CN115936819A - Commodity scoring system and establishment method - Google Patents
Commodity scoring system and establishment method Download PDFInfo
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- CN115936819A CN115936819A CN202310004189.0A CN202310004189A CN115936819A CN 115936819 A CN115936819 A CN 115936819A CN 202310004189 A CN202310004189 A CN 202310004189A CN 115936819 A CN115936819 A CN 115936819A
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Abstract
The invention discloses a commodity scoring system and an establishing method thereof, relating to the technical field of electronic commerce and comprising a commodity historical sales performance scoring module, a commodity current health degree scoring module and a commodity quality grading module. The establishing method comprises the following steps: establishing a comprehensive scoring module, establishing an analysis model required by the comprehensive scoring module, and performing data fusion analysis processing. After the system grades and scores massive commodities, commodity operators of E-commerce can conveniently carry out differentiated operation and management on the commodities according to needs, and the overstocked commodities are reduced by reducing the pressure or price of the overstocked commodities so as to reduce the overstocked inventory and the like, so that the efficiency problem of quickly screening the commodities from the massive commodities is solved for the operators, the problems of how to stock and how to stock the commodities with money explosion and good sale are solved, and the accurate operation and management level of the commodities and the inventory is improved.
Description
Technical Field
The invention relates to the technical field of electronic commerce, in particular to a commodity scoring system and an establishment method.
Background
Electronic commerce refers to transaction activities and related service activities in an electronic transaction mode on the internet, an intranet and a value-added network, and is also electronization and networking of all links of the traditional commercial activities. With the improvement of quality of life and the continuous progress of science and technology, electronic commerce has become an indispensable part of life, and therefore, the development of the back-end system of electronic commerce is continuously perfected.
At present, in the field of electronic commerce, commodity scoring and grading algorithms are relatively single, most commodities are evaluated based on historical data of the commodities, the current health degree of the commodities, some event-driven factors in the future and the like are not considered, the commodities are sold by a supplier generally, namely, a supply decision demand mode, and therefore the commodities cannot be accurately positioned, unnecessary loss is influenced, and operation and management of inventory are difficult, so that a commodity scoring system and a commodity scoring establishing method are provided, and the problems are solved.
Disclosure of Invention
The invention aims to provide a commodity scoring system and an establishment method thereof, so as to solve any problem provided by the background technology.
In order to achieve the purpose, the invention provides the following technical scheme: a merchandise scoring system, comprising:
the commodity historical sales performance grading module is used for introducing data capable of influencing sales performance and analyzing the data;
the system comprises a commodity current health degree scoring module, a commodity current health degree scoring module and a control module, wherein the commodity current health degree scoring module judges the health degree of a current commodity by calling basic information of the commodity current and gives data;
the commodity quality grading module is used for grading commodities by calling negative data and combining an algorithm;
and the data obtained by the commodity historical sales performance scoring module, the commodity current health degree scoring module and the commodity quality grading module are unified, merged and fused to obtain the current data condition of the commodity.
Preferably, the product historical sales performance scoring module includes:
the item price grading model is used for calling historical prices and dividing the historical prices according to respective item price intervals in proportion;
and the commodity historical sales expression scoring model is used for calling the user purchase interest and the sales data of the commodity through a commodity heat attribute model and a user interest time model to carry out comprehensive fusion processing.
Preferably, the new commodities which are not obtained by the item price grading model and the commodity historical sales expression grading model are subjected to cold starting through weighting processing.
Preferably, the current health degree scoring module for the commodity comprises:
the seasonal judging model is used for carrying out fusion analysis processing on the seasonal attribute of the commodity basic information and the current season to judge;
the commodity inventory model is used for carrying out fusion analysis processing on the data extracted from the inventory data and the data obtained from the forecast sales volume model;
the discount strength comparison model is used for carrying out comparison analysis by extracting the current commodity price and the historical selling price;
and merging and fusing the data analyzed and judged by the season judging model, the commodity inventory model and the commodity inventory model.
Preferably, the negative data called by the commodity quality grading module comprise commodity historical poor evaluation quantity, commodity complaint data, commodity quantity changed due to quality reasons and commodity quantity returned due to quality reasons, and negative scoring is performed to reduce the weight of the commodity
A method for establishing a commodity scoring system sequentially comprises the following steps:
s1, establishing a comprehensive grading module, namely establishing three module frames of a commodity historical sales performance grading module, a commodity current health degree grading module and a commodity quality grading module respectively;
s2, establishing an analysis model required by the comprehensive grading module, and respectively establishing data extraction models required by three module frames of the commodity historical sales performance grading module, the commodity current health degree grading module and the commodity quality grading module which are established in the S1;
and S3, data fusion analysis processing, namely fusing, comparing and analyzing the data through the data extraction model established in the S2, and collecting the data into a corresponding module, wherein the commodity historical sales performance scoring module, the commodity current health degree scoring module and the commodity quality grading module push the fused data into the system.
Preferably, the model required by the commodity historical sales expression scoring module in the S2 is a product price grading model and a commodity historical sales expression scoring model;
the item price grading model is divided according to commodity proportion by extracting item price intervals in the database;
the commodity historical sales expression scoring model comprehensively scores commodity historical sales volume, number of users purchased, province coverage and time effect obtained by combining the commodity heat attribute model and the user interest time model, and the scoring formula is as follows:
the commodity heat attribute model is used for carrying out related empowerment according to the importance of different factors by introducing related factors such as influence factors of commodity historical sales, sales volume, number of purchased users, provincial coverage and the like. The scoring formula is as follows: y is 1 ＝w 0 +w 1 x 1 +w 2 x 2 +…w n x n
y1 is the product hot sales attribute score, w1, w2, wn and the like are different influence factor weights, and x1, x2 and x3 represent different influence factor data variables.
And the user interest time model introduces a time attenuation function to process the score. The attenuation function is formulated as follows:
ni (T) is the recent popularity of item i, a is the attenuation coefficient, T is the current time, T is the time when the user behavior occurred.
And weighting the new products without historical data, thereby solving the problem of cold start of the commodities. And finally scoring according to the hot sales attributes of the commodities, and setting a threshold value to realize grading of explosive money, good sales, flat sales and late sales of the commodities.
Preferably, the models required by the current health degree scoring module of the commodities in the S2 are a season judgment model, a commodity inventory model and a preference degree comparison model;
the season judging model extracts the seasonal attribute of the commodity basic information from the database, if the supplier does not input the seasonal attribute of the commodity when inputting the commodity basic information, the seasonal attribute model marks the corresponding seasonal attribute for the commodity according to the sale distribution condition of the commodity in four seasons, then the comparison is carried out according to the sale time of the commodity, if the current time is matched with the seasonal attribute of the commodity, a season-corresponding label is marked, otherwise, an anti-season label is marked, when the commodity is sold in the current season or in the future season, the weighting is given when the commodity is graded, otherwise, the right-reducing treatment is carried out;
the commodity inventory model predicts the sales volume of a commodity at a future time through the predicted sales volume model, and performs comparison calculation by combining the residual inventory number to calculate the inventory days of the commodity, when the inventory days are less than or equal to the safety inventory days set by the service, the inventory state is unhealthy, the inventory needs to be supplemented, otherwise, the inventory is healthy; the size health of the residual inventory quantity is based on the historical sales distribution of each size of the commodity, the mainstream size of the commodity is calculated, and then whether the mainstream size is complete or not is judged by combining the inventory of the mainstream size. When the stock and the size are unhealthy, if the mainstream size of the commodity is insufficient, certain negative weight reduction processing is given when the commodity is scored or the sales volume is predicted;
the preferential strength comparison model is used for carrying out comparative analysis by extracting the current commodity price and the historical sale price, and carrying out weighting processing if the current commodity price is superior, otherwise, carrying out weight reduction processing.
Preferably, the model required by the commodity quality grading module in the S2 is a negative data model;
the negative data model extracts the historical poor evaluation quantity, commodity complaint data, commodity quantity change due to quality reasons and quantity return data due to quality reasons of the commodities to carry out negative scoring, and carries out weight reduction processing on the commodities, wherein the scoring formula is as follows: y is 2 ＝-(w 0 +w 1 x 1 +w 2 x 2 +…w n x n )。
Wherein y1 is the commodity quality score, w1, w2, wn and the like are different influence factor weights, and x1, x2 and x3 represent different influence factor data variables.
Compared with the prior art, the invention has the beneficial effects that:
the invention shows through the historical sales of the goods, such as: sales amount, daily average sales, conversion rate and the like, and the health degree of the commodity under the current conditions, such as: whether the commodity should be used in season or not, whether the stock is healthy or not, whether the size is complete or not, the price (activity) strength and the commodity quality are shown as follows: the system is characterized in that a user reviews conditions, returns and exchanges goods and the like, comprehensively scores commodities according to a series of data in an all-round mode, corresponding grade labels such as money explosion, good sales, low sales, late sales and the like are marked on the commodities based on scoring results, and after massive commodities are graded and scored through the system, commodity operators of e-commerce can conveniently carry out differentiated operation and management on the commodities as required: more flow, stock and the like are provided for the exploded and mass-market commodities, the overstocked inventory is reduced by descending and suppressing or reducing the price of the unsalable commodities, and further, the future sales volume of the commodities can be predicted based on the algorithm, so that the efficiency problem of quickly screening the commodities from a large quantity of commodities is solved for operators, the problem of how to stock and how to stock the exploded and mass-market commodities is solved, and the accurate operation and management level of the commodities and the inventory is improved.
Drawings
FIG. 1 is a schematic flow chart of a merchandise scoring system according to the present invention;
FIG. 2 is a schematic flow chart of a product historical sales performance scoring module of the product scoring system according to the present invention;
FIG. 3 is a schematic flow chart of a commodity current health rating module of the commodity rating system according to the present invention;
fig. 4 is a schematic diagram of a commodity quality grading module of the commodity grading system according to the invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, belong to the protection scope of the present invention.
Referring to fig. 1-4, the present invention provides a technical solution: a merchandise scoring system, comprising:
the commodity historical sales performance grading module is used for introducing data which can influence the sales performance and analyzing the data;
the module for scoring the historical sales performance of the commodity comprises:
the item price grading model is used for calling historical prices and dividing the historical prices according to respective item price intervals in proportion;
and the commodity historical sales expression scoring model is used for calling the user purchase interest and the sales data of the commodity through a commodity heat attribute model and a user interest time model to carry out comprehensive fusion processing.
And solving cold start of the new commodities which cannot be obtained by the item price grading model and the commodity historical sales performance grading model through weighting processing.
The system comprises a commodity current health degree scoring module, a commodity current health degree scoring module and a control module, wherein the commodity current health degree scoring module judges the health degree of a current commodity by calling basic information of the commodity current and gives data;
the commodity current health degree grading module comprises:
the seasonal judging model is used for carrying out fusion analysis processing on the seasonal attribute of the commodity basic information and the current season to judge;
the commodity inventory model is used for carrying out fusion analysis processing on the data extracted from the inventory data and the data obtained from the forecast sales volume model;
the discount strength comparison model is used for carrying out comparison analysis by extracting the current commodity price and the historical selling price;
and merging and fusing the data analyzed and judged by the season judging model, the commodity inventory model and the commodity inventory model.
The commodity quality grading module is used for grading commodities by calling negative data and combining an algorithm;
the commodity quality grading module carries out negative grading on commodities by calling negative data including commodity historical poor evaluation quantity, commodity complaint data, commodity quantity change due to quality reasons and commodity quantity withdrawal due to quality reasons, and carries out right-reducing treatment on the commodities.
And the data obtained by the commodity historical sales performance scoring module, the commodity current health degree scoring module and the commodity quality grading module are unified, merged and fused to obtain the current data condition of the commodity.
Referring to fig. 1-4, the present invention provides a technical solution: a method for establishing a commodity scoring system sequentially comprises the following steps:
s1, establishing a comprehensive grading module, namely establishing three module frames of a commodity historical sales performance grading module, a commodity current health degree grading module and a commodity quality grading module respectively;
s2, establishing an analysis model required by the comprehensive grading module, and respectively establishing data extraction models required by three module frames of the commodity historical sales performance grading module, the commodity current health degree grading module and the commodity quality grading module which are established in the S1;
the model required by the commodity historical sales expression scoring module is a product price grading model and a commodity historical sales expression scoring model;
the item price grading model is used for extracting item price intervals in the database and dividing the item price intervals according to commodity proportions;
the commodity historical sales expression scoring model comprehensively scores commodity historical sales volume, number of users purchased, province coverage and time effect obtained by combining the commodity heat attribute model and the user interest time model, and the scoring formula is as follows:
the commodity heat degree attribute model is used for carrying out related empowerment according to the importance of different factors by introducing related factors such as influence factors of commodity historical sales, number of purchased users, province coverage and the like. The scoring formula is as follows: y is 1 ＝w 0 +w 1 x 1 +w 2 x 2 +…w n x n
y1 is the product hot sales attribute score, w1, w2, wn and the like are different influence factor weights, and x1, x2 and x3 represent different influence factor data variables.
And the user interest time model introduces a time attenuation function to process the score. The attenuation function is formulated as follows:
ni (T) is the recent popularity of item i, a is the attenuation coefficient, T is the current time, T is the time when the user behavior occurred.
And weighting the new products without historical data, thereby solving the problem of cold start of the commodities. And finally scoring according to the hot sale attribute of the commodity, and setting a threshold value to realize grading of explosive money, good sale, flat sale and late sale of the commodity.
The models required by the current commodity health degree grading module are a season judgment model, a commodity inventory model and a preference comparison model;
the season judging model extracts the seasonal attribute of the commodity basic information from the database, if the supplier does not input the seasonal attribute of the commodity when inputting the commodity basic information, the seasonal attribute model marks the corresponding seasonal attribute for the commodity according to the sale distribution condition of the commodity in four seasons, then the comparison is carried out according to the sale time of the commodity, if the current time is matched with the seasonal attribute of the commodity, a season-corresponding label is marked, otherwise, an anti-season label is marked, when the commodity is sold in the current season or in the future season, the weighting is given when the commodity is graded, otherwise, the right-reducing treatment is carried out;
the commodity inventory model predicts the sales volume of a commodity at a future time through the predicted sales volume model, and performs comparison calculation by combining the residual inventory number to calculate the inventory days of the commodity, when the inventory days are less than or equal to the safety inventory days set by the service, the inventory state is unhealthy, the inventory needs to be supplemented, otherwise, the inventory is healthy; the size health of the residual inventory quantity is based on the historical sales distribution of each size of the commodity, the mainstream size of the commodity is calculated, and then whether the mainstream size is complete or not is judged by combining the inventory of the mainstream size. When the stock and the size are unhealthy, if the mainstream size of the commodity is insufficient, certain negative weight reduction processing is given when the commodity is scored or the sales volume is predicted;
the preferential strength comparison model carries out comparison analysis by extracting the current commodity price and the historical sale price, and carries out weighting processing if the current commodity price is superior, otherwise, carries out weight reduction processing.
The model required by the commodity quality grading module is a negative data model;
the negative data model extracts the historical poor evaluation quantity, commodity complaint data, commodity quantity due to quality change and quantity due to quality return of the commodity for negative scoring, and carries out weight reduction processing on the commodity, wherein the scoring formula is as follows: y is 2 ＝-(w 0 +w 1 x 1 +w 2 x 2 +…w n x n )。
Wherein y1 is the commodity quality score, w1, w2, wn and the like are different influence factor weights, and x1, x2 and x3 represent different influence factor data variables.
And S3, data fusion analysis processing, namely fusing, comparing, analyzing and processing the data through the data extraction model established in the S2, and then collecting the data into a corresponding module, wherein the commodity historical sales performance scoring module, the commodity current health degree scoring module and the commodity quality grading module push the fused data into the system.
Those not described in detail in this specification are well within the skill of the art.
Although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that various changes in the embodiments and/or modifications of the invention can be made, and equivalents and modifications of some features of the invention can be made without departing from the spirit and scope of the invention.
Claims (9)
1. A merchandise scoring system, comprising:
the commodity historical sales performance grading module is used for introducing data capable of influencing sales performance and analyzing the data;
the system comprises a commodity current health degree scoring module, a commodity current health degree scoring module and a control module, wherein the commodity current health degree scoring module judges the health degree of a current commodity by calling basic information of the commodity current and gives data;
the commodity quality grading module is used for grading commodities by calling negative data and combining an algorithm;
and the data obtained by the commodity historical sales performance scoring module, the commodity current health degree scoring module and the commodity quality grading module are unified, merged and fused to obtain the current data condition of the commodity.
2. A merchandise scoring system according to claim 1, wherein: the commodity historical sales performance scoring module comprises:
the item price grading model is used for calling historical prices and dividing the historical prices according to respective item price intervals in proportion;
and the commodity historical sales expression scoring model is used for calling the user purchase interest and the sales data of the commodity through a commodity heat attribute model and a user interest time model to carry out comprehensive fusion processing.
3. A product scoring system as claimed in claim 2, wherein: and solving cold start of the new commodities which cannot be obtained by the item price grading model and the commodity historical sales performance grading model through weighting processing.
4. A merchandise scoring system according to claim 1, wherein: the commodity current health degree scoring module comprises:
the seasonal judging model is used for carrying out fusion analysis processing on the seasonal attribute of the commodity basic information and the current season to judge;
the commodity inventory model is processed by extracting inventory data and fusing and analyzing the inventory data and the data obtained by the forecast sales volume model;
the discount strength comparison model is used for carrying out comparison analysis by extracting the current commodity price and the historical selling price;
and merging and fusing the data analyzed and judged by the season judging model, the commodity inventory model and the commodity inventory model.
5. A merchandise scoring system according to claim 1, wherein: the commodity quality grading module carries out negative scoring and commodity right reducing treatment through the called negative data including commodity historical poor evaluation quantity, commodity complaint data, commodity quantity change due to quality reasons and commodity quantity returning due to quality reasons.
6. A method for establishing a commodity scoring system is characterized by comprising the following steps: sequentially comprises the following steps:
s1, establishing a comprehensive grading module, namely establishing three module frames of a commodity historical sales performance grading module, a commodity current health degree grading module and a commodity quality grading module respectively;
s2, establishing an analysis model required by the comprehensive grading module, and respectively establishing data extraction models required by three module frames of the commodity historical sales performance grading module, the commodity current health degree grading module and the commodity quality grading module which are established in the S1;
and S3, data fusion analysis processing, namely fusing, comparing and analyzing the data through the data extraction model established in the S2, and collecting the data into a corresponding module, wherein the commodity historical sales performance scoring module, the commodity current health degree scoring module and the commodity quality grading module push the fused data into the system.
7. The system and method of claim 1, wherein the system comprises: the model required by the commodity historical sales expression scoring module in the S2 is a commodity price grading model and a commodity historical sales expression scoring model;
the item price grading model is divided according to commodity proportion by extracting item price intervals in the database;
the commodity historical sales expression scoring model comprehensively scores commodity historical sales volume, number of users purchased, province coverage and time effect obtained by combining the commodity heat attribute model and the user interest time model, and the scoring formula is as follows:
and weighting the new products without historical data, thereby solving the problem of cold start of the commodities. And finally scoring according to the hot sale attribute of the commodity, and setting a threshold value to realize grading of explosive money, good sale, flat sale and late sale of the commodity.
8. The method for establishing a commodity scoring system according to claim 1, wherein: s2, models required by the commodity current health degree grading module are a season judgment model, a commodity inventory model and a preference comparison model;
the season judging model extracts the seasonal attribute of the commodity basic information from the database, if the supplier does not input the seasonal attribute of the commodity when inputting the commodity basic information, the seasonal attribute model marks the corresponding seasonal attribute for the commodity according to the sale distribution condition of the commodity in four seasons, then the comparison is carried out according to the sale time of the commodity, if the current time is matched with the seasonal attribute of the commodity, a season-corresponding label is marked, otherwise, an anti-season label is marked, when the commodity is sold in the current season or in the future season, the weighting is given when the commodity is graded, otherwise, the right-reducing treatment is carried out;
the commodity inventory model predicts the sales volume of a commodity at a future time through the predicted sales volume model, and performs comparison calculation by combining the residual inventory number to calculate the inventory days of the commodity, when the inventory days are less than or equal to the safety inventory days set by the service, the inventory state is unhealthy, the inventory needs to be supplemented, otherwise, the inventory is healthy; the size health of the residual inventory quantity is based on the historical sales distribution of each size of the commodity, the mainstream size of the commodity is calculated, and then whether the mainstream size is complete or not is judged by combining the inventory of the mainstream size. When the stock and the size are unhealthy, if the mainstream size of the commodity is insufficient, certain negative weight reduction processing is given when the commodity is scored or the sales volume is predicted;
the preferential strength comparison model carries out comparison analysis by extracting the current commodity price and the historical sale price, and carries out weighting processing if the current commodity price is superior, otherwise, carries out weight reduction processing.
9. The system and method of claim 1, wherein the system comprises:
s2, a model required by the commodity quality grading module is a negative data model;
extracting historical bad evaluation quantity of commodity by negative data modelThe commodity complaint data, the commodity quantity of changing goods due to quality reasons and the quantity of returning goods due to quality reasons are negatively scored, the commodity is subjected to weight reduction treatment, and the scoring formula is as follows: y is 2 ＝-(w 0 +w 1 x 1 +w 2 x 2 +…w n x n )。
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| CN116579634A (en) * | 2023-07-14 | 2023-08-11 | 深圳市科脉技术股份有限公司 | Store operation intelligent decision method and system based on big data |
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