional embodiments of the present application, which will not be described one by one here.

[0080] The following is an embodiment of the device of the present application, which can be used to execute the embodiment of the method of the present application. For details not disclosed in the embodiment of the device of the present application, please refer to the embodiment of the method of the present application.

[0081] Figure 3 Schematic diagram of a price verification device provided in an embodiment of the present application. Figure 3 As shown, the price verification device comprises:

[0082] The acquisition module 301 is configured to acquire target attributes, initial unit prices, and standard unit prices corresponding to each target in a preset area, and determine a predicted unit price corresponding to the target according to the standard unit price and the target attributes;

[0083] A first verification module 302 is configured to verify the initial unit price according to the predicted unit price to obtain a first verification result;

[0084] The second verification module 303 is configured to classify the targets according to a preset rule, verify the initial unit price of the targets in each category, and obtain a second verification result;

[0085] The third verification module 304 is configured to determine a target verification result according to the first verification result and the second verification result, and display the target verification result through an interactive interface.

[0086] In some embodiments, the acquisition module 301 is specifically used to obtain the standard coefficient of the first attribute and the standard coefficient of the second attribute, the first attribute represents the first consideration for pricing the target, the second attribute represents the second consideration for pricing the target, and the standard coefficient represents the standard influence on pricing the target; the standard coefficient of the first attribute, the standard coefficient of the second attribute and the standard unit price are multiplied to obtain the predicted unit price.

[0087] In some embodiments, the second verification module 303 is specifically used to classify the targets according to preset dimensions, which include the standard unit price and the second attribute; wherein the targets are classified based on the standard unit price to obtain a first category corresponding to the standard unit price, and each first category corresponds to the same standard unit price; and the targets are classified based on the second attribute to obtain a second category corresponding to the standard coefficient of the second attribute, and each second category corresponds to the same standard coefficient of the second attribute.

[0088] In some embodiments, the second verification module 303 is specifically used to verify each first category based on a first verification rule, the first verification rule represents obtaining a first target quantity in each first category whose initial unit price is lower than the predicted unit price, and calculating the pricing matching rate of each first category based on the first target quantity and all target quantities of the corresponding first category; verifying the second category based on a second verification rule, the second verification rule represents obtaining a second attribute verification result by calculating an actual coefficient of the second attribute, and comparing the actual coefficient of the second attribute with the standard coefficient of the second attribute, the actual coefficient of the second attribute represents the actual influence of the second attribute on the pricing of the target; wherein the second verification result includes the pricing matching rate and the second attribute verification result.

[0089] In some embodiments, the second verification module 303 is specifically used to obtain the target corresponding to the standard coefficient of the same second attribute, and obtain the predicted unit price of each corresponding target, calculate the average predicted unit price corresponding to the standard coefficient of the same second attribute; based on the average predicted unit price and the standard unit price, calculate the actual coefficient of the second attribute.

[0090] In some embodiments, the third verification module 304 is specifically used to send a first price adjustment signal based on the first verification result if the pricing match rate is lower than a preset value, and the second attribute verification result represents that the actual coefficient of the second attribute is lower than the standard coefficient of the second attribute, and the target verification result represents the information indicated by the first price adjustment signal; if the pricing match rate is lower than a preset value, and the second attribute verification result represents that the actual coefficient of the second attribute is not lower than the standard coefficient of the second attribute, then send a second price adjustment signal based on the first verification result, and the target verification result represents the information indicated by the second price adjustment signal.

[0091] In some embodiments, the third verification module 304 is specifically used to respond to manual adjustments to obtain a target unit price corresponding to the target; obtain a budget unit price, compare the target unit price with the budget unit price, obtain a comparison result, and determine the final unit price of the target based on the comparison result.

[0092] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0093] Figure 4 Schematic diagram of an electronic device 4 provided in an embodiment of the present application. Figure 4 As shown, the electronic device 4 of this embodiment includes: a processor 401, a memory 402, and a computer program 403 stored in the memory 402 and executable on the processor 401. When the processor 401 executes the computer program 403, the steps in the above-mentioned method embodiments are implemented. Alternatively, when the processor 401 executes the computer program 403, the functions of the modules / units in the above-mentioned device embodiments are implemented.

[0094] The electronic device 4 may be a desktop computer, a notebook, a PDA, a cloud server, or other electronic device. The electronic device 4 may include, but is not limited to, a processor 401 and a memory 402. Those skilled in the art will appreciate that Figure 4 The electronic device 4 is merely an example and does not limit the electronic device 4 , and may include more or less components than those shown in the figure, or different components.

[0095] The processor 401 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.

[0096] The memory 402 may be an internal storage unit of the electronic device 4, for example, a hard disk or memory of the electronic device 4. The memory 402 may also be an external storage device of the electronic device 4, for example, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the electronic device 4. The memory 402 may also include both an internal storage unit and an external storage device of the electronic device 4. The memory 402 is used to store computer programs and other programs and data required by the electronic device.

[0097] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units.

[0098] If the integrated module / 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 storage medium. Based on this understanding, the present application implements all or part of the process in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. The computer program may include computer program code, which may be in source code form, object code form, executable file or some intermediate form. Computer-readable media may include: any entity or device capable of carrying computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium, etc.

[0099] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A price verification method, characterized in that: include: Obtaining target attributes, initial unit prices, and standard unit prices corresponding to each target in a preset area, and determining a predicted unit price corresponding to the target according to the standard unit prices and the target attributes; Verifying the initial unit price according to the predicted unit price to obtain a first verification result; Classifying the targets according to preset rules, and verifying the initial unit prices of the targets in each classification to obtain a second verification result; A target verification result is determined according to the first verification result and the second verification result, and the target verification result is displayed through an interactive interface.

2. The method according to claim 1, characterized in that The target attribute includes a first attribute and a second attribute, and determining the predicted unit price corresponding to the target according to the standard unit price and the target attribute includes: Acquire a standard coefficient of the first attribute and a standard coefficient of the second attribute, wherein the first attribute represents a first consideration factor for pricing the target, the second attribute represents a second consideration factor for pricing the target, and the standard coefficient represents a standard influence degree on pricing the target; The predicted unit price is obtained by multiplying the standard coefficient of the first attribute, the standard coefficient of the second attribute, and the standard unit price.

3. The method according to claim 2, characterized in that The targets include targets corresponding to at least two different standard unit prices and targets corresponding to at least two standard coefficients of the second attribute, and the classifying of the targets according to the preset rules includes: Classifying the targets respectively according to preset dimensions, where the preset dimensions include the standard unit price and the second attribute; Among them, the target is classified based on the standard unit price to obtain a first category corresponding to the standard unit price, and each of the first categories corresponds to the same standard unit price; the target is classified based on the second attribute to obtain a second category corresponding to the standard coefficient of the second attribute, and each of the second categories corresponds to the same standard coefficient of the second attribute.

4. The method according to claim 3, characterized in that The verifying the initial unit price of the target in each category to obtain a second verification result includes: Verify each of the first categories based on a first verification rule, wherein the first verification rule indicates obtaining a first target quantity in each of the first categories whose initial unit price is lower than the predicted unit price, and calculating a pricing matching rate for each of the first categories based on the first target quantity and all corresponding target quantities of the first categories; Verifying the second classification based on a second verification rule, wherein the second verification rule indicates that an actual coefficient of the second attribute is calculated, and a second attribute verification result is obtained based on the actual coefficient of the second attribute and compared with a standard coefficient of the second attribute, wherein the actual coefficient of the second attribute indicates an actual influence of the second attribute on the pricing of the target; The second verification result includes the pricing matching rate and the second attribute verification result.

5. The method according to claim 4, characterized in that The calculating the actual coefficient of the second attribute comprises: Obtaining the target corresponding to the standard coefficient of the same second attribute, obtaining the predicted unit price of each corresponding target, and calculating the average of the predicted unit prices corresponding to the standard coefficient of the same second attribute; Based on the predicted unit price mean and the standard unit price, an actual coefficient of the second attribute is calculated.

6. The method according to claim 5, characterized in that The determining a target verification result according to the first verification result and the second verification result includes: If the pricing match rate is lower than a preset value, and the second attribute verification result indicates that the actual coefficient of the second attribute is lower than the standard coefficient of the second attribute, a first price adjustment signal is issued based on the first verification result, and the target verification result indicates information indicated by the first price adjustment signal; If the pricing matching rate is lower than the preset value, and the second attribute verification result represents that the actual coefficient of the second attribute is not lower than the standard coefficient of the second attribute, a second price adjustment signal is issued based on the first verification result, and the target verification result represents the information indicated by the second price adjustment signal.

7. The method according to claim 1, characterized in that After displaying the target verification result through the interactive interface, the method further includes: In response to the manual adjustment, a target unit price corresponding to the target is obtained; Obtain a budget unit price, compare the target unit price with the budget unit price, obtain a comparison result, and determine a final unit price of the target based on the comparison result.

8. A price verification device, characterized in that: include: An acquisition module is configured to acquire target attributes, an initial unit price, and a standard unit price corresponding to each target in a preset area, and determine a predicted unit price corresponding to the target according to the standard unit price and the target attributes; A first verification module is configured to verify the initial unit price according to the predicted unit price to obtain a first verification result; A second verification module is configured to classify the targets according to a preset rule, verify the initial unit price of the targets in each category, and obtain a second verification result; The third verification module is configured to determine a target verification result according to the first verification result and the second verification result, and to display the target verification result through an interactive interface.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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