KR102608725B1 - Method, server and computer program for providing rpoducts automatic ordering service of unmanned store - Google Patents

Abstract

A method for providing an automatic product ordering service for unmanned stores, a server, and a computer program are provided. A method of providing an automatic product ordering service for an unmanned store according to an embodiment of the present invention is a method performed by a computing device, comprising the steps of collecting data on a plurality of unmanned stores, analyzing the collected data, and analyzing the plurality of unmanned stores. It includes generating order data for each of the unmanned stores and processing orders for each of the plurality of unmanned stores using the generated order data.

Description

Method of providing automatic product ordering service for unmanned stores, server and computer program {METHOD, SERVER AND COMPUTER PROGRAM FOR PROVIDING RPODUCTS AUTOMATIC ORDERING SERVICE OF UNMANNED STORE}

Various embodiments of the present invention relate to a method, server, and computer program for providing an automatic product ordering service in an unmanned store.

Untact is a compound word of the prefix Un, meaning negation, and Contact, meaning contact, and refers to purchasing goods or receiving services without meeting a person in person.

Recently, the culture of not wanting to communicate directly with people has spread, especially among the younger generation, and it is not uncommon to see employees in downtown or university restaurants taking orders through Kiosk 2 rather than directly. This phenomenon is recognized as a culture and is referred to as untact culture. Unmanned use in the retail industry is accelerating due to the spread of untact culture and the advantages of reducing labor costs.

In addition, due to the impact of the environment where highly contagious viruses such as COVID-19 are prevalent, non-face-to-face digital transformation (non-face-to-face payment, etc.) has accelerated across all fields, and as a result, online and non-face-to-face short-distance consumption has increased. An active distribution environment has been created.

With the spread of untact culture, the number of companies applying unmanned systems, especially in the retail industry, is increasing. Domestic unmanned stores that have adopted advanced technology at the level of advanced companies such as Amazon and Alibaba have also appeared. An unmanned system incorporating advanced technology can provide convenience to daily life and reduce labor costs and rent. However, there are problems with high technology costs and the inability to provide customer-friendly services.

The problem to be solved by the present invention is to analyze various data related to a plurality of unmanned stores to determine the ordered product and the order quantity of the product, and to process automatic ordering for the product based on the determined type and order quantity of the ordered product. It provides a method, server, and computer program to provide an automatic product ordering service for unmanned stores that can not only improve the convenience of store owners but also maximize the efficiency of product sales.

Another problem that the present invention aims to solve is to provide a product sales service in unmanned stores to improve the problems of conventional unmanned stores, thereby providing customer-friendly services such as product recommendations, event & promotion provision, etc. It provides automatic ordering service provision methods, servers, and computer programs.

The problems to be solved by the present invention are not limited to the problems mentioned above, and other problems not mentioned can be clearly understood by those skilled in the art from the description below.

A method of providing an automatic product ordering service for an unmanned store according to an embodiment of the present invention to solve the above-described problem is a method performed by a computing device, comprising the steps of collecting data about a plurality of unmanned stores, the collection It may include analyzing the generated data to generate order data for each of the plurality of unmanned stores, and processing orders for each of the plurality of unmanned stores using the generated order data.

In various embodiments, the collected data includes inventory data for a plurality of products displayed in each of the plurality of unmanned stores, and the step of generating the order data includes analyzing the inventory data to select one of the plurality of products. Selecting one or more products whose inventory is less than or equal to a preset number, and generating ordering data including ordering information for the selected one or more products - the ordering information includes information about the product to be ordered and the ordering quantity. It can be included.

In various embodiments, the step of generating the order data includes analyzing the collected data to score each of the plurality of products and assigning information to each of the plurality of products based on the scoring results for each of the plurality of products. It may include determining whether to process an order and the order quantity, and generating order data including information on whether to process an order and the order quantity for each of the determined plurality of products.

In various embodiments, the collected data includes sales volume data for each of a plurality of products displayed in the plurality of unmanned stores, and the step of scoring each of the plurality of products includes analyzing the sales volume data to Calculating the number of sales per one-time payment for each product, assigning a weight to each of the plurality of products based on the calculated number of sales per one-time payment, and using the assigned weight to determine the number of products sold per one-time payment. It may include a step of correcting the scoring results for each.

In various embodiments, the collected data includes sales volume data for each of a plurality of products displayed in the plurality of unmanned stores, and the step of scoring each of the plurality of products includes analyzing the sales volume data to Calculating a change in sales volume over time for each product, assigning a weight to each of the plurality of products based on the calculated change in sales volume over time, and using the assigned weight to each of the plurality of products. It may include a step of correcting the scoring result.

In various embodiments, the collected data includes sales volume data for each of a plurality of products displayed in the plurality of unmanned stores, and the step of scoring each of the plurality of products includes analyzing the sales volume data to Calculating seasonal sales volume and weather-specific sales volume for each of the products and seasonal information and weather information for a predetermined period based on the time of analyzing the sales data, and seasonal sales volume and weather for each of the calculated plurality of products It may include assigning a weight to each of the plurality of products based on individual sales volume, and correcting the scoring result for each of the plurality of products using the assigned weight.

In various embodiments, the collected data includes customer infrastructure data for each of the plurality of unmanned stores, and the step of scoring each of the plurality of products includes analyzing the customer infrastructure data to store each of the plurality of unmanned stores. Calculate the number of companies located nearby and the salary level of company employees, assign a weight to each of the plurality of products based on the calculated number of companies and the calculated salary level, and use the given weight to It may include correcting the scoring result for each of the plurality of products.

In various embodiments, the collected data includes sales volume data and customer infrastructure data for each of a plurality of products displayed in the plurality of unmanned stores, and the step of scoring each of the plurality of products includes the sales volume data and Analyzing the customer infrastructure data to calculate a repurchase rate for each of the plurality of products; assigning a weight to each of the plurality of products based on the calculated repurchase rate; and using the assigned weight to determine the repurchase rate for each of the plurality of products. It may include a step of correcting the scoring results for each product.

In various embodiments, the collected data includes sales volume data for each of a plurality of products displayed in the plurality of unmanned stores, and the step of scoring each of the plurality of products includes analyzing the sales volume data to Calculating the expected appropriate price for each unmanned store for each product, sequentially sorting the plurality of products starting from the product with the calculated expected appropriate price for each unmanned store, and based on the order in which each of the plurality of products is sorted. It may include differentially assigning weights to each of the plurality of products and correcting scoring results for each of the plurality of products using the differentially assigned weights.

In various embodiments, the collected data includes location data for each of the plurality of unmanned stores, and the step of generating the order data includes assigning a weight to each of the plurality of products based on the location data, It may include correcting the scoring result for each of the plurality of products using the assigned weight.

In various embodiments, the collected data includes social data about the plurality of unmanned stores and a plurality of products displayed in each of the plurality of unmanned stores, and the step of generating the order data includes collecting the social data from the social data. Extracting one or more keywords, assigning weights to each of the plurality of products based on the one or more extracted keywords, and correcting scoring results for each of the plurality of products using the assigned weights. may include.

In various embodiments, the collected data includes sales volume data and customer infrastructure data for each of a plurality of products displayed in the plurality of unmanned stores, and the step of generating the order data includes one of the plurality of unmanned stores. Attributes of a new unmanned store - the attributes include at least one of the size, location, and customer infrastructure of the unmanned store - selecting one or more unmanned stores having the same or similar attributes and sales volume data of the selected one or more unmanned stores It may include the step of analyzing and generating order data for placing an initial order for the new unmanned store.

In various embodiments, the step of processing the order includes performing a simulation of product sales at the first unmanned store using first order data generated by analyzing data about the first unmanned store, wherein the simulation The scenario applied to is set based on sales data of the first unmanned store, and based on the steps and results of the simulation, verification of the first order data is performed, and the first order data is It may include determining a processing method for the first order data based on the verification result.

According to another embodiment of the present invention to solve the above-described problem, a service providing server for automatically ordering products in an unmanned store includes a processor, a network interface, a memory, and a computer program loaded into the memory and executed by the processor. Including, the computer program includes instructions for collecting data on a plurality of unmanned stores, instructions for analyzing the collected data to generate order data for each of the plurality of unmanned stores, and the generated order. It may include instructions for processing orders for each of the plurality of unmanned stores using data.

A computer program recorded on a computer-readable recording medium according to another embodiment of the present invention for solving the above-described problem includes the steps of combining with a computing device to collect data on a plurality of unmanned stores, the collection A computer-readable record for executing the steps of analyzing the received data to generate order data for each of the plurality of unmanned stores and processing orders for each of the plurality of unmanned stores using the generated order data. Can be stored on media.

Other specific details of the invention are included in the detailed description and drawings.

According to various embodiments of the present invention, various data regarding a plurality of unmanned stores are analyzed to determine the ordered product and the order quantity of the product, and automatic ordering for the product is processed based on the determined type and order quantity of the ordered product, It has the advantage of not only improving the convenience of unmanned store owners, but also maximizing the efficiency of product sales.

In addition, by providing product sales services in unmanned stores to improve the problems of conventional unmanned stores, there is an advantage in being able to provide customer-friendly services such as product recommendations and provision of events & promotions.

The effects of the present invention are not limited to the effects mentioned above, and other effects not mentioned will be clearly understood by those skilled in the art from the description below.

Figure 1 is a diagram illustrating a system for providing a service for selling products in an unmanned store according to an embodiment of the present invention.
Figure 2 is a hardware configuration diagram of a server providing a service for selling products in an unmanned store according to another embodiment of the present invention.
Figure 3 is a flowchart of a method for providing product sales services in an unmanned store according to another embodiment of the present invention.
FIG. 4 is a flowchart illustrating a procedure for purchasing a product using a user terminal in various embodiments.
FIG. 5 is a flowchart illustrating a procedure for purchasing a product using a kiosk in an unmanned store in various embodiments.
FIG. 6 is a flowchart illustrating a personal registration procedure for using a service for selling products at an unmanned store, according to various embodiments.
Figure 7 is a flowchart illustrating a company registration process for using a service for selling products at an unmanned store, according to various embodiments.
Figure 8 is a flowchart for explaining a method of providing an automatic product ordering service in an unmanned store, according to various embodiments.
Figure 9 is a diagram illustrating a process for automatically ordering products in an unmanned store, according to various embodiments.
Figure 10 is a diagram illustrating data related to an unmanned store required to provide an automatic product ordering service for an unmanned store in various embodiments.
FIG. 11 is a flowchart illustrating a procedure for receiving a product purchased using a user terminal at a location and time desired by the purchaser, in various embodiments.
Figure 12 is a flowchart for explaining a procedure for providing advertisements suitable for buyers in various embodiments.
Figure 13 is a flowchart for explaining a procedure for selling alcohol products to a buyer, according to various embodiments.
Figure 14 is a diagram illustrating the process of data processing and automatic order processing using data generated in an unmanned store and artificial intelligence technology in various embodiments.

The advantages and features of the present invention and methods for achieving them will become clear by referring to the embodiments described in detail below along with the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below and may be implemented in various different forms. The present embodiments are merely provided to ensure that the disclosure of the present invention is complete and to provide a general understanding of the technical field to which the present invention pertains. It is provided to fully inform the skilled person of the scope of the present invention, and the present invention is only defined by the scope of the claims.

The terminology used herein is for describing embodiments and is not intended to limit the invention. As used herein, singular forms also include plural forms, unless specifically stated otherwise in the context. As used in the specification, “comprises” and/or “comprising” does not exclude the presence or addition of one or more other elements in addition to the mentioned elements. Like reference numerals refer to like elements throughout the specification, and “and/or” includes each and every combination of one or more of the referenced elements. Although “first”, “second”, etc. are used to describe various components, these components are of course not limited by these terms. These terms are merely used to distinguish one component from another. Therefore, it goes without saying that the first component mentioned below may also be a second component within the technical spirit of the present invention.

Unless otherwise defined, all terms (including technical and scientific terms) used in this specification may be used with meanings commonly understood by those skilled in the art to which the present invention pertains. Additionally, terms defined in commonly used dictionaries are not interpreted ideally or excessively unless clearly specifically defined.

As used in the specification, the term “unit” or “module” refers to a hardware component such as software, FPGA, or ASIC, and the “unit” or “module” performs certain roles. However, “part” or “module” is not limited to software or hardware. A “unit” or “module” may be configured to reside on an addressable storage medium and may be configured to run on one or more processors. Thus, as an example, a “part” or “module” refers to components such as software components, object-oriented software components, class components, and task components, processes, functions, properties, Includes procedures, subroutines, segments of program code, drivers, firmware, microcode, circuits, data, databases, data structures, tables, arrays, and variables. The functionality provided within components and “parts” or “modules” can be combined into smaller components and “parts” or “modules” or into additional components and “parts” or “modules”. Could be further separated.

Spatially relative terms such as “below”, “beneath”, “lower”, “above”, “upper”, etc. are used as a single term as shown in the drawing. It can be used to easily describe the correlation between a component and other components. Spatially relative terms should be understood as terms that include different directions of components during use or operation in addition to the directions shown in the drawings. For example, if a component shown in a drawing is flipped over, a component described as “below” or “beneath” another component will be placed “above” the other component. You can. Accordingly, the illustrative term “down” may include both downward and upward directions. Components can also be oriented in other directions, so spatially relative terms can be interpreted according to orientation.

In this specification, a computer refers to all types of hardware devices including at least one processor, and depending on the embodiment, it may be understood as encompassing software configurations that operate on the hardware device. For example, a computer can be understood to include, but is not limited to, a smartphone, tablet PC, desktop, laptop, and user clients and applications running on each device.

In addition, in this specification, a method of providing a product sales service in an unmanned store is applied to an unmanned store where there is no permanent staff working in the store, and performs operations such as selling products in the unmanned store, providing advertising and promotions, inventory management, and automatic order processing. and a method of providing an automatic product ordering service in an unmanned store are explained, but this is only an example and is not limited to this, and can also be applied to general stores with personnel working in the store at all times.

Hereinafter, embodiments of the present invention will be described in detail with reference to the attached drawings.

Each step described in this specification is described as being performed by a computer, but the subject of each step is not limited thereto, and depending on the embodiment, at least part of each step may be performed in a different device.

Figure 1 is a diagram illustrating a system for providing a service for selling products in an unmanned store according to an embodiment of the present invention.

The unmanned store product sales service provision system according to an embodiment of the present invention may include an unmanned store product sales service provision server 100, a user terminal 201, a kiosk 202, and an external server 300. .

Here, the product sales service provision system of the unmanned store shown in FIG. 1 is according to one embodiment, and its components are not limited to the embodiment shown in FIG. 1, and may be added, changed, or deleted as necessary. there is.

In one embodiment, the product sales service providing server 100 of an unmanned store may provide a product sales service of an unmanned store.

Here, unmanned stores can be opened in banks, general private companies, 24-hour special companies (e.g. logistics centers), sports facilities (indoor and outdoor), lodging facilities (resorts, pensions, general hotels in downtown areas, etc.), general residential areas, etc. , may mean a store that does not have personnel working full-time in the store. However, it is not limited to this.

In addition, here, the product sales service of the unmanned store receives input of one or more products displayed in the unmanned store, performs a payment process for the entered product, and sells the product in response to the completion of the payment process. This may refer to a service that approves and prints sales data (e.g. receipts) accordingly. However, it is not limited to this.

In various embodiments, the unmanned store product sales service providing server 100 may provide software (e.g., an application) for providing the unmanned store product sales service to each of the user terminal 201 and the kiosk 202. . Thereafter, each of the user terminal 201 and the kiosk 202 can independently execute and provide the product sales service of the unmanned store by running software provided from the product sales service providing server 100 of the unmanned store.

In one embodiment, the user terminal 201 (e.g., the store owner terminal of the unmanned store and the purchaser terminal of the unmanned store) may be connected to the product sales service providing server 100 of the unmanned store through the network 400, and the unmanned store A product sales service of an unmanned store can be provided from the product sales service provision server 100 of .

Here, the network 400 may mean a connection structure that allows information exchange between nodes, such as a plurality of terminals and servers. For example, the network 400 includes a local area network (LAN), a wide area network (WAN), the World Wide Web (WWW), a wired and wireless data communication network, a telephone network, and a wired and wireless television communication network. do.

In addition, here, the wireless data communication network includes 3G, 4G, 5G, 3GPP (3rd Generation Partnership Project), 5GPP (5th Generation Partnership Project), LTE (Long Term Evolution), WIMAX (World Interoperability for Microwave Access), and Wi-Fi (Wi-Fi). Fi), Internet, LAN (Local Area Network), Wireless LAN (Wireless Local Area Network), WAN (Wide Area Network), PAN (Personal Area Network), RF (Radio Frequency), Bluetooth network, It includes, but is not limited to, Near-Field Communication (NFC) networks, satellite broadcasting networks, analog broadcasting networks, and Digital Multimedia Broadcasting (DMB) networks.

In various embodiments, the user terminal 201 may receive a product sales service from an unmanned store by downloading, installing, and executing an application provided from the product sales service providing server 100 of an unmanned store. To this end, the user terminal 201 may include an operating system (eg, Android, iOS, etc.) capable of running applications.

In various embodiments, the user terminal 201 is connected to the unmanned store product sales service providing server 100 through the network 400, and the unmanned store product sales service providing server 100 provides unmanned store products. The sales service provision user interface (UI) can be printed. To this end, the user terminal 201 may be a smartphone that includes a display in at least a portion of the user terminal 201. However, it is not limited to this, and the user terminal 201 is a wireless communication device that guarantees portability and mobility, and includes navigation, Personal Communication System (PCS), Global System for Mobile communications (GSM), Personal Digital Cellular (PDC), and PHS. (Personal Handyphone System), PDA (Personal Digital Assistant), IMT (International Mobile Telecommunication)-2000, CDMA (Code Division Multiple Access)-2000, W-CDMA (W-Code Division Multiple Access), Wibro (Wireless Broadband Internet) It may include, but is not limited to, all types of handheld-based wireless communication devices such as terminals, smartpads, tablet PCs, etc.

In one embodiment, the kiosk 202 is connected to the product sales service providing server 100 of the unmanned store through the network 400, and receives and executes software from the product sales service providing server 100 of the unmanned store, Buyers can provide product sales services in unmanned stores through the kiosk 202.

In various embodiments, the kiosk 202 may include a display in at least a portion of the kiosk 202 to output the unmanned store product sales service providing UI provided by the unmanned store product sales service provision server 100 as described above.

In various embodiments, the kiosk 202 may be placed in an unmanned store, and a plurality of kiosks 202 may be placed in one unmanned store. However, it is not limited to this.

In one embodiment, the external server 300 may be connected to the product sales service providing server 100 of the unmanned store through the network 400, and the product sales service providing server 100 of the unmanned store may sell products of the unmanned store. You can store and manage various information and data necessary to provide services.

In addition, the external server 300 can receive, store, and manage various information and data generated in the process of the unmanned store product sales service providing server 100 providing the unmanned store product sales service. For example, the external server 300 may be a storage server separately provided outside the product sales service provision server 100 of an unmanned store, but is not limited thereto. Hereinafter, with reference to FIG. 2, the hardware configuration of the unmanned store product sales service providing server 100 that provides the unmanned store product sales service will be described.

Figure 2 is a hardware configuration diagram of a server providing a service for selling products in an unmanned store according to another embodiment of the present invention.

Referring to FIG. 2, a product sales service providing server 100 (hereinafter referred to as “computing device 100”) in an unmanned store according to another embodiment of the present invention is operated by one or more processors 110 and the processor 110. It may include a memory 120 that loads the computer program 151 to be executed, a bus 130, a communication interface 140, and a storage 150 that stores the computer program 151. Here, only components related to the embodiment of the present invention are shown in Figure 2. Accordingly, anyone skilled in the art to which the present invention pertains will know that other general-purpose components may be included in addition to the components shown in FIG. 2.

The processor 110 controls the overall operation of each component of the computing device 100. The processor 110 includes a Central Processing Unit (CPU), Micro Processor Unit (MPU), Micro Controller Unit (MCU), Graphic Processing Unit (GPU), or any other type of processor well known in the art of the present invention. It can be.

Additionally, the processor 110 may perform operations on at least one application or program for executing methods according to embodiments of the present invention, and the computing device 100 may include one or more processors.

In various embodiments, the processor 110 includes random access memory (RAM) (not shown) and read memory (ROM) that temporarily and/or permanently store signals (or data) processed within the processor 110. -Only Memory, not shown) may be further included. Additionally, the processor 110 may be implemented in the form of a system on chip (SoC) that includes at least one of a graphics processing unit, RAM, and ROM.

Memory 120 stores various data, commands and/or information. Memory 120 may load a computer program 151 from storage 150 to execute methods/operations according to various embodiments of the present invention. When the computer program 151 is loaded into the memory 120, the processor 110 can perform the method/operation by executing one or more instructions constituting the computer program 151. The memory 120 may be implemented as a volatile memory such as RAM, but the technical scope of the present disclosure is not limited thereto.

Bus 130 provides communication functionality between components of computing device 100. The bus 130 may be implemented as various types of buses, such as an address bus, a data bus, and a control bus.

The communication interface 140 supports wired and wireless Internet communication of the computing device 100. Additionally, the communication interface 140 may support various communication methods other than Internet communication. To this end, the communication interface 140 may be configured to include a communication module well known in the technical field of the present invention. In some embodiments, communication interface 140 may be omitted.

Storage 150 may store the computer program 151 non-temporarily. When performing a process for providing an automatic product ordering service for an unmanned store through the computing device 100, the storage 150 may store various types of information necessary to provide a process for providing an automatic product ordering service for an unmanned store.

The storage 150 is a non-volatile memory such as Read Only Memory (ROM), Erasable Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), flash memory, a hard disk, a removable disk, or a device well known in the technical field to which the present invention pertains. It may be configured to include any known type of computer-readable recording medium.

The computer program 151, when loaded into the memory 120, may include one or more instructions that cause the processor 110 to perform methods/operations according to various embodiments of the present invention. That is, the processor 110 can perform the method/operation according to various embodiments of the present invention by executing the one or more instructions.

In one embodiment, the computer program 151 includes collecting data on a plurality of unmanned stores, analyzing the collected data to generate order data for each of the plurality of unmanned stores, and using the generated order data. It may include one or more instructions for performing a method of providing an automatic product ordering service for an unmanned store, including the step of processing orders for each of a plurality of unmanned stores.

The steps of the method or algorithm described in connection with embodiments of the present invention may be implemented directly in hardware, implemented as a software module executed by hardware, or a combination thereof. The software module may be RAM (Random Access Memory), ROM (Read Only Memory), EPROM (Erasable Programmable ROM), EEPROM (Electrically Erasable Programmable ROM), Flash Memory, hard disk, removable disk, CD-ROM, or It may reside on any type of computer-readable recording medium well known in the art to which the present invention pertains.

The components of the present invention may be implemented as a program (or application) and stored in a medium in order to be executed in conjunction with a hardware computer. Components of the invention may be implemented as software programming or software elements, and similarly, embodiments may include various algorithms implemented as combinations of data structures, processes, routines or other programming constructs, such as C, C++, , may be implemented in a programming or scripting language such as Java, assembler, etc. Functional aspects may be implemented as algorithms running on one or more processors. Hereinafter, a method of providing a product sales service in an unmanned store performed by the computing device 100 will be described with reference to FIG. 3 .

Figure 3 is a flowchart of a method for providing product sales services in an unmanned store according to another embodiment of the present invention.

The method of providing a product sales service in an unmanned store according to FIG. 3 is described as being performed by the computing device 100, but is not limited thereto, and the user terminal 201 (or the processor within the user terminal 201) is the computing device. A method of providing a product sales service in an unmanned store is performed by executing an application provided from 100, or the kiosk 202 (or a processor in the kiosk 202) executes software provided by the computing device 100 to sell products in an unmanned store. It can be implemented in the form of performing a sales service provision method.

Referring to FIG. 3, in step S110, the computing device 100 may receive one or more products to be purchased from the buyer.

For example, the computing device 100 inputs one or more products to be purchased from the buyer through the product sales service UI of an unmanned store that is output as the application is executed on the buyer's user terminal 201 (e.g., the user terminal ( 201) can receive touch input through the display touch panel.

In addition, the computing device 100 inputs one or more products to be purchased from the buyer through the product sales service UI of the unmanned store, which is output as the software is executed in the kiosk 202 (e.g., through the display touch panel of the kiosk 202). (touch input through) can be received.

Additionally, the computing device 100 can receive one or more products to be purchased by recognizing the barcode printed on each of the one or more products through the barcode reader included in the kiosk 202. However, it is not limited to this, and any method of receiving one or more products to be purchased from the buyer can be applied.

In step S120, the computing device 100 may perform a payment process for one or more products entered in step S110.

Here, the payment process may refer to a process of paying for one or more products entered by the buyer. For example, the payment process includes the operation of guiding payment details (e.g., the operation of guiding information about one or more products entered by the buyer and the payment amount for one or more products), the operation of selecting a payment method for the payment amount, The operation of processing the payment amount using a payment method may be included. However, it is not limited to this, and other general operations applicable to the payment process (e.g., discount and accumulation selection operation, point use selection operation, etc.) may be additionally applied.

In various embodiments, the computing device 100 may receive a user input indicating a payment application for one or more entered products (e.g., selecting a payment request button placed on the UI) after the buyer completes the input for one or more products. When entering a user input), a payment process can be performed for one or more products entered by the buyer. However, it is not limited to this.

In various embodiments, the computing device 100 may include a camera module (e.g., an internal camera module provided on the user terminal 201 or the kiosk 202, an external camera module connected to the user terminal 201 or the kiosk 202). camera module) can be used to collect product raw material information printed on one or more products, and determine whether the product is suitable for the buyer to consume based on the allergy and avoidance food information entered by the buyer and the raw material information of the product. can be determined, and the judgment result can be provided to the buyer's user terminal 201 or kiosk 202.

At this time, if the buyer logs in to his/her account before selecting the product, the computing device 100 selects the product from the buyer and simultaneously collects the allergy and avoidance food information (entered at the time of membership registration) entered by the buyer. By providing the result determined according to the product's raw material information and the product's raw material information to the user terminal 201 or kiosk 202, the buyer can prevent the purchaser from purchasing the product if the product is judged to be unsuitable.

Meanwhile, if the buyer logs in to his or her account after completing payment for the product, the computing device 100 cannot confirm information about the buyer until sales data is generated by performing payment. At the point when the information is recognized (e.g., when sales data according to payment is generated), the user immediately receives the results determined based on the allergy and avoidance food information already entered by the purchaser (information entered at the time of membership registration) and the raw material information of the product. It can be provided through the terminal 201 or kiosk 202 so that if the buyer determines that the product is not suitable, he or she will not consume the product or receive a refund.

In step S130, when the payment process for one or more products is completed through step S120, the computing device 100 approves the sale of the one or more products paid in response to the completion of the payment process, and approves the sale of the one or more products. You can create and output sales data about sales.

Here, sales data refers to data containing various information such as information about one or more products, price information, payment method, and whether the payment process is completed. For example, sales data may be, but is not limited to, a receipt (paper receipt or electronic receipt).

In various embodiments, the computing device 100 generates sales data regarding the sale of one or more products, but determines an output method (e.g., electronic receipt or paper receipt) of the sales data or outputs the sales data according to the buyer's request. You may not. However, it is not limited to this. Hereinafter, with reference to FIGS. 4 and 5, the method of selling products through the buyer's user terminal 201 and the method of selling products through the kiosk 202 will be described in more detail.

FIG. 4 is a flowchart illustrating a procedure for purchasing a product using a user terminal in various embodiments.

The procedure for purchasing a product using the buyer's user terminal according to FIG. 4 is described as being performed by the computing device 100, but is not limited to this and is performed by the user terminal 201 (or the processor within the user terminal 201). ) may be implemented in the form of performing a procedure for purchasing a product using the user terminal 201 by executing an application provided from the computing device 100.

Referring to FIG. 4, in step S210, the computing device 100 may execute an application. For example, the computing device 100 may execute the application according to a user input of selecting an application for providing a product sales service at an unmanned store from among a plurality of applications pre-installed on the user terminal 201 by the purchaser.

In various embodiments, the computing device 100 may provide the user terminal 201 with a URL of a web page providing a product sales service of an unmanned store, and a buyer may access the page providing a product sales service of an unmanned store through the URL. You can. However, it is not limited to this.

In step S220, the computing device 100 may select one or more products that the buyer wishes to purchase. For example, the computing device 100 may provide a UI that outputs a product list containing information about a plurality of products sold at an unmanned store as the application is executed on the buyer's user terminal 201. , Through the UI, buyers can select one or more products they wish to purchase among multiple products included in the product list.

In various embodiments, the computing device 100 may receive one or more keywords related to a product from a buyer and select one or more products corresponding to one or more input keywords. For example, the computing device 100 may provide a UI to search for a product to be purchased, and through the UI, the buyer may input one or more keywords to search for a specific product, and search according to the inputted keyword. One or more products (or one product selected by the buyer among one or more searched products) can be selected.

In various embodiments, the computing device 100 provides a UI to the user terminal 201, receives one or more products to be purchased from the buyer through the UI, and sells products at an unmanned store provided by the computing device 100. UI is provided only when a member registers for the service, or the buyer can select one or more products. To this end, the computing device 100 determines whether the buyer who wishes to purchase the product is registered as a member of the product sales service of the unmanned store, and if not, may provide a membership registration process for membership registration. . Here, the membership registration process refers to the process of registering a buyer account to use the product sales service of an unmanned store. A more detailed description of the membership registration process will be provided with reference to Figures 6 and 7, which will be described later.

In step S230, the computing device 100 may determine a payment method for paying for one or more products selected in step S220.

In various embodiments, the computing device 100 may process payment for one or more products using at least one of cash and a card according to the buyer's request.

In various embodiments, when receiving a request from a purchaser to use first points, the computing device 100 may pay at least a portion of the payment amount for one or more products with the first points according to a preset first rate. Here, the first point may mean an external point such as an affiliated card company point or an affiliated telecommunications company point, but is not limited thereto.

In various embodiments, when receiving a request from a buyer to use second points, the computing device 100 may pay at least a portion of the payment amount for one or more products with the second points according to a preset second rate. Here, the second point may refer to a company welfare point issued from each of a plurality of companies affiliated with the unmanned store.

In various embodiments, the computing device 100 may pay at least a portion of the payment amount for one or more products by simultaneously applying the first point and the second point, and may pay for one or more products using only the first point and the second point. You can pay the entire amount for the product. However, it is not limited to this.

In step S240, the computing device 100 may perform a payment process for one or more products. For example, the computing device 100 may pay for one or more products according to the payment method determined in step S230. Here, the payment process performance operation performed by the computing device 100 may be performed in the same or similar form as the payment process performance operation (eg, step S120) of FIG. 3, but is not limited thereto.

In step S250, the computing device 100 approves the sale of one or more products when the payment process for one or more products is completed through step S240, and collects sales data (e.g., electronic receipt data, transaction history data, etc.) can be generated and output. Here, the sales data output operation performed by the computing device 100 may be performed in the same or similar form as the sales data output operation (eg, step S130) of FIG. 3, but is not limited thereto.

FIG. 5 is a flowchart illustrating a procedure for purchasing a product using a kiosk in an unmanned store in various embodiments.

The procedure for purchasing a product using a kiosk in an unmanned store according to FIG. 5 is described as being performed by the computing device 100, but is not limited thereto, and the kiosk 202 (or the processor within the kiosk 202) It may be implemented in the form of performing a procedure for purchasing a product using a kiosk by executing software provided from the computing device 100.

Referring to FIG. 5 , in step S310, the computing device 100 may identify one or more products that the buyer wishes to purchase through product selection and barcode recognition operations.

For example, a buyer can pick up a product he or she wants to purchase among a plurality of products displayed in an unmanned store and input the barcode printed on the product he or she wants to purchase into a barcode reader provided in the kiosk 202. Afterwards, the computing device 100 can scan the barcode of the product the buyer wishes to purchase through a barcode reader, and identify the product the buyer wishes to purchase based on the type of the scanned barcode.

In various embodiments, the computing device 100 may provide a UI that outputs a product list including information about a plurality of products sold in an unmanned store through a display provided in the kiosk 202, and may provide a UI that outputs a product list including information about a plurality of products sold in an unmanned store through the UI. The buyer can select one or more products he or she wishes to purchase among a plurality of products included in the product list. However, it is not limited to this.

In step S320, the computing device 100 may run an application for providing a product sales service in an unmanned store and generate a one-time security QR code for security.

In step S330, the computing device 100 may determine a payment method for payment of one or more products identified in step S310. Here, the operation of determining the payment method performed by the computing device 100 may be performed in the same or similar form as the operation of determining the payment method of FIG. 4 (e.g., step S230), but is not limited thereto.

In step S340, the computing device 100 may perform a payment process for one or more products. Here, the payment process performed by the computing device 100 may be performed in the same or similar form as the payment process performed in FIG. 4 (eg, step S240), but is not limited thereto.

In step S350, when the payment process for one or more products is completed through step S340, the computing device 100 may approve the sale of one or more products and generate and output sales data (e.g., paper receipt). there is. Here, the sales data output operation performed by the computing device 100 may be performed in the same or similar form as the sales data output operation (eg, step S130) of FIG. 3, but is not limited thereto. Hereinafter, with reference to FIGS. 6 and 7, the membership registration process performed by the computing device 100 will be described.

FIG. 6 is a flowchart illustrating a personal registration procedure for using a service for selling products at an unmanned store, according to various embodiments.

The personal registration procedure for using the product sales service of the unmanned store according to FIG. 6 is described as being performed by the computing device 100, but is not limited thereto, and is performed by the user terminal 201 (or the user terminal 201). a processor within the kiosk 202 (or a processor within the kiosk 202) performs a personal sign-up process by executing an application provided from the computing device 100, or a personal sign-up procedure is performed by the kiosk 202 (or a processor within the kiosk 202) executing software provided from the computing device 100 It can be implemented in the form of performing .

Referring to FIG. 6, in step S410, the computing device 100 may receive a personal subscription application from the purchaser. For example, the computing device 100 may provide a UI for performing a membership registration process, and may receive a personal membership application input from a purchaser by obtaining user input regarding a personal membership application through the UI. However, it is not limited to this.

In step S420, the computing device 100 may perform an identity authentication process for the purchaser who entered the personal subscription application. For example, the computing device 100 may use an identity authentication method using a mobile phone, an identity authentication method using an ID card, an identity authentication method using a card (credit card and check card), and an identity authentication method using a QR code (e.g., PASS). The identity authentication process for the purchaser may be performed using at least one of the following identity authentication methods. However, it is not limited to this, and any method that can perform the identity authentication process for the purchaser can be applied.

In step S430, the computing device 100 may issue an account for the purchaser who entered the personal subscription application. For example, the computing device 100 may receive an ID and password input from the purchaser, and may issue an account for the purchaser using the ID and password entered by the purchaser.

In various embodiments, the computing device 100 may receive personal information from a user along with a personal registration application, and combine N random numbers and letters based on the input personal information to create an ID and password corresponding to the purchaser. can be issued automatically. However, it is not limited to this.

In step S440, the computing device 100 may register personal payment information for the buyer. For example, when the payment method for a product is a card, the computing device 100 may register information about one or more cards to be used for payment, and when the payment method for a product is a bank transfer, the computing device 100 may register information about one or more cards to be used for payment. You can register information about it. However, it is not limited to this, and various information related to payment, such as information about the first point to be used when paying at least part of the payment amount for the product with the first point, can be registered. However, it is not limited to this.

Figure 7 is a flowchart illustrating a company registration process for using a service for selling products at an unmanned store, according to various embodiments.

The company registration process for using the product sales service of the unmanned store according to FIG. 7 is described as being performed by the computing device 100, but is not limited to this and is performed by the user terminal 201 (or the user terminal 201). The processor within the kiosk 202 (or the processor within the kiosk 202) performs a company sign-up procedure by executing an application provided from the computing device 100, or the kiosk 202 (or a processor within the kiosk 202) performs a company sign-up procedure by executing software provided from the computing device 100. It can be implemented in the form of performing .

Referring to FIG. 7, in step S510, the computing device 100 may receive an application for company membership from the purchaser. For example, the computing device 100 may provide a UI for performing a membership registration process with the purchaser's user terminal 201 or kiosk 202, and obtain user input regarding the application for company membership through the UI. , you can receive an application for company membership from the buyer. However, it is not limited to this.

In step S520, the computing device 100 may receive a company selection from the purchaser. For example, the computing device 100 may provide, through a UI, a company list containing information about a plurality of companies with which a partnership agreement has been made in advance in relation to the use of company welfare points, and a plurality of lists included in the company list. You can select any one of the companies as your affiliated company.

In various embodiments, the computing device 100 receives one or more keywords (e.g., the name of the affiliated company, the business registration number of the affiliated company, etc.) related to the affiliated company from the user, and selects a company corresponding to the one or more input keywords as a purchaser. You can select your company as an affiliated company. However, it is not limited to this.

In step S530, the computing device 100 may perform an identity authentication process for the purchaser who has entered an application to join the company. Here, the identity authentication procedure performed by the computing device 100 may be performed in the same or similar form as the identity authentication procedure (eg, step S420) of FIG. 6, but is not limited thereto.

In step S540, the computing device 100 transmits the information about the buyer who entered the application for company membership and the contents of the application for company membership entered by the buyer to the company server selected by the buyer or the user terminal 201 of the person in charge in step S520. You can.

At this time, the computing device 100 transmits information about the purchaser who entered the application to join the company and the contents of the application to join the company entered by the purchaser to the user terminal 201 of the company server or the person in charge of the company. You can query information about whether a person is employed at the company and the amount of company welfare points paid to the buyer. However, it is not limited to this.

In step S550, the computing device 100 may issue an account for the buyer who entered an application to join the company. Here, the operation of issuing an account for the purchaser performed by the computing device 100 may be performed in the same or similar form as the operation of issuing an account for the purchaser in FIG. 6 (e.g., step S430), but is limited thereto. It doesn't work.

In various embodiments, the computing device 100 responds to delivering information about the purchaser who entered the application to join the company and the contents of the application to join the company entered by the purchaser in step S540, when approval is processed by the person in charge of the company. Accounts can only be issued to buyers

In step S560, the computing device 100 may provide company welfare points issued by the company to the buyer's account issued through step S550.

In step S570, the computing device 100 may register personal payment information for the buyer. Here, the operation of registering the personal payment information for the buyer may be performed in the same or similar form as the operation of registering the personal payment information of FIG. 6 (e.g., step S440), but is not limited thereto.

In various embodiments, the computing device 100 performs an operation of selecting an affiliated company (e.g., step S520) when the purchaser who has requested a company subscription procedure is a member who has already registered according to the individual subscription procedure of FIG. 6, and sends a message to the affiliated company representative. Only the operation of transmitting the subscription application (e.g., step S540) and the operation of paying the company's welfare points (e.g., step S560) are additionally performed, and the performance results are stored in the buyer's account created according to the personal subscription procedure in FIG. 6. It can be reflected. Hereinafter, with reference to FIGS. 8 to 10, a method of providing an automatic product ordering service in an unmanned store performed by the computing device 100 will be described.

Figure 8 is a flowchart for explaining a method of providing an automatic ordering service for products in an unmanned store in various embodiments, Figure 9 is a diagram showing a process for automatically ordering products in an unmanned store in various embodiments, and Figure 10 is a diagram illustrating data related to an unmanned store required to provide an automatic product ordering service for an unmanned store in various embodiments.

The method of providing the product automatic ordering service in an unmanned store according to FIGS. 8 to 10 is described as being performed by the computing device 100, but is not limited thereto, and is performed by the user terminal 201 (or the user terminal 201) of the unmanned store owner. The processor within the kiosk 202 may execute an application provided from the computing device 100, or the kiosk 202 (or a processor within the kiosk 202) may execute software provided from the computing device 100. there is.

Referring to FIGS. 8 to 10 , in step S610, the computing device 100 may collect data regarding a plurality of unmanned stores.

Here, the data regarding the plurality of unmanned stores 10 includes information on the number of people, sales, number of sales per product, number of sales per payment, time of sale, sales volume of the previous day/month/previous year, etc., as shown in FIG. 10. Store (sales volume) data, season/weather data including information on season/season, yellow dust/heat wave/cold wave/humidity, snow/rain, etc., salary level, repurchase status, member age, batch store attributes, etc. Product data including information on infrastructure/demographic data, price, category/type, release date/production date, reviews/ratings, brand, revenue per sale, etc., information on health, SNS, main ingredients, diet/functionality, etc. It may include issue data and other data (e.g., stock quantity data for multiple products displayed in each of the multiple unmanned stores 10, etc.), but is not limited thereto.

In step S620, the computing device 100 may generate order data for each of the plurality of unmanned stores 10 by analyzing data related to the plurality of unmanned stores 10 collected in step S610.

Here, the order data is data for order processing for a specific product, and may include information about the product, whether the product has been ordered, and information about the order quantity of the product.

In various embodiments, when the first product is selected as an order target, the computing device 100 may generate order data so that the selected first product is ordered by a preset order amount. However, it is not limited to this, and the order quantity for the first product is determined according to the results of analyzing data on a plurality of unmanned stores 10 (e.g., determined based on expected sales volume), or is determined by the plurality of unmanned stores 10. Depending on the results of analyzing related data, a decision may be made to correct the pre-set order quantity (e.g., if sales volume is judged to increase, increase the order quantity set in the assessment by a predetermined percentage).

In various embodiments, the computing device 100 analyzes inventory data for a plurality of products displayed in each of a plurality of unmanned stores 10, and selects one or more products whose inventory amount is less than or equal to a preset number among the plurality of products, Order data containing ordering information for one or more selected products (e.g., information about the product to be ordered and order quantity) can be created. For example, the computing device 100 may select a product whose inventory amount is 30% or less as a product to be ordered.

At this time, the computing device 100 may generate order data and set a preset number based on the time at which the order is to be processed using the generated order data. For example, the computing device 100 may select a product with an inventory of 30% or less as the product to be ordered when the time at which the order is to be processed is Monday, Tuesday, or Wednesday, and when the time at which the order is to be processed is Thursday or Friday. In this case, considering weekends or holidays, products with less than 40% of inventory can be selected as products to be ordered. However, it is not limited to this.

In various embodiments, the computing device 100 scores each of a plurality of products by analyzing data related to the plurality of unmanned stores 10 collected in step S610, and provides ordering data based on the scoring results for each of the plurality of products. can be created.

First, the computing device 100 may analyze data regarding the plurality of unmanned stores 10 and score each of the plurality of products.

Here, the method of scoring each of a plurality of products by analyzing data related to a plurality of unmanned stores 10 is based on a score table for a plurality of items (e.g., sales volume, unit price, etc.) for a specific product included in the data. A model that calculates a score for each of multiple products (e.g., 1 point if the sales volume of the first product is less than or equal to the first size, 2 points if the sales volume of the first product is less than or equal to the second size, and 3 points if the sales volume of the first product is greater than the second size. A model that calculates the final score by adding up the scores given to each item may be applied, but the method is not limited to this, and the score for each of multiple products is calculated by analyzing data according to preset standards. Any method of calculating can be applied.

At this time, in order to prevent products with a large inventory from being unnecessarily ordered in the unmanned store 10, the computing device 100 excludes one or more products whose inventory is above a certain level among the plurality of products from the scoring target, that is, from the ordering target. You can. However, it is not limited to this, and even if the inventory quantity is large, additional orders may be necessary. Based on the inventory quantity of each of the plurality of products, the plurality of products are sorted in ascending order from the product with the lowest inventory quantity, and based on the sorted order. By differentially assigning weights so that the product located at the top is given the greatest weight and the product located at the bottom is given the smallest weight, it can be set so that products with low inventory can be ordered first.

In various embodiments, the computing device 100 may analyze sales volume data for each of a plurality of products displayed in a plurality of unmanned stores 10 to calculate the number of sales per one payment for each of the plurality of products. , weights can be assigned to each of the plurality of products based on the calculated number of sales per payment, and the scoring results for each of the plurality of products can be corrected based on the weights. Here, the weight is set to have a value within a preset range (e.g., 1 to 2), but may be set in proportion to the number of sales per one-time payment.

For example, when the number of units sold per payment for the first product is greater than or equal to the first standard number, the computing device 100 assigns a weight of 1.1, and adds the assigned weight of 1.1 to the scoring result for the first product by 1.1. By multiplying, the scoring result for the first product can be corrected. In other words, small products in which multiple products are sold at one time may run out of inventory faster than large products, so these products can be set to be ordered first.

Here, the method of correcting the scoring result for a product using a weight is explained as multiplying the final scoring result (e.g., the sum of scores for each of a plurality of items) by the weight assigned. However, this is an example to more easily explain how to correct scores using weights, and since the weights for each of a plurality of items can be set individually, the score of the item related to the weight among the plurality of items It is desirable to apply it in the form of individually multiplying the weights.

In various embodiments, the computing device 100 may analyze sales volume data to calculate a change in sales volume over time for each of a plurality of products, and may calculate a change in sales volume over time for each of the plurality of products based on the calculated change in sales volume over time. Weights can be assigned, and the scoring results for each of a plurality of products can be corrected using the assigned weights.

For example, the computing device 100 analyzes sales volume data and determines that the change in sales volume of the first product over time has a positive value, that is, that the sales volume of the first product is continuously increasing. By assigning weight to the first product, you can set it so that products whose sales volume is continuously increasing are ordered first.

In various embodiments, the computing device 100 may calculate sales volume by season and sales volume by weather for each of a plurality of products by analyzing sales volume data, and may provide seasonal information for a predetermined period based on the time of analyzing the sales volume data. And, weights can be assigned to each of the plurality of products based on the weather information and the calculated sales volume by season and sales volume by weather for each of the plurality of products, and the scoring results for each of the plurality of products can be corrected using the assigned weights. You can.

For example, the computing device 100 determines that the rainy season begins based on seasonal information and weather information for a predetermined period based on the time of analyzing sales data, and seasonal sales volume and weather information for each of a plurality of products. If it is determined that the sales volume of the first product on a rainy day is high based on the individual sales volume, greater weight may be given to the first product than other products with relatively low sales volume on the rainy day. In addition, the computing device 100 assigns weights so that more seasonal foods (e.g., strawberry cookies, etc.) can be ordered during the seasonal period based on seasonal information and weather information for a certain period of time, thereby It can be set so that suitable products can be ordered first.

In various embodiments, the computing device 100 analyzes customer infrastructure data for each of a plurality of unmanned stores 10 to calculate the number of companies located near each of the plurality of unmanned stores 10 and the salary level of company employees. And, a weight can be assigned to each of the plurality of products based on the calculated number of companies and salary levels, and the scoring results for each of the plurality of products can be corrected using the assigned weight.

For example, the computing device 100 assigns a higher weight to expensive products as the salary level of employees of companies near the unmanned store 10 is higher, and assigns a higher weight to low-priced products as the salary level is lower, It is set so that relatively high-priced products are ordered in unmanned stores (10) located near companies with high salary levels, and relatively low-priced products are ordered in unmanned stores (10) located near companies with relatively low salary levels. It can be set to be issued in large numbers.

In various embodiments, the computing device 100 analyzes sales volume data and customer infrastructure data, calculates a repurchase rate for each of a plurality of products, and calculates a repurchase rate for each of the plurality of products based on the calculated repurchase rate for each of the plurality of products. Weights can be assigned, and the scoring results for each of a plurality of products can be corrected using the assigned weights.

For example, the computing device 100 may set products with a high repurchase rate to be ordered preferentially by assigning greater weight to products with a high repurchase rate than products with a relatively low repurchase rate.

In various embodiments, the computing device 100 analyzes sales volume data to calculate an expected appropriate price for each unmanned store 10 for each of a plurality of products, and selects a plurality of products based on the calculated expected appropriate price for each unmanned store 10. are sorted in descending order, weights are differentially assigned to each of the plurality of products based on the order in which each of the plurality of products is sorted, and the scoring results for each of the plurality of products can be corrected using the differentially assigned weights. Through this, it can be set so that products with a high expected fair price are ordered in greater quantities than products with a relatively low expected fair price.

In various embodiments, the computing device 100 analyzes the location data of each of the plurality of unmanned stores 10, assigns a weight to each of the plurality of products, and scores each of the plurality of products using the assigned weight. The results can be corrected.

For example, the computing device 100 assigns weight to beverage products when it is determined that the unmanned store 10 is located within a golf course, and to alcohol products when it determines that the unmanned store 10 is located within an apartment complex. By assigning weights, the unmanned store 10 can be set to order optimized products preferentially based on location.

At this time, the product to be weighted based on the location of the unmanned store 10, the sales volume data of other unmanned stores 10 in the location of the same attribute (e.g., if the first unmanned store 10 is located within a golf course, the golf course It may be set based on sales volume data of other unmanned stores 10 located within, but is not limited to this, and various methods such as setting in advance by the manager may be applied.

In various embodiments, the computing device 100 includes a plurality of unmanned stores 10 and social data (e.g., SNS, news, reviews of online shopping malls, etc.) about a plurality of products displayed in each of the plurality of unmanned stores 10. By analyzing, one or more keywords can be extracted, a weight can be assigned to each of a plurality of products based on the one or more extracted keywords, and the scoring results for each of a plurality of products can be corrected using the assigned weight. .

For example, the computing device 100 may collect social data in the form of text about a first product, analyze the collected social data (e.g., OCR analysis) to extract one or more keywords, and extract the extracted keywords and By comparing previously stored attribute data for each keyword, the attributes of one or more keywords can be determined, and through this, the attributes (e.g., positive or negative) of the first product itself can be determined. At this time, if it is determined that the first product has a positive attribute, the computing device 100 may assign a weight within the range of 1 to 2 so that the first product can be ordered preferentially, and if the first product is determined to have a negative attribute, the computing device 100 may assign a weight within the range of 1 to 2. If it is determined to have an attribute, the ordering priority of the first product can be lowered by assigning a weight in the range of 0 to 1.

In various embodiments, the computing device 100 may calculate the number of customers by age group visiting each of the plurality of unmanned stores 10 by analyzing customer infrastructure data, and may select a plurality of products based on the calculated number of customers by age group. A weight can be assigned to each, and the scoring results for each of a plurality of products can be corrected using the assigned weight.

For example, when the computing device 100 determines that customers in their 20s visit the first unmanned store 10 the most, the computing device 100 assigns weight to products preferred by customers in their 20s to select products preferred by customers in their 20s. By setting orders to be given priority, sales of the unmanned store 10 can be increased by increasing customer consumption.

In various embodiments, the computing device 100 analyzes social data, extracts one or more keywords (e.g., product names) related to each of a plurality of products, and assigns a weight to each of the plurality of products based on the number of extracted keywords. It can be granted. In other words, the computing device 100 can assign weight to products (popular products) that are frequently mentioned on SNS, etc., so that these products are ordered preferentially.

In various embodiments, the computing device 100 may assign weight to health-friendly foods among a plurality of products and set the health-friendly foods to be ordered first.

In various embodiments, the computing device 100 may assign weight to products containing specific functionality according to social norms among a plurality of products and set such products to be ordered preferentially.

In various embodiments, the computing device 100 may receive an unfavorable product line in advance from a user (e.g., a manager or a store owner of the unmanned store 10), and select 0 to 0 for one or more products set as an unfavorable product line among a plurality of products. By assigning a weight within the range of 1, the ordering priority of these products can be lowered.

In various embodiments, the computing device 100 may receive a preferred brand in advance from a user (e.g., a manager or a store owner of the unmanned store 10), and weight the product corresponding to the preferred brand among a plurality of products. By assigning , you can set these products to be ordered preferentially.

In various embodiments, the computing device 100 may calculate sales revenue for each of a plurality of products by analyzing sales volume data, and sort the plurality of products in descending order based on the calculated sales revenue, according to the sorted order. By differentially assigning weights so that the product located at the top is given the greatest weight and the product located at the bottom is given the smallest weight, it can be set so that products with large operating profits are ordered first.

Thereafter, the computing device 100 determines whether to process an order and the order amount for each of the plurality of products based on the scoring results for each of the plurality of products, and provides information on whether to process an order for each of the determined plurality of products and the order amount. You can create ordering data that includes

For example, based on the scoring result (corrected scoring result), the computing device 100 may sort a plurality of products in descending order and select N products starting from the product located at the top as the order processing target. However, it is not limited to this, and the computing device 100 uses various methods, such as selecting one or more products whose scoring results (scores) are equal to or higher than a preset standard score as the target for order processing, based on the scoring results for each of the plurality of products. It can be applied.

Additionally, the computing device 100 may determine the order quantity of the product selected for order processing. For example, when the computing device 100 receives order quantity information for each product from a user (e.g., an unmanned store owner) in advance, it may determine the order quantity of the product selected for order processing based on the registered information. However, it is not limited to this, and may be determined based on the sales volume and sales volume change (e.g., sales volume/sales volume change during a predetermined period based on the time of ordering) for the product selected for order processing.

In various embodiments, the computing device 100 may calculate the number of displays for each of a plurality of products in the unmanned store 10 by analyzing sales volume data, and provide information about the calculated number of displays for each of the plurality of products to the user. can be provided to.

In various embodiments, the computing device 100 may calculate the sales volume for each of a plurality of products by analyzing sales volume data, adjust the unit price for each of the plurality of products based on the calculated sales volume, and adjust the unit price for each of the plurality of products. Unit price information for each can be provided to the user.

In various embodiments, the computing device 100 analyzes sales volume data to calculate the hourly sales volume of each of a plurality of products, and determines the display priority of each of the plurality of products in the unmanned store 10 based on the calculated hourly sales volume. It can be set, and information about the display priority of each of the set multiple products can be provided to the user.

In various embodiments, the computing device 100 analyzes sales volume data to calculate the turnover rate of each of the plurality of products displayed in the first unmanned store 10, and orders the first product whose calculated turnover rate is less than the preset turnover rate. can be excluded from. At this time, in response to the first product being excluded from the ordering target, the computing device 100 may select a second product different from the first product as the ordering target.

Here, the second product is a product (especially a product with a high turnover rate) whose turnover rate is higher than a preset turnover rate among a plurality of products (excluding the first product) displayed in the first unmanned store (10), or The turnover rate among the plurality of products displayed in each of the plurality of second unmanned stores (10) having similar attributes (e.g. location, size, buyer age group, gender, occupation, surrounding environment, commercial district, etc.) is greater than the preset turnover rate. At the same time, it may be a product that is not displayed in the first unmanned store 10. However, it is not limited to this.

In various embodiments, the computing device 100 calculates a margin rate for a plurality of products displayed in the first unmanned store 10, but orders a product whose calculated margin rate is less than a preset margin rate, that is, a first product with a low margin rate. It can be excluded from the target. At this time, in response to the first product being excluded from the ordering target, the computing device 100 may select a second product different from the first product as the ordering target.

Here, the second product is a product (particularly a product with a high margin) whose margin rate is higher than a preset margin rate among a plurality of products (excluding the first product) displayed in the first unmanned store (10), or Among the plurality of products displayed in each of the plurality of second unmanned stores 10 having properties similar to those of , the margin rate may be higher than a preset margin rate and may be a product that is not displayed in the first unmanned store 10 . However, it is not limited to this.

In various embodiments, computing device 100 may analyze sales volume data to determine if the margin rate of the first product is less than a preset margin rate or if the first product is sold together with other products, such as a second product or a third product. If a pattern is shown and the turnover rate and margin rate of the second or third product sold together with the first product are greater than or equal to the preset turnover rate and preset margin rate, the first product may be selected as the ordering target.

In various embodiments, the computing device 100 may determine the order quantity according to the attributes of the product to be ordered. For example, in the case of dairy products or fresh foods, the expiration date is shorter than that of products such as snacks or ramen, so it is difficult to order large quantities even if sales volume is high or turnover and margin rates are high. In consideration of this, the computing device 100 may determine that, depending on the attributes of the product, if the product has a relatively short expiration date, such as dairy products or fresh food, a relatively small amount is ordered compared to products with a long expiration date. .

At this time, the computing device 100 increases the number and cycle of order processing (e.g., increases the standard value for selecting an order target) in consideration of the sales volume of the product, thereby preventing the product from being sold out due to the high sales volume of the product. It can be prevented.

In step S630, the computing device 100 may process an order for each of the plurality of unmanned stores 10 using the order data generated in step S620.

In various embodiments, the computing device 100 may perform a simulation of product sales in the unmanned store 10 using order data generated according to the above method, and order data based on the results of the simulation. can be verified, and a processing method for the generated order data can be determined based on the verification results.

Here, the simulation is performed according to a preset scenario, and the scenario may be set based on sales data of the first unmanned store 10, but is not limited to this and is performed by the manager or the store owner of the unmanned store 10. It can be set by direct input.

At this time, the computing device 100 may perform a plurality of simulations using one scenario, but is not limited to this, and generates a plurality of scenarios by modifying the standard scenario (e.g., changing the type and number of products included in the scenario). (change at a predetermined rate within a predetermined range, change the time a customer visits, etc.), and perform multiple simulations using each of the multiple generated scenarios.

In various embodiments, the computing device 100 may process an order using the corresponding order data when sales of the unmanned store 10 are greater than or equal to a reference value as a result of performing a simulation based on the generated order data. Meanwhile, when the computing device 100 performs a simulation based on the generated order data and the sales of the unmanned store 10 are less than the reference value, the computing device 100 may re-perform step S620 to regenerate the order data.

As described above, the computing device 100 analyzes data regarding the plurality of unmanned stores 10 to determine the optimal order target product and order quantity, and automatically performs order processing based on the determined order target product and order quantity. , there is an advantage that not only can the convenience of the unmanned store (10) be improved, but also the sales of the unmanned store (10) can be maximized.

In various embodiments, the computing device 100 analyzes data about a plurality of unmanned stores 10 to perform automatic order processing for existing unmanned stores 10 as well as initial processing of new unmanned stores 10. You can determine the quantity and process the order for the determined initial quantity.

For example, the computing device 100 analyzes sales volume data and customer infrastructure data for each of a plurality of products displayed in a plurality of unmanned stores 10 and selects a new unmanned store 10 among the plurality of unmanned stores 10. Select one or more unmanned stores (10) with the same or similar attributes (e.g. location, size, buyer age group, gender, occupation, surrounding environment, commercial district, etc.), and sales volume data of one or more unmanned stores (10) selected. By analyzing, it is possible to generate ordering data for ordering the initial quantity of a new unmanned store (10).

Considering that this is a business model that imposes a large cost burden on inventory at the time of initial store opening, we analyzed the sales data of the unmanned stores (10) with the attributes most similar to those of the new unmanned store (10) to be opened, and used this There is an advantage in that the problem of inventory costs can be resolved by determining the types and inventory amounts of products to be sold in the new unmanned store 10.

In various embodiments, the computing device 100 analyzes data regarding a plurality of unmanned stores 10 to automatically process (collect, return) a plurality of products displayed in each of the plurality of unmanned stores 10. You can.

In various embodiments, the computing device 100 may automatically collect and automatically return each of the plurality of products based on the disposal date of each of the plurality of products displayed in the unmanned store 10 (10). For example, the computing device 100 may determine that the expiration date and disposal date of each of the plurality of products is within a preset period based on the time of automatic collection and automatic return processing, or is already based on the time of automatic collection and automatic return processing. If it has expired, the product can be automatically collected and returned.

In various embodiments, the computing device 100 may automatically collect and automatically return at least a portion of the additionally ordered products when the external factors disappear. For example, when the computing device 100 normally orders only 10 candies, but orders 50 candies in consideration of the White Day season, among the 40 candies additionally ordered in response to the end of the White Day season, the White Day Candy left after being sold during the season can be automatically collected and automatically returned.

In various embodiments, the computing device 100 may include a camera module (e.g., an internal camera module provided on the user terminal 201 or the kiosk 202, an external camera module connected to the user terminal 201 or the kiosk 202). camera module) to scan the barcode printed on one or more products while simultaneously identifying the expiration date for one or more products, and automatically dispose of one or more products according to the identified expiration date (e.g., automatic collection and Return processing) is possible.

For example, the barcode for fresh food only displays information about the product and does not display the expiration date for the product. Therefore, when identifying a product through a barcode, it is possible to recognize whether the product is fresh food, but it is not distributed There is a problem that it is impossible to determine whether it can be sold within the deadline, that is, the validity of the sale. In consideration of this, the computing device 100 extracts text regarding the expiration date indicated on the packaging of fresh food through a camera module (e.g., OCR analysis) and uses a text analysis model (e.g., artificial intelligence model) By analyzing the text, the expiration date can be identified, and the sales validity of the product can be determined based on the identified expiration date.

In addition, if the computing device 100 determines that the sale of the product is invalid (e.g., the expiration date has passed or the expiration date is imminent), the computing device 100 orders the disposal of products whose expiration date is approaching among the remaining inventory of the product. You can order and notify. Hereinafter, with reference to FIG. 11, a method performed by the computing device 100 that allows the buyer to receive the product he or she wishes to purchase at a desired location and on a desired date according to the buyer's request will be described.

FIG. 11 is a flowchart illustrating a procedure for receiving a product purchased using a user terminal at a location and time desired by the purchaser, in various embodiments.

The procedure of receiving the product purchased using the purchaser's user terminal according to FIG. 11 at the place and time desired by the purchaser is described as being performed by the computing device 100, but is not limited to this, and is performed by the user terminal 201. (or the processor within the user terminal 201) executes the application provided from the computing device 100, thereby performing a procedure for receiving the product purchased using the buyer's user terminal at a location and time desired by the buyer. It can be.

Referring to FIG. 11, in step S710, the computing device 100 may execute an application according to the purchaser's request. Here, the application execution operation performed by the computing device 100 may be performed in the same or similar form as the application execution operation (eg, step S210) of FIG. 4, but is not limited thereto.

In step S720, the computing device 100 may select one or more products that the buyer wishes to purchase. Here, the operation of selecting one or more products from the buyer performed by the computing device 100 may be performed in the same or similar form as the operation of selecting one or more products of FIG. 4 (e.g., step S220), but is limited thereto. It doesn't work.

In various embodiments, the computing device 100 uses the user terminal 201 to provide a product search function according to search terms and product names, a product search function according to product categories, a product search function according to price range, and a product search function according to preferences by gender, age, and store. A product search function and a product search function based on purchase history can be provided, and the buyer can search for and select a product using any one of the product search functions above.

In step S730, the computing device 100 may receive information about the pickup location and pickup date of one or more products from the purchaser.

In various embodiments, the computing device 100 may provide a pickup location search function based on a search term, a pickup location search function based on a category, a pickup location search function based on map selection, and a pickup location search function based on purchase history, The buyer can search for and select a pickup location using any one of the pickup location search functions above.

In various embodiments, the computing device 100 is located in a place adjacent to the purchaser based on the location of the purchaser (e.g., location information collected from a location sensor (e.g., GPS sensor) provided in the purchaser's user terminal 201). A nearby unmanned store can be recommended as a pick-up location.

Here, the pickup location entered by the buyer is explained as one of a plurality of unmanned stores, but it is not limited to this, and in some cases, the address entered by the buyer (e.g. home, work, etc.) is used as the pickup location. You can choose. For example, when multiple buyers belonging to a first company purchase a product, the location where the multiple buyers will receive the product in response to the number of buyers purchasing the product (or the order quantity of the product) exceeding a certain amount. You can select as the first company.

In addition, here, the computing device 100 is described as performing an operation of selecting a product to be purchased (e.g., S720) and an operation of entering a pickup location and receipt date (e.g., S730) in that order, but the present invention is not limited thereto. , the operation of entering the pickup location and receipt date (e.g., S730) is performed before the operation of selecting the product to be purchased (e.g., S720), or the operation of selecting the product to be purchased (e.g., S720) and the pickup location and The operation of entering the receipt date (e.g. S730) can be performed at the same time. However, it is not limited to this.

In step S740, the computing device 100 may provide information about a plurality of purchase histories created when the buyer purchases a product, and in response to the buyer selecting one of the plurality of purchase histories, You can select the product and pickup location to repurchase existing products. At this time, the computing device 100 determines that the receipt date entered in the purchase history corresponds to a date that has already passed in the past, so if the buyer wishes to repurchase a previously purchased product, only the receipt date for the product can be reselected.

In step S750, the computing device 100 analyzes information on a plurality of purchase histories generated when the buyer purchases a product, and selects one or more recommended products (e.g., recommended products by time zone, recommended products by location, product ranking, event products, discount products, etc.) can be selected, and information about one or more selected recommended products can be provided to the buyer. For example, the computing device 100 analyzes a plurality of sales data generated when a plurality of buyers sell each of a plurality of products in an unmanned store, and determines that other buyers have similar attributes to the buyer, such as the buyer's age, gender, and occupation. You can select products that people have purchased a lot, products with good evaluations (reviews or ratings), and recommend the selected product to the buyer as a recommended product.

Thereafter, the computing device 100 may select one recommended product from among one or more recommended products and receive input of the receipt location and receipt date of the selected recommended product.

In step S760, the computing device 100 may perform a purchase and payment process for the product the buyer wishes to purchase among the product selected through step S720 and step S730, the product selected through step S740, and the product selected through step S750. there is. Here, the payment process performance operation performed by the computing device 100 may be performed in the same or similar form as the payment process performance operation (eg, step S120) of FIG. 3, but is not limited thereto.

In step S770, the computing device 100 may perform a purchase authentication procedure for the buyer if the buyer wishes to receive the purchased product at the pickup location after the payment process is completed in step S760. For example, the computing device 100 authenticates sales data generated as a result of performing a payment process along with an identity authentication procedure for the buyer (e.g., step S420 of FIG. 6), thereby verifying that the buyer has purchased the product. You can judge whether it is correct or not. However, it is not limited to this.

In step S780, when purchase authentication for the buyer is completed through step S770, the computing device 100 may provide the product purchased by the buyer to the buyer.

In various embodiments, the computing device 100 receives input information about the buyer, information about the object to be delivered, a delivery address, etc., and provides a courier service (or delivery service) that delivers the object to be delivered to the delivery location according to the input information. ) can be provided. For example, a buyer may request a courier service (or delivery service) to deliver a specific product from a first unmanned store to a second unmanned store and have the second buyer receive the delivered specific product, and request a courier service. In response to receiving, a specific product may be delivered from the first unmanned store to the second unmanned store. Hereinafter, with reference to FIG. 12, a method of providing advertisements suitable for buyers, which is performed by the computing device 100, will be described.

Figure 12 is a flowchart for explaining a procedure for providing advertisements suitable for buyers in various embodiments.

The procedure for providing advertisements suitable for the purchaser according to FIG. 12 is described as being performed by the computing device 100, but is not limited thereto, and is performed by the purchaser's user terminal 201 (or a processor within the user terminal 201). Perform a procedure to provide advertisements suitable for the purchaser by executing an application provided from the computing device 100, or the kiosk 202 (or a processor within the kiosk 202) executes software provided from the computing device 100 to provide an advertisement suitable for the purchaser. It can be implemented in the form of performing a procedure to provide appropriate advertisements.

Referring to FIG. 12 , in step S810, the computing device 100 may collect buyer information and sales history data (eg, sales data). For example, the computing device 100 performs a membership registration process to use the product sales service of an unmanned store, and stores information (e.g., age information, gender information, etc.) on a plurality of buyers (members) and a plurality of unmanned stores. Sales data generated at each store (e.g., product information purchased through the buyer's user terminal 201 and kiosk 202, purchase number information, purchase time information, etc.) can be collected.

In various embodiments, the computing device 100 may analyze buyer information and sales data to analyze buyer tendencies and purchase patterns.

In various embodiments, the computing device 100 may group a plurality of buyers who purchased each of a plurality of products displayed in an unmanned store into a plurality of groups according to preset criteria, and the plurality of buyers may purchase each of the plurality of products. By analyzing multiple sales data generated through purchases, purchasing patterns for each of multiple groups can be extracted. However, it is not limited to this.

In other words, the computing device 100 can build an enterprise resource planning (ERP) system that analyzes purchase patterns (consumption patterns) of buyers by analyzing a plurality of sales data.

In various embodiments, the computing device 100 receives information about the age, gender, and number of employees belonging to the affiliated company from an affiliated company (or an affiliated company server, or a representative terminal of the affiliated company) located adjacent to the unmanned store. You can collect and analyze purchase patterns by gender and age of buyers using data on products paid for with company welfare points of the affiliated company and information collected from the affiliated company.

Currently, in general stores (e.g., nearby commercial areas such as convenience stores), the buyer is not specified, so analysis of specific age and gender is not possible, and even if it is possible, there is a problem that the analysis results are inaccurate. Accordingly, the computing device 100 collects information on age, gender, and number of employees from surrounding affiliated companies and standardizes all affiliated company employees to a specific age and gender, thereby specifically targeting buyers and combining this with sales data. By combining them, more accurate purchasing patterns for each buyer can be extracted. For example, if an affiliate company has 10 employees, 8 of whom are women, and 7 of whom are in their 20s, all 10 employees of the affiliate company can be standardized as being women in their 20s. However, it is not limited to this.

In step S820, the computing device 100 selects a plurality of advertising contents waiting to be transmitted (e.g., new product, season, You can judge the suitability for each product (product, issue product, promotion, etc.).

Here, the suitability for advertising content is based on the purchasing pattern of the buyer or the purchasing pattern of the group to which the buyer belongs, whether the product included in the advertising content is a product that the buyer or the group to which the buyer belongs is likely to purchase, and whether the product has a high purchase volume. It may mean a score calculated by scoring depending on whether it is a product, etc., but is not limited to this.

In step S830, the computing device 100 may transmit advertising content based on the suitability determined in step S820. For example, when the first buyer operates the buyer's user terminal 201 or kiosk 202 to use the product sales service of an unmanned store, the computing device 100 operates the first buyer's user terminal 201 or Through the display provided in the kiosk 202, among a plurality of advertisement contents, the advertisement content that has a high degree of suitability with the first purchaser can be output.

In various embodiments, the computing device 100 selects an unmanned store among a plurality of advertising contents through an advertising output device (e.g., Digital Out-Of-Home Advertising, DOOH) provided in each of a plurality of unmanned stores. You can output advertising content that is highly relevant to buyers who visit. To this end, the unmanned store may include one or more display terminals for outputting advertising content, a main server, and a hub and control device connecting one or more display terminals and the main server. However, it is not limited to this.

In step S840, the computing device 100 may generate content of transmitting advertising content and result data resulting from transmitting the advertising content through step S830. For example, the computing device 100 provides information about which advertising content was transmitted to which buyer and whether the buyer was interested in the product included in the advertising content according to the transmission of the advertising content (e.g., selected as the product of interest). , it can generate result data that points to information about what was added to the shopping cart or whether a purchase was made.

Thereafter, the computing device 100 may analyze the contents of the advertising content transmitted and the resulting data resulting from transmitting the advertising content, and regenerate the advertising content transmission schedule for each day and hour.

The method of providing product sales services in the above-described unmanned store was explained with reference to the flow chart shown in the drawing. For simple explanation, the method of providing a product sales service in an unmanned store is illustrated as a series of blocks, but the present invention is not limited to the order of the blocks, and some blocks are performed in a different order from that shown and performed herein. may be performed or may be performed simultaneously. Additionally, new blocks not described in this specification and drawings may be added, or some blocks may be deleted or changed. Hereinafter, with reference to FIG. 13, the procedure for selling alcohol products to buyers will be described.

Figure 13 is a flowchart for explaining a procedure for selling alcohol products to a buyer, according to various embodiments.

The procedure for selling mainstream products to buyers according to FIG. 13 is described as being performed by the computing device 100, but is not limited thereto, and the user terminal 201 (or the processor within the user terminal 201) is the computing device. Perform procedures for selling alcoholic products to a purchaser by executing an application provided from 100, or enable kiosk 202 (or a processor within kiosk 202) to sell alcoholic beverages to a purchaser by executing software provided from computing device 100. It can be implemented in the form of performing a selling procedure.

Referring to FIG. 13, in step S910, when the buyer wishes to purchase alcohol, the computing device 100 identifies the buyer's face through a facial recognition method (e.g., Face ID) and provides information about the identified face. You can obtain prior consent to use. For example, the computing device 100 may obtain prior consent for the facial recognition method while the buyer performs a membership registration process (eg, FIGS. 6 and 7). However, it is not limited to this.

In step S920, when a purchaser transmits a request to purchase an alcoholic product, the computing device 100 may perform a real name authentication procedure (e.g., adult authentication) for the purchaser in response to the request to purchase an alcoholic product.

For example, an unmanned store may be equipped with a liquor refrigerator that displays and stores a plurality of liquor products, and the computing device 100 keeps the liquor refrigerator in a locked state until the real name authentication process for the purchaser is completed. It can be maintained.

At this time, when the buyer transmits a request to purchase an alcohol product, that is, when requesting to change the state of the alcohol refrigerator from the locked state to the open state, the computing device 100 uses an external real name authentication tool (e.g., an external platform (e.g., Naver) The real-name authentication process for the buyer can be performed using a QR code generated through a real-time QR generator provided by , Kakao, etc.). Here, the external real name authentication tool is explained as a QR code generated through a real-time QR generator provided by an external platform, but it is not limited to this and various tools for real name authentication are applicable.

In step S930, the computing device 100 may obtain a payment request for a mainstream product from the buyer. For example, when real name authentication for the purchaser is completed through step S920, the computing device 100 may change the locked liquor refrigerator to the open state.

Additionally, the computing device 100 may receive an input of a liquor product picked up from a liquor refrigeration store from a purchaser and obtain a user input indicating a payment request for the input liquor product. However, it is not limited to this.

At this time, the computing device 100 can proceed with the procedure of selling alcohol products only when the buyer who has received the payment request has registered as a member of the product sales service of the unmanned store provided by the computing device 100. However, it is not limited to this.

In step S940, the computing device 100 sends the buyer's phone number (e.g., the mobile phone number entered through the buyer's user terminal 201 or kiosk 202) in response to the payment request obtained from the buyer in step S930. A face recognition request can be sent using the face recognition method.

Afterwards, the purchaser can perform a face recognition procedure through the application of his or her user terminal 201, and the computing device 100 responds to sending a face recognition request through a facial recognition method, and the user terminal 201 By performing a facial recognition procedure, information about the identified buyer's face can be obtained.

Additionally, the computing device 100 may perform authentication for the purchaser based on information about the identified purchaser's face.

In step S950, the computing device 100 may provide a payment process for selling alcohol products when authentication for the buyer is completed in step S940.

In various embodiments, the computing device 100 may preset the number of alcohol products that can be purchased per buyer, and provide a payment process that allows only the preset number of alcohol products to be paid (e.g., 2 alcohol products per buyer). A payment process that restricts the purchase of alcoholic products) may be used.

In other words, the computing device 100 allows the buyer to pick up alcohol products from the liquor refrigerator through real name authentication and at the same time allows the buyer to access and purchase alcohol products through two authentication procedures (adult authentication procedures). It has the advantage of clearly preventing minors from purchasing alcoholic products. Hereinafter, with reference to FIG. 14, the process of data processing and automatic order processing using data generated in an unmanned store and artificial intelligence technology will be described.

Figure 14 is a diagram illustrating the process of data processing and automatic order processing using data generated in an unmanned store and artificial intelligence technology in various embodiments.

The process of data processing and automatic order processing using data generated in the unmanned store according to FIG. 14 and artificial intelligence technology is described as being performed by the computing device 100, but is not limited to this and is performed by the user terminal 201. (or the processor in the user terminal 201) executes the application provided from the computing device 100 to perform data processing and automatic order processing using data generated in an unmanned store and artificial intelligence technology, or performs a process of processing data and automatic order processing at the kiosk (202) ) (or the processor in the kiosk 202) executes software provided from the computing device 100 to perform data processing and automatic order processing using data generated in unmanned stores and artificial intelligence technology. You can.

Referring to FIG. 14, first, when a situation occurs where a buyer purchases a product at each of a plurality of unmanned stores, the computing device 100 collects each data generated by selling the product to the buyer (e.g., sales volume data (online , offline sales information), sales environment data (telecommunications company partnership, commercial area analysis, company (store) information, credit card, discount information), collection/linked data (sold product information, seasonal product sales information, buyer age information, buyer location) information, buyer's company information, repurchase information, order information, sales amount information, etc.) can be loaded into the analysis server within the computing device 100 (1-1).

The computing device 100 distributes each data loaded into the analysis server according to pre-categorized analysis models (e.g., daily/weekly/monthly information, statistics, FF (Fresh Food) pre-order, purchase information through applications, etc. ) can do.

Afterwards, the computing device 100 analyzes each data using an artificial intelligence model to make recommended orders of artificial intelligence (AI) (e.g., sold out products, popular products, new products, high margin products, etc.). Can be created (1-2). For example, the computing device 100 analyzes the above data to perform predictive analysis and visualization (e.g., sales budget and product forecast, automatic ordering and ordering forecast, season/issue/promotion product forecast, sales forecast, new product sales period) forecast, new store sales forecast, new store product composition forecast), and based on this, recommended orders can be created.

Here, the artificial intelligence model may be a model that has been previously learned based on machine learning technology using various data related to sales and changes in sales volume for each product accordingly as learning data, but is not limited to this.

Thereafter, the computing device 100 may present a recommended ordering plan to consider the recommended ordering of artificial intelligence (AI) generated using an artificial intelligence model (1-3).

In addition, the computing device 100 compares the product sales volume of each unmanned store with that of other unmanned stores (sales/purchase analysis) to check increase/decrease data for each product, and thus determine whether a problem affecting sales volume has occurred. It can be done (2-1).

Thereafter, the computing device 100 may create a list of out-of-stock products based on the inventory amount for each product and generate an order request according to the list of out-of-stock products (2-2).

Thereafter, the computing device 100 may perform automatic order processing by considering both the recommended order plan and the order request plan according to the list of out-of-stock products (2-3).

In addition, the computing device 100 automatically places an order by considering both the recommended order plan and the order request plan according to the list of products that are out of stock. However, in the case of a product that is out of stock, it is replaced with a recommended product to ultimately proceed with automatic ordering. It can be done (3-1).

In addition, the computing device 100 provides accounting data (e.g., deposit slip, cost slip, withdrawal slip, VAT report, cost calculation, and tax invoice) generated when selling (ordering) a product to the settlement server for storage and automatic sales reporting. It can be handled (4-1).

Above, embodiments of the present invention have been described with reference to the attached drawings, but those skilled in the art will understand that the present invention can be implemented in other specific forms without changing its technical idea or essential features. You will be able to understand it. Therefore, the embodiments described above should be understood in all respects as illustrative and not restrictive.

100: Server (or computing device) providing product sales service in unmanned stores
201: user terminal
202: Kiosk
300: external server
400: Network

Claims (15)

In a method performed by a computing device,
Collecting data on a plurality of unmanned stores;
Analyzing the collected data - the collected data includes sales volume data for each of a plurality of products displayed in the plurality of unmanned stores - generating order data for each of the plurality of unmanned stores; and
Processing orders for each of the plurality of unmanned stores using the generated order data,
The step of generating the order data is,
Scoring each of the plurality of products by analyzing the collected data; and
Based on the scoring results for each of the plurality of products, determine whether to process an order and the order amount for each of the plurality of products, and generate ordering data including information on whether to process an order and the order amount for each of the determined plurality of products. Including the step of generating,
The step of scoring each of the plurality of products is,
Analyzing the sales volume data to calculate the number of sales per one-time payment for each of the plurality of products; and
A step of assigning a weight to each of the plurality of products based on the calculated number of sales per payment, and correcting the scoring result for each of the plurality of products using the assigned weight,
The step of processing the order is,
By performing a simulation on product sales in the first unmanned store using the first order data generated by analyzing data on the first unmanned store, the sales of the first unmanned store are calculated, and applied to the simulation. The scenario is set based on sales data of the first unmanned store; and
Based on the results of the simulation, performing verification of the first order data, and determining a processing method of the first order data based on the verification result of the first order data,
The step of determining a processing method for the first order data is,
Based on the results of the simulation, if the sales of the first unmanned store are more than the reference value, the order is processed using the first order data, and if the sales of the first unmanned store are less than the reference value, the order is processed in the first unmanned store. Including the step of regenerating order data by analyzing related data,
How to provide automatic product ordering service for unmanned stores. According to paragraph 1,
The collected data is,
Contains inventory data for a plurality of products displayed in each of the plurality of unmanned stores,
The step of generating the order data is,
The inventory data is analyzed to select one or more products whose inventory is less than a preset number among a plurality of products, and ordering information for the selected one or more products - the ordering information includes information on the product to be ordered and the ordering quantity - Including the step of generating order data containing,
How to provide automatic product ordering service for unmanned stores. delete delete According to paragraph 1,
The collected data is,
Contains sales volume data for each of the plurality of products displayed in the plurality of unmanned stores,
The step of scoring each of the plurality of products is,
Analyzing the sales volume data to calculate a change in sales volume over time for each of the plurality of products; and
Comprising the step of assigning a weight to each of the plurality of products based on the calculated change in sales volume over time, and correcting the scoring result for each of the plurality of products using the assigned weight.
How to provide automatic product ordering service for unmanned stores. According to paragraph 1,
The collected data is,
Contains sales volume data for each of the plurality of products displayed in the plurality of unmanned stores,
The step of scoring each of the plurality of products is,
Analyzing the sales volume data to calculate sales volumes by season and weather for each of the plurality of products; and
Assigning a weight to each of the plurality of products based on season information and weather information for a predetermined period based on the time of analyzing the sales volume data and the calculated sales volume by season and weather for each of the plurality of products, Comprising the step of correcting the scoring result for each of the plurality of products using the assigned weight,
How to provide automatic product ordering service for unmanned stores. According to paragraph 1,
The collected data is,
Contains customer infrastructure data for each of the plurality of unmanned stores,
The step of scoring each of the plurality of products is,
The customer infrastructure data is analyzed to calculate the number of companies located near each of the plurality of unmanned stores and the salary level of company employees, and each of the plurality of products is based on the calculated number of companies and the calculated salary level. Comprising the step of assigning weights to and correcting the scoring results for each of the plurality of products using the assigned weights,
How to provide automatic product ordering service for unmanned stores. According to paragraph 1,
The collected data is,
Contains sales volume data and customer infrastructure data for each of the plurality of products displayed in the plurality of unmanned stores,
The step of scoring each of the plurality of products is,
Analyzing the sales volume data and the customer infrastructure data to calculate a repurchase rate for each of the plurality of products; and
Comprising the step of assigning a weight to each of the plurality of products based on the calculated repurchase rate and correcting the scoring result for each of the plurality of products using the assigned weight.
How to provide automatic product ordering service for unmanned stores. According to paragraph 1,
The collected data is,
Contains sales volume data for each of the plurality of products displayed in the plurality of unmanned stores,
The step of scoring each of the plurality of products is,
Analyzing the sales volume data to calculate an expected appropriate price for each of the plurality of products in each unmanned store;
Sorting the plurality of products sequentially, starting from the product with the calculated expected appropriate price for each unmanned store; and
Comprising the step of differentially assigning weights to each of the plurality of products based on the order in which each of the plurality of products is sorted, and correcting the scoring result for each of the plurality of products using the differentially assigned weights,
How to provide automatic product ordering service for unmanned stores. According to paragraph 1,
The collected data is,
Contains location data for each of the plurality of unmanned stores,
The step of generating the order data is,
Comprising the step of assigning a weight to each of the plurality of products based on the location data, and correcting the scoring result for each of the plurality of products using the assigned weight.
How to provide automatic product ordering service for unmanned stores. According to paragraph 1,
The collected data is,
Contains social data about the plurality of unmanned stores and a plurality of products displayed in each of the plurality of unmanned stores,
The step of generating the order data is,
extracting one or more keywords from the social data;
assigning a weight to each of the plurality of products based on the one or more extracted keywords; and
Comprising the step of correcting the scoring result for each of the plurality of products using the assigned weight,
How to provide automatic product ordering service for unmanned stores. According to paragraph 1,
The collected data is,
Contains sales volume data and customer infrastructure data for each of the plurality of products displayed in the plurality of unmanned stores,
The step of generating the order data is,
Selecting one or more unmanned stores having the same or similar properties as the properties of a new unmanned store among the plurality of unmanned stores - the properties include at least one of the size, location, and customer infrastructure of the unmanned store; and
Comprising the step of analyzing sales volume data of the selected one or more unmanned stores to generate order data for placing an initial quantity order for the new unmanned store,
How to provide automatic product ordering service for unmanned stores. delete processor;
network interface;
Memory; and
Includes a computer program loaded into the memory and executed by the processor,
The computer program is,
Instructions for collecting data on multiple unmanned stores;
Instructions for analyzing the collected data - the collected data includes sales volume data for each of a plurality of products displayed in the plurality of unmanned stores - to generate order data for each of the plurality of unmanned stores; and
Includes instructions for processing orders for each of the plurality of unmanned stores using the generated order data,
The instruction for generating the order data is,
Instructions for scoring each of the plurality of products by analyzing the collected data; and
Based on the scoring results for each of the plurality of products, determine whether to process an order and the order amount for each of the plurality of products, and generate ordering data including information on whether to process an order and the order amount for each of the determined plurality of products. Contains instructions that create
Instructions for scoring each of the plurality of products are:
Instructions for analyzing the sales volume data to calculate the number of sales per one payment for each of the plurality of products; and
Includes instructions for assigning a weight to each of the plurality of products based on the calculated number of sales per payment, and correcting the scoring result for each of the plurality of products using the assigned weight,
The instructions for processing the order are:
By performing a simulation on product sales in the first unmanned store using the first order data generated by analyzing data on the first unmanned store, the sales of the first unmanned store are calculated, and applied to the simulation. Instructions, wherein the scenario is set based on sales data of the first unmanned store; and
An instruction for performing verification of the first order data based on a result of the simulation and determining a processing method of the first order data based on the verification result of the first order data,
The instruction for determining the processing method of the first order data is,
Based on the results of the simulation, if the sales of the first unmanned store are more than the reference value, the order is processed using the first order data, and if the sales of the first unmanned store are less than the reference value, the order is processed in the first unmanned store. Containing instructions for regenerating order data by analyzing related data,
A server that provides automatic product ordering service for unmanned stores. Combined with a computing device,
Collecting data on a plurality of unmanned stores;
Analyzing the collected data - the collected data includes sales volume data for each of a plurality of products displayed in the plurality of unmanned stores - generating order data for each of the plurality of unmanned stores; and
Processing orders for each of the plurality of unmanned stores using the generated order data,
The step of generating the order data is,
Scoring each of the plurality of products by analyzing the collected data; and
Based on the scoring results for each of the plurality of products, determine whether to process an order and the order amount for each of the plurality of products, and generate ordering data including information on whether to process an order and the order amount for each of the determined plurality of products. Including the step of generating,
The step of scoring each of the plurality of products is,
Analyzing the sales volume data to calculate the number of sales per one-time payment for each of the plurality of products; and
A step of assigning a weight to each of the plurality of products based on the calculated number of sales per payment, and correcting the scoring result for each of the plurality of products using the assigned weight,
The step of processing the order is,
By performing a simulation on product sales in the first unmanned store using the first order data generated by analyzing data on the first unmanned store, the sales of the first unmanned store are calculated, and applied to the simulation. The scenario is set based on sales data of the first unmanned store; and
Based on the results of the simulation, performing verification of the first order data, and determining a processing method of the first order data based on the verification result of the first order data,
The step of determining a processing method for the first order data is,
Based on the results of the simulation, if the sales of the first unmanned store are more than the reference value, the order is processed using the first order data, and if the sales of the first unmanned store are less than the reference value, the order is processed in the first unmanned store. Stored on a computer-readable recording medium to execute a method of providing an automatic product ordering service in an unmanned store, which includes the step of analyzing related data and regenerating ordering data,
A computer program recorded on a computer-readable recording medium.