A system and method for optimizing the output of multi-commodity sorting

Abstract

The present invention provides a system and method for optimizing the output of multi-product sorting. The output system includes a data collection module, a database module, a processing module, and an output module. The data collection module is used to collect output-related data of products in normal ordering transactions. The database module is used to mark and store the collected data. The processing module is used to create sorting attributes for products. The output module is used to output products according to the sorting attributes. The output-related data collected by the collection module includes user stay time, supplier success rate, supplier complaint rate, supplier abnormal order incidence rate, interface response rate, and delivery and account arrival rate. The present invention can sort the output products according to the transaction data of the products to solve the problems of uneven output of existing product marketing and poor user experience.

Description

Technical Field

[0001] The present invention relates to the technical field of commodity marketing systems, and in particular to a system and method for optimizing the sorting and output of multiple commodities. Background Art

[0002] Marketing ecological platform: An integrated B&C terminal, a comprehensive mall marketing platform created by integrating diverse activity templates and integrating payment and points capabilities. The commodities output by the platform include physical objects, virtual direct recharge, virtual card numbers, etc.

[0003] However, the timeliness, content variability, and non-exclusivity of current Internet virtual commodities make the output of virtual commodities by suppliers vary, and the output timeliness also varies greatly. In the face of the diverse needs of users and such a complex supplier market, the platform will face a complex and uncontrollable choice of commodity supply output. Summary of the Invention

[0004] Aiming at the deficiencies of the existing technology, the purpose of the present invention is to provide a system and method for optimizing the sorting and output of multiple commodities, which can sort the output commodities according to the transaction data of the commodities, so as to solve the problems of uneven output of existing commodity marketing and poor user experience.

[0005] To achieve the above purpose, the present invention is realized through the following technical solutions: A sorting optimization output system for multiple commodities, the output system includes a data collection module, a database module, a processing module, and an output module;

[0006] The data collection module is used to collect output-related data of commodities in normal ordering transactions; the database module is used to mark and store the collected data; the processing module is used to create sorting attributes for commodities; the output module is used to output commodities according to the sorting attributes;

[0007] The output-related data collected by the collection module includes user stay time, supplier success rate, supplier complaint rate, supplier abnormal order incidence rate, interface response rate, and delivery and account arrival rate;

[0008] The database module is used to store the output-related data of the commodity corresponding to the commodity after collection; the database module also includes basic commodity sorting data; the basic commodity sorting data includes: total supplier success rate, price of this commodity of the supplier, supplier level, and supplier weight;

[0009] The processing module includes a first configuration unit and a second configuration unit; the first configuration unit is used to manually create the attributes of commodities; the second configuration unit is used to create sorting attributes according to the data stored in the database module;

[0010] The output module includes a basic output unit, an analysis output unit, and a replenishment output unit. The basic output unit is used to output products according to preset sorting data; the analysis output unit is used to perform sorting and output after processing according to the user types of the products; the replenishment output unit is used to continue to push products after the user does not perform a selection behavior.

[0011] Further, the first configuration unit is configured with a first configuration strategy, and the first configuration strategy includes: bringing the supplier success rate, supplier complaint rate, supplier abnormal order incidence rate, interface response rate, total supplier success rate, and the price of this product of the supplier into a first algorithm, and assigning a supplier weight to calculate the grade value of the supplier;

[0012] When the grade value of the supplier is greater than or equal to the first grade threshold, the grade of the supplier is set as the first grade; when the grade value of the supplier is less than the first grade threshold and greater than or equal to the second grade threshold, the grade of the supplier is set as the second grade; when the grade value of the supplier is less than the second grade threshold and greater than or equal to the third grade threshold, the grade of the supplier is set as the third grade; when the grade value of the supplier is less than the third grade threshold and greater than or equal to the fourth grade threshold, the grade of the supplier is set as the fourth grade; when the grade value of the supplier is less than the fourth grade threshold, the grade of the supplier is set as the fifth grade.

[0013] Further, the first algorithm is configured as:

[0014] P d = α(k 1 G c + k 2 G ts + k 3 G yc + k 4 J y + k 5 G zc + k 6 G j )), where Pd is the grade value of the supplier, α is the supplier weight, Gc is the supplier success rate, Gts is the supplier complaint rate, Gyc is the supplier abnormal order incidence rate, Jy is the interface response rate, Gzc is the total supplier success rate, and Gj is the price of this product of the supplier.

[0015] Further, the second configuration unit is configured with a second configuration strategy, and the second configuration strategy includes: sequentially obtaining the user stay time, supplier complaint rate, supplier abnormal order incidence rate, interface response rate, delivery and account arrival rate, total supplier success rate, and the price of this product of the top three suppliers in terms of success rate for different types of products;

[0016] Respectively add and subtract the first residence time from the residence times of the top three users to obtain the first residence range, the second residence range, and the third residence range;

[0017] Respectively add and subtract the first complaint value from the complaint rates of the top three suppliers to obtain the first complaint range, the second complaint range, and the third complaint range;

[0018] Respectively add and subtract the first anomaly value from the incidence rates of abnormal orders of the top three suppliers to obtain the first anomaly range, the second anomaly range, and the third anomaly range;

[0019] Respectively add and subtract the first response value from the interface response rates of the top three to obtain the first response range, the second response range, and the third response range;

[0020] Respectively add and subtract the first delivery value from the delivery-to-account rates of the top three to obtain the first delivery-to-account range, the second delivery-to-account range, and the third delivery-to-account range;

[0021] Respectively add and subtract the first success value from the total success rates of the top three suppliers to obtain the first success range, the second success range, and the third success range;

[0022] Respectively add and subtract the first price from the prices of this commodity of the top three suppliers to obtain the first price range, the second price range, and the third price range.

[0023] Furthermore, the basic output unit is configured with a basic output strategy, and the basic output strategy includes: sorting the obtained levels of the suppliers from the first level to the fifth level, and then outputting the commodities according to the sorting order.

[0024] Furthermore, the analysis output unit is configured with an analysis output strategy, and the analysis output strategy includes: sorting and classifying this type of commodity according to the residence times of the top three users, the complaint rates of the suppliers, the incidence rates of abnormal orders of the suppliers, the interface response rates, the delivery-to-account rates, the total success rates of the suppliers, and the prices of this commodity of the suppliers. The user selects a sorting type according to the sorting classification, and outputs the sorting of this type of commodity according to the user's sorting classification selection.

[0025] Furthermore, the replenishment output unit is configured with a replenishment output strategy, and the replenishment output strategy includes: sorting the types of the sorting classification, obtaining the residence time of the first sorting push. When the residence time exceeds the first time threshold, perform sequential sorting pushes according to the re-sorting of the sorting classification.

[0026] A method for a sorting optimization output system for multiple commodities, the method comprising the following steps:

[0027] Step S1, collect output-related data of the product in a normal ordering transaction; the output-related data includes user stay time, supplier success rate, supplier complaint rate, supplier abnormal order incidence rate, interface response rate, and delivery and account arrival rate;

[0028] Step S2, store the collected output-related data of the product after corresponding it to the product; and pre-store the basic product sorting data; the basic product sorting data includes: total supplier success rate, price of this product of the supplier, supplier level, and supplier weight;

[0029] Step S3, create sorting attributes for the product; creating sorting attributes includes: manually creating product attributes and creating sorting attributes according to the data stored in the database module;

[0030] Step S4, output the product according to the preset sorting data; perform sorting and output after processing according to the user type of the product; continue to push products after the user does not make a selection.

[0031] Further, step S3 further includes step A1, and step A1 includes: substituting the supplier success rate, supplier complaint rate, supplier abnormal order incidence rate, interface response rate, total supplier success rate, and price of this product of the supplier into the first algorithm, and assigning a supplier weight to calculate the level value of the supplier;

[0032] When the level value of the supplier is greater than or equal to the first level threshold, set the level of the supplier as the first level; when the level value of the supplier is less than the first level threshold and greater than or equal to the second level threshold, set the level of the supplier as the second level; when the level value of the supplier is less than the second level threshold and greater than or equal to the third level threshold, set the level of the supplier as the third level; when the level value of the supplier is less than the third level threshold and greater than or equal to the fourth level threshold, set the level of the supplier as the fourth level; when the level value of the supplier is less than the fourth level threshold, set the level of the supplier as the fifth level;

[0033] Successively obtain the user stay time, supplier complaint rate, supplier abnormal order incidence rate, interface response rate, delivery and account arrival rate, total supplier success rate, and price of this product of the supplier with the top three supplier success rates for different types of products.

[0034] Further, step S4 further includes step B1, and step B1 includes: sort the obtained suppliers' levels from the first level to the fifth level, and then output the products according to the sorting order;

[0035] Sort and classify this type of product according to the top three user stay times, supplier complaint rates, supplier abnormal order incidence rates, interface response rates, delivery and account arrival rates, total supplier success rates, and supplier prices for this product. The user selects a sorting type based on the sorting classification, and the sorted output of this type of product is selected according to the user's sorting classification.

[0036] Sort the types of sorting classifications, obtain the user stay time pushed in the first sorting. When the user stay time exceeds the first time threshold, perform one-by-one sorting and pushing according to the re-sorting of the sorting classification.

[0037] Advantages of the present invention: By collecting output-related data of products in normal ordering transactions, storing the collected output-related data corresponding to the products after marking, creating sorting attributes for the products; outputting the products according to the preset sorting data; performing sorting and output after processing according to the user types of the products; continuing to push products after the user has no selection behavior; through personalized product attribute configuration and relevant data analysis, the success rate of product ordering can be greatly improved. It also has absolute control over suppliers, and can specify the output of products of a certain specific supplier, solving some problems caused by numerous and inconsistent suppliers. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Other features, objects, and advantages of the present invention will become more apparent by reading the detailed description of the non-limiting embodiments with reference to the following drawings:

[0039] Figure 1 It is a principle block diagram of the present invention;

[0040] Figure 2 It is a method flow chart of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0041] To make the technical means, creative features, achieved purposes, and functions of the present invention easy to understand, the present invention will be further described below in conjunction with specific embodiments.

[0042] Please refer to Figure 1 , a sorting optimization output system for multiple products, the output system includes a data collection module, a database module, a processing module, and an output module;

[0043] The data collection module is used to collect output-related data of products in normal ordering transactions; the database module is used to mark and store the collected data; the processing module is used to create sorting attributes for products; the output module is used to output products according to the sorting attributes;

[0044] The output-related data collected by the collection module includes user stay time, supplier success rate, supplier complaint rate, supplier abnormal order incidence rate, interface response rate, and delivery and account arrival rate;

[0045] The database module is used to store the output-related data collected for the product after corresponding it to the product; the database module also includes basic product sorting data; the basic product sorting data includes: total supplier success rate, supplier price for this product, supplier level, and supplier weight;

[0046] The processing module includes a first configuration unit and a second configuration unit; the first configuration unit is used to manually create the attributes of the product; the second configuration unit is used to create sorting attributes according to the data stored in the database module;

[0047] The output module includes a basic output unit, an analysis output unit, and a replenishment output unit. The basic output unit is used to output the product according to the preset sorting data; the analysis output unit is used to process and sort and output according to the user type of the product; the replenishment output unit is used to continue to push products after the user does not perform a selection behavior.

[0048] The first configuration unit is configured with a first configuration strategy, and the first configuration strategy includes: by bringing the supplier success rate, supplier complaint rate, supplier abnormal order incidence rate, interface response rate, total supplier success rate, and supplier price for this product into the first algorithm, and assigning a supplier weight to calculate the level value of the supplier;

[0049] When the level value of the supplier is greater than or equal to the first level threshold, the level of the supplier is set as the first level; when the level value of the supplier is less than the first level threshold and greater than or equal to the second level threshold, the level of the supplier is set as the second level; when the level value of the supplier is less than the second level threshold and greater than or equal to the third level threshold, the level of the supplier is set as the third level; when the level value of the supplier is less than the third level threshold and greater than or equal to the fourth level threshold, the level of the supplier is set as the fourth level; when the level value of the supplier is less than the fourth level threshold, the level of the supplier is set as the fifth level.

[0050] The first algorithm is configured as: P d =α(k 1 G c +k 2 G ts +k 3 G yc +k 4 J y +k 5 G zc +k 6G j ) where Pd is the grade value of the supplier, α is the supplier weight, Gc is the supplier success rate, Gts is the supplier complaint rate, Gyc is the incidence rate of abnormal orders of the supplier, Jy is the interface response rate, Gzc is the total success rate of the supplier, and Gj is the price of this commodity of the supplier.

[0051] The second configuration unit is configured with a second configuration strategy, and the second configuration strategy includes: sequentially obtaining the user stay time, supplier complaint rate, incidence rate of abnormal orders of the supplier, interface response rate, delivery and account arrival rate, total success rate of the supplier, and the price of this commodity of the supplier for the top three in the success rate ranking of suppliers of different types of commodities; this design conducts separate sorting for different types based on the final success rate of the commodity, can more accurately analyze the factors for the final transaction of the commodity, and outputs more conducive to the transaction of the commodity according to the sorting of the transaction factors.

[0052] Add and subtract the first stay time from the top three in the user stay time ranking to obtain the first stay range, the second stay range, and the third stay range respectively;

[0053] Add and subtract the first complaint value from the top three in the supplier complaint rate ranking to obtain the first complaint range, the second complaint range, and the third complaint range respectively;

[0054] Add and subtract the first abnormal value from the top three in the incidence rate of abnormal orders of the supplier to obtain the first abnormal range, the second abnormal range, and the third abnormal range respectively;

[0055] Add and subtract the first corresponding value from the top three in the interface response rate to obtain the first response range, the second response range, and the third response range respectively;

[0056] Add and subtract the first delivery value from the top three in the delivery and account arrival rate to obtain the first delivery and account arrival range, the second delivery and account arrival range, and the third delivery and account arrival range respectively;

[0057] Add and subtract the first success value from the top three in the total success rate of the supplier to obtain the first success range, the second success range, and the third success range respectively;

[0058] Add and subtract the first price from the top three in the price of this commodity of the supplier to obtain the first price range, the second price range, and the third price range respectively.

[0059] The basic output unit is configured with a basic output strategy, and the basic output strategy includes: sorting according to the obtained grades of the suppliers from the first grade to the fifth grade, and then outputting the commodities according to the sorting order.

[0060] The analysis and output unit is configured with an analysis and output strategy, which includes: sorting and classifying this type of product according to the top three user stay times, supplier complaint rates, supplier abnormal order incidence rates, interface response rates, delivery and account arrival rates, total supplier success rates, and supplier prices for this product. The user selects a sorting type based on the sorting classification and the sorted products of this type are output according to the user's sorting classification. In each sorting type, sorting and classification are performed according to the top three ranges, and sorting is performed in descending order of values within each sorting range; and sorting by type is performed for the above-mentioned user stay times, supplier complaint rates, supplier abnormal order incidence rates, interface response rates, delivery and account arrival rates, total supplier success rates, and supplier prices for this product, facilitating subsequent continuous replenishment and output of products.

[0061] The replenishment and output unit is configured with a replenishment and output strategy, which includes: sorting the types of sorting classification, obtaining the user stay time of the first sorting push, and when the user stay time exceeds the first time threshold, performing sequential sorting pushes according to the re-sorting of the sorting classification.

[0062] Please refer to Figure 2 , a method for a sorting optimization output system for multiple products, the method comprising the following steps:

[0063] Step S1, collecting output-related data of products in normal ordering transactions; the output-related data includes user stay time, supplier success rate, supplier complaint rate, supplier abnormal order incidence rate, interface response rate, and delivery and account arrival rate;

[0064] Step S2, storing the output-related data of the product after corresponding it to the product; and pre-storing product basic sorting data; the product basic sorting data includes: total supplier success rate, supplier price for this product, supplier level, and supplier weight;

[0065] Step S3, creating sorting attributes for the product; creating sorting attributes includes: manually creating attributes of the product and creating sorting attributes according to the data stored in the database module;

[0066] By bringing the supplier success rate, supplier complaint rate, supplier abnormal order incidence rate, interface response rate, total supplier success rate, and supplier price for this product into the first algorithm and assigning a supplier weight, the supplier level value is calculated;

[0067] When the level value of a supplier is greater than or equal to the first level threshold, the level of the supplier is set as the first level; when the level value of the supplier is less than the first level threshold and greater than or equal to the second level threshold, the level of the supplier is set as the second level; when the level value of the supplier is less than the second level threshold and greater than or equal to the third level threshold, the level of the supplier is set as the third level; when the level value of the supplier is less than the third level threshold and greater than or equal to the fourth level threshold, the level of the supplier is set as the fourth level; when the level value of the supplier is less than the fourth level threshold, the level of the supplier is set as the fifth level;

[0068] Successively obtain the user stay time, supplier complaint rate, supplier abnormal order incidence rate, interface response rate, delivery and account arrival rate, total supplier success rate, and the price of this commodity of the supplier with the top three success rates for different types of commodities.

[0069] Step S4, output the commodities according to the preset sorting data, sort the obtained levels of the suppliers from the first level to the fifth level, and then output the commodities according to the sorting order;

[0070] Process and then sort and output according to the user types of the commodities; sort and classify this type of commodity according to the top three user stay time, supplier complaint rate, supplier abnormal order incidence rate, interface response rate, delivery and account arrival rate, total supplier success rate, and the price of this commodity of the supplier. The user selects a sorting type according to the sorting classification, and output the sorting of this type of commodity according to the user's sorting classification selection;

[0071] Continue to push commodities after the user does not make a selection behavior, sort the types of the sorting classification, obtain the user stay time of the first sorting push. When the user stay time exceeds the first time threshold, perform a one-by-one sorting push according to the re-sorting of the sorting classification.

[0072] Finally, it should be noted that: the above-mentioned embodiments are only specific implementation manners of the present invention, used to illustrate the technical solutions of the present invention, rather than limiting it. The protection scope of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: any person skilled in the art within the technical scope disclosed by the present invention can still modify the technical solutions recorded in the foregoing embodiments, or can easily think of changes, or perform equivalent replacements on some of the technical features; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be covered by the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.

Claims

1. A sorting optimization output system for multiple commodities, characterized in that, the output system includes a data collection module, a database module, a processing module, and an output module; the data collection module is used to collect output-related data of commodities in normal ordering transactions; the database module is used to mark and store the collected data; the processing module is used to create sorting attributes for commodities; the output module is used to output commodities according to the sorting attributes; the output-related data collected by the collection module includes user stay time, supplier success rate, supplier complaint rate, supplier abnormal order incidence rate, interface response rate, and delivery and account arrival rate; the database module is used to store the output-related data collected for the commodity after corresponding it to the commodity; the database module also includes basic commodity sorting data; the basic commodity sorting data includes: total supplier success rate, supplier price of this commodity, supplier level, and supplier weight; the processing module includes a first configuration unit and a second configuration unit; the first configuration unit is used to manually create the attributes of commodities; the second configuration unit is used to create sorting attributes according to the data stored in the database module; the output module includes a basic output unit, an analysis output unit, and a replenishment output unit. The basic output unit is used to output commodities according to the preset sorting data; the analysis output unit is used to process and sort and output according to the user type of the commodity; the replenishment output unit is used to continue to push commodities after the user does not make a selection behavior; the first configuration unit is configured with a first configuration strategy, and the first configuration strategy includes: bringing the supplier success rate, supplier complaint rate, supplier abnormal order incidence rate, interface response rate, total supplier success rate, and supplier price of this commodity into the first algorithm, and assigning a supplier weight to calculate the level value of the supplier; when the level value of the supplier is greater than or equal to the first level threshold, the level of the supplier is set as the first level; when the level value of the supplier is less than the first level threshold and greater than or equal to the second level threshold, the level of the supplier is set as the second level; when the level value of the supplier is less than the second level threshold and greater than or equal to the third level threshold, the level of the supplier is set as the third level; when the level value of the supplier is less than the third level threshold and greater than or equal to the fourth level threshold, the level of the supplier is set as the fourth level; when the level value of the supplier is less than the fourth level threshold, the level of the supplier is set as the fifth level; The first algorithm is configured as follows: , where P d is the level value of the supplier, α is the supplier weight, G c is the supplier success rate, G ts is the supplier complaint rate, G yc is the incidence rate of abnormal orders of the supplier, J y is the interface response rate, G zc is the total success rate of the supplier, G j is the price of this commodity of the supplier; the second configuration unit is configured with a second configuration strategy, and the second configuration strategy includes: sequentially obtaining the user stay time, supplier complaint rate, supplier abnormal order incidence rate, interface response rate, delivery and account arrival rate, total supplier success rate, and supplier price of this commodity for the top three in terms of supplier success rate of different types of commodities; the basic output unit is configured with a basic output strategy, and the basic output strategy includes: sorting according to the obtained supplier levels from the first level to the fifth level, and then outputting commodities according to the sorting order; The analysis output unit is configured with an analysis output strategy, and the analysis output strategy includes: sorting and classifying products according to the top three user residence times, supplier complaint rates, supplier abnormal order incidence rates, interface response rates, delivery and account arrival rates, total supplier success rates, and supplier prices for this product. The user selects a sorting type according to the sorting classification, and outputs the sorting of the product according to the user's sorting classification selection. The replenishment output unit is configured with a replenishment output strategy, and the replenishment output strategy includes: sorting the types of the sorting classification, obtaining the user residence time of the first sorting push, and when the user residence time exceeds the first time threshold, performing sequential sorting pushes according to the re-sorting of the sorting classification.

2. A method for optimizing the sorting output of multiple products, applicable to a system for optimizing the sorting output of multiple products described in claim 1, the method comprising the following steps: Step S1, collecting output-related data of products in a normal ordering transaction; the output-related data includes user residence time, supplier success rate, supplier complaint rate, supplier abnormal order incidence rate, interface response rate, and delivery and account arrival rate. Step S2, storing the output-related data collected for the product after corresponding it to the product. And pre-storing product basic sorting data. The product basic sorting data includes: total supplier success rate, supplier price for this product, supplier level, and supplier weight. Step S3, creating sorting attributes for the product; creating sorting attributes includes: manually creating product attributes and creating sorting attributes according to the data stored in the database module. Step S4, outputting the product according to the preset sorting data; performing sorting output after processing according to the user type of the product; continuing to push products after the user does not make a selection. The step S3 further includes step A1, and the step A1 includes: substituting the supplier success rate, supplier complaint rate, supplier abnormal order incidence rate, interface response rate, total supplier success rate, and supplier price for this product into the first algorithm, and assigning a supplier weight to calculate the level value of the supplier. When the level value of the supplier is greater than or equal to the first level threshold, the level of the supplier is set as the first level; when the level value of the supplier is less than the first level threshold and greater than or equal to the second level threshold, the level of the supplier is set as the second level; when the level value of the supplier is less than the second level threshold and greater than or equal to the third level threshold, the level of the supplier is set as the third level; when the level value of the supplier is less than the third level threshold and greater than or equal to the fourth level threshold, the level of the supplier is set as the fourth level; when the level value of the supplier is less than the fourth level threshold, the level of the supplier is set as the fifth level. Sequentially obtain the user residence time, supplier complaint rate, supplier abnormal order incidence rate, interface response rate, delivery and account arrival rate, total supplier success rate, and supplier price for this product of the top three suppliers in terms of success rate for different types of products. The step S4 further includes a step B1, and the step B1 includes: sorting the obtained grades of the suppliers from the first grade to the fifth grade, and then outputting products according to the sorting order; Sort and classify the products according to the top three users' stay time, supplier complaint rate, supplier abnormal order incidence rate, interface response rate, delivery and account arrival rate, total supplier success rate, and the price of this product of the supplier. The user selects a sorting type according to the sorting classification, and outputs the sorting of the products according to the user's sorting classification selection; Sort the types of the sorting classification, obtain the user stay time of the first sorting push, and when the user stay time exceeds the first time threshold, perform a one-by-one sorting push according to the re-sorting of the sorting classification.

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