CN114708057A

CN114708057A - Commodity display information diagnosis system and method and electronic equipment

Info

Publication number: CN114708057A
Application number: CN202210316200.2A
Authority: CN
Inventors: 常旭东; 谢宗杰; 李威
Original assignee: Rajax Network Technology Co Ltd
Current assignee: Rajax Network Technology Co Ltd
Priority date: 2022-03-23
Filing date: 2022-03-23
Publication date: 2022-07-05

Abstract

The present application relates to the field of data processing technologies, and in particular, to a system and a method for diagnosing merchandise display information. The system comprises: an evaluation dimension determination module to: determining an evaluation dimension corresponding to the identification of the target brand; a dimension score determination module to: for a target evaluation dimension, determining a corresponding dimension score according to an actual commodity score and a target commodity score corresponding to the target evaluation dimension, wherein the actual commodity score is determined according to information generated by commodities of a target brand, and the target commodity score is determined according to information generated by commodities of other brands in the same industry as the target brand; a diagnostic information determination module to: and determining the diagnosis information of the commodity display information of the target brand according to the dimension value corresponding to the evaluation dimension. According to the scheme, optimization suggestions can be provided for the display information of the target brand, and the commodity operation effect is favorably improved.

Description

Commodity display information diagnosis system and method and electronic equipment

Technical Field

The present application relates to the field of data processing technologies, and in particular, to a system and a method for diagnosing merchandise display information, and an electronic device.

Background

The commodity display information (e.g., menu) plays an important role in the commodity operation effect, for example, the optimized commodity display information is beneficial to increasing the sales volume of commodities. Therefore, a diagnosis scheme for commodity display information is needed in the prior art to achieve the effect of optimizing the commodity display information of related brands.

It is to be noted that the information disclosed in the above background section is only for enhancement of understanding of the background of the present specification and therefore may include information that does not constitute prior art known to those of ordinary skill in the art.

Disclosure of Invention

An object of the present invention is to provide a system and a method for diagnosing merchandise display information, and an electronic device, which can optimize merchandise display information of a brand to at least a certain extent.

Additional features and advantages of the description herein will be set forth in the detailed description which follows, and in part will be obvious from the description, or may be learned by practice of the description.

According to an aspect of the present specification, there is provided a diagnosis system of merchandise display information, the apparatus including: the system comprises an evaluation dimension determining module, a dimension score determining module and a diagnostic information determining module.

Wherein the evaluation dimension determination module is configured to: determining at least one evaluation dimension corresponding to the identification of the target brand, wherein the evaluation dimension comprises: the method comprises the following steps of (1) evaluating the target brand by at least one evaluation dimension, wherein the evaluation dimension is used for evaluating the target brand; the dimension score determining module is configured to: determining a dimension score corresponding to a target evaluation dimension according to an actual commodity score and a target commodity score corresponding to the target evaluation dimension, wherein the actual commodity score is determined according to information generated by commodities of the target brand, and the target commodity score is determined according to information generated by commodities of other brands in the same industry as the target brand; and the diagnostic information determination module is configured to: and determining the diagnostic information of the commodity display information of the target brand according to the dimension value corresponding to the at least one evaluation dimension.

According to another aspect of the present specification, there is provided a method of diagnosing merchandise display information, the method including: determining at least one evaluation dimension corresponding to the identification of the target brand, wherein the evaluation dimension comprises: the method comprises the following steps of (1) evaluating the target brand by at least one evaluation dimension, wherein the evaluation dimension is used for evaluating the target brand; determining a dimension score corresponding to a target evaluation dimension according to an actual commodity score and a target commodity score corresponding to the target evaluation dimension, wherein the actual commodity score is determined according to information generated by commodities of the target brand, and the target commodity score is determined according to information generated by commodities of other brands in the same industry as the target brand; and determining the diagnostic information of the commodity display information of the target brand according to the dimension value corresponding to the at least one evaluation dimension.

According to still another aspect of the present specification, there is provided an electronic device including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method for diagnosing merchandise display information according to the above embodiment.

The method and the system for diagnosing the commodity display information and the electronic equipment provided by the embodiment of the specification have the following technical effects:

the scheme provided by the exemplary embodiment of the present specification is suitable for diagnosing the commodity display information (for example, the menu of the brand) corresponding to each brand, and the diagnosis information determined based on the scheme is beneficial to optimizing the commodity display information of the corresponding brand, so that the optimization of the commodity operation effect of each brand is facilitated. Specifically, the evaluation dimensions provided by the scheme include: and collecting related information of a target brand (any one brand) according to the determined evaluation dimension, wherein the related information comprises one or more of the richness of the commodity, the new index on the commodity, the commodity sale index, the commodity price index, the commodity conversion rate and the commodity repurchase rate. Further, the dimension score of each evaluation dimension is determined based on the commodity score of the target brand-related evaluation dimension (denoted as actual commodity score) and the commodity scores of other brands of the same industry (denoted as target commodity scores). The score value is helpful for fully understanding the commodity business situation of the target brand, and can be beneficial to comparison and analysis among different brands of commodities in the same industry in each evaluation dimension, so that the diagnostic information of the targeted commodity display information is determined according to the target brand. Therefore, a promotion suggestion is provided for the display information of the target brand, and the optimization of the commodity operation effect is facilitated.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the specification.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present specification and together with the description, serve to explain the principles of the specification. It is obvious that the drawings in the following description are only some embodiments of the present description, and that for a person skilled in the art, other drawings can be derived from them without inventive effort.

Fig. 1 is a schematic structural diagram of a diagnosis system for merchandise display information provided in an embodiment of the present specification.

Fig. 2 is a schematic structural diagram of a dimension score determining module according to an embodiment of the present disclosure.

Fig. 3 is a flowchart illustrating a method for determining a dimension score according to an embodiment of the present disclosure.

FIG. 4 is a schematic structural diagram of the dimension score determination module in the case where the target evaluation dimension is commodity richness.

Fig. 5 is a flowchart illustrating the dimension score determination method in the case where the target evaluation dimension is the richness of the product.

FIG. 6 is a schematic diagram showing the structure of the dimension score determination module in the case where the target evaluation dimension is a new index on the commodity.

Fig. 7 is a flowchart illustrating the dimension score determination method in the case where the target evaluation dimension is a new index on the commodity.

Fig. 8 is a schematic diagram showing the configuration of the dimension score determination module in the case where the target evaluation dimension is the commodity sales index.

Fig. 9 is a flowchart illustrating a dimension score determination method in the case where the target evaluation dimension is a commodity sales index.

Fig. 10 is a schematic diagram showing the structure of the dimension score determination module in the case where the target evaluation dimension is the item price index.

Fig. 11 is a flowchart illustrating a dimension score determination method in the case where the target evaluation dimension is a commodity price index.

Fig. 12 is a schematic diagram showing the structure of the dimension score determination module in the case where the target evaluation dimension is the commodity conversion rate.

Fig. 13 is a flowchart illustrating a dimension score determination method in the case where the target evaluation dimension is the commodity conversion rate.

Fig. 14 is a schematic structural diagram showing the dimension score determination module in the case where the target evaluation dimension is the commodity repurchase rate.

Fig. 15 is a flowchart illustrating a dimension score determination method in the case where the target evaluation dimension is the commodity repurchase rate.

Fig. 16 is a schematic diagram showing a display graph of a plurality of evaluation dimensions and scores of the dimensions corresponding to the evaluation dimensions.

Fig. 17 is a flowchart illustrating a method for diagnosing merchandise display information according to an embodiment of the present disclosure.

Fig. 18 is a schematic structural diagram of an electronic device provided in an embodiment of this specification.

Detailed Description

To make the objects, technical solutions and advantages of the present specification clearer, embodiments of the present specification will be described in further detail below with reference to the accompanying drawings.

When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present specification. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the specification, as detailed in the appended claims.

Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many different forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of embodiments of the present description. One skilled in the relevant art will recognize, however, that the embodiments of the disclosure can be practiced without one or more of the specific details, or with other methods, components, devices, steps, and so forth. In other instances, well-known technical solutions have not been shown or described in detail to avoid obscuring aspects of the present description.

Furthermore, the drawings are merely schematic illustrations of the present specification and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and thus their repetitive description will be omitted. Some of the block diagrams shown in the figures are functional entities and do not necessarily correspond to physically or logically separate entities. These functional entities may be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor devices and/or microcontroller devices.

The display information of the commodity is information displayed to the user by a brand, so that the user can know the selling price, the promotion activity, the package information and the like of various types of commodities of the brand through the commodity display information. Therefore, the commodity display information has influence on whether the user orders. Therefore, the technical scheme takes commodity display information (such as a menu) diagnosis as an entry point, improves the digitization capability of merchants and data processing middleboxes, and specifically comprises aspects of digitization diagnosis, digitization enabling, digitization duplication and the like. Furthermore, the platform outputs the dimension values of each brand in multiple evaluation dimensions, which is beneficial to improving the commodity operation capacity of the merchant, thereby improving the output of the merchant and promoting the realization of platform targets (such as plans or templates like commodity operation effects) at the merchant side.

The embodiment of the specification can provide a diagnosis system of commodity display information, a diagnosis method of commodity display information and electronic equipment, can optimize commodity display information of related brands at least to a certain extent, provides promotion suggestions for display information of target brands, and further contributes to optimizing commodity operation efficiency. Specifically, the following detailed description will be made on the embodiments of the diagnosis system of the merchandise display information provided in the present specification by using fig. 1 to fig. 16:

fig. 1 is a schematic structural diagram of a diagnosis system for merchandise display information provided in an embodiment of the present disclosure. The system for diagnosing the commodity display information provided by the embodiment of the specification can be computing equipment on the e-commerce platform side, and can acquire the related commodity information of all brands registered on the e-commerce platform side, optimize the commodity display information for each brand based on the diagnosis scheme of the commodity display information provided by the embodiment of the specification, provide promotion suggestions for the display information of the target brand, and further contribute to optimizing the commodity operation effect.

As shown in fig. 1, a diagnosis system 100 for merchandise display information provided in an embodiment of the present disclosure includes: an evaluation dimension determination module 110, a dimension score determination module 120, and a diagnostic information determination module 130.

Wherein the evaluation dimension determining module 110 is configured to: at least one evaluation dimension corresponding to the identity of the target brand is determined.

The diagnosis of the merchandise display information provided in the embodiment of the present specification is applicable to any brand registered on the e-commerce platform side, and the embodiment of the present specification takes a "target brand" as an example for description. That is, the "target brand" refers to any brand registered on the e-commerce platform side.

In order to evaluate commodity information of a target brand from multiple angles, evaluation dimensions provided by embodiments of the present specification include: the commodity abundance, the commodity innovation index, the commodity sale index, the commodity price index, the commodity conversion rate and the commodity repurchase rate. Any combination of the above evaluation dimensions may be employed to measure the commodity information of the target brand. The evaluation dimensions corresponding to the brand are not limited in the specification, and the combination of the evaluation dimensions can be determined as required.

The dimension score determination module 120 is configured to: and for a target evaluation dimension, determining a dimension score corresponding to the target evaluation dimension according to the actual commodity score and the target commodity score corresponding to the target evaluation dimension.

The actual commodity score is determined according to information generated by commodities of the target brand, and the target commodity score is determined according to information generated by commodities of other brands in the same industry as the target brand.

Illustratively, the system further comprises: and a display module. Therefore, the dimension value corresponding to each dimension is displayed through the display module image. Specifically, under the condition that the evaluation dimensions are not less than three, determining the number of edges of the displayed graph according to the number of the evaluation dimensions; and determining the fixed point position of the display graph through the dimension score of the evaluation dimension. The information shown by the display module will be described in detail in the corresponding embodiment of fig. 16.

The dimension score determination module 120 determines the dimension score of each evaluation dimension based on the commodity score of the target brand-related evaluation dimension (denoted as actual commodity score) and the commodity scores of other brands of the same industry (denoted as target commodity scores). The score value is helpful for fully understanding the commodity business situation of the target brand, and can be beneficial to comparison and analysis among different brands of commodities in the same industry in each evaluation dimension, so that the diagnostic information of the targeted commodity display information is determined according to the target brand. Therefore, a promotion suggestion is provided for the display information of the target brand, and the optimization of the commodity operation effect is facilitated.

With continued reference to fig. 1, the diagnostic information determination module 130 is configured to: and determining the diagnostic information of the commodity display information of the target brand according to the dimension value corresponding to the at least one evaluation dimension.

In this embodiment, the level of the target brand in the same industry as the target brand in the dimension can be determined according to the score of any dimension, so that possible problems of the brand in the current dimension can be analyzed, and the diagnosis information of the commodity display information of the target brand can be determined.

In an exemplary embodiment, fig. 2 is a schematic structural diagram of a dimension score determining module provided in an embodiment of the present specification. Referring to FIG. 2, the dimension score determination module 120 includes: an information determining unit 210, an actual factor score determining unit 220, an actual commodity score determining unit 230, a target factor score determining unit 220 ', a target commodity score determining unit 230', and a dimension score determining unit 240.

Fig. 3 is a flowchart illustrating a method for determining a dimension score according to an embodiment of the present disclosure. The role of each unit of the dimension score determining module 120 in the dimension score determining process is specifically described below with reference to fig. 2 and 3.

In S310, at least one influence factor regarding the target evaluation dimension and a weight corresponding to each of the influence factors are determined by the information determination unit 210.

The target evaluation dimension can be commodity abundance, commodity novelty index, commodity sale index, commodity price index, commodity conversion rate or commodity repurchase rate. The target influence factor is any one of at least one influence factor that influences the target evaluation dimension, and the target influence factors are different when the target evaluation dimensions are different.

For example, in the case where the target evaluation dimension is the commodity abundance, the influence factor is the number of sales categories and the number of store-average commodities of the target brand. When the target evaluation dimension is a new product index, the influence factor is the number of new products of the target brand.

Exemplarily, under the condition that the influence factor of the target evaluation dimension is more than one, the influence degrees of different influence factors on the current evaluation dimension need to be determined through respectively corresponding weights, so that the evaluation dimension of the commodity can be refined, and the accuracy of the dimension score can be improved.

In S320, the actual factor score I20 corresponding to the target influence factor is determined by the actual factor score determining unit 220 from the information I10 generated from the target brand of merchandise.

For example, the information I10 generated by the target brand of merchandise may be the number of categories of merchandise with a payment transaction amount increase rate of more than 1% in the last 30 days, the total number of merchandise related to the target brand, the number of stores related to the target brand, and so on.

Illustratively, information I10 generated by commodities of a target brand related to a target evaluation dimension is acquired and is further used for determining an actual factor score I20 corresponding to a target influence factor.

In S330, the actual commodity score determining unit 230 determines the actual commodity score I40 according to the actual factor score I20 corresponding to the target influence factor and the weight I30 corresponding to the target influence factor.

Wherein the target influence factor is any one of the at least one influence factor.

Illustratively, the influence factors of the target evaluation dimension include factor 1 and factor 2, and the weight corresponding to factor 1 is 0.3 and the weight corresponding to factor 2 is 0.7, then the product of 0.3 and the actual factor score I20 of factor 1 is calculated, the product of 0.7 and the actual factor score I20 of factor 2 is calculated, and the sum of the two products is calculated as the actual commodity score I40.

In S320 ', determining, by the target factor score determining unit 220', a target factor score I20 'corresponding to the target influence factor according to information I10' generated from other brands of goods in the same industry; and, in S330 ', the target commodity score determining unit 230 ' determines a target commodity score I40 ' based on the target factor score I20 ' corresponding to the target influence factor and the weight I30 ' corresponding to the target influence factor.

In order to improve the objectivity of the scores of all the evaluation dimensions of the target brand, in the scheme provided by the embodiment, the target commodity score I40' of other brands in the same industry in the related evaluation dimensions is also calculated. Further, in S340, the dimension score corresponding to the target evaluation dimension is determined according to the actual commodity score I40 and the target commodity score I40' corresponding to the target evaluation dimension by the dimension score determining unit 240.

In this embodiment, the dimension score corresponding to the target evaluation dimension may be determined by the ratio of the actual commodity score I40 to the target commodity score I40'.

The following embodiments will explain the specific actions of the dimension score determination module 120 and the diagnostic information determination module 130, respectively, in different evaluation dimensions:

in an exemplary embodiment, fig. 4 is a schematic structural diagram of the dimension score determining module 120 in the case that the target evaluation dimension is commodity richness. Fig. 5 is a flowchart illustrating a dimension score determination method in the case where the target evaluation dimension is commodity richness.

The following describes the role of each unit of the dimension score determining module 120 in the dimension score determining process in detail with reference to fig. 4 and 5.

In this embodiment, the dimension score determining module 120 includes: the system comprises an information determining unit, an actual commodity score determining unit, a target commodity score determining unit and a dimension score determining unit;

referring to fig. 4, the actual product score determining unit in this embodiment may specifically include: a first influence factor determination unit 410 and a second influence factor determination unit 420; the dimension score determining unit includes: a first factor score determining unit 450, a second factor score determining unit 460, and a commodity richness determining unit 470.

In S510, the information determining unit 440 determines that the influence factors of the richness of the product are the number of sales categories and the number of store-average products of the target brand; and determining a first weight corresponding to the number of sales categories and a second weight corresponding to the number of store-average goods of the target brand.

For example, the weight determination unit 430 may determine the weights of the two impact factors to be 0.5 and 0.5, respectively.

In S520, the number of categories of the target brand satisfying the first preset condition among the target brand of merchandise is determined as the number of sales categories I420 of the target brand by the first influence factor determination unit 410.

In this embodiment, the information I410 generated by the target brand of goods is information for calculating the richness of the target brand of goods, and includes the number of categories of goods satisfying the first preset condition in the target brand of goods.

For example, the category of the goods may also be referred to as a type of goods, and in the case that the target brand is a restaurant of a certain brand, the category of the goods may refer to: hot dishes, cold dishes, and beverages. In the determining process of the commodity richness provided by the embodiment, statistics is carried out at the commodity category level, so that the diagnostic information of the commodity category in the commodity display information can be determined, and the display effect of the commodity display information at the category level is favorably improved.

Illustratively, the above categories of the commodities meeting the first preset condition are: and paying the commodity category of which the transaction amount increase rate is greater than the first preset value within the first preset time. For example, the commodity categories satisfying the first preset condition are: the number of categories of goods having a rate of increase of more than 1% of the amount paid within the last 30 days.

In S520 ', the second influence factor determination unit 420 acquires the total number of products of the target brand, acquires the number of stores of the target brand, and obtains the total number of products and the number of stores to obtain the number of store-average products I420' of the target brand.

In this embodiment, the information I410 generated by the target brand of goods is information for calculating the richness of the target brand of goods, and includes the total number of goods of the target brand and the number of stores of the target brand. For example, the platform may determine that the total number of items of the target brand is X and the number of stores of the target brand is a, and then calculate the number of stores of the target brand as X/a. Illustratively, rounding operations may also be performed on X/a.

The number of sales categories of the target brand and the number of average store commodities of the target brand may be determined as an actual commodity score of the target brand with respect to the target evaluation dimension.

In S530, the target commodity score determining unit 460 obtains the target commodity score corresponding to the target evaluation dimension according to the information generated by the commodities of other brands in the same industry, and obtains the sales category target number target value I430 and the store average commodity number target value I430'.

Illustratively, by the target commodity score determining unit 460, an actual commodity score of each brand in other brands in the same industry about the target evaluation dimension is obtained, and the maximum value is determined as the target commodity score corresponding to the target evaluation dimension. That is, the number of sales categories of each brand in other brands in the same industry is obtained, and the maximum value of the number of sales categories is determined as the target value of the number of sales categories I430, and the number of store-average commodities of each brand in other brands in the same industry is obtained, and the maximum value of the number of store-average commodities is determined as the target value of the number of store-average commodities I430'.

In S540, a first influence factor score I450 is determined by the first factor score determining unit 450 according to the sales category number I420, the sales category number target value I430, and the first weight I440 of the target brand.

In this embodiment, a ratio between the number I420 of the sales category of the target brand and the target value I430 of the number of the sales category may be calculated first, so as to obtain a difference between the target brand and the current industry in terms of the number of the sales category. Further, the ratio is multiplied by the first weight I440 to reflect the degree of influence of the number of sales categories of the target brand on the richness dimension of the target brand, so as to obtain a first influence factor score I450.

In S540 ', a second influence factor score I450' is determined by the second factor score determining unit 460 according to the store-average commodity number standard value I430 ', the store-average commodity number I430 of the target brand, and the second weight I440'.

In this embodiment, a ratio between the number of the store-average commodities I430 of the target brand and the number standard value I430' of the store-average commodities may be calculated first, so as to obtain a difference between the target brand and the current same industry in terms of the number of the store-average commodities. Further, the ratio is multiplied by the second weight I440 'to reflect the influence degree of the number of the average store commodities of the target brand on the commodity richness dimension, so as to obtain a second influence factor score I450'.

Further, in S550, the commodity richness I460 of the target brand is determined according to the first influence factor score I450 and the second influence factor score I450'.

In this embodiment, the dimension score corresponding to the target evaluation dimension may be determined by the sum of the first influence factor score I450 and the second influence factor score I450'.

In an exemplary embodiment, in the case that the objective evaluation dimension is commodity richness, the diagnostic information determination module 130 specifically functions as follows:

and acquiring the actual commodity score (including the number of sales categories and the number of shop-average commodities of the same brand) of each brand in other brands in the same industry about the target evaluation dimension, and calculating the target value of the other brands about the commodity richness.

For example, if the platform can obtain N brands of the same industry as the target brand, the number A of sales categories for the ith brand (any of the N brands mentioned above) is_iNumber of average commodities of Heshou B_iN number of sales category A can be obtained₁-A_NAnd obtaining the average commodity number B of N shops₁-B_N。

Further, in one embodiment, the average of the N sales categories may be obtained and multiplied by a first weight, the average of the N average store commodities may be obtained and multiplied by a second weight, and the sum of the two products may be used as the target value for the richness of the commodities. In another embodiment, the median of the N sales categories can be obtained and multiplied by the first weight to obtain the median of the N average store commodities, and the median of the N average store commodities can be multiplied by the second weight, and the sum of the two products can be used as the target value of the commodity richness. In another embodiment, the average value of the top 30 percent sales categories of the N sales categories is obtained and multiplied by the first weight; obtaining the average value of the number of the top 30 percent sales categories in the N store average commodities in the sequence from high to low, and multiplying the average value by a second weight; and the sum of the two products is used as a target value related to the richness of the commodity. In another embodiment, in the N sales category numbers, obtaining an average value of the sales category numbers larger than a preset value, and multiplying the average value by the first weight; obtaining the average value of the number of the shop-average commodities larger than the preset value in the N sales categories, and multiplying the average value by a second weight; and the sum of the two products is used as a target value related to the richness of the commodity.

The embodiment of the specification provides multiple determination modes of target values of commodity abundance, and is beneficial to promoting real-time activity of a scheme.

In an exemplary embodiment, in a case where the commodity abundance of the target brand is smaller than the target value regarding the commodity abundance, first menu diagnosis information for the target brand is generated, and the first menu diagnosis information is used to suggest the target brand to increase the supply amount of commodities so as to increase the number of commodity categories of the target brand and the number of average commodities of the target brand.

The embodiment of the present specification provides a calculation scheme for the richness of the commodities through fig. 4 and fig. 5, wherein the influence factors include the number of the commodity categories and the number of the shop-average commodities. And comparing the target brand with other brands in the same industry from the angle of two influence factors. Furthermore, the corresponding diagnosis information can be determined according to the comparison result so as to guide the recommendation information of the target brand in the number of the commodity categories and the number of the average commodities in the shop, and finally the display effect of the commodity display information of the target brand is improved.

In an exemplary embodiment, fig. 6 shows a schematic structural diagram of the dimension score determining module 120 in the case that the target evaluation dimension is a new index on a commodity. Fig. 7 is a flowchart illustrating the dimension score determination method in the case where the target evaluation dimension is a new index on the commodity.

The following describes the role of each unit of the dimension score determining module 120 in the dimension score determining process in detail with reference to fig. 6 and 7.

Referring to fig. 6, the dimension score determining module 120 in this embodiment includes: an information determination unit 610, a unified processing unit 620, an influence factor determination unit 630, an actual commodity score determination unit 640, a target commodity score determination unit 650, and a commodity-up-to-date index determination unit 660.

In S710, the information determination unit 610 determines the number of new products whose influence factors on the new value of the product are the target brand.

For example, the information determining unit 610 may be configured to determine a weight corresponding to the influence factor, in addition to the influence factor related to the new index on the product. In this embodiment, if the number of the influence factors of the new index on the commodity is 1, the weight value is 1. In other embodiments, if there are a plurality of influence factors added to the new index on the commodity, the weight corresponding to each influence factor may be determined according to the actual situation.

In S720, the unifying unit 620 performs unification processing on the product names of the target brands.

For example, for the same dish in the same brand, there may be a phenomenon that names in different shops are different, and this embodiment identifies the above situations through an algorithm and processes the situations into a unified name in a unified way. The commodity names of the target brands after unified processing can improve commodity statistical efficiency and accuracy.

In S730, the influence factor determination unit 630 determines the number of commodities satisfying the second preset condition among the commodities of the target brand as the last new commodity number I620 of the target brand.

Illustratively, the commodities meeting the second preset condition are: the commodities appearing for the first time within a second preset time length, and the shop coverage rate of the commodities in the target brand is larger than a second preset value, for example, the shop coverage rate of a new product selection shop is larger than 10%. And/or the number of orders for the commodity within the third preset time period is greater than a third preset value, for example, the number of orders for a new commodity in the past 90 days is > 100.

In this embodiment, the threshold conditions set by the second preset value and the third preset value can be used to screen out invalid "new commodities" that do not meet the threshold conditions in terms of the shop coverage of the new commodities and the recent sales volume, respectively, so as to facilitate the statistical accuracy of the new indexes on the commodities.

In S740, the actual product score I650 of the target brand with respect to the target evaluation dimension is determined by the actual product score determining unit 640 from the number I620 of top-new products of the target brand.

In this embodiment, the number of the influence factors of the new index on the commodity is only 1, and therefore the value of the weight I640 is 1. That is, in the present embodiment, the last new commodity number I620 of the target brand may be determined as the actual commodity score I650 of the target brand with respect to the target evaluation dimension.

In S740 ', the target product score determining unit 650 obtains the target product score I650 ' corresponding to the target evaluation dimension according to the information I610 ' generated by the products of other brands in the same industry.

Illustratively, by the target commodity score determining unit 650, an actual commodity score of each of the other brands in the same industry about the target evaluation dimension is obtained, and the maximum value is determined as the target commodity score corresponding to the target evaluation dimension. That is, the number of new commodities of each brand in other brands in the same industry is obtained, and the maximum value of the number of new commodities is determined as the target commodity score I650'.

In S750, the new on-product index determining unit 660 determines the new on-product index I660 of the target brand according to the actual product score I650 and the target product score I650' corresponding to the target evaluation dimension.

In this embodiment, a ratio between the actual commodity score I650 and the target commodity score I650' of the target brand may be calculated, so as to obtain a new commodity index of the target brand.

In an exemplary embodiment, in the case that the objective evaluation dimension is a new index on a commodity, the above diagnostic information determination module 130 specifically functions as follows:

and acquiring the actual commodity score (particularly, the new number of commodities on which each brand of other brands in the same industry meets the second preset condition and/or the third preset condition) of each brand of other brands in the same industry about the target evaluation dimension, and calculating the target value of the other brands about the new index of the commodities.

For example, if the platform can obtain N brands of the same industry as the target brand, the new index C is provided for the i-th brand (any one of the N brands)_iN new indexes C on the commodities can be obtained₁-C_N。

Further, according to the new index C on N commodities₁-C_NThe specific implementation of calculating the target value of the new index on the commodity is the same as the specific implementation of determining the target value of the richness of the commodity, and therefore, the detailed description is omitted in this embodiment. The embodiment of the specification provides various determination modes of target values of new indexes on commodities, and is beneficial to improving the real-time flexibility of the scheme.

In an exemplary embodiment, in a case that the new index on the target brand is smaller than the target value related to the new index on the target brand, second menu diagnosis information for the target brand is generated, and the second menu diagnosis information is used for suggesting the target brand to increase the research and development strength and the update frequency of the target brand.

The embodiment of the present specification provides a calculation scheme for a new commodity number through fig. 6 and fig. 7, where the influence factor is the number of the above-mentioned last new commodities, and a plurality of condition thresholds are set in the process of determining the number of the last new commodities so as to ensure the validity of the number of the last new commodities. And comparing the target brand with other brands in the same industry in the angle of the influence factor. Furthermore, the corresponding diagnosis information can be determined according to the comparison result so as to guide the suggestion information of the target brand on the number of the new commodities, and finally, the display effect of the commodity display information of the target brand can be improved.

In an exemplary embodiment, fig. 8 shows a schematic structural diagram of the dimension score determining module 120 in the case that the target evaluation dimension is a commodity sales index. Fig. 9 is a flowchart illustrating a dimension score determination method in the case where the target evaluation dimension is a commodity sales index.

The following describes the role of each unit of the dimension score determining module 120 in the dimension score determining process in detail with reference to fig. 8 and 9.

referring to fig. 8, the actual product score determining unit in this embodiment may specifically include: a third influence factor determination unit 810 and a fourth influence factor determination unit 820; the dimension score determining unit includes: a third factor score determining unit 850, a fourth factor score determining unit 860, and a commodity sales index determining unit 870.

In S910, determining, by the information determining unit 840, that the influence factors of the commodity sale index are package order permeability and the average commodity number of the non-package orders of the target brand; and determining a third weight corresponding to the package order permeability and a fourth weight corresponding to the average commodity number of the non-package orders of the target brand.

Illustratively, the weights of the two impact factors can be determined to be 0.3 and 0.7 by the weight determination unit 830.

In S920, the third influence factor determining unit 810 determines, as package order permeability I820 of the target brand, a ratio of the package order to all orders included in the orders of the target brand in the first preset time period.

In this embodiment, the information I810 generated by the target brand of goods is information for calculating the target brand of goods sales index, and includes all orders of the target brand within the first preset time period and orders containing packages within the first preset time period.

For example, the package refers to a combination of multiple commodities, and in the case that the target brand is a restaurant of a certain brand, the order containing the package may be: an order containing only one or more packages, or an order containing one or more packages and a single point of sale. In the process of determining the commodity sale index provided by this embodiment, whether the order of the commodity contains the package level is counted to determine the diagnostic information related to the commodity package in the commodity display information, which is beneficial to improving the display effect of the commodity display information at the category level.

Illustratively, all orders within the first preset time period, for example, all orders of the target brand within the last 30 days; the order of the goods related to the target brand within the first preset time period is, for example, an order containing a package of the target brand within the last 30 days.

In S920 ', the third influence factor determining unit 820 acquires the number of non-package orders of the target brand and the total number of commodities corresponding to the non-package orders within the first preset time period, and determines the ratio of the total number of commodities corresponding to the non-package orders to the number of non-package orders as an average number of commodities I820' of the non-package orders of the target brand.

In this embodiment, the information I810 generated by the target brand of goods is information for calculating the target brand of goods sale index, and includes the number of non-package orders of the target brand and the total number of goods corresponding to the non-package orders within the first preset time length. It should be noted that the total number of items does not include the number of accessories (e.g., dishes in the take-out order, etc.) to improve the accuracy of the dimension score in order to avoid distracters. For example, the platform may determine that the number of non-package orders of the target brand within the first preset time duration of the target brand is b and the total number of commodities corresponding to the non-package orders is Y, and then calculate the number of stores of the target brand as Y/b. Illustratively, rounding operations may also be performed on Y/b.

The package order permeability of the target brand and the average commodity number of non-package orders of the target brand can be determined as the actual commodity score of the target brand with respect to the target evaluation dimension.

In S930, the target product score determining unit 860 obtains the target product score corresponding to the target evaluation dimension according to the information generated by the products of other brands in the same industry, and obtains the package order permeability target value I830 and the non-package order average product number standard value I830'.

Illustratively, by the target commodity score determining unit 860, the actual commodity score of each brand in other brands in the same industry about the target evaluation dimension is obtained, and the maximum value is determined as the target commodity score corresponding to the target evaluation dimension. That is to say, package order permeability of each brand in other brands in the same industry is obtained, and the maximum value of package order permeability is determined as the package order permeability target value I830, and the product number average value of non-package orders of each brand in other brands in the same industry is obtained, and the maximum value of product number average value of non-package orders is determined as the product number average value I830'.

At S940, a third influence factor score I850 is determined by the third factor score determination unit 850 according to the package order permeability I820, the package order permeability target value I830, and the third weight I840 of the target brand.

In this embodiment, a ratio between package order permeability I820 of the target brand and package order permeability target value I830 may be calculated first, so as to obtain a gap between the target brand and the current same industry in terms of package order permeability. Further, the ratio is multiplied by the third weight I840 to reflect the influence degree of the package order permeability of the target brand on the commodity sale index dimension of the target brand, and a third influence factor score I850 is obtained.

In S940 ', a fourth factor score determining unit 860 determines a fourth influence factor score I850' according to the non-package order average commodity number index value I830 ', the target brand non-package order average commodity number I830, and the fourth weight I840'.

In this embodiment, the ratio between the average number of non-package-order commodities I830 of the target brand and the standard value I830' of the average number of non-package-order commodities may be calculated first, so as to obtain the difference between the target brand and the current same industry in terms of the average number of non-package-order commodities. Further, the ratio is multiplied by the third weight I840 'to reflect the influence degree of the average number of non-package orders of the target brand on the commodity sales index dimension, so as to obtain a fourth influence factor score I850'.

Further, in S950, the commodity sales index I860 of the target brand is determined according to the third influence factor score I850 and the fourth influence factor score I850'.

In this embodiment, the dimension score corresponding to the target evaluation dimension may be determined by the sum of the third influence factor score I850 and the fourth influence factor score I850'.

In an exemplary embodiment, in the case that the target evaluation dimension is a commodity sales index, the diagnostic information determination module 130 specifically functions as follows:

and acquiring actual commodity scores (including package order permeability and non-package order average commodity number of the same brand) of each brand in other brands in the same industry about the target evaluation dimension, and calculating target values of the other brands about the commodity sales index.

For example, if N brands of the same industry as the target brand are available to the platform, package order penetration D for the ith brand (any of the N brands mentioned above) is provided_iAnd average number of non-package orders E_iN package order permeability D can be obtained₁-D_NAnd obtaining the average commodity number E of the N non-package orders₁-E_N。

Further, in one embodiment, the average value of the permeability of the N package orders may be obtained and multiplied by a third weight to obtain the average value of the number of commodities in the N non-package orders, and multiplied by a fourth weight, and the sum of the two products may be used as the target value of the commodity sale index. In another embodiment, the median of the permeability of the N package orders can be obtained and multiplied by a third weight to obtain the median of the average number of the commodities of the N non-package orders, and the median of the average number of the commodities can be multiplied by a fourth weight, and then the sum of the two products can be used as a target value of the commodity selling index. In yet another embodiment, in descending order, the average value of the permeability of the top 30 percent of the permeability of the N package orders is obtained and multiplied by the third weight; obtaining the average value of the permeability of the first 30 percent of the N non-package order average commodities in the sequence from high to low, and multiplying the average value by a fourth weight; the sum of the two products is then used as a target value for the commodity sales index. In another embodiment, the average value of the permeability of package orders which is greater than a preset value is obtained from the permeability of N package orders, and the average value is multiplied by a third weight; obtaining the average value of the average commodity number of the non-package orders which is larger than the preset value in the permeability of the N package orders, and multiplying the average commodity number by a fourth weight; the sum of the two products is then used as a target value for the commodity sales index.

The embodiment of the specification provides various determination modes of the target value of the commodity sales promotion index, and is beneficial to improving the real-time activity of the scheme.

In an exemplary embodiment, in a case where the commodity sales index of the target brand is smaller than the target value regarding the commodity sales index, third menu diagnosis information for the target brand is generated, and the third menu diagnosis information is used to suggest the target brand to add package categories and to determine a replacement commodity.

The embodiment of the present specification provides a calculation scheme for a commodity sales index through fig. 8 and fig. 9, wherein the influence factors include the package order permeability and the non-package order average commodity number. And comparing the target brand with other brands in the same industry from the angle of the two influence factors. Furthermore, the corresponding diagnostic information can be determined according to the comparison result so as to guide the recommendation information of the target brand in the package order permeability and the non-package order average commodity number, and finally the display effect of the commodity display information of the target brand is favorably improved.

In an exemplary embodiment, fig. 10 is a schematic structural diagram of the dimension score determining module 120 in the case that the target evaluation dimension is a commodity price index. Fig. 11 is a flowchart illustrating the dimension score determination method in the case where the target evaluation dimension is a new index on the commodity.

The following describes the role of each unit of the dimension score determining module 120 in the dimension score determining process in detail with reference to fig. 10 and 11.

Referring to fig. 10, the dimension score determining module 120 in this embodiment includes: an information determination unit, a target city determination unit 1010, a target commodity determination unit 1020, a target commodity determination unit 1030, an actual commodity score determination unit 1040, a target commodity score determination unit 1050, and a commodity price index determination unit 1060.

In S1110, the information determining unit determines that the influence factor related to the price index of the product is the price comparison value of the target brand.

For example, the information determination unit may be configured to determine, in addition to the influence factor related to the price index of the product, a weight corresponding to the influence factor. In this embodiment, if the number of the influencing factors of the commodity price index is 1, the weight value is 1. In other embodiments, if there are a plurality of influence factors for increasing the price index of the product, the weight corresponding to each influence factor may be determined according to the actual situation.

In S1120, by the target city determining unit 1010, a target city satisfying a third preset condition is determined among the sales cities corresponding to the target brand.

Illustratively, the platform obtains all sales cities for the target brand. In the present embodiment, the influence of the price factor on the commodities in the city with the higher increase rate of the actual payment transaction amount is measured, so that the city with the highest increase rate of the actual payment transaction amount in the last 14 days is determined as the target city. Meanwhile, the real payment transaction amount of the brand goods in each city is constantly changed, so that the time length threshold value is set in the embodiment, the target city can be determined again every day, and the accuracy of the dimension score is improved in a mode of dynamically changing the target city. For example, a target city (i.e., a city with the highest growth rate of the real payment transaction amount during 8/15/2021-8/15/2021) was determined to be shanghai in 2021, and a target city (i.e., a city with the highest growth rate of the real payment transaction amount during 8/1/2021-8/6/2021) was determined to be beijing in 8/20/2021.

In this embodiment, the information I1010 generated by the target brand of goods is information for calculating the target brand of goods sale index, including all sale cities of the target brand and the increase rate of the payment transaction amount in the past preset time period.

In S1130, the target article determination unit 1020 determines, from among articles sold by the target brand in the target city, the first article set I1020 satisfying the fourth preset condition.

Exemplarily, the commodities meeting the fourth preset condition are: and calculating the commodities (single goods) with the current sales volume ranked k (positive integer) from high to low according to the commodity orders corresponding to the target cities. For example, in the embodiment of the commodities which are ranked top 10 from high to low in the current sales amount in the target city, the commodity which meets the fourth preset condition may be selected and recorded as the first commodity set I1020.

Further, in S1140, the target product determining unit 1030 acquires the target product I1030 corresponding to the target product in the first product set I1020 in the target city.

The target product is any one of the first product set I1020. In the embodiment, for each commodity with the rank k from high to low, the benchmarking commodity is obtained. The benchmarking commodities are commodities meeting a fifth preset condition in other brands. The fifth preset condition is: if the targeted commodity of the jth (j takes a value of 1 to k) commodity with the sales volume from high to low in the first commodity set is Sj, the similarity between the jth commodity with the sales volume from high to low and the targeted commodity Sj is higher, and the number of stores of the commodity Sj in the target city is greater than a preset value (for example, the number of stores is greater than 5).

In this embodiment, after the target city is determined, the "hot goods" (k before the sales is ranked from high to low) of the target brand is determined according to the sales of the goods, so that the pertinence of the goods display information is improved. Furthermore, in the same city, the 'benchmarking commodities' which have competitiveness with the popular commodities are obtained, and then prices between the popular commodities of the target brand and the benchmarking commodities of other brands are compared, so that the practicability of commodity display information is improved.

If the commodity corresponding to the 5 th rank in the sales volume of the first commodity set is ranked from high to low, and the target commodity meeting the fifth preset condition does not exist in the target city, the commodity corresponding to the 5 th rank in the sales volume from high to low is not considered in the process of determining the price comparison value of the target brand. That is, since the commodity corresponding to the 5 th rank from high to low in the sales volume currently has no competitor for a while, the price of the commodity may not be involved in the calculation process of the price comparison value of the target brand.

In S1150, the actual commodity score determining unit 1040 determines, as the price comparison value of the target commodity, the ratio of the real payment transaction amount corresponding to the target commodity (any commodity in the first commodity set I1020) to the real payment transaction amount of the target commodity to the target commodity I1030; and determining a price comparison value of the target brand according to the price comparison value corresponding to each commodity in the first commodity set to obtain an actual commodity score I1040 of the target brand with respect to the target evaluation dimension.

In S1150 ', a target product score I1040 ' corresponding to the target evaluation dimension is obtained by the target product score determining unit 1050 according to the information I1010 ' generated by the products of other brands in the same industry.

Illustratively, by the target product score determining unit 1050, an actual product score of each brand in other brands in the same industry about the target evaluation dimension is obtained, and a maximum value is determined as the target product score corresponding to the target evaluation dimension. That is, the price comparison value of each brand in other brands in the same industry is obtained, and the maximum value of the price comparison value is determined as the target commodity score I1040'.

In S1160, the product price index determining unit 1060 determines the product price index I1060 of the target brand from the actual product score I1040 and the target product score I1040' corresponding to the target evaluation dimension.

In this embodiment, a ratio between the actual commodity score I1140 and the target commodity score I1140' of the target brand may be calculated, thereby obtaining the commodity price index of the target brand.

In an exemplary embodiment, in the case that the target evaluation dimension is a commodity price index, the above diagnostic information determination module 130 specifically functions as follows:

and acquiring the actual commodity score (specifically, the price comparison value of each brand in other brands) of each brand in other brands in the same industry about the target evaluation dimension, and calculating the target value of each brand in other brands about the commodity price index.

For example, if the platform can obtain N brands of the same industry as the target brand, the price comparison value F for the ith brand (any one of the N brands) is_iN price comparison values F can be obtained₁-F_N。

Further, comparing the value F according to the N prices₁-F_NThe specific implementation of calculating the target value of the price index of the product is the same as the specific implementation of determining the target value of the richness of the product, and therefore, the detailed description thereof is omitted in this embodiment. The embodiment of the specification provides various determination modes of the target value of the commodity price index, and is beneficial to promoting the real-time flexibility of the scheme.

In an exemplary embodiment, in a case where the commodity price index of the target brand is greater than the comparison value regarding the commodity price index, fourth menu diagnosis information for the target brand is generated, and the fourth menu diagnosis information is used to suggest that the commodity price of the target brand is reduced.

The embodiment of the present specification provides a calculation scheme for a price index of an article through fig. 10 and fig. 11, wherein the influence factor is a price comparison value of a brand, and a plurality of condition thresholds are set in the process of determining a target city, a first article set, and a target article to ensure the validity of the price comparison value. And comparing the target brand with other brands in the same industry in the angle of the influence factor. Furthermore, the corresponding diagnosis information can be determined according to the comparison result so as to guide the suggestion information of the target brand in the aspect of price setting, and finally the display effect of the commodity display information of the target brand can be improved.

In an exemplary embodiment, fig. 12 shows a schematic structural diagram of the dimension score determination module 120 in the case where the target evaluation dimension is a commodity conversion rate (purchase rate). Fig. 13 is a flowchart illustrating a dimension score determination method in the case where the target evaluation dimension is the commodity conversion rate.

The following describes the role of each unit of the dimension score determining module 120 in the dimension score determining process in detail with reference to fig. 12 and 13.

Referring to fig. 12, the dimension score determining module 120 in this embodiment includes: a target commodity determination unit 1210, a daily average conversion rate calculation unit 1220, an actual commodity score determination unit 1230, a target commodity score determination unit 1240, and a commodity conversion rate determination unit 1250.

In S1310, the target product determining unit 1210 determines a second product set I1220 satisfying a sixth preset condition among the products of the target brand.

In this embodiment, the information I1010 generated by the target brand of goods is information for calculating the conversion rate of the target brand of goods, and includes the sales volume of all goods in the target brand.

Illustratively, the commodity satisfying the sixth preset condition is: and calculating the commodities (single goods) with the current sales volume ranked k before from high to low according to the commodity orders corresponding to the target city. For example, the product that satisfies the sixth preset condition in the product embodiment that is ranked 10 from high to low in the current sales volume in the target city may be selected and recorded as the second product set I1220. The present embodiment also determines "hot commodities" (sales are ranked from high to low) of the target brand according to the commodity sales, and performs the following operations for the hot commodities.

For example, after the information I1010 generated by the target brand of the commodity is acquired, the commodity names in the information are unified, and the statistical efficiency and accuracy of the popular commodity can be improved through the unified commodity name of the target brand.

In S1320, the average daily conversion rate calculating unit 1220 calculates the average daily conversion rate I1230 of the target commodities in the second commodity set I1220 within a fourth preset time period.

Illustratively, the target product is any product in the second product set I1220. In this embodiment, for each commodity ranked from high to low and ranked at the top k, the average daily conversion rate in the last 14 days is calculated, and the average daily conversion rate X in the last 14 days of the commodity ranked from high to low and ranked at the 1 st in sales volume is obtained₁Daily average conversion X of the 2 nd commodity with sales from high to low in the past 14 days₂… … average daily conversion X over the last 14 days for the kth commercial product ranked from high to low in sales_k。

In S1330, the actual commodity score determining unit 1230 determines the actual commodity score I1240 of the target brand with respect to the target evaluation dimension according to the average daily conversion rate I1230 corresponding to each commodity in the second commodity set I1220.

Illustratively, the average value of the average daily conversion rate in the last 14 days corresponding to each commodity with the sale amount from high to low ranking k is calculated to obtain the actual commodity score I1240. For example, the actual good score I1240 equals (X)₁+X₂+……X_k)/k。

In S1330 ', the target product score determining unit 1240' obtains the target product score I1240 'corresponding to the target evaluation dimension, based on the information I1210' generated from the products of other brands in the same industry.

For example, by the target product score determining unit 1240, an actual product score of each brand in other brands in the same industry with respect to the target evaluation dimension is obtained, and the maximum value is determined as the target product score corresponding to the target evaluation dimension. That is, the commodity conversion rate of each brand among other brands in the same industry is acquired, and the maximum value of the commodity conversion rate is determined as the target commodity score I1240'.

In S1340, the commodity conversion rate determining unit 1250 determines the commodity conversion rate of the target brand according to the actual commodity score I1240 and the target commodity score I1240' corresponding to the target evaluation dimension.

In this embodiment, a ratio between the actual commodity score I1240 and the target commodity score I1240' of the target brand may be calculated, so as to obtain the commodity conversion rate I1250 of the target brand.

In an exemplary embodiment, in the case that the target evaluation dimension is the commodity conversion rate, the diagnostic information determination module 130 specifically functions as follows:

and acquiring the actual commodity score (particularly the commodity conversion rate of each brand in other brands in the same industry) of each brand in the other brands in the same industry about the target evaluation dimension, and calculating the target value of the other brands about the commodity conversion rate.

For example, if the platform can obtain N brands of the same industry as the target brand, the commodity conversion rate G for the ith brand (any one of the N brands) is_iN commodity conversion rates G can be obtained₁-G_N。

Further, according to N commodity conversion rates G₁-G_NThe specific implementation of calculating the target value of the commodity conversion rate is the same as the specific implementation of determining the target value of the commodity abundance, and therefore, the detailed description thereof is omitted in this embodiment. The embodiment of the specification provides various determination modes of target values of commodity conversion rate, and is beneficial to promoting real-time activity of a scheme.

In an exemplary embodiment, in a case where the commodity conversion rate of the target brand is less than the target value regarding the commodity conversion rate, fifth menu diagnosis information for the target brand is generated, the fifth menu diagnosis information being used to suggest a user profile to be determined and to add a commodity determined from the user profile.

The embodiment of the specification provides a calculation scheme about commodity conversion rate through fig. 12 and fig. 13, and diagnosis and suggestion for displaying information to branded commodities are generated from the perspective of different users making visits to target branded commodities. Specifically, a plurality of condition thresholds are set in the process of determining the actual commodity score of the target evaluation dimension to ensure the effectiveness of the commodity conversion rate. The target brand is compared with other brands in the same industry. Furthermore, the corresponding diagnosis information can be determined according to the comparison result so as to guide the suggestion information of the target brand on the commodity conversion rate, and finally the display effect of the commodity display information of the target brand can be improved.

In an exemplary embodiment, fig. 14 is a schematic structural diagram of the dimension score determination module 120 in the case that the target evaluation dimension is the commodity repurchase rate. Fig. 15 is a flowchart illustrating a dimension score determination method in the case where the target evaluation dimension is the commodity repurchase rate.

The role of each unit of the dimension score determining module 120 in the determination of the dimension score is specifically described below with reference to fig. 14 and 15.

Referring to fig. 14, the dimension score determining module 120 in this embodiment includes: a target item determination unit 1410, a repurchase rate calculation unit 1420, an actual item score determination unit 1430, a target item score determination unit 1440, and an item repurchase rate determination unit 1450.

In S1510, the target product determination unit 1410 determines a third product set I1420 satisfying a seventh preset condition among the products of the target brand.

In this embodiment, the information I1010 generated by the target brand of goods is information for calculating the repurchase rate of the target brand of goods, and includes the sales volume of all goods in the target brand.

Illustratively, the commodity satisfying the seventh preset condition is: and calculating the commodities (single goods) with the current sales volume ranked k before from high to low according to the commodity orders corresponding to the target city. For example, in the present embodiment, the commodities that satisfy the seventh preset condition in the current sales volume ranked from high to low 10 in the target city may be selected and recorded as the third commodity set I1420. The present embodiment also determines "hot commodities" (sales are ranked from high to low) of the target brand according to the commodity sales, and performs the following operations for the hot commodities.

For example, after the information I1410 generated by the target brand of the commodity is acquired, the commodity names in the information are unified, and the statistical efficiency and accuracy of the popular commodity can be improved through the unified commodity name of the target brand.

In S1520, the repurchase rate calculating unit 1420 calculates the repurchase rate I1430 of the target product in the third product set I1420 within a fifth preset time period.

Illustratively, the target product is any product in the third product set I1420. In this embodiment, for each commodity whose sales are ranked k top from high to low, the repurchase rate of the commodity in the last 30 days is calculated, that is, the number of purchases of the same commodity by the same user is greater than 1. Obtaining the repurchase rate Z of the 1 st commodity with the sales volume from high to low in the last 30 days₁The repurchase rate Z of the 2 nd commodity with the sales volume ranked from high to low in the past 30 days₂… …, rate of repurchase Z of k-th commodity ranked from high to low in sales volume in the past 30 days_k。

In S1530, the actual product score determining unit 1430 determines the actual product score I1440 of the target brand with respect to the target evaluation dimension, based on the repurchase rate I1430 associated with each product in the third product set I1420.

Illustratively, the average value of the repurchase rate of each commodity in the top k of the ranking from high to low in the sales volume in the last 30 days is calculated to obtain the actual commodity score I1440. For example, the actual good score I1440 is equal to (Z)₁+Z₂+……Z_k)/k。

In S1530 ', the target product score determining unit 1440 acquires the target product score I1440 ' corresponding to the target evaluation dimension according to the information I1410 ' generated by the products of other brands in the same industry.

For example, by the target product score determining unit 1240, an actual product score of each brand in other brands in the same industry with respect to the target evaluation dimension is obtained, and the maximum value is determined as the target product score corresponding to the target evaluation dimension. That is, the product repurchase rate of each brand in other brands in the same industry is obtained, and the maximum value of the product repurchase rate is determined as the target product score I1440'.

In S1540, the product repurchase rate determination unit 1450 determines the product repurchase rate I1450 of the target brand according to the actual product score I1440 and the target product score I1440' corresponding to the target evaluation dimension.

In this embodiment, a ratio between the actual commodity score I1440 and the target commodity score I1440' of the target brand may be calculated, so as to obtain the commodity repurchase rate I1450 of the target brand.

In an exemplary embodiment, in the case that the target evaluation dimension is a commodity repurchase rate, the diagnostic information determination module 130 specifically functions as follows:

and acquiring the actual commodity score (particularly the commodity repurchase rate of each brand in other brands in the same industry) of each brand in other brands in the same industry relative to the target evaluation dimension, and calculating the target value of the other brands relative to the commodity repurchase rate.

For example, if the platform can obtain N brands of the same industry as the target brand, the product repurchase rate H for the ith brand (any one of the N brands mentioned above)_iThe repurchase rate H of N commodities can be obtained₁-H_N。

Further, according to the N commodity repurchase rates H₁-H_NThe specific implementation of calculating the target value of the commodity repurchase rate is the same as the specific implementation of determining the target value of the commodity abundance, and therefore, the detailed description thereof is omitted in this embodiment. The embodiment of the specification provides a plurality of determination modes of target values of commodity repurchase rate, and is beneficial to improving the real-time activity of a scheme.

In an exemplary embodiment, in a case that the article repurchase rate of the target brand is less than the target value related to the article repurchase rate, sixth menu diagnosis information for the target brand is generated, and the sixth menu diagnosis information suggests promoting marketing strength for an article with a high repurchase rate.

The embodiment of the specification provides a calculation scheme about the commodity repurchase rate through fig. 14 and fig. 15, and diagnosis and suggestion for showing information to brands and commodities are generated in the aspect that related users make ordering purchases of the same commodities in target brands. Specifically, a plurality of condition thresholds are set in the process of determining the actual commodity score of the target evaluation dimension to ensure the effectiveness of the commodity repurchase rate. The target brand is compared with other brands in the same industry. Furthermore, the corresponding diagnosis information can be determined according to the comparison result so as to guide the recommendation information of the target brand on the commodity repurchase rate, and finally the display effect of the commodity display information of the target brand can be improved.

The embodiment of the specification provides a diagnosis scheme for commodity display information of a brand (for example, a menu of the brand), and the diagnosis information determined based on the diagnosis scheme is beneficial to optimizing the commodity display information of the corresponding brand, so that the optimization of the commodity operation effect of each brand is facilitated. Specifically, the evaluation dimensions provided by the scheme include: and collecting related information of a target brand (any one brand) according to the determined evaluation dimension, wherein the related information comprises one or more of the richness of the commodity, the new index on the commodity, the commodity sale index, the commodity price index, the commodity conversion rate and the commodity repurchase rate. Further, the dimension score of each evaluation dimension is determined based on the commodity score of the target brand-related evaluation dimension (denoted as actual commodity score) and the commodity scores of other brands of the same industry (denoted as target commodity scores). The score value is helpful for fully understanding the commodity business condition of the target brand, and is also beneficial to comparison and analysis among different brands of commodities in the same industry in each evaluation dimension, so that the diagnostic information of the targeted commodity display information is determined for the target brand. Therefore, a promotion suggestion is provided for the display information of the target brand, and the optimization of the commodity operation effect is facilitated.

In an exemplary embodiment, fig. 16 is a schematic diagram illustrating a display graph of dimension scores corresponding to various evaluation dimensions and each evaluation dimension, and the graph may specifically represent the multi-dimension scores of various brands in the form of a radar map, and may measure gaps of different brands in the same dimension.

Referring to FIG. 16, a graph showing the dimension scores of multiple evaluation dimensions corresponding to 3 brands is shown, wherein the dimension scores corresponding to the 3 brands are distinguished by different icons. The total score for each dimension in the display graph is 5. And the dimension scores corresponding to different brands in each evaluation dimension are obtained after normalization.

Illustratively, for one of the evaluation dimensions, such as "richness of goods", the richness of goods corresponding to brand 161 and brand 163 is 5 points, and the richness of goods corresponding to brand 162 is 3 points. Therefore, the dimension scores of all the brands can be visually checked through the display graph, and the level of the brands in the same industry and the gaps between the brands and other brands in the same industry in each dimension.

Fig. 17 is a flowchart illustrating a method for diagnosing merchandise display information according to an embodiment of the present disclosure. Referring to fig. 17, the method shown therein includes:

s1710, determining at least one evaluation dimension corresponding to the target brand identifier, wherein the evaluation dimension comprises: the system comprises a commodity abundance degree, a commodity novelty index, a commodity sale index, a commodity price index, a commodity conversion rate and a commodity repurchase rate, wherein the at least one evaluation dimension is used for evaluating the target brand.

And S1720, determining a dimension score corresponding to a target evaluation dimension according to an actual commodity score and a target commodity score corresponding to the target evaluation dimension, wherein the actual commodity score is determined according to information generated by commodities of the target brand, and the target commodity score is determined according to information generated by commodities of other brands in the same industry as the target brand. And the number of the first and second groups,

s1730, according to the dimension value corresponding to the at least one evaluation dimension, determining diagnostic information of the commodity display information of the target brand.

The method for diagnosing merchandise display information shown in fig. 17 and the embodiment of the system for diagnosing merchandise display information belong to the same concept, and therefore, for details that are not disclosed in the embodiment of the system for diagnosing merchandise display information in this specification, please refer to the embodiment of the system for diagnosing merchandise display information in this specification, which is not described herein again.

It is to be noted that the above-mentioned figures are only schematic illustrations of the processes involved in the method according to the exemplary embodiment of the present description, and are not intended to be limiting. It will be readily understood that the processes shown in the above figures are not intended to indicate or limit the chronological order of the processes. In addition, it is also readily understood that these processes may be performed synchronously or asynchronously, e.g., in multiple modules.

The above example numbers are for description only and do not represent the merits of the examples.

The embodiments of the present specification further provide an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the computer program, the steps of the method according to any of the embodiments described above are implemented.

FIG. 18 schematically illustrates a block diagram of an electronic device in an exemplary embodiment according to this description. Referring to fig. 18, the electronic device 180 includes: a processor 1801 and a memory 1802.

In this embodiment, the processor 1801 is a control center of a computer system, and may be a processor of a physical machine or a processor of a virtual machine. The processor 1801 may include one or more processing cores, such as a 4-core processor, an 8-core processor, and so on. The processor 1801 may be implemented in at least one hardware form of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), and Programmable Logic Array (PLA). The processor 1801 may also include a main processor and a coprocessor, the main processor being a processor for processing data in an awake state; a coprocessor is a low power processor for processing data in a standby state.

In an embodiment of the present specification, the processor 1801 is specifically configured to:

determining at least one evaluation dimension corresponding to the identification of the target brand, the evaluation dimension comprising: the method comprises the following steps of (1) commodity richness, commodity new-on-market index, commodity sale index, commodity price index, commodity conversion rate and commodity repurchase rate, wherein the at least one evaluation dimension is used for evaluating the target brand; for a target evaluation dimension, determining a dimension score corresponding to the target evaluation dimension according to an actual commodity score and a target commodity score corresponding to the target evaluation dimension, wherein the actual commodity score is determined according to information generated by commodities of the target brand, and the target commodity score is determined according to information generated by commodities of other brands in the same industry as the target brand; and determining diagnostic information of the commodity display information of the target brand according to the dimension value corresponding to the at least one evaluation dimension.

Further, the processor 1801 is further specifically configured to execute the methods shown in fig. 3, fig. 5, fig. 7, fig. 9, fig. 11, fig. 13, and fig. 15.

Memory 1802 may include one or more computer-readable storage media, which may be non-transitory. Memory 1802 may also include high speed random access memory, as well as non-volatile memory, such as one or more magnetic disk storage devices, flash memory storage devices. In some embodiments of the present description, a non-transitory computer readable storage medium in memory 1802 is used to store at least one instruction for execution by processor 1801 to implement a method in embodiments of the present description.

In some embodiments, the electronic device 180 further comprises: a peripheral interface 1803 and at least one peripheral. The processor 1801, memory 1802, and peripheral interface 1803 may be connected by a bus or signal line. Each peripheral device may be connected to the peripheral device interface 1803 by a bus, signal line, or circuit board. Specifically, the peripheral device includes: at least one of a display 1804, a camera 1805, and an audio circuit 1806.

The peripheral interface 1803 may be used to connect Input/Output (I/O) related at least one peripheral to the processor 1801 and the memory 1802. In some embodiments of the present description, the processor 1801, memory 1802, and peripheral interface 1803 are integrated on the same chip or circuit board; in some other embodiments of the present description, any one or both of the processor 1801, the memory 1802, and the peripheral device interface 1803 may be implemented on separate chips or circuit boards. The examples in this specification are not particularly limited thereto.

The display screen 1804 is used to display a User Interface (UI). The UI may include graphics, text, icons, video, and any combination thereof. When the display screen 1804 is a touch display screen, the display screen 1804 also has the ability to acquire touch signals on or above the surface of the display screen 1804. The touch signal may be input to the processor 1801 as a control signal for processing. At this point, the display 1804 may also be used to provide virtual buttons and/or a virtual keyboard, also referred to as soft buttons and/or a soft keyboard. In some embodiments of the present description, the display 1804 may be one, providing a front panel of the electronic device 180; in other embodiments of the present description, the display 1804 may be at least two, each disposed on a different surface of the electronic device 180 or in a folded configuration; in still other embodiments of the present description, the display 1804 may be a flexible display disposed on a curved surface or a folded surface of the electronic device 180. Even further, the display 1804 may be arranged in a non-rectangular irregular pattern, i.e., a shaped screen. The Display 1804 may be made of Liquid Crystal Display (LCD), Organic Light-Emitting Diode (OLED), or the like.

The camera 1805 is used to capture images or video. Optionally, the cameras 1805 include a front camera and a rear camera. Generally, a front camera is disposed on a front panel of an electronic apparatus, and a rear camera is disposed on a rear surface of the electronic apparatus. In some embodiments, the number of the rear cameras is at least two, and each rear camera is any one of a main camera, a depth-of-field camera, a wide-angle camera and a telephoto camera, so that the main camera and the depth-of-field camera are fused to realize a background blurring function, and the main camera and the wide-angle camera are fused to realize panoramic shooting and a Virtual Reality (VR) shooting function or other fusion shooting functions. In some embodiments of the present description, the camera 1805 may also include a flash. The flash lamp can be a monochrome temperature flash lamp or a bicolor temperature flash lamp. The double-color-temperature flash lamp is a combination of a warm-light flash lamp and a cold-light flash lamp and can be used for light compensation under different color temperatures.

The audio circuitry 1806 may include a microphone and a speaker. The microphone is used for collecting sound waves of a user and the environment, converting the sound waves into electric signals, and inputting the electric signals to the processor 1801 for processing. For stereo sound collection or noise reduction purposes, the microphones may be multiple and disposed at different locations of the electronic device 180. The microphone may also be an array microphone or an omni-directional pick-up microphone.

The power supply 1807 is used to supply power to various components in the electronic device 180. The power supply 1807 may be alternating current, direct current, disposable or rechargeable. When the power supply 1807 includes a rechargeable battery, the rechargeable battery may be a wired rechargeable battery or a wireless rechargeable battery. The wired rechargeable battery is a battery charged through a wired line, and the wireless rechargeable battery is a battery charged through a wireless coil. The rechargeable battery may also be used to support fast charge technology.

The block diagram of the electronic device structure shown in the embodiments of the present specification does not constitute a limitation on the electronic device 180, and the electronic device 180 may include more or less components than those shown, or combine some components, or adopt a different arrangement of components.

In the description herein, it is to be understood that the terms "first," "second," and the like are used for descriptive purposes only and are not to be construed as indicating or implying relative importance. The specific meanings of the above terms in the present specification can be understood in specific cases by those of ordinary skill in the art. Further, in the description of the present specification, "a plurality" means two or more unless otherwise specified. "and/or" describes the association relationship of the associated objects, meaning that there may be three relationships, e.g., a and/or B, which may mean: a exists alone, A and B exist simultaneously, and B exists alone. The character "/" generally indicates that the former and latter associated objects are in an "or" relationship.

It should be noted that the above describes specific embodiments of the present specification. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.

The above description is only for the specific embodiments of the present disclosure, but the scope of the present disclosure is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope disclosed in the present disclosure, and all the changes or substitutions should be covered by the scope of the present disclosure. Accordingly, all equivalent changes made by the claims of this specification are intended to be covered by this specification.

Claims

1. A merchandise display information diagnostic system, the system comprising:

an evaluation dimension determination module to: determining at least one evaluation dimension corresponding to the identification of the target brand, the evaluation dimension comprising: the method comprises the following steps of (1) commodity richness, commodity new-on-market index, commodity sale index, commodity price index, commodity conversion rate and commodity repurchase rate, wherein the at least one evaluation dimension is used for evaluating the target brand;

a dimension score determination module to: for a target evaluation dimension, determining a dimension score corresponding to the target evaluation dimension according to an actual commodity score and a target commodity score corresponding to the target evaluation dimension, wherein the actual commodity score is determined according to information generated by commodities of the target brand, and the target commodity score is determined according to information generated by commodities of other brands in the same industry as the target brand;

a diagnostic information determination module to: and determining the diagnostic information of the commodity display information of the target brand according to the dimension value corresponding to the at least one evaluation dimension.

2. The system of claim 1, wherein the dimension score determination module is specifically configured to:

determining at least one influence factor related to the target evaluation dimension and a weight corresponding to each influence factor;

determining an actual factor value corresponding to a target influence factor according to information generated by the target brand of commodity, and determining the actual commodity value according to the actual factor value corresponding to the target influence factor and the weight corresponding to the target influence factor; wherein the target influence factor is any one of the at least one influence factor;

determining a target factor score corresponding to the target influence factor according to information generated by the other brands of commodities, and determining the target commodity score according to the target factor score corresponding to the target influence factor and the weight corresponding to the target influence factor;

and determining a dimension score corresponding to the target evaluation dimension according to the actual commodity score and the target commodity score corresponding to the target evaluation dimension.

3. The system of claim 1 or 2, wherein the target evaluation dimension is commodity richness; the dimension score determination module comprises: the system comprises an information determining unit, an actual commodity score determining unit, a target commodity score determining unit and a dimension score determining unit;

wherein the information determination unit is configured to: determining the influence factors of the commodity richness as the number of sales categories and the number of shop-average commodities of the target brand; determining a first weight corresponding to the number of sales categories and a second weight corresponding to the number of store-average goods of the target brand;

the actual commodity score determining unit is configured to:

determining the number of commodity categories meeting a first preset condition in the commodities of the target brand as the number of sales categories of the target brand, wherein the commodity categories meeting the first preset condition are as follows: paying the commodity category with the transaction amount increase rate larger than a first preset value within a first preset time length;

acquiring the total number of commodities of the target brand, acquiring the number of shops of the target brand, and acquiring the average number of shops of the target brand according to the total number of commodities and the number of shops;

determining the sales category number of the target brand and the average store commodity number of the target brand as an actual commodity score of the target brand with respect to the target evaluation dimension;

the target commodity score determining unit is configured to: according to information generated by commodities of other brands in the same industry, acquiring a target commodity score corresponding to the target evaluation dimension to obtain a sales category target number value and a shop average commodity number value;

the dimension score determining unit is configured to: determining a first influence factor score according to the sales category number of the target brand, the sales category number target value and the first weight, determining a second influence factor score according to the store average commodity number target value, the store average commodity number of the target brand and the second weight, and determining the commodity richness of the target brand according to the first influence factor score and the second influence factor score.

4. The system of claim 3, wherein the diagnostic information determination module is specifically configured to:

acquiring actual commodity scores of each brand in the other brands about the target evaluation dimension, and calculating target values of the other brands about the commodity richness;

and if the commodity abundance of the target brand is smaller than the target value of the commodity abundance of the other brands, generating first menu diagnosis information for the target brand, wherein the first menu diagnosis information is used for recommending the target brand to increase the supply quantity of commodities so as to increase the commodity number of the target brand and the average commodity number of the target brand.

5. The system according to claim 3, wherein the target good score determining unit is specifically configured to:

and acquiring the actual commodity score of each brand in the other brands about the target evaluation dimension, and determining the maximum value as the target commodity score corresponding to the target evaluation dimension.

6. The system of claim 1 or 2, wherein the target evaluation dimension is a commodity new index; the dimension score determination module comprises: the system comprises an information determining unit, an actual commodity score determining unit, a target commodity score determining unit and a commodity new index determining unit;

wherein the information determination unit is configured to: determining the influence factor of the new indexes on the commodities as the number of new commodities of the target brand;

the actual goods score determining unit is configured to:

determining the quantity of the commodities meeting a second preset condition in the commodities of the target brand as the number of the latest new commodities of the target brand, wherein the commodities meeting the second preset condition are as follows: the method comprises the steps that commodities appear for the first time within a second preset time period, the shop coverage rate of the commodities in the target brand is larger than a second preset value, and/or the number of orders of the commodities within a third preset time period is larger than a third preset value;

determining the actual commodity score of the target brand about the target evaluation dimension according to the number of the last new commodities of the target brand;

the target commodity score determining unit is configured to: obtaining a target commodity score corresponding to the target evaluation dimension according to information generated by commodities of other brands in the same industry;

the commodity freshness index determination unit is configured to: and determining a new commodity index of the target brand according to the actual commodity score and the target commodity score corresponding to the target evaluation dimension.

7. The system of claim 6, wherein the actual good score determination unit is further configured to:

and performing unified processing on the commodity names of the target brands to acquire the quantity of the commodities meeting the second preset condition in the commodities of the target brands according to the commodity names of the target brands after the unified processing.

8. The system of claim 6, wherein the diagnostic information determination module is specifically configured to:

acquiring actual commodity scores of each brand in the other brands about the target evaluation dimension, and calculating target values of the other brands about new indexes on the commodities;

and generating second menu diagnosis information for the target brand when the new index on the target brand is smaller than the target value of the other brands about the new index on the target brand, wherein the second menu diagnosis information is used for suggesting the target brand to increase the research and development strength and the new frequency of the target brand.

9. A method for diagnosing merchandise display information, the method comprising:

determining at least one evaluation dimension corresponding to the identification of the target brand, the evaluation dimension comprising: the method comprises the following steps of (1) commodity richness, commodity new-on-market index, commodity sale index, commodity price index, commodity conversion rate and commodity repurchase rate, wherein the at least one evaluation dimension is used for evaluating the target brand;

for a target evaluation dimension, determining a dimension score corresponding to the target evaluation dimension according to an actual commodity score and a target commodity score corresponding to the target evaluation dimension, wherein the actual commodity score is determined according to information generated by commodities of the target brand, and the target commodity score is determined according to information generated by commodities of other brands in the same industry as the target brand;

and determining the diagnostic information of the commodity display information of the target brand according to the dimension value corresponding to the at least one evaluation dimension.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the merchandise display information diagnosis method according to claim 9 when executing the computer program.