KR102321786B1 - Server predicting price of goods and operating method thereof - Google Patents

Abstract

A method of predicting a price of a product according to an embodiment of the present disclosure includes: receiving product information and a pricing parameter corresponding to the product from a first electronic device; receiving the subscription request for the product and counting the subscription quantity corresponding to the subscription request; calculating a first selling price corresponding to the product according to a preset selling price calculation formula based on the subscription quantity and the pricing parameter; and calculating an additional discount price by using the prediction parameter. The method may include estimating a second selling price corresponding to the product by a predetermined time point by reflecting the additional discount price in the first selling price. In addition to this, various embodiments identified through the specification are possible.

Description

Product price prediction server and its operation method {SERVER PREDICTING PRICE OF GOODS AND OPERATING METHOD THEREOF}

Embodiments disclosed in this document relate to a product price prediction server and an operating method thereof, and to a product price prediction server capable of predicting the price of a product at a specific point in time in the future based on past sales history, and an operating method thereof .

Internet shopping or mobile shopping, characterized by convenience and reasonable price, has become so common that it threatens sales through traditional distribution channels. When purchasing a product online, the consumer can purchase the product without being restricted by time and place, and since it does not go through a complicated distribution channel, the price of the product can be set relatively low. In addition, consumers can instantly compare multiple products on the web.

In the conventional Internet shopping, a seller announces a sale price or provides a certain discount benefit from a consumer price. In addition, the seller sets the selling price through an online auction or reverse auction, or provides a special discount to consumers based on an open or closed membership system, or provides a certain reward when a member sells their products.

Although these sales methods are different in degree rather than a business model in which both consumers and sellers are actually active actors in the distribution structure, sellers tend to treat consumers passively.

In the conventional sales method, since the seller is given the initiative in price provision, the price provided to individual consumers may not be reasonable or reasonable. Not all sellers could be satisfied. Therefore, in order to overcome this limitation, a business model in which both consumers and sellers can be active actors is needed.

The embodiments disclosed in this document are devised to overcome the above difficulties, and provide a system in which both consumers and sellers act as subjects to determine the price of a product, an execution server, and an operating method of the server. There is a purpose.

In a price prediction method according to an embodiment of the present invention, the method comprising: receiving product information and a pricing parameter corresponding to a product from a first electronic device; receiving the subscription request for the product and counting the subscription quantity corresponding to the subscription request; calculating a first selling price corresponding to the product according to a preset selling price calculation formula based on the subscription quantity and the pricing parameter; and calculating an additional discount price by using the prediction parameter. and predicting a second selling price corresponding to the product by a predetermined time point by reflecting the additional discount price in the first selling price, wherein the pricing parameters include the initial price of the product, the marginal sales amount, and a threshold It includes the sales volume and the marginal discount rate, and the prediction parameters may include a repurchase pattern, a past sales amount, a reserved purchase quantity, and a purchase increase/decrease.

In the predicting of the second selling price, the second selling price is predicted by using Equation 5 below,

[Equation 5]

은 해당일에 대응하는 예약구매수량,

은 1일(日) 전 상품의 판매량,

은 n-1주부터 n주 이내에 재구매한 구매자수,

은 n-1주부터 n주 이내에 재구매한 구매량,

은 n-1주부터 n주 이내에 재구매에 대한 가중치,

는 현재부터 상품판매 플랫폼을 생성한 기간,

는 해당 상품의 판매순위 증가/감소 폭 및

는 사전 설정된 상수를 나타낼 수 있다.In Equation 5, PRICE is the additional discount price,

is the number of reservation purchases corresponding to the day,

The sales volume of all products for 1 day (day),

is the number of buyers who repurchased within n weeks from n-1 weeks,

is the amount of purchases repurchased within n weeks from n-1 weeks,

is the weight for repurchase within n weeks from n-1 weeks,

is the period in which the product sales platform was created from the present,

is the increase/decrease in the sales ranking of the product and

may represent a preset constant.

In the predicting of the second selling price, the second selling price is predicted by using Equation 6 below,

[Equation 6]

은 해당일에 대응하는 예약구매수량,

은 1주(週) 전 상품의 판매량,

은 n-1주부터 n주 이내에 재구매한 구매자수,

은 n-1주부터 n주 이내에 재구매한 구매량,

은 n-1주부터 n주 이내에 재구매에 대한 가중치,

는 현재부터 상품판매 플랫폼을 생성한 기간,

는 해당 상품의 판매순위 증가/감소 폭 및

는 사전 설정된 상수를 나타낼 수 있다. In Equation 6, PRICE is the additional discount price,

is the number of reservation purchases corresponding to the day,

Sales of all products in one week,

is the number of buyers who repurchased within n weeks from n-1 weeks,

is the amount of purchases repurchased within n weeks from n-1 weeks,

is the weight for repurchase within n weeks from n-1 weeks,

is the period in which the product sales platform was created from the present,

is the increase/decrease in the sales ranking of the product and

may represent a preset constant.

The step of calculating the selling price of the product is

는 판매가격,

는 청약수량,

는 초기가격,

은 제1 판매가격,

은 제2 판매가격,

은 한계판매량,

은 임계판매량,

은 제1 할인지점에 대응하는 수량,

은 제2 할인지점에 대응하는 수량일 수 있다.Calculate the selling price according to

is the selling price,

is the subscription quantity,

is the initial price,

is the first selling price,

is the second selling price,

is the limit of sales,

silver threshold sales,

is the quantity corresponding to the first discount point,

may be a quantity corresponding to the second discount point.

The step of calculating the selling price of the product is

는 판매가격,

는 청약수량,

은 한계판매량,

은 임계판매량,

은 한계할인율,

는 초기가격일 수 있다.Calculate the selling price of the product according to

is the selling price,

is the subscription quantity,

is the limit of sales,

silver threshold sales,

is the marginal discount rate,

may be the initial price.

에 따라 계산하고,

는 판매가격,

는 청약수량,

은 한계판매량,

은 임계판매량,

은 한계할인율,

는 초기가격이다.The step of calculating the price of the product is

calculated according to

is the selling price,

is the subscription quantity,

is the limit of sales,

silver threshold sales,

is the marginal discount rate,

is the initial price.

In a server according to an embodiment of the present invention, there is provided a server for calculating a selling price of a product, comprising: a database for storing product information, pricing parameters, and predictive parameters provided from a first electronic device; and receiving the subscription request for the product, counting the subscription quantity corresponding to the subscription request, and first selling corresponding to the product according to a preset sales price calculation formula based on the subscription quantity and the pricing parameter A processor that calculates a price, calculates an additional discount price by using a prediction parameter, and predicts a second selling price corresponding to the product by a predetermined time point by reflecting the additional discount price in the first selling price; , the pricing parameter may include the initial price of the product, the marginal sales volume, the critical sales volume, and the marginal discount rate, and the prediction parameters may include a repurchase pattern, past sales volume, pre-order purchase quantity, and purchase increase/decrease.

The server according to an embodiment of the present invention may provide a reasonable price for a product to a consumer, and may predict and provide a future price for an efficient purchase.

1 is a diagram illustrating an environment in which a system for performing a pricing method according to an embodiment of the present invention is implemented.
2 is a diagram showing the configuration of a server according to an embodiment of the present invention.
3 is a sequence-chart for explaining the operations of a purchaser electronic device, a seller electronic device, and a server according to an embodiment of the present invention.
4A to 4E are graphs in which a selling price is determined according to a selling price calculation formula according to an embodiment of the present invention.
5 is a flow-chart for explaining the operation of the server 150 according to an embodiment of the present invention.
6 shows a state in which a first selling price and a second selling price are disclosed according to an embodiment of the present invention.

Hereinafter, various embodiments of the present invention will be described with reference to the accompanying drawings. It should be understood that the present invention is not limited to specific embodiments, and includes various modifications, equivalents, and/or alternatives of the embodiments of the present invention. In connection with the description of the drawings, like reference numerals may be used for like components.

In this document, expressions such as "have", "may have", "includes", or "may include" refer to the presence of a corresponding characteristic (eg, a numerical value, function, operation, or component such as a part). and does not exclude the presence of additional features.

In this document, expressions such as "A or B", "at least one of A and/and B", or "one or more of A or/and B" may include all possible combinations of the items listed together. . For example, "A or B", "at least one of A and B", or "at least one of A or B" means (1) includes at least one A, (2) includes at least one B; Or (3) it may refer to all cases including both at least one A and at least one B.

Expressions such as "first", "second", "first", or "second" used in this document may modify various elements, regardless of order and/or importance, and may modify one element in another. It is used only to distinguish it from the components, and does not limit the components. For example, without departing from the scope of the rights described in this document, a first component may be referred to as a second component, and similarly, the second component may also be renamed as a first component.

The expression "configured to (or configured to)" as used in this document, depending on the context, for example, "suitable for", "having the capacity to" It can be used interchangeably with "," "designed to", "adapted to", "made to", or "capable of". The term "configured (or set up to)" does not necessarily mean only "specifically designed to".

In this document, transmitted and received between the first electronic device(s) and the second electronic device(s), for example, “command”, “instruction”, “control information”, “message”, “ "Information", "data", "packet", "data packet", "intent" and/or "signal" means any human perceptible idea or specific electrical representation (e.g., digital code/analog physical quantity) or refer to itself. It will be apparent to those skilled in the art that the above-listed exemplary expressions may be interpreted in various ways depending on the context in which they are used. In this document, “A is greater than B” not only means “A is greater than B”, but also includes “A is greater than or equal to B”.

Terms used in this document are only used to describe specific embodiments, and may not be intended to limit the scope of other embodiments. The singular expression may include the plural expression unless the context clearly dictates otherwise. Terms used herein, including technical or scientific terms, may have the same meanings as commonly understood by one of ordinary skill in the art described in this document. Among the terms used in this document, terms defined in a general dictionary may be interpreted with the same or similar meaning as the meaning in the context of the related art, and unless explicitly defined in this document, have an ideal or excessively formal meaning. not interpreted In some cases, even terms defined in this document cannot be construed to exclude embodiments of this document.

1 is a diagram illustrating an environment in which a system for performing a pricing method according to an embodiment of the present invention is implemented.

Referring to FIG. 1 , a system according to an embodiment of the present invention may include a purchaser device 110 , a seller device 130 , and a server 150 .

The purchaser device 110 and the seller device 130 refer to devices capable of accessing the server 150 through a wired/wireless network. For example, the buyer device 110 and the seller device 130 may include a PC, a laptop computer, a smart phone, and the like. According to an embodiment of the present invention, the buyer and the seller may access the server 150 using the buyer device 110 and the seller device 130 , respectively. The buyer may be a customer who accesses the server 150 using the buyer device 110 to purchase the product, and the seller may be a business operator who accesses the server 150 using the seller device 130 to sell the product. have.

The server 150 may refer to a server for selling or purchasing a product to a purchaser who accesses the service page through the purchaser electronic device 110 . For example, the product may include products that can be used in a cafe, such as coffee beans, coffee extraction device, coffee grinder, cup, straw, syrup, and the like. However, this is only an example, and is not limited thereto.

2 is a diagram showing the configuration of a server 150 according to an embodiment of the present invention.

Referring to FIG. 2 , the server 150 according to an embodiment of the present invention includes a bus 210 , a display 220 , a communication circuit 230 , a database 240 , a memory 250 , and an I/O interface 260 . ) and a processor 270 . In another embodiment, the server 150 may omit at least one of the components or additionally include other components.

The bus 210 may electrically connect the components 220 to 270 to each other. Bus 210 may include circuitry for communication (eg, control messages and/or data) between components 220 - 270 .

The display 220 may display text, images, videos, icons, or symbols constituting various contents. The display 220 may include a touch screen, and may receive a touch, gesture, proximity, or hovering input using an electronic pen or a part of the user's body.

For example, the display 220 may be a liquid crystal display (LCD), a light emitting diode (LED) display, an organic light emitting diode (organic LED) display, or a microelectromechanical systems (MEMS) display, or an electronic paper (electronic paper) display. It may include a display. The display 220 may be implemented as being included in the server 150 , or implemented separately from the server 150 , but may be operatively connected to the server 150 .

The communication circuit 230 may establish a communication channel between the server 150 and external devices (eg, the purchaser electronic device 110 and the seller electronic device 130 ). For example, the communication circuit 230 may access the network 280 through wireless communication or wired communication to communicate with external devices.

The network 280 may include at least one of a telecommunications network, a computer network, the Internet, or a telephone network. Wireless communication protocols for accessing the network 280 include, for example, Long-Term Evolution (LTE), LTE Advanced (LTE-A), Code Division Multiple Access (CDMA), Wideband CDMA (WCDMA), Universal At least one of Mobile Telecommunications System), Wireless Broadband (WiBro), Global System for Mobile communications (GSM), or 5G standard communication protocol may be used.

The database 240 may be implemented in the memory 250 or in a separate storage medium. The database 240 is used for the implementation of the present invention, such as member information of the seller and the buyer, product information and pricing parameters provided from the seller electronic device 130, subscription information provided from the buyer electronic device 110, reservation purchase information, etc. A variety of data can be stored. The subscription information may include product information, quantity, purchase location, etc. of the product the buyer wants to purchase. The reservation purchase information may include a reservation quantity, a reservation date, and the like. According to various embodiments, since the data stored in the database 240 is sensitive information of the customer, it may be distributed and stored in a blockchain network to improve security regarding the use of the information. When the database 240 is distributed and stored in the blockchain network, the history of transmission, modification, deletion, addition, etc. of information included in the database 240 can be more safely managed in the blockchain network.

Memory 250 may include volatile and/or non-volatile memory. The memory 250 may store commands or data related to at least one other component in the server 150 . For example, the memory 250 may store instructions that, when executed, cause the processor 270 to perform various operations described herein. For example, the command may be included in a package file of the application program.

The I/O interface 260 may serve to transmit a command or data input from a user or other external device to other components of the server 150 . The I/O interface 260 may be implemented as hardware or software, and may be used as a concept encompassing a user interface (UI) and terminals for communication with other external devices.

The processor 270 may include at least one of a central processing unit (CPU), an application processor (AP), and a communication processor (CP). The processor 270 is electrically connected to the memory 250 , the display 220 , and the communication circuit 230 through the bus 210 , and, during operation, has a different configuration depending on instructions, programs, or software stored in the memory 250 . Calculations or data processing related to control and/or communication of elements may be performed. Accordingly, the execution of the instruction, application program, or software may be understood as an operation of the processor 270 .

The processor 270 according to an embodiment of the present invention may calculate the selling price of the product based on the pricing parameter provided from the seller electronic device 130 . The process of calculating the selling price of the product will be described in more detail with reference to FIGS. 3 to 4D .

The operations of the processor 270 are representative examples, and the technical spirit of the present invention is not limited thereto. For example, the operation of the "server 150" described directly or indirectly in this specification may be understood as the operation of the processor 270 included in the corresponding "server 150". In addition, it will be apparent to those skilled in the art that at least some of the operations performed in the server 150 may be performed by a third device through a server-client architecture, cloud computing, and/or parallel computing. .

Hereinafter, various embodiments of the present invention implemented in an environment including the individual subjects as described above will be described.

3 is a sequence-chart for explaining the operations of the purchaser electronic device 110 , the seller electronic device 130 , and the server 150 according to an embodiment of the present invention.

In step S301 , the seller may provide the server 150 with product information and pricing parameters corresponding to a product that the seller intends to sell (hereinafter, referred to as a sale product) by using the seller electronic device 130 . Product information refers to unique information of a product that can be identified from other products. For example, the product information may include a product name, a brand, a model name, and the like. Meanwhile, the pricing parameter refers to a factor that can determine the selling price of a product. For example, the pricing parameters include 'initial price', which is the selling price to which no discount is applied, 'limit sales', which is the maximum quantity that the seller can sell for a specified period of time, and the minimum quantity at which the seller can sell products. It may include a 'threshold sales volume', a 'marginal discount rate' that is the maximum discount rate that a seller can offer, a 'discount point' that is a critical point at which the selling price is discounted, and a 'branch discount rate' according to the discount point. The pricing parameter may be set by the seller.

Also, although not shown in the drawings, the seller electronic device 130 may provide the selling price calculation formula selected by the seller to the server 150 . This will be described in more detail in step S323.

In step S303 , the server 150 may build the database 240 based on product information and pricing parameters provided from the seller electronic device 130 .

In step S305 , the server 150 may register the seller's product in the product sales platform based on the product information and pricing parameters stored in the database 240 .

In step S307 , the purchaser may request access to the server 150 while providing his or her member information to the server 150 using the purchaser electronic device 110 . Member information may include ID, password, whether the buyer or seller, etc.

In step S309 , the server 150 may identify the user based on the access request provided from the purchaser electronic device 110 . For example, the server 150 may identify that the user requesting access is a purchaser. Although not shown in the drawing, when the access request is provided to the server from the seller electronic device 130 , the server 150 may identify that the user who requested the access is the seller.

In step S311 , the server 150 may provide the purchaser electronic device 110 with a response indicating that the purchaser electronic device 110 is permitted to access the server 150 according to the access request.

In step S313 , the server 150 may provide product information corresponding to each of a plurality of products registered in the product sales platform to the purchaser electronic device 110 .

In step S315 , the purchaser electronic device 110 may output product information provided from the server 150 through the display of the purchaser electronic device 110 . The purchaser may check product information corresponding to each of the plurality of products through the display.

In step S317 , the purchaser may select a product to be purchased by the purchaser from among a plurality of products through the purchaser electronic device 110 . The purchaser electronic device 110 may provide a subscription request for the product selected by the purchaser to the server 150 . The subscription request may include subscription information. As described in FIG. 2 , the subscription information may include product information, quantity, and place of purchase of a product that the buyer wants to purchase.

In step S319 , the server 150 may receive the subscription request provided from the purchaser electronic device 110 . In addition, the server 150 may receive the subscription request received for a specified time. For example, the server 150 may receive the subscription request received for 24 hours.

In step S321, the server 150 may aggregate the subscription quantity of the product corresponding to the subscription request received during the specified time. For example, the server 150 may aggregate the subscription quantity of products corresponding to the subscription request received for 24 hours. In addition, the server 150 may not only aggregate the subscription quantity of the product corresponding to the subscription request of a single buyer, but also accumulate and aggregate the subscription quantity of the product corresponding to the subscription request of each of a plurality of purchasers. For example, when one purchaser requests a subscription for 100 first products during a specified time, the server 150 may count the number of subscriptions for the first product as '100'. For another example, when the first buyer requests a subscription for 100 second products during a specified time, and the second buyer requests an subscription for 50 second products, the server 150 may The number of subscriptions can be counted as '150'.

In step S323, the server 150 may calculate the selling price of the product by using the pricing parameter and the selling price calculation formula. According to an embodiment of the present invention, the server 150 may calculate the selling price in units of units.

According to an embodiment of the present invention, the server 150 may calculate the selling price according to Equation 1 below.

[Equation 1]

는 산출된 판매가격이고,

는 청약수량이며,

은 한계판매량이고,

은 임계판매량이며,

은 한계할인율이고,

는 초기가격이다.In Equation 1,

is the calculated selling price,

is the subscription quantity,

is the marginal sales volume,

is the threshold sales volume,

is the marginal discount rate,

is the initial price.

According to another embodiment of the present invention, the server 150 may calculate the selling price according to Equation 2 below.

[Equation 2]

는 산출된 판매가격이고,

는 청약수량,

는 초기가격,

은 제1 판매가격,

은 제2 판매가격,

은 한계판매량,

은 임계판매량,

은 제1 할인지점에 대응하는 수량,

은 제2 할인지점에 대응하는 수량이다.In Equation 2,

is the calculated selling price,

is the subscription quantity,

is the initial price,

is the first selling price,

is the second selling price,

is the limit of sales,

silver threshold sales,

is the quantity corresponding to the first discount point,

is a quantity corresponding to the second discount point.

및 제2 판매가격

을 가격결정 파라미터에 포함된 할인지점 및 지점할인율, 최대할인율에 따라 설정할 수 있다. 예컨대, 집계된 청약수량이 임계판매량보다 크고, 제1 할인지점에 대응하는 수량

보다 작은 경우, 할인율은 0%일 수 있다. 또한, 청약수량이 제1 할인지점에 대응하는 수량

보다 크고, 제2 할인지점에 대응하는 수량

보다 작은 경우, 할인율이 10%일 수 있다. 청약수량이 제2 할인지점에 대응하는 수량

보다 큰 경우, 제2 할인율(=최대할인율)이 20%이다. Server 150 is the first selling price

and a second selling price

can be set according to the discount point, branch discount rate, and maximum discount rate included in the pricing parameter. For example, the aggregated subscription quantity is greater than the threshold sales quantity and the quantity corresponding to the first discount point

If less than, the discount rate may be 0%. In addition, the subscription quantity corresponds to the first discount point

Quantity greater than and corresponding to the second discount point

If smaller, the discount rate may be 10%. The quantity corresponding to the second discount point

If greater than , the second discount rate (=maximum discount rate) is 20%.

을

로 산출할 수 있다. 한편, 제2 할인율이 적용된 상품에 대하여, 서버(150)는 제2 판매가격

을

로 산출할 수 있다.Accordingly, with respect to the product to which the first discount rate is applied, the server 150 sets the first selling price.

second

can be calculated as On the other hand, with respect to the product to which the second discount rate is applied, the server 150 sets the second selling price.

second

can be calculated as

According to another embodiment of the present invention, the server 150 may calculate the selling price according to Equation 3 below.

[Equation 3]

는 산출된 판매가격이고,

는 청약수량이며,

은 한계판매량이고,

은 임계판매량이며,

은 한계할인율이고,

는 초기가격이다.In Equation 3,

is the calculated selling price,

is the subscription quantity,

is the marginal sales volume,

is the threshold sales volume,

is the marginal discount rate,

is the initial price.

According to another embodiment of the present invention, the server 150 may calculate the selling price according to Equation 4 below.

[Equation 4]

는 산출된 판매가격이고,

는 청약수량이며,

은 한계판매량이고,

은 임계판매량이며,

은 한계할인율이고,

는 초기가격이다.In Equation 4,

is the calculated selling price,

is the subscription quantity,

is the marginal sales volume,

is the threshold sales volume,

is the marginal discount rate,

is the initial price.

According to an embodiment of the present invention, the seller may select any one of Equations 1 to 4 above. The server 150 may calculate the selling price of the product according to the selling price calculation formula selected by the seller.

According to another embodiment of the present invention, the server 150 may automatically set any one of Equations 1 to 4 as the selling price calculation formula in consideration of at least one of product characteristics, seller characteristics, and buyer characteristics. And, it is possible to calculate the selling price by using the set selling price calculation formula.

For example, in the case of a product having a relatively continuous purchase cycle, such as coffee beans, the server 150 can calculate the selling price by using the balanced equation 1 that can satisfy both the buyer and the seller. have. For another example, in the case of a product having a relatively single purchase cycle, such as a coffee extraction machine, the server 150 uses Equation 2 to induce purchase of the product at a specific point to induce the sale price. can be calculated. On the other hand, when the seller is a small-volume sales company, the server 150 may calculate the selling price by using Equation 3 that can induce a small-scale purchase of the product. On the other hand, if the seller is a mass-selling company, the server 150 may calculate the selling price by using Equation 4 that can induce mass purchase of the product. The above examples are merely exemplary, and are not limited thereto.

The server 150 may analyze product characteristics, seller characteristics, and purchaser characteristics using various big data analysis techniques, and store them in the database 240 .

In step S325 , the server 150 may provide the calculated selling price to the purchaser electronic device 110 in real time. The purchaser may check the selling price by using the purchaser electronic device 110 , and may determine whether to purchase the product according to the selling price.

Although not shown in the drawings, the buyer may purchase the product at the selling price if the selling price is satisfactory. In this case, the purchaser electronic device 110 may provide a purchase request for the product to the server 150 .

According to an embodiment of the present invention, the server 150 may redirect the purchaser electronic device 110 to a web page operated by the seller. That is, the web page operated by the seller may be provided to the purchaser electronic device 110 in the product sales platform in the server 150 , so that the purchaser electronic device 110 and the web page may be connected. Buyers can purchase products from the linked web page.

According to another embodiment of the present invention, the server 150 may directly provide a purchase request provided from the purchaser electronic device 110 to the seller electronic device 130 . That is, the server 150 may serve as an intermediate bridge between the purchaser electronic device 110 and the seller electronic device 130 .

In the same way as above, the seller can sell the product to the buyer.

As discussed above, in the pricing method according to the embodiment of the present invention, both the buyer and the seller may be the subject of determining the price by applying a discount rate differently depending on the purchase quantity. As a result, both the buyer and the seller can determine the price of the product that they are satisfied with.

4A to 4E are graphs in which a selling price is determined according to an equation according to an embodiment of the present invention.

4A shows a graph in which a selling price is determined according to Equation 1 according to an embodiment of the present invention. Referring to FIG. 4A , the selling price is linearly decreased as the subscription quantity increases. Equation 1 is a calculation formula that considers both the buyer and the seller, and may have a feature of calculating a relatively balanced selling price.

4B is a graph showing a sales price calculated according to Equation 2 according to an embodiment of the present invention. Referring to FIG. 4B , it can be seen that the selling price is decreased stepwise as the subscription quantity increases. Equation 2 may have a feature that can induce purchase at a specific point.

4C shows a graph in which a selling price is calculated according to Equation 3 according to an embodiment of the present invention. Referring to FIG. 4C , it can be seen that the selling price decreases in a convex form as the subscription quantity increases. Equation 3 has a feature that can induce a small amount of product purchase.

4D shows a graph in which a selling price is calculated according to Equation 4 according to an embodiment of the present invention. Referring to FIG. 4D , it can be seen that the selling price is decreased in the upper block form as the subscription quantity increases. Equation 4 has a feature that can induce mass purchase of goods.

4E is a graph showing a sales price is calculated according to various embodiments of the present invention. According to an embodiment, the server 150 may combine Equation 1 shown in FIG. 4A and Equation 4 shown in FIG. 4D .

Referring to FIG. 4E , when the aggregated subscription quantity is greater than the threshold sales quantity and less than the quantity corresponding to the third discount point, the server 150 may calculate the selling price of the product according to Equation 1. Meanwhile, when the aggregated subscription quantity is greater than the quantity corresponding to the third discount point, the server 150 may calculate the selling price of the product according to Equation (4).

FIG. 4E is only an example, and two or more of Equations 1 to 4 described in FIGS. 4A to 4D may be combined depending on the section of the subscription quantity.

Previously, information regarding a method for determining the selling price of a product has been posted in FIGS. 3 to 4E . Hereinafter, information on a method of predicting future sales prices based on the forecast parameters is posted.

5 is a flow-chart for explaining the operation of the server 150 according to an embodiment of the present invention.

In step S501, the server 150 may collect predictive parameters. The predictive parameter may include information about the sales volume of the product, the purchase pattern of the purchaser, the reservation purchase, and the like.

The sales volume information may include past daily (daily) unit, monthly (month) unit, and year (year) unit sales volume corresponding to the corresponding product. Purchase pattern information may include the number of purchasers who repurchase within a specific period, such as the number of purchasers who repurchase within 1 week, the number of purchasers who repurchase within 1 to 2 weeks, and the number of purchasers who purchase again within 2 to 3 weeks. have. The reserved purchase information may include the reserved purchase quantity included in the reserved purchase information provided by the purchaser to the server 150 by using the purchaser electronic device 110 .

The server 150 may collect the information and store it in the database 240 .

In step S503, the server 150 may calculate a current price (hereinafter, referred to as a first selling price) of the product. The server 150 according to an embodiment of the present invention may calculate the first selling price according to Equations 1 to 4 described with reference to FIG. 3 .

In step S505, the server 150 may calculate the additional discount price by utilizing the prediction parameters collected in step S501.

According to an embodiment of the present invention, the server 150 may calculate the additional discount price by using Equation (5).

[Equation 5]

은 해당일에 대응하는 예약구매수량,

은 1일(日) 전 상품의 판매량,

은 n-1주부터 n주 이내에 재구매한 구매자수,

은 n-1주부터 n주 이내에 재구매한 구매량,

은 n-1주부터 n주 이내에 재구매에 대한 가중치,

는 현재부터 상품판매 플랫폼을 생성한 기간,

는 해당 상품의 판매순위 증가/감소 폭 및

는 사전 설정된 상수를 나타낸다.

는 상품판매 플랫폼을 구축한 설계자에 의하여 설정될 수 있다. 또한, 상기 가중치는 설계자에 의하여 설정될 수 있다.In Equation 5, PRICE is the additional discount price,

is the number of reservation purchases corresponding to the day,

The sales volume of all products for 1 day (day),

is the number of buyers who repurchased within n weeks from n-1 weeks,

is the amount of purchases repurchased within n weeks from n-1 weeks,

is the weight for repurchase within n weeks from n-1 weeks,

is the period in which the product sales platform was created from the present,

is the increase/decrease in the sales ranking of the product and

represents a preset constant.

can be set by the designer who has built the product sales platform. Also, the weight may be set by a designer.

According to another embodiment of the present invention, the server 150 may calculate the additional discount price by using Equation (6).

[Equation 6]

은 해당일에 대응하는 예약구매수량,

은 1주(週) 전 상품의 판매량,

은 n-1주부터 n주 이내에 재구매한 구매자수,

은 n-1주부터 n주 이내에 재구매한 구매량,

은 n-1주부터 n주 이내에 재구매에 대한 가중치,

는 현재부터 상품판매 플랫폼을 생성한 기간,

는 해당 상품의 판매순위 증가/감소 폭 및

는 사전 설정된 상수를 나타낸다.

는 상품판매 플랫폼을 구축한 설계자에 의하여 설정될 수 있다. 또한, 상기 가중치는 설계자에 의하여 설정될 수 있다.In Equation 6, PRICE is the additional discount price,

is the number of reservation purchases corresponding to the day,

Sales of all products in one week,

is the number of buyers who repurchased within n weeks from n-1 weeks,

is the amount of purchases repurchased within n weeks from n-1 weeks,

is the weight for repurchase within n weeks from n-1 weeks,

is the period in which the product sales platform was created from the present,

is the increase/decrease in the sales ranking of the product and

represents a preset constant.

can be set by the designer who has built the product sales platform. Also, the weight may be set by a designer.

In step S507, the server 150 may calculate the second selling price by reflecting the additional discount price to the first selling price.

According to an embodiment of the present invention, the server 150 may predict the second selling price for a certain period of time. For example, the server 150 may predict the second selling price from the present to 7 days later.

In step S509, the server 150 may disclose the predicted second selling price on the platform.

6 shows a state in which a first selling price and a second selling price are disclosed according to an embodiment of the present invention. For convenience of explanation, it is assumed that the recommended consumer price of the product is 20,000 won.

Referring to FIG. 6 , a price of a past product and a price of a future product may be distinguished based on 'today'.

First, looking at the past based on 'today', the price of a product 7 days ago was 17,000 won, a 3,000 won discount to the consumer's recommended price of 20,000 won. That is, the first selling price 7 days ago is 17,000 won. In addition, the price of the product 6 days ago is 10,000 won, which is a discount of 10,000 won from the recommended consumer price of 20,000 won. That is, the first selling price 6 days ago is 10,000 won. The price of the product 5 days ago is 15,000 won, a 5,000 won discount from the recommended consumer price of 20,000 won. That is, the first selling price 5 days ago is 15,000 won. The price of the product 4 days ago is 17,000 won, 3,000 won discounted from the recommended consumer price of 20,000 won. That is, the first selling price 4 days ago is 17,000 won. The price of the product three days ago is 13,000 won, a 7,000 won discount from the recommended consumer price of 20,000 won. That is, the first selling price three days ago is 13,000 won. The price of the product two days ago is 18,000 won, 2,000 won off the recommended consumer price of 20,000 won. That is, the first selling price two days ago is 18,000 won. The price of the product the day before is 19,000 won, 1,000 won discounted from the recommended consumer price of 20,000 won. That is, the first selling price one day ago is 19,000 won. As described above, the server 150 may calculate the first selling price by using Equations 1 to 4.

Similarly, in the case of 'today', the server 150 may calculate the first selling price by using Equations 1 to 4. The server 150 may calculate 17,000 won, which is 3,000 won discounted from the consumer recommended price of 20,000 won, as the first selling price.

In addition, the server 150 may calculate the first selling price by using Equations 1 to 4, and at the same time, the server 150 calculates the additional discount price by using Equation 5 or 6 and predicting the second selling price based thereon. In this case, the server 150 may predict the second selling price by reflecting the additional discount price based on the first selling price calculated in 'today'.

For example, since the first selling price calculated in 'today' was 20,000 won and 3,000 won discounted, the server 150 sets the second selling price of 10,000 won with an additional discount of 7,000 won 'one day after' from 'today'. It can be predicted that there will be In the same principle, the server 150 may predict that 15,000 won with an additional discount of 2,000 won will be the second selling price 'two days later' from 'today'. Also, the server 150 may predict that 17,000 won will be the second selling price without additional discount after '3 days from today'. The server 150 may predict that the second selling price will be 13,000 won, which is an additional discount of 4,000 won, 'four days later' from 'today'. The server 150 may predict that the second selling price will be 18,000 won, which is an increase of 1,000 won, rather than 'five days from today'. The server 150 may predict that 19,000 won, which is an increase of 2,000 won, will be the second selling price '6 days later' from 'today'. The server 150 may predict that 17,000 won, which is not additionally discounted, will be the second selling price '7 days later' from 'today'. This is only an example, and is not limited thereto.

Through this, the selection range of the seller can be expanded through the pricing method and the price prediction method, and the selection of the product that best meets the seller's will can be induced.

The electronic device, server, or external device according to various embodiments of the present document described above, for example, a smartphone, a tablet PC, a mobile phone, a video phone, a desktop PC, a laptop PC, a personal digital assistant (PDA), It may include at least one of a portable multimedia player (PMP), an MP3 player, a mobile medical device, a camera, and a wearable device.

According to various embodiments, the wearable device may be an accessory type (eg, a watch, ring, bracelet, anklet, necklace, glasses, contact lens, or head-mounted-device (HMD)), a fabric or an integral type of clothing ( For example, it may include at least one of an electronic garment), a body attachable type (eg a skin pad or a tattoo), or a bioimplantable type (eg, an implantable circuit).

In some embodiments, the electronic device or the external device may be a home appliance. Home appliances are, for example, televisions, DVD players (Digital Video Disk players), audio systems, refrigerators, air conditioners, vacuum cleaners, ovens, microwaves, washing machines, air purifiers, set-top boxes, home automation It may include at least one of a home automation control panel, a security control panel, a TV box, a game console, an electronic dictionary, an electronic key, a camcorder, or an electronic picture frame.

In another embodiment, the electronic device, the external device, and the wearable device may include various medical devices (eg, various portable medical measuring devices (eg, a blood glucose monitor, a heart rate monitor, a blood pressure monitor, or a body temperature monitor), magnetic resonance angiography (MRA), and MRI. (magnetic resonance imaging, computed tomography (CT), imager, or ultrasound machine, etc.), navigation device, global navigation satellite system (GNSS), EDR (event data recorder), FDR (flight data recorder) ), automobile infotainment devices, home robots, or internet of things (e.g. light bulbs, sensors, electricity or gas meters, sprinkler devices, fire alarms, thermostats, street lights, exercise equipment) , hot water tank, heater, boiler, etc.) may include at least one of.

The embodiments disclosed in this document are provided for explanation and understanding of the disclosed and technical content, and do not limit the scope of the present invention. Accordingly, the scope of this document should be construed to include all modifications or various other embodiments based on the technical spirit of the present invention.

Claims (7)

receiving, by a processor, product information and pricing parameters corresponding to the product from the first electronic device;
receiving the subscription request for the product and counting the subscription quantity corresponding to the subscription request by the processor;
calculating, by the processor, a first selling price corresponding to the product according to a preset selling price calculation formula based on the subscription quantity and the pricing parameter; and
calculating, by the processor, an additional discount price by using a prediction parameter;
and predicting, by the processor, a second selling price corresponding to the product by a predetermined time point by reflecting the additional discount price in the first selling price;
The pricing parameters include an initial price, a marginal sales volume, a critical sales volume, and a marginal discount rate of the product,
The prediction parameters include a repurchase pattern, past sales volume, reservation purchase quantity and purchase increase/decrease,
Predicting the second selling price by the processor comprises:
A method of predicting the second selling price by using Equation 5 below.
[Equation 5]

In Equation 5, PRICE is the additional discount price,

is the number of reservation purchases corresponding to the day,

The sales volume of all products for 1 day (day),

is the number of buyers who repurchased within n weeks from n-1 weeks,

is the amount of purchases repurchased within n weeks from n-1 weeks,

is the weight for repurchase within n weeks from n-1 weeks,

is the period in which the product sales platform was created from the present,

is the increase/decrease in the sales ranking of the product and

indicates a preset constant.
delete The method according to claim 1,
Predicting the second selling price by the processor comprises:
A method of predicting the second selling price by using Equation 6 below.
[Equation 6]

In Equation 6, PRICE is the additional discount price,

is the number of reservation purchases corresponding to the day,

Sales of all products in one week,

is the number of buyers who repurchased within n weeks from n-1 weeks,

is the amount of purchases repurchased within n weeks from n-1 weeks,

is the weight for repurchase within n weeks from n-1 weeks,

is the period in which the product sales platform was created from the present,

is the increase/decrease in the sales ranking of the product and

indicates a preset constant.
delete The method according to claim 1,
Calculating the selling price of the product by the processor comprises:

Calculate the selling price of the product according to

is the selling price,

is the subscription quantity,

is the limit of sales,

silver threshold sales,

is the marginal discount rate,

is the initial price.
The method according to claim 1,
Calculating the selling price of the product by the processor comprises:

Calculate the selling price of the product according to

is the selling price,

is the subscription quantity,

is the limit of sales,

silver threshold sales,

is the marginal discount rate,

is the initial price.
In the server for calculating the selling price of a product,
a database for storing product information, pricing parameters, and prediction parameters provided from the first electronic device; and
Receives a subscription request for the product, counts the subscription quantity corresponding to the subscription request, and the first selling price corresponding to the product according to a preset sales price calculation formula based on the subscription quantity and the pricing parameter and a processor for calculating an additional discount price by using the prediction parameter, and predicting a second selling price corresponding to the product by a predetermined time point by reflecting the additional discount price in the first selling price;
The pricing parameters include the initial price, marginal sales volume, critical sales volume and marginal discount rate of the product, and the predictive parameters include repurchase patterns, past sales volume, reservation purchase quantity, and purchase increase/decrease,
The server predicts the second selling price by using Equation 5 below.
[Equation 5]

In Equation 5, PRICE is the additional discount price,

is the number of reservation purchases corresponding to the day,

The sales volume of all products for 1 day (day),

is the number of buyers who repurchased within n weeks from n-1 weeks,

is the amount of purchases repurchased within n weeks from n-1 weeks,

is the weight for repurchase within n weeks from n-1 weeks,

is the period in which the product sales platform was created from the present,

is the increase/decrease in the sales ranking of the product and

indicates a preset constant.

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