CN112288480A - Information processing method and device for retail commodity structure adjustment - Google Patents
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- 235000008446 instant noodles Nutrition 0.000 description 12
- 235000015278 beef Nutrition 0.000 description 5
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Abstract
The present disclosure discloses an information processing method for retail commodity structure adjustment, including: acquiring basic information of a preset commodity, wherein the basic information of the preset commodity comprises first basic information of the preset commodity and second basic information of the preset commodity; standardizing the first basic information of the preset commodity based on a preset data cleaning rule to obtain standard preset commodity information; based on the second basic information of the preset commodities, performing primary and secondary classification on the preset commodities corresponding to the standard preset commodity information to determine the category corresponding to each preset commodity; and calculating the proportion of the preset commodity quantity of each category by using a preset calculation method so as to judge whether the proportion meets the preset proportion.
Description
Technical Field
The disclosure relates to the technical field of retail commodity data processing, and in particular relates to an information processing method and device for retail commodity structure adjustment.
Background
A commodity category, a multi-level category determined by commodity classification.
In the prior art, when determining a management strategy (for example, updating or eliminating) of commodities in any shop in an e-commerce platform, the management strategy is generally determined based on data of commodities with high or low sales volumes on the market, and good market control data cannot be provided for the shop, so that the updating or eliminating of commodities is further inaccurate.
Disclosure of Invention
The main purpose of the present disclosure is to provide an information processing method and apparatus for retail product configuration adjustment, so as to solve the problem that good market comparison data cannot be provided for any store in an e-commerce platform when determining a management policy of the store product in the e-commerce platform in the prior art.
In order to achieve the above object, according to a first aspect of the present disclosure, there is provided an information processing method for retail merchandise structure adjustment, including: acquiring basic information of a preset commodity, wherein the basic information of the preset commodity comprises first basic information of the preset commodity and second basic information of the preset commodity; standardizing the first basic information of the preset commodity based on a preset data cleaning rule to obtain standard preset commodity information; based on the second basic information of the preset commodities, performing primary and secondary classification on the preset commodities corresponding to the standard preset commodity information to determine the category corresponding to each preset commodity; and calculating the proportion of the preset commodity quantity of each category by using a preset calculation method so as to judge whether the proportion meets the preset proportion.
Optionally, after calculating the ratio of the preset number of commodities in each category by using a preset calculation method to determine whether the ratio satisfies a preset ratio, the method further includes: if the proportion meets a preset proportion, acquiring main price belt information of the preset commodity; verifying the main price belt information of each preset commodity to obtain whether the main price belt information of each preset commodity meets preset gear information or not; counting the number of the standard preset commodity information which simultaneously meets a preset proportion and preset gear information; and if the number is larger than a preset threshold value, determining the standard preset commodity information as comparison information.
Optionally, the method further comprises: acquiring price band information of a preset commodity corresponding to the comparison information; acquiring price band information of a target commodity; and comparing the price band information of the preset commodity corresponding to the comparison information with the price band information of the target commodity to obtain a price band information comparison result.
Optionally, the obtaining of the preset basic information of the commodity includes: acquiring first basic information of a preset commodity, including acquiring preset commodity category information and name information of the preset commodity; and acquiring second basic information of the preset commodity, including acquiring sales data of the preset commodity.
Optionally, based on second basic information of preset commodities, primary and secondary classification is performed on the preset commodities corresponding to the standard preset commodity information, and determining the category corresponding to each preset commodity includes: determining second basic information of the preset commodities as evaluation indexes, and determining preset categories corresponding to the preset commodities under the evaluation indexes; calculating the grade of the preset commodity under the preset category by using the weight of the predetermined evaluation index; and determining the category corresponding to the preset commodity based on the grading interval to which the grade belongs.
According to a second aspect of the present disclosure, there is provided an information processing apparatus for retail merchandise structure adjustment, comprising: the system comprises a first acquisition unit, a second acquisition unit and a display unit, wherein the first acquisition unit is used for acquiring basic information of a preset commodity, and the basic information of the preset commodity comprises first basic information of the preset commodity and second basic information of the preset commodity; the data cleaning unit is used for standardizing the first basic information of the preset commodity based on a preset data cleaning rule to obtain standard preset commodity information; the classification unit is used for carrying out primary and secondary classification on the preset commodities corresponding to the standard preset commodity information based on the second basic information of the preset commodities so as to determine the corresponding classes of the preset commodities; and the calculating unit is used for calculating the proportion of the preset commodity quantity of each category by using a preset calculating method so as to judge whether the proportion meets the preset proportion.
Optionally, the apparatus further comprises: a second obtaining unit that obtains main price band information of the preset commodity if the ratio satisfies a preset ratio; the price band verification unit is used for verifying the main price band information of each preset commodity to obtain whether the main price band information of each preset commodity meets preset gear information or not; the counting unit is used for counting the number of the standard preset commodity information which simultaneously meets a preset proportion and preset gear information; and the determining unit is used for determining the standard preset commodity information as comparison information if the number is larger than a preset threshold value.
Optionally, the apparatus further comprises: a third obtaining unit, configured to obtain price band information of a preset commodity corresponding to the comparison information; a fourth obtaining unit that obtains price band information of the target commodity; and the comparison unit is used for comparing the price band information of the preset commodity corresponding to the comparison information with the price band information of the target commodity to obtain a price band information comparison result.
Optionally, the first obtaining unit includes: acquiring first basic information of a preset commodity, including acquiring preset commodity category information and name information of the preset commodity; and acquiring second basic information of the preset commodity, including acquiring sales data of the preset commodity.
Optionally, the classification unit comprises: determining second basic information of the preset commodities as evaluation indexes, and determining preset categories corresponding to the preset commodities under the evaluation indexes; calculating the grade of the preset commodity under the preset category by using the weight of the predetermined evaluation index; and determining the category corresponding to the preset commodity based on the grading interval to which the grade belongs.
In the embodiment of the disclosure, basic information of a preset commodity is acquired, wherein the basic information of the preset commodity comprises first basic information of the preset commodity and second basic information of the preset commodity; standardizing the first basic information of the preset commodity based on a preset data cleaning rule to obtain standard preset commodity information; based on the second basic information of the preset commodities, performing primary and secondary classification on the preset commodities corresponding to the standard preset commodity information to determine the category corresponding to each preset commodity; the proportion of the number of the preset commodities of each category is calculated by using a preset calculating method to judge whether the proportion meets the preset proportion, market comparison data with good market operation can be more accurately determined to be used as comparison data for further determining a management strategy, and therefore commodities can be accurately introduced or eliminated based on the comparison data, and the technical problem that when the management strategy (such as introduction or elimination) of any store commodity in an e-commerce platform is determined in the prior art, the commodities are generally determined based on high or low commodity data of sales volume in the market, and the commodities cannot be well operated and cannot be introduced or eliminated due to the fact that the good market comparison data cannot be provided for the store, and therefore the commodities are introduced or eliminated further and are inaccurate is solved.
Drawings
In order to more clearly illustrate the embodiments of the present disclosure or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present disclosure, and other drawings can be obtained by those skilled in the art without creative efforts.
FIG. 1 is a flow chart of an information processing method for retail merchandise structure adjustment according to an embodiment of the present disclosure;
FIG. 2 is a first application scenario diagram of an information processing method for retail merchandise structure adjustment according to an embodiment of the present disclosure;
fig. 3 is a second application scenario diagram of an information processing method for retail merchandise structure adjustment according to an embodiment of the present disclosure;
fig. 4 is a schematic structural diagram of an information processing apparatus for retail merchandise structural adjustment according to an embodiment of the present disclosure.
Fig. 5 is a schematic diagram of an electronic device according to an embodiment of the disclosure.
Detailed Description
In order to make the technical solutions of the present disclosure better understood by those skilled in the art, the technical solutions of the embodiments of the present disclosure will be clearly and completely described below with reference to the drawings in the embodiments of the present disclosure, and it is obvious that the described embodiments are only some embodiments of the present disclosure, not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments disclosed herein without making any creative effort, shall fall within the protection scope of the present disclosure.
It should be noted that the terms "first," "second," and the like in the description and claims of the present disclosure and in the above-described drawings are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It should be understood that the data so used may be interchanged under appropriate circumstances such that embodiments of the present disclosure may be described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
It should be noted that, in the present disclosure, the embodiments and features of the embodiments may be combined with each other without conflict. The present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
According to an embodiment of the present disclosure, there is provided a method for retail merchandise structure adjustment, as shown in fig. 1, the method comprising steps 101 through 104 as follows.
Step 101: the method comprises the steps of obtaining basic information of a preset commodity, wherein the basic information of the preset commodity comprises first basic information of the preset commodity and second basic information of the preset commodity.
In this embodiment, the execution subject may be a server, the retail goods may be convenience provider super goods in the e-commerce platform, and the convenience provider super goods are characterized by being of various kinds and having a low classification granularity, so that the difficulty in managing the convenience provider super goods is high. The preset commodities are commodities in the same preset business state, the preset area and the preset commercial shop in the trade area.
As an optional implementation manner of this embodiment, the first basic information of the preset commodity is obtained, including obtaining the category information of the preset commodity and the name information of the preset commodity; and acquiring second basic information of the preset commodity, including acquiring sales data of the preset commodity.
In this embodiment, the basic information of the preset commodity may be acquired from the database, where the basic information includes first basic information, and the first basic information may be commodity category information of the preset commodity and commodity name information of the preset commodity; the second basic information of the preset commodity may be sales information of the preset commodity, and may be sales amount, gross profit amount, sales amount, and inventory amount.
Step 102: and standardizing the first basic information of the preset commodity based on a preset data cleaning rule to obtain standard preset commodity information.
In this embodiment, the cleaning rule is used to unify different preset product shopping guide categories contained in different preset products into a standard product category, which may be a category standardized into three levels of products, for example, the shopping guide category of instant noodles with different names is standardized into a standard category, for example, the first level category "food and beverage", the second level category "instant food", and the third level category "instant noodles", and the standard category information after standardization is determined as the standard preset product information. The names of commodities with different names are washed to be commodity names with uniform names, for example, spaces, Chinese and English brackets and Chinese brackets are washed out, and finally one commodity corresponds to one standard category information. The standard preset goods information may be three-level category information of standardized goods.
Step 103: and based on the second basic information of the preset commodities, performing primary and secondary classification on the preset commodities corresponding to the standard preset commodity information, and determining the category corresponding to each preset commodity.
In this embodiment, based on the sales information of the preset goods, the ABC classification method is used to classify the preset goods corresponding to the standard preset goods information so as to determine the category corresponding to each preset goods.
As an optional implementation manner of this embodiment, based on second basic information of a preset commodity, primary and secondary classification is performed on the preset commodity corresponding to the standard preset commodity information, and determining a category corresponding to each preset commodity includes: determining second basic information of the preset commodities as evaluation indexes, and determining preset categories corresponding to the preset commodities under the evaluation indexes; calculating the grade of the preset commodity under the preset category by using the weight of the predetermined evaluation index; and determining the category corresponding to the preset commodity based on the grading interval to which the grade belongs.
In this embodiment, referring to fig. 2, classifying the preset product corresponding to the standard preset product information by using the ABC classification method includes:
firstly, taking the sales amount, gross profit amount, sales quantity and inventory amount in the sales information as evaluation indexes, respectively calculating A, B and C products of each index, wherein 70% of products before accumulation are A types, 70% -90% of products are B types, and 90% -100% of products are C types. For example, under the sales evaluation index, the determination that the "instant noodle" sales ranks 70% before is class a; the sale of the instant noodles is ranked 70% -90% and is determined as B class; the determination that the sales of the instant noodles are ranked 70% before is that the A category accumulates 90% -100% and is the C category. Specifically, for example, if the sales of 80g (standard) of the master kang (brand) braised beef in soy sauce instant noodles and 100g (standard) of the jin Mailang (brand) old jar pickled vegetable instant noodles are before 70%, 80g of the master kang braised beef in soy sauce instant noodles and 100g of the jin Mailang old jar pickled vegetable instant noodles are in class a under the "sales" index; the sales of the Kangshifu spicy noodle 100g and the unified stretched noodle 150g are between 70% and 90%, and then the Kangshifu spicy noodle 100g and the unified stretched noodle 150g are in class B under the index of sales. Similarly, 80g of Kangshifu braised beef instant noodles can be B under the index of gross profit amount, or B under the index of sales quantity, and C under the index of stock amount. The principle of determining the category of other preset commodities is the same.
Secondly, preset weight values and scores can be set for each evaluation index, and then the scores of various commodities under each index are determined. For example, the four items of index weight of the sales information are set to be 0.25 respectively, the A type is set to be 10 points, the B type is set to be 5 points, and the C type is set to be 1 point, and each item of score is multiplied by the corresponding weight to be added to obtain the comprehensive score. For example, the score of "Kangshifu braised beef instant noodle 80 g" under the sales index is 2.5 points, the score is 1.25 points under the "gross amount" index, the score is 1.25 points under the "sales number" index, and the score is 0.25 points under the "stock amount" index, so the score of Kangshifu braised beef instant noodle 80g "is 5.25 points.
Then, based on the scores of the determined preset commodities, the preset commodities with the scores above 7.5 are divided into a class A, and the class B is between 4.0 and 7.5; class C below class 4.0.
Step 104: and calculating the proportion of the quantity of the target commodities of each category by using a preset calculation method so as to judge whether the proportion meets the preset proportion.
In this embodiment, based on the preset commodities of each category obtained in step 103, the ratio of the number of the target commodities of each category is calculated by using a preset calculation method, if the ratio meets the preset ratio, the structure of the preset commodities in the preset store is reasonable, and if the ratio does not meet the preset ratio, the structure of the preset commodities in the preset store is unreasonable. Specifically, based on the preset commodities of each category obtained in step 103, whether the proportion of the ABC commodity item meets a preset proportion is calculated, for example, whether the proportion meets 10: 30: and 60, if the ratio is met, the structure of the preset commodity is reasonable, and if the ratio is not met, the structure of the preset commodity is unreasonable.
In the embodiment, the basic information of each preset commodity is standardized, the category of ABC corresponding to each preset commodity is determined based on the standardized basic information and the sales information of the preset commodity, and finally, the proportion of the number of the preset commodities in each category is determined to judge whether the proportion meets the preset proportion, so as to judge whether the commodity structure is reasonable.
As an optional implementation manner of this embodiment, the method further includes: if the proportion meets a preset proportion, acquiring the preset commodity price band information; verifying the price band information of each preset commodity to obtain whether the price band information of each preset commodity meets preset gear information or not; counting the number of the standard preset commodity information which simultaneously meets a preset proportion and preset gear information; and if the number is larger than a preset threshold value, determining the standard preset commodity information as comparison information.
In this embodiment, referring to fig. 3, after determining that the ratio satisfies the preset ratio based on step 104, obtaining main price band information of the preset product, where the main price band information of the preset product is determined based on the price band information, and the main price band information is a peak interval in a price band, that is, a price interval in which an item ratio is the highest in the SKU information of the product, for example, the price band interval of the preset product is [ 0-20 ], so that the main price band information may be [ 6-8 ], for example, the determination process of "convenience" in the third class as the price band information of the target product may include: firstly, dividing a price interval to obtain the highest price and the lowest price in the commodity in the subclass (under the third class), averagely dividing the price interval into 12 sections, wherein the interval is (maximum value-minimum value)/12, the expression of a single interval is (left interval, right interval), when the interval can be completely removed, the average price is divided, if the interval cannot be completely removed, an integer +1 is taken as an interval value, the interval value is divided into 12 sections from the minimum value according to the interval value, and after the price interval is divided, the price can be divided into three high/medium/low gears by adopting a clustering algorithm.
Specifically, after the main price band information is acquired, the main price band is verified, and when the main price band is in a middle/low gear, the main price band is determined to be verified. And then counting the number of the same three-level categories which simultaneously satisfy the rational structure and pass the price band verification, and if the number is greater than a preset threshold (for example, greater than 10), determining all the three-level category related data as market comparison, wherein the market comparison is used for providing comparison data for the target stores needing to diagnose the commodity structure so as to further realize further diagnosis of the commodities of the target stores.
As an optional implementation manner of this embodiment, the method further includes acquiring price band information of a preset commodity corresponding to the comparison information; acquiring price band information of a target commodity; and comparing the price band information of the preset commodity corresponding to the comparison information with the price band information of the target commodity to obtain a price band information comparison result.
In this embodiment, through price band comparison analysis, a management policy for a target product corresponding to a comparison result may be determined, so as to determine a lead-in or a drop-out policy based on the target product.
From the above description, it can be seen that the present disclosure achieves the following technical effects: the commodity category information which is good and reasonable in market operation can be selected, and then the data is used as comparison data, so that the precision of introducing new commodities or eliminating commodities can be further improved.
It should be noted that the steps illustrated in the flowcharts of the figures may be performed in a computer system such as a set of computer-executable instructions and that, although a logical order is illustrated in the flowcharts, in some cases, the steps illustrated or described may be performed in an order different than presented herein.
According to an embodiment of the present disclosure, there is also provided an apparatus for implementing the information processing method for retail product structure adjustment, as shown in fig. 4, the apparatus includes: a first obtaining unit 401, configured to obtain basic information of a preset commodity, where the basic information of the preset commodity includes first basic information of the preset commodity and second basic information of the preset commodity; the data cleaning unit 402 is used for standardizing the first basic information of the preset commodity based on a preset data cleaning rule to obtain standard preset commodity information; a classification unit 403, configured to perform primary and secondary classification on the preset product corresponding to the standard preset product information based on the second basic information of the preset product, so as to determine a category corresponding to each preset product; the calculating unit 404 calculates the ratio of the preset commodity quantity of each category by using a preset calculating method to determine whether the ratio satisfies a preset ratio.
As an optional implementation manner of this embodiment, the apparatus further includes: a second obtaining unit that obtains main price band information of the preset commodity if the ratio satisfies a preset ratio; the price band verification unit is used for verifying the main price band information of each preset commodity to obtain whether the main price band information of each preset commodity meets preset gear information or not; the counting unit is used for counting the number of the standard preset commodity information which simultaneously meets a preset proportion and preset gear information; and the determining unit is used for determining the standard preset commodity information as comparison information if the number is larger than a preset threshold value.
As an optional implementation manner of this embodiment, the apparatus further includes: a third obtaining unit, configured to obtain price band information of a preset commodity corresponding to the comparison information; a fourth obtaining unit that obtains price band information of the target commodity; and the comparison unit is used for comparing the price band information of the preset commodity corresponding to the comparison information with the price band information of the target commodity to obtain a price band information comparison result.
As an optional implementation manner of this embodiment, the first obtaining unit 401 includes: acquiring first basic information of a preset commodity, including acquiring preset commodity category information and name information of the preset commodity; and acquiring second basic information of the preset commodity, including acquiring sales data of the preset commodity.
As an optional implementation manner of this embodiment, the classifying unit 403 includes: determining second basic information of the preset commodities as evaluation indexes, and determining preset categories corresponding to the preset commodities under the evaluation indexes; calculating the grade of the preset commodity under the preset category by using the weight of the predetermined evaluation index; and determining the category corresponding to the preset commodity based on the grading interval to which the grade belongs.
The embodiment of the present disclosure also provides an electronic device, as shown in fig. 5, the electronic device includes one or more processors 51 and a memory 52, and one processor 53 is taken as an example in fig. 5.
The controller may further include: an input device 53 and an output device 54.
The processor 51, the memory 52, the input device 53 and the output device 54 may be connected by a bus or other means, and fig. 5 illustrates the connection by a bus as an example.
The processor 51 may be a Central Processing Unit (CPU). The processor 51 may also be other general purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or combinations thereof. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 52, which is a non-transitory computer readable storage medium, may be used to store non-transitory software programs, non-transitory computer executable programs, and modules, such as program instructions/modules corresponding to the control methods in the embodiments of the present disclosure. The processor 51 executes various functional applications of the server and data processing by running the non-transitory software programs, instructions and modules stored in the memory 52, that is, implements the information processing method for retail product structure adjustment of the above-described method embodiment.
The memory 52 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to use of a processing device operated by the server, and the like. Further, the memory 52 may include high speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, the memory 52 may optionally include memory located remotely from the processor 51, which may be connected to a network connection device via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The input device 53 may receive input numeric or character information and generate key signal inputs related to user settings and function control of the processing device of the server. The output device 54 may include a display device such as a display screen.
One or more modules are stored in the memory 52, which when executed by the one or more processors 51 perform the method as shown in fig. 1.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program to instruct related hardware, and the program can be stored in a computer readable storage medium, and when executed, the program can include the processes of the embodiments of the motor control methods described above. The storage medium may be a magnetic disk, an optical disk, a Read-only memory (ROM), a Random Access Memory (RAM), a flash memory (FlashMemory), a hard disk (hard disk drive, abbreviated as HDD) or a Solid State Drive (SSD), etc.; the storage medium may also comprise a combination of memories of the kind described above.
Although the embodiments of the present disclosure have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present disclosure, and such modifications and variations fall within the scope defined by the appended claims.
Claims (10)
1. An information processing method for retail merchandise structure adjustment, comprising:
acquiring basic information of a preset commodity, wherein the basic information of the preset commodity comprises first basic information of the preset commodity and second basic information of the preset commodity;
standardizing the first basic information of the preset commodity based on a preset data cleaning rule to obtain standard preset commodity information;
based on the second basic information of the preset commodities, performing primary and secondary classification on the preset commodities corresponding to the standard preset commodity information to determine the category corresponding to each preset commodity;
and calculating the proportion of the preset commodity quantity of each category by using a preset calculation method so as to judge whether the proportion meets the preset proportion.
2. The information processing method for retail merchandise structure adjustment according to claim 1, wherein after calculating the ratio of the preset merchandise amount of each category by using a preset calculation method to determine whether the ratio satisfies a preset ratio, the method further comprises:
if the proportion meets a preset proportion, acquiring main price belt information of the preset commodity;
verifying the main price belt information of each preset commodity to obtain whether the main price belt information of each preset commodity meets preset gear information or not;
counting the number of the standard preset commodity information which simultaneously meets a preset proportion and preset gear information;
and if the number is larger than a preset threshold value, determining the standard preset commodity information as comparison information.
3. The information processing method for retail merchandise structural adjustment according to claim 2, characterized in that the method further comprises:
acquiring price band information of a preset commodity corresponding to the comparison information;
acquiring price band information of a target commodity;
and comparing the price band information of the preset commodity corresponding to the comparison information with the price band information of the target commodity to obtain a price band information comparison result.
4. The information processing method for retail merchandise structure adjustment according to claim 1, wherein the acquiring preset merchandise basic information includes:
acquiring first basic information of a preset commodity, including acquiring preset commodity category information and name information of the preset commodity;
and acquiring second basic information of the preset commodity, including acquiring sales data of the preset commodity.
5. The retail product structure adjustment according to claim 1, wherein the primary and secondary classification of the preset product corresponding to the standard preset product information is performed based on second basic information of the preset product, and the determining of the category corresponding to each preset product includes:
determining second basic information of the preset commodities as evaluation indexes, and determining preset categories corresponding to the preset commodities under the evaluation indexes;
calculating the grade of the preset commodity under the preset category by using the weight of the predetermined evaluation index;
and determining the category corresponding to the preset commodity based on the grading interval to which the grade belongs.
6. An information processing apparatus for retail merchandise structure adjustment, comprising:
the system comprises a first acquisition unit, a second acquisition unit and a display unit, wherein the first acquisition unit is used for acquiring basic information of a preset commodity, and the basic information of the preset commodity comprises first basic information of the preset commodity and second basic information of the preset commodity;
the data cleaning unit is used for standardizing the first basic information of the preset commodity based on a preset data cleaning rule to obtain standard preset commodity information;
the classification unit is used for carrying out primary and secondary classification on the preset commodities corresponding to the standard preset commodity information based on the second basic information of the preset commodities so as to determine the corresponding classes of the preset commodities;
and the calculating unit is used for calculating the proportion of the preset commodity quantity of each category by using a preset calculating method so as to judge whether the proportion meets the preset proportion.
7. The information processing apparatus for retail merchandise structural adjustment of claim 1, wherein the apparatus further comprises:
a second obtaining unit that obtains main price band information of the preset commodity if the ratio satisfies a preset ratio;
the price band verification unit is used for verifying the main price band information of each preset commodity to obtain whether the main price band information of each preset commodity meets preset gear information or not;
the counting unit is used for counting the number of the standard preset commodity information which simultaneously meets a preset proportion and preset gear information;
and the determining unit is used for determining the standard preset commodity information as comparison information if the number is larger than a preset threshold value.
8. The information processing apparatus for retail merchandise structural adjustment of claim 7, wherein the apparatus further comprises:
a third obtaining unit, configured to obtain price band information of a preset commodity corresponding to the comparison information;
a fourth obtaining unit that obtains price band information of the target commodity;
and the comparison unit is used for comparing the price band information of the preset commodity corresponding to the comparison information with the price band information of the target commodity to obtain a price band information comparison result.
9. The information processing apparatus for retail merchandise structure adjustment according to claim 6, characterized in that the first acquisition unit includes:
acquiring first basic information of a preset commodity, including acquiring preset commodity category information and name information of the preset commodity;
and acquiring second basic information of the preset commodity, including acquiring sales data of the preset commodity.
10. The apparatus for retail merchandise structure adjustment information processing according to claim 6, wherein the classification unit includes:
determining second basic information of the preset commodities as evaluation indexes, and determining preset categories corresponding to the preset commodities under the evaluation indexes;
calculating the grade of the preset commodity under the preset category by using the weight of the predetermined evaluation index;
and determining the category corresponding to the preset commodity based on the grading interval to which the grade belongs.
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