TWM643269U - E-commerce commodity value estimation system - Google Patents

Abstract

This work is an e-commerce commodity value estimation system. The e-commerce product value estimation system of the present model is set in the host computer of the e-commerce platform. The e-commerce commodity value estimation system includes a transaction database and a processing module. The transaction database stores commodity transaction data. The processing module calculates the commodity market price index and price drop risk index of the commodity based on the commodity transaction data, so as to estimate the commodity commodity valuation index of the commodity based on the commodity market price index, price drop risk index and the risk control constant of the corresponding commodity.

Description

E-commerce commodity value estimation system

The present invention relates to an e-commerce commodity value estimation system, in particular to an e-commerce commodity value estimation system that can evaluate commodities based on data from an e-commerce platform.

Loan collaterals in the market are mainly houses, cars and other high-priced commodities due to factors such as the feasibility and price loss of collateral resale, and the difficulty of commodity valuation and appraisal. For some borrowers, they may have many low-to-medium-priced commodities, but they lack accurate commodity valuation methods and can only estimate them at market prices. For the e-commerce platform, the e-commerce platform has mastered the prices and sales of many commodities. There is a large amount of data, but the data is not effectively used, which limits the derivative business opportunities of the e-commerce platform.

Therefore, it is necessary to create a new e-commerce product value estimation system to solve the lack of previous technologies.

The main purpose of this model is to provide an e-commerce commodity value estimation system, which has the technology to evaluate commodities based on the data of the e-commerce platform.

In order to achieve the above-mentioned purpose, the e-commerce commodity value estimation system of the present invention is set in the host computer of the e-commerce platform. The e-commerce commodity value estimation system includes a transaction database and a processing module. The transaction database stores commodity transaction data. The processing module is electrically connected to the transaction database, and the processing module calculates the commodity market price index and price risk index of the commodity based on the commodity transaction data, so as to estimate the commodity valuation index of the commodity based on the commodity market price index, price decline risk index and the risk control constant of the corresponding commodity.

1: E-commerce platform host

10: E-commerce commodity value estimation system

20: Transaction database

21: Commodity transaction data

30: Processing modules

FIG. 1 is a schematic diagram of the structure of the new e-commerce product value estimation system.

In order to allow your review committee members to better understand the technical content of the present invention, preferred specific embodiments are specially cited as follows.

Please refer to Figure 1, which is a schematic diagram of the structure of the new e-commerce product value estimation system.

The new e-commerce commodity value estimation system 10 is installed in the e-commerce platform host 1, so that operators can use the e-commerce commodity value estimation system 10 to estimate the value of commodities sold on the e-commerce platform. The e-commerce platform host 1 can be a server host, but the present invention is not limited to the above-mentioned equipment. The e-commerce product value estimation system 10 is a system constructed in the e-commerce platform host 1 by means of hardware devices, software programs combined with hardware devices, firmware combined with hardware devices, and the like. The e-commerce product value estimation system 10 includes a transaction database 20 and a processing module 30, and the above modules are electrically connected to each other.

The transaction database 20 stores a commodity transaction data 21 . The processing module 30 is electrically connected to the transaction database 20, and the processing module 30 calculates a commodity market price index and a price drop risk index based on the commodity transaction data, so as to estimate a commodity valuation index based on the commodity market price index, the price drop risk index and the risk control constant. Risk control constants can be set by e-commerce operators for different commodities, and the risk of different commodities The control constants may be the same or different. In addition, the processing module 30 further calculates the ratio of the sold quantity of the commodity to the sold quantity of the category of the commodity, so as to obtain a sold risk index. The processing module 30 calculates the commodity valuation index when the selling risk index is greater than or equal to a set index.

其中SR為售出風險指數，A為商品近6個月售出數量，B為商品近3個月售出數量，C為商品近1個月售出數量，D為該商品之所屬類別之標準單位近6個月售出數量，E為該商品之所屬類別之標準單位近3個月售出數量，F為該商品之所屬類別之標準單位近1個月售出數量。藉由該商品售出數量與其所屬類別商品售出數量的比較，即可得知此商品售出的風險為何。當售出風險指數越大，代表此商品較容易被售出。售出風險指數越小，此商品就有滯銷的可能。所以處理模組30係先判斷該售出風險指數是否大於或等於一設定指數。於本新型之一實施方式中，設定指數可以設定為0.5，但本新型並不限於此。售出風險指數大於等於0.5時，處理模組30可以判斷此商品有較大機會可以賣出，所以處理模組30 可以再進行後續的估價流程。然而，當售出風險指數小於0.5時，處理模組30可以判斷此商品比較沒有機會可以賣出，商業價值較低，所以處理模組30不會進行後續的估價流程。 In one implementation of the present invention, the formula for calculating the selling risk index may be:

Among them, SR is the sales risk index, A is the sales volume of the product in the past 6 months, B is the sales volume of the product in the past 3 months, C is the sales volume of the product in the past 1 month, D is the sales volume of the standard unit of the category of the product in the past 6 months, E is the sales volume of the standard unit of the category of the product in the past 3 months, and F is the sales volume of the standard unit of the category of the product in the past 1 month. By comparing the sold quantity of the product with the sold quantity of the product of its category, it is possible to know the risk of selling the product. When the selling risk index is higher, it means that the product is easier to be sold. The smaller the selling risk index, the more likely the commodity will be unsalable. Therefore, the processing module 30 first determines whether the selling risk index is greater than or equal to a set index. In one embodiment of the present invention, the setting index can be set to 0.5, but the present invention is not limited thereto. When the selling risk index is greater than or equal to 0.5, the processing module 30 can determine that the product has a high chance of being sold, so the processing module 30 can carry out the subsequent valuation process. However, when the selling risk index is less than 0.5, the processing module 30 can judge that the commodity has little chance to be sold and has low commercial value, so the processing module 30 will not perform the subsequent valuation process.

For example, for example, if the product is a bottle, the number of bottle sold in the past 6 months is 200, the number of bottle sold in the past 3 months is 90, and the number of bottle sold in the past month is 35. The standard unit of the category of the bottle in the past 6 months is 65. The standard unit of the category of the bottle is 18 in the past month, which can be counted as the selling risk index of 2.53. The selling risk index (2.53) here is greater than the set index (0.5), so the processing module 30 will carry out the subsequent valuation process.

In one embodiment of the present model, the calculation formula of the commodity market price index can be: PV=X*0.3+Y*0.3+Z*0.4 where PV is the commodity market price index, X is the transaction price of the commodity in the past 6 months, Y is the transaction price of the commodity in the past 3 months, and Z is the transaction price of the commodity in the past 1 month. That is to say, the processing module 30 makes a comprehensive judgment based on the transaction prices of the commodity in multiple months, so as to obtain the commodity market price index of the commodity. For example, if the transaction price of the milk bottle in the past 6 months is 450, the milk The transaction price of the bottle in the past 3 months is 420, and the transaction price of the baby bottle in the past 1 month is 416, so the processing module 30 can be substituted into the formula to calculate the commodity market price index as 427.

其中FR為跌價風險指數。亦即處理模組30根據此商品的複數月份之成交價格之變化幅度，以得知此商品的跌價風險指數。舉例來說，若奶瓶近3個月成交價格為420，奶瓶近1個月成交價格為416，所以處理模組30就可以代入公式算出跌價風險指數為0.99。 Then, in one implementation of the present invention, the formula for calculating the commodity market price index can be:

Among them, FR is the price risk index. That is to say, the processing module 30 obtains the price drop risk index of the commodity according to the variation range of the transaction price of the commodity in multiple months. For example, if the transaction price of the baby bottle in the past three months is 420, and the transaction price of the baby bottle in the past one month is 416, so the processing module 30 can be substituted into the formula to calculate the price risk index as 0.99.

Then the processing module 30 uses a value estimation algorithm formula to calculate the commodity valuation index. In one embodiment of the present invention, the value estimation algorithm formula is: PV*FR*R, wherein PV is the commodity market price index, FR is the price risk index, and R is the risk control constant.

From the above formula, it can be known that the commodity market price index is 427, the price risk index is 0.99, and the risk control constant of the baby bottle is set at 0.8. Therefore, after the processing module 30 substitutes the value estimation algorithm formula, the commodity valuation index can be obtained as 388. By this, It can be known that the valuation of this product is 388 yuan, as a follow-up commercial behavior, for example, the business uses this product as collateral for loan. The e-commerce platform can provide funds for loans, or provide the valuation of this product to the bank, and the bank will borrow money, but this model does not limit subsequent behaviors.

It should be noted that the various modules of the e-commerce commodity value estimation system 10 can be structured in the form of hardware devices, software programs combined with hardware devices, firmware combined with hardware devices, etc. For example, a computer program product can be stored in a computer-readable medium such as a smart phone, a tablet computer, or other computer systems, read and executed to achieve various functions of the present model, but the present model is not limited to the above-mentioned methods. In addition, this embodiment is only an example of a preferred embodiment of the present invention, and all possible combinations of changes are not described in detail in order to avoid redundant description. However, those skilled in the art should understand that not all the above-mentioned modules or components are necessary. And in order to implement the present invention, other more detailed conventional modules or components may also be included. Each module or component may be omitted or modified as required, and there may not be other modules or components between any two modules.

With the e-commerce commodity value estimation system 10 in this case, the data of the e-commerce platform can be used to estimate the price that the commodity should have when it is used as collateral, so that the e-commerce platform or the operator can conduct more commercial activities.

In addition, this embodiment is only an example of a preferred embodiment of the present invention, and is not limited to the embodiment. In order to avoid redundant description, all possible combinations of changes are not described in detail. However, those skilled in the art should understand that not all the above-mentioned modules or components are necessary. And in order to implement the present invention, other more detailed conventional modules or components may also be included. Each module or component may be omitted or modified as required, and there may not be other modules or components between any two modules. Anything that does not deviate from the basic framework of the present invention shall be within the scope of rights claimed by this patent, and the scope of the patent application shall prevail.

1: E-commerce platform host

10: E-commerce commodity value estimation system

20: Transaction Database

21: Commodity transaction information

30: Processing modules

Claims (7)

An e-commerce commodity value estimation system. The e-commerce commodity value estimation system is installed in an e-commerce platform host to estimate the value of a commodity. The e-commerce commodity value estimation system includes: a transaction database, which stores a commodity transaction data; and A processing module is electrically connected to the transaction database. The processing module calculates a commodity market price index and a price drop risk index for the commodity based on the commodity transaction data, so as to estimate a commodity valuation index for the commodity based on the commodity market price index, the price drop risk index, and a risk control constant corresponding to the commodity. The e-commerce product value estimation system as described in Claim 1, wherein the processing module further calculates the ratio of the sold quantity of the product to the sold quantity of the category of the product, so as to obtain a sales risk index. The e-commerce commodity value estimation system as described in Claim 2, wherein the processing module calculates the commodity valuation index when the selling risk index is greater than or equal to a set index. The e-commerce commodity value estimation system as described in Claim 1, wherein the processing module calculates the transaction price of the commodity in multiple months, so as to know the market price index of the commodity. The e-commerce commodity value estimation system as described in Claim 1, wherein the processing module calculates the change range of the transaction price of the commodity in multiple months, so as to obtain the price risk index. The e-commerce commodity value estimation system as described in Claim 1, wherein the processing module calculates the commodity valuation index through a value estimation algorithm formula. The e-commerce commodity value estimation system as described in Claim 6, wherein the value estimation algorithm formula is: PV*FR*R; Among them, PV is the commodity market price index, FR is the price risk index, and R is the risk control constant.

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