KR20210059252A - Method of providing a fulfillment service and service system therefor - Google Patents

Abstract

A method of providing a fulfillment service in a service server between a plurality of online sellers and an offline warehouse according to an embodiment of the present invention comprises: a step of acquiring sales data including sales article data of each online seller and location information about an article sales region and stock data of articles in the offline warehouse; a step of receiving order information from at least one online seller; a step of calculating a logistics cost based on the received order information; a step of determining whether the calculated logistics cost exceeds a threshold; a step of calculating an expected minimum logistics cost and an expected waiting time to reach the minimum logistics cost based on the acquired data when the logistics cost exceeds a threshold; a step of generating first fulfillment service data relating to the calculated expected minimum logistics cost and expected waiting time to reach the minimum logistics cost; and a step of transmitting the generated first fulfillment service data to a corresponding online seller. Accordingly, the present invention can provide a variety of fulfillment services to help optimize logistics costs for commerce businesses.

Description

TECHNICAL FIELD [Method OF PROVIDING A FULFILLMENT SERVICE AND SERVICE SYSTEM THEREFOR}

The present invention relates to a fulfillment service, and more particularly, to a method for providing a full-fillment service and a service system therefor through a service platform for optimizing distribution costs for commerce business between online sellers and offline warehouses. About.

In the conventional offline commerce, as media and consumption are gradually personalized, online commerce has been activated. Such online commerce is also moving from the one-person media era to the one-person customized consumption era, and now to the one-person seller era with the advancement of mobile environment and ICT technology.

In this process, the new generation, which has emerged as a core consumption group, gradually trusts each other as influencers, and searches, purchases, and shares products that satisfy their tastes. Due to such changes in the environment, in the new generation, individual sellers that manufacture or source products that more easily satisfy their tastes and sell them through online malls are increasing.

However, in the case of one-person sellers or individual sellers, there is a realistic problem in terms of logistics processing along with the establishment of online sales channels.

In addition, small and medium-sized warehouse owners are also faced with difficulties as there is a demand for change of constitution that requires frequent stocking and releasing of products in small quantities of various types.

Therefore, it is required to develop a system for online commerce that meets new trends between sellers and warehouse owners.

An object of the present invention is to provide a service platform for linking between online sellers and offline warehouses, as well as providing various full-filment services to help optimize logistics costs for commerce business.

Another object of the present invention is to provide a service platform that supports various scenarios of commerce business between online sellers and offline warehouses in relation to logistics cost optimization.

Another object of the present invention is to provide a computing device for the above-described method and a full-filment service system including the same.

The technical problems to be achieved in the present invention are not limited to the above technical problems, and other technical problems not mentioned 　 will be clearly understood by those of ordinary skill in the technical field to which the present invention belongs from the following description.

A method of providing a full-filment service in a service server between a plurality of online sellers and an offline warehouse according to an embodiment of the present invention for solving the above-described problem is, Obtaining sales data including location information and inventory data of goods in the offline warehouse; Receiving order information from at least one online seller; Calculating a distribution cost based on the received order information; Determining whether the calculated distribution cost exceeds a threshold value; If the distribution cost exceeds a threshold, calculating an expected minimum distribution cost and an expected waiting time for reaching the minimum distribution cost based on the acquired data; Generating first full-filment service data related to the calculated estimated minimum distribution cost and the expected waiting time to arrive at the corresponding minimum distribution cost; And transmitting the generated first full-filment service data to a corresponding online seller.

In a method of providing a full-filment service in a service server between a plurality of online sellers and an offline warehouse according to an embodiment of the present invention, feedback information on the transmitted first full-filment service data is received from the corresponding online seller. The step of doing; And determining a generation time of second full-filment service data related to packing and releasing inventory of goods in the offline warehouse based on the received feedback information.

In a method of providing a full-filment service in a service server between a plurality of online sellers and an offline warehouse according to an embodiment of the present invention, the determined second full-filment service data is generated or before a predetermined time Upon arrival, calculating a logistics cost at a corresponding point in time and comparing the calculated logistics cost with the estimated minimum logistics cost; And, as a result of the comparison, if the difference between the calculated logistics cost at the time point and the calculated expected minimum logistics cost exceeds a predetermined threshold, the estimated minimum logistics cost calculated based on the calculated logistics cost at the time point. It characterized in that it further comprises a; step of recalculating the expected waiting time reachable up to the cost within the threshold value of.

In a method for providing a full-filment service in a service server between a plurality of online sellers and an offline warehouse according to an embodiment of the present invention, the expected waiting time for reaching the corresponding minimum logistics cost includes an online seller, an article, and a sales area. It is characterized in that it is calculated based on at least one of the online seller, the product, and the location information based on the delivery forecast data generated by referring to at least one of the location information.

In a method for providing a full-filment service in a service server between a plurality of online sellers and an offline warehouse according to an embodiment of the present invention, the distribution cost and the expected minimum distribution cost are spaces in which inventory items in the offline warehouse exist. It is characterized in that it is calculated by referring to the unit of the number of boxes for the inventory item, not by the unit.

In a method for providing a full-filment service in a service server between a plurality of online sellers and an offline warehouse according to another embodiment of the present invention, sales including data on sales items of each online seller and location information on sales regions Acquiring data and inventory data of goods in the offline warehouse; Receiving order information from at least one online seller; Generating first full-filment service data related to packing and releasing stock of goods in the offline warehouse according to the received order information based on the acquired data; And transmitting the generated first full-filment service data to the offline warehouse terminal.

A method of providing a full-filment service in a service server between a plurality of online sellers and an offline warehouse according to an embodiment of the present invention, wherein the first full-filment service data is the received order by referring to the acquired data. It is characterized in that it is generated when the distribution cost calculated based on the information is reduced below a threshold or is the minimum distribution cost.

In a method for providing a full-filment service in a service server between a plurality of online sellers and an offline warehouse according to an embodiment of the present invention, the first full-filment service data includes the calculated distribution cost based on a preset distribution cost. When it exceeds, in order to reduce the corresponding logistics cost, by referring to the acquired data, the predictable minimum logistics cost data is calculated compared to the calculated cost.

In a method of providing a full-filment service in a service server between a plurality of online sellers and an offline warehouse according to an embodiment of the present invention, a reference time is set by referring to the acquired data, and the calculated When a predictable minimum distribution cost is reached or falls within a range less than a threshold value of the minimum distribution cost at the elapsed time of the reference time, the first full-filment service data is generated.

In a method for providing a full-filment service in a service server between a plurality of online sellers and an offline warehouse according to an embodiment of the present invention, the reference time is at least one of location information including an online seller, an article, and a sales area. It is characterized in that the adjustment is made based on at least one of the online seller, the product, and the location information based on the delivery forecast data generated with reference to.

A service server providing a full-filment service between a plurality of online sellers and an offline warehouse according to an embodiment of the present invention includes: a communication interface unit; A database unit for storing various types of data; And sales data including sales data of each online seller and location information on the sales area of the product, and product inventory data in the offline warehouse, and when order information is received from at least one online seller, the received order information Based on the calculation of the logistics cost, it is determined whether the calculated logistics cost exceeds the threshold value, and if the logistics cost exceeds the threshold value, the expected minimum logistics cost and the expected minimum logistics cost is expected to arrive based on the acquired data. And a control unit that calculates time, generates first full-filment service data on the calculated minimum distribution cost and expected waiting time to arrive at the minimum distribution cost, and controls to transmit it to a corresponding online seller; .

In a service server that provides a full-filment service between a plurality of online sellers and an offline warehouse according to an embodiment of the present invention, the control unit includes feedback information on the first full-filment service data transmitted from the corresponding online seller. When is received, based on the received feedback information, it is characterized in that it is characterized in that it determines the generation time of the second full-filment service data related to the packaging and delivery of goods in the offline warehouse.

In a service server that provides a full-filment service between a plurality of online sellers and an offline warehouse according to an embodiment of the present invention, the control unit is configured to: If it arrives before time, the logistics cost is calculated at the time and compared with the estimated minimum logistics cost previously calculated, and as a result of the comparison, the difference between the calculated logistics cost at the time and the estimated minimum logistics cost previously calculated is When the predetermined threshold is exceeded, the estimated waiting time that can reach a cost within the threshold of the previously calculated estimated minimum distribution cost is recalculated based on the calculated distribution cost at that time.

In a service server providing a full-filment service between a plurality of online sellers and an offline warehouse according to an embodiment of the present invention, the control unit refers to at least one of location information including an online seller, an article, and a sales area. The estimated waiting time for reaching the corresponding minimum distribution cost is calculated based on at least one of the online seller, product, and location information based on the generated delivery forecast data.

In a service server that provides a full-filment service between a plurality of online sellers and an offline warehouse according to an embodiment of the present invention, the control unit is configured for It is characterized in that the logistics cost and the expected minimum logistics cost are calculated by referring to the number of boxes.

A service server providing a full-filment service between a plurality of online sellers and an offline warehouse according to another embodiment of the present invention includes: a communication interface unit; A database unit for storing various types of data; And sales data including sales product data of each online seller and location information on the product sales area, and product inventory data in the offline warehouse, and when order information is received from at least one online seller, the obtained data is Based on the received order information, a control unit that generates first full-filment service data related to packing and releasing of goods in the offline warehouse according to the received order information, and controls to transmit the generated first full-filment service data to the offline warehouse terminal. It characterized in that it includes;

In a service server that provides a full-filment service between a plurality of online sellers and an offline warehouse according to an embodiment of the present invention, the control unit includes a distribution calculated based on the received order information by referring to the acquired data. It characterized in that the first full-filment service data is generated when the cost is reduced below the threshold value or is the minimum logistics cost.

In a service server that provides a full-filment service between a plurality of online sellers and an offline warehouse according to an embodiment of the present invention, the control unit, when the calculated logistics cost exceeds a preset logistics cost, the corresponding logistics In order to reduce costs, it is characterized in that, by referring to the acquired data, the minimum predictable logistics cost data is calculated relative to the calculated cost.

In a service server providing a full-filment service between a plurality of online sellers and an offline warehouse according to an embodiment of the present invention, the control unit sets a reference time by referring to the acquired data, and within the reference time When it reaches a predictable minimum distribution cost compared to the calculated cost or falls within a range less than the threshold value of the minimum distribution cost at the elapsed time of the reference time, the first full-filment service data is generated.

In a service server providing a full-filment service between a plurality of online sellers and an offline warehouse according to an embodiment of the present invention, the control unit refers to at least one of location information including an online seller, an article, and a sales area. And adjusting the reference time based on at least one of the online seller, product, and location information based on the generated delivery prediction data.

According to the present invention as described above, the effects described below can be obtained. However, the effect that can be obtained through the present invention is not limited thereto.

First, it is effective not only to provide a service platform for linking between online sellers and offline warehouses, but also to provide various full-filment services to help optimize logistics costs for commerce business.

Second, in relation to logistics cost optimization, there is an effect of providing a service platform that supports various scenarios of commerce business between online sellers and offline warehouses.

Third, there is an effect of providing a computing device for the above method and a full-filment service system including the same.

1(a) is a diagram showing a service system for providing a full-fill service between an online seller and an offline warehouse according to an embodiment of the present invention, and FIG. 1(b) is a full-fill according to an embodiment of the present invention. It is a diagram illustrating the function of the management service server 120.
2(a) is a block diagram for explaining the configuration of a full-filment service server 120 according to an embodiment of the present invention.
2(b) is a block diagram for explaining the configuration of a full-filment service server 120 according to another embodiment of the present invention.
3(a) to 3(c) and 4 are diagrams for explaining performing a full-filment service based on an image included in order information in the full-filment service server 120 according to the present invention.
5(a) is a flow chart illustrating the concept of a full-filment service.
5(b) is a diagram illustrating a full-filment service process in the full-filment service system 100 according to an embodiment of the present invention.
6 is a diagram illustrating a method of providing a full-filment service according to an embodiment of the present invention.
7 is a diagram illustrating a method of providing a full-filment service according to another embodiment of the present invention.
8 is a diagram illustrating a management system UI for a full-filment service according to another embodiment of the present invention.
9(a) is a diagram illustrating a method of providing a full-filment service according to another embodiment of the present invention.
9(b) is a diagram illustrating a method of providing a full-filment service according to another embodiment of the present invention.
10 is a diagram illustrating a method of providing a full-filment service according to another embodiment of the present invention.
11 is a flowchart illustrating a method of providing a full-filment service in a service server between a plurality of online sellers and an offline warehouse according to an embodiment of the present invention.
12 is a flowchart illustrating a method of providing a full-filment service in a service server between a plurality of online sellers and an offline warehouse according to another embodiment of the present invention.
13 is a diagram illustrating a relationship between a plurality of online sellers and inventory items according to an embodiment of the present invention.
14 is a flowchart illustrating a full-filment service method for optimizing distribution cost according to an embodiment of the present invention.
15 is a flowchart illustrating a full-filment service method for optimizing distribution cost according to another embodiment of the present invention.

Hereinafter, with reference to the accompanying drawings, preferred embodiments according to the present invention will be described in detail. The detailed description to be disclosed hereinafter together with the accompanying drawings is intended to describe exemplary embodiments of the present invention, and is not intended to represent the only embodiments in which the present invention may be practiced.

Only these embodiments are provided to make the posting of the present invention complete, 　 to fully inform the scope of the invention to those of ordinary skill in the art to which the present invention belongs, and 　 the present invention to be defined by the scope of the claims. Only.

In some cases, in order to avoid obscuring the concept of the present invention, well-known structures and devices may be omitted, or may be illustrated in block diagram form centering on the core functions of each structure and device. In addition, the same components will be described using the same reference numerals throughout this specification.

Throughout the specification, 　when a certain part 　"comprising 　 or 　including", 　 means that other components may be further included rather than excluding other components unless otherwise stated. do.

In addition, the term "?? unit" described in the specification refers to a unit that processes at least one function or operation, which may be implemented by hardware or software or a combination of hardware and software. Furthermore, "one (a 　 or 　an)", "one", 　 and similar related words are all in the singular and plural unless otherwise indicated in the specification or clearly contradicted by the context in the context describing the present invention. It can be used in a sense including.

In addition, 　specific terms used in the embodiments of the present invention are provided to aid understanding of the present invention, and 　unless defined otherwise, 　all terms used herein including technical or scientific terms are It has the same meaning as commonly understood by those of ordinary skill in the art to which it belongs. The use of these specific terms may be changed in other forms without departing from the technical spirit of the present invention.

Hereinafter, even though it is referred to as an online seller, an off-line warehouse, etc. in this specification, this does not mean a user, such as a person, but rather the online seller, offline warehouse, and computing to be described later. As a computing device, it may mean a means capable of communicating with a fulfillment service server, for example, a terminal of an online seller, a terminal of an offline warehouse, and the like.

Meanwhile, in the above, all of the terminals and devices may include software for driving them based on hardware. For example, the full-fillment service server may perform various operations based on a fulfillment service platform to be described later as a computing device. In addition, these devices are not limited to stationary devices such as TVs and PCs, and include mobile devices such as mobile phones, smartphones, tablet PCs, and notebook computers.

In addition, hereinafter, various configurations described in the present specification or illustrated by drawings are mainly described in the singular form to aid understanding of the present invention and for convenience of description, but the present invention is not necessarily limited thereto. Therefore, even if it is described in the singular through context or the like or shown in the singular form in the drawings, it may have a plural meaning.

Hereinafter, various embodiments according to the present invention will be described with reference to the accompanying drawings, as follows.

1(a) is a diagram showing a service system for providing a full-filment service between an online seller and an offline warehouse according to an embodiment of the present invention.

Referring to FIG. 1(a), a system for providing a full-fillment service (hereinafter referred to as a'fulfillment service server') 100 includes an online seller 110 and an offline warehouse 130. Including, the computing device 120 for providing a full-filment service is included between the online seller 110 and the offline warehouse 130.

Accordingly, both devices, that is, the online seller 110 and the offline warehouse 130 may be connected to each other through the full-filment service server 120.

The online seller 110 may perform data communication with the full-filment service server 120 through a wired/wireless communication network.

Here, the wired/wireless communication network supports a communication protocol so that various data can be exchanged between components of the full-filment service system 100 according to the present invention, and the type is not particularly limited. If necessary, it is possible to support this even when data is collected through the web or the like through the full-filment service server 120 or the like. According to one embodiment, 　the wired/wireless communication network is, 　Internet Protocol (IP) network supporting large-capacity data communication through Internet Protocol (IP), or All IP integrating different 　IP　 networks. I can. According to another embodiment, the wired/wireless communication network is a wired network, a mobile communication network including WCDMA, a high speed downlink packet access (HSDPA), and a mobile communication network including Long Term Evolution (LTE), LTE advanced (LTE-A). ), a mobile communication network, a satellite communication network, and a Wi-Fi network, or may be formed by a combination of at least two or more of them. Bluetooth communication can also be supported here.

The full-filment service server 120 is a component that supports and performs full-filment service provision through the offline warehouse 130 at the request of the online seller 110, and may be located remotely, but is limited thereto. no.

As described above, this full-filment service server 120 refers to hardware/software (Hardware/Software) that implements the full-filment service platform according to the present invention to generate, process, and store various data, or support it. As such, depending on the embodiment, it may be described as being named as a processor, a controller, and the like, but it should be noted in advance that it should not be limited and interpreted by the name.

On the other hand, according to an embodiment, 　 full-filment service server 120, 　 Cloud 　 server, IMS (IP Multimedia Subsystem) 　 server, 　 Telephony Application (Telephony Application) 　 server, IM (Instant Messaging) 　 Server, MGCF (Media Gateway Control) Function) 　 server, MSG (Messaging Gateway) 　 server, CSCF (Call Session Control Function) 　 can be implemented in any one of the form of server.

Meanwhile, the full-filment service server 120 may provide a file for installing a full-filment service or a related application type program or software to an online seller 110 connected through a wired/wireless communication network. In this case, the online seller 110 may download or/and install an application using a file provided from the full-filment service server 120. In addition, the online seller 110 can receive or use the full-filment service by being connected to the full-filment service server 120 through its operating system or program.

In particular, the full-filment service server 120 receives order information from the online seller 110 and compares it with keyword data learned through artificial intelligence from the received order information according to the present invention. A full-filment service may be provided to the online seller 110 by searching for.

Meanwhile, although not shown, in FIG. 1(a), the full-filment service server 120 may be implemented as an internal component of the online seller 110 in the form of a single module, or the internal configuration of the online seller 110 Any one of the elements may perform some or all of the functions of the full-filment service server 120. For example, when the full-filment service according to the present invention is performed through an application installed in the online seller 110, an internal control configuration such as a central processing unit (CPU) of the online seller 110 is used for the full-filment service. It may replace or partially perform the functions of the server 120.

1(b) is a diagram illustrating the function of the full-filment service server 120 according to an embodiment of the present invention, and FIG. 2(a) is a full-filment service server according to an embodiment of the present invention. A block diagram for explaining the configuration of 120), FIG. 2(b) is a block diagram for explaining the configuration of the full-filment service server 120 according to another embodiment of the present invention, FIGS. 3(a) to 3( c) and 4 are views for explaining the execution of a full-filment service based on an image included in the order information in the full-filment service server 120 according to the present invention, and FIG. 5(b) is a diagram illustrating a full-filment service process in the full-filment service system 100 according to an embodiment of the present invention, and FIGS. 6 and 7 are A diagram illustrating a method of providing a full-filment service according to the present invention, and FIGS. 8 to 10 are diagrams illustrating a method of providing a full-filment service according to an embodiment of the present invention.

Hereinafter, various methods of providing full-filment services will be described to aid understanding of the present invention and for convenience of description. In this case, although the steps are sequentially described for the sake of explanation in the accompanying drawings or description, they are not necessarily limited to the illustrated order. For example, some of the steps may be performed simultaneously or in different steps than the order shown.

Referring to FIG. 1(b), the full-filment service server 120 according to an embodiment of the present invention may participate in or support the following functions.

That is, the full-filment service server 120 may be involved in or process product warehousing, storage, order, packaging, delivery, return/inventory management, settlement, distribution support, and the like.

In connection, the concept of the full-filment service will be briefly described with reference to FIG. 5(a) as follows.

For example, when a consumer in a first country (US) places an order to a seller in a second country (AU) through online (S110), the second seller finds the product in an offline warehouse after receiving the order, packs it, and then sends it. Request (S120).

Accordingly, the goods are shipped to the first country after declaration to the customs (S130), and finally delivered last mile to consumers in the first country (S140).

This whole process can be called full-filment service.

Referring to FIG. 3, a block diagram of a full-filment service server 120 according to an embodiment of the present invention is shown. Hereinafter, the configuration of FIG. 2(a) will be described together while describing FIGS. 9(a) and 9(b).

Basically, the full-filment service server 120 includes a communication interface unit 310, a data extraction/classification unit 320, a data processing unit 330, a control unit 340, and a database 350.

According to an embodiment, referring to FIGS. 9(a) and 2(a), the full-filment service according to the present invention may be performed as follows.

The communication interface unit 310 may receive order information for shipping goods from the online seller terminal 110 (S402).

The data extracting/classifying unit 320 may extract search data within the received order information and classify the extracted search data (S403).

The controller 340 may directly or control the data processing unit 330 to register a service keyword through artificial intelligence learning (S401), and compare the classified search data with the registered service keywords (S404). In addition, the control unit 340 generates full-filment service data related to a corresponding service keyword according to the comparison result (S405), and transmits the generated full-filment service data to the offline warehouse terminal 130 to It can be controlled to be released (S406).

According to another embodiment, referring to FIGS. 9(b) and 2(a), the full-filment service according to the present invention may be performed as follows.

The communication interface unit 310 may receive order information for shipping goods from the online seller terminal 110 (S502).

The data extracting/classifying unit 320 may extract search data within the received order information and classify the extracted search data (S503).

The control unit 340 may directly or control the data processing unit 330 to register a service keyword through artificial intelligence learning (S501), and compare the classified search data with the registered service keywords (S504/S505). . In addition, if there is no service keyword matching the comparison result, the control unit 340 generates a new service keyword (S506), and generates first full-filment service data related to the generated new service keyword (S507). , By transmitting the generated first full-filment service data to the offline warehouse terminal, it is possible to control the goods to be shipped (S508).

In the above, the service keyword registration process is continuously performed and updated, and may have been performed before the order information is received, and may be continuously updated after that.

In the above, the order information may include at least one of text data, image data, and audio data. A detailed description of the data processing process for each case will be described later.

Meanwhile, referring to FIG. 10, in the above, the control unit 340 transmits confirmation data including the generated first full-filment service data to the online seller terminal 110 (S601), and the online seller terminal When feedback data for the confirmation data is received from 110 (S602), the generated first full-filment service data is then transmitted to the offline warehouse terminal 130 to control the delivery of the corresponding article.

In the above, at least one of the first full-filment service data and the confirmation data is the new service keyword, information on the goods received in the offline warehouse 130 corresponding to the service keyword, and the quantity of goods orders extracted from the order information. It may include at least one or more of information, inventory information on the corresponding article, and total inventory information on articles received by the online seller 110 in the offline warehouse 130.

The controller 340 may control to register the generated new service keyword as a service keyword and update the service keyword database 350.

The controller 340 may parse the feedback data received from the online seller terminal 110 and identify the parsed feedback data content (S603).

If the content of the identified feedback data is a negative message (S604), the control unit 340 re-comparisons the search data re-extraction/reclassification and reclassified search data in the received order information with a registered service keyword ( S605), if there is no service keyword matching the recomparison result (S606), a new service keyword is generated (S607), and second full-filment service data related to the generated new service keyword is generated (S608), Alternatively, if there is a service keyword matching the re-comparison result, control may be performed to generate second full-filment service data according to the matching service keyword (S507).

As described above, the full-filment service server 120 accurately catches the products requested by the online seller 110 or its customers from the order information received from the online seller 110, and through the offline warehouse 120 The product is shipped or delivered to the customer.

In this case, the order information may be implemented in various forms, as described above, but may be a text data form, an image data form, another data form, or any combination of the aforementioned data forms. .

However, in the present specification, for convenience, in the case where the order information is made of text data and the case where the order information is made of image data, the contents of obtaining accurate logistics search data according to artificial intelligence learning from the two cases will be described.

First, when the order information is text data (including voice data), the processing or operation process of the full-filment service server 120 will be described as follows.

FIG. 2(b) may itself be a full-filment service server 120 according to an embodiment different from that of FIG. 3, or may be a detailed configuration of a configuration in the full-filment service server 120 shown in FIG. 2(a).

To aid in understanding of the present invention and for convenience of explanation, FIG. 2(b) is described below as a detailed configuration of the control unit 240 of the full-filment service server 120 of FIG. 2(a), but the scope of the present invention is limited thereto. It does not become. The control unit 240 automatically maps the goods of the offline warehouse 130 from the order information of the online seller 110 using an artificial intelligence-based search engine including contents to be described later.

Meanwhile, in FIG. 2(b), only core components are shown and described for convenience, but the present invention is not limited thereto.

2(b), the full-filment service server 120 includes a communication module 310, a speech-to-text (STT) module 410, and a text-to-speech ; TTS) module 420, a natural language processing module 430, an operation/comparison/control module 440, and the like.

The communication interface unit 310 may communicate with the database 350 or may communicate with the online seller 110 and the offline warehouse 130 described above. The communication interface unit 310 receives order information including text data from the online seller 110.

The communication interface unit 302 may receive information of the separate online seller 110 or/and the offline warehouse 130 in or together with the above-described order information. Here, the information of the online seller 110 is, for example, identification information (ID) for identifying the corresponding online seller 110, various status information (eg, physical state of the online seller terminal 110, online It may be a software and/or hardware state of the seller terminal 110, etc.). Meanwhile, the offline warehouse information may include information on the type or type of items in the warehouse, information on items from a specific seller, information on the quantity of each item, and other information on the state of the warehouse.

The STT module 410 may receive a voice input among order information received through the communication interface unit 310 and convert the received voice input into text data based on various known methods. The STT module 410 may generate a feature vector sequence by extracting features such as a keyword, such as a specific word, from a voice input.

The STT module 410 may generate a text recognition result, eg, a sequence of words, based on various models such as a deep neural network model. In this case, the STT module 410 may refer to the database 350 when processing the received voice input, that is, converting it into text data. but,

The natural language processing module 430 may receive a text input from the communication interface unit 310 or the STT module 410. Text input received from the natural language processing module 430 is, for example, from the text input received from the online seller 110 in the communication interface unit 310 or the voice input received from the communication interface unit 310 in the STT module 304 The generated text recognition result may be, for example, a sequence of words. The natural language processing module 430 may receive status information associated with a corresponding user input, for example, status information of the online seller 110 at the time of the user input, and the like, together with or after receiving the text input. As described above, the status information is, for example, various status information related to the online seller 110 at the time of user voice input and/or text input in the online seller 110 (eg, physical status of the online seller 110, software And/or hardware status, environment status information around the online seller 110, etc.).

The natural language processing module 430 may correspond the received text input to one or more service keywords. Here, the service keyword may be associated with a series of operation(s) that can be understood and performed by the operation/comparison/control module 440. The natural language processing module 430 may refer to the above-described state information in mapping the received text input to one or more service keywords. The natural language processing module 430 may refer to data of the database 350 to be described later in correlating the received text input to one or more service keywords.

The operation/comparison/control module 440 may include, for example, a predefined ontology model. The ontology model may be expressed as, for example, a hierarchical structure between nodes, and each node may be a service keyword or one of its sub-attributes. The ontology model may be dynamically changed by adding or deleting nodes in relation to a new service keyword, or by modifying a relationship between nodes.

The operation/comparison/control module 440 may be associated with words and/or phrases related to a service keyword or sub-attributes from text data, respectively. The operation/comparison/control module 440 may implement the ontology model in the form of, for example, a vocabulary dictionary (not shown) consisting of a set of nodes of a hierarchical structure and words and/or phrases associated with each node, The natural language processing module 430 may determine a service keyword based on the ontology model implemented in the form of a vocabulary dictionary as described above.

Upon receiving a text input or a sequence of words, the natural language processing module 430 may determine which nodes in the ontology model are associated with each word in the sequence, and determine a corresponding service keyword or attribute based on the determination. I can. Through this determination, the item corresponding to the service keyword can be identified.

When the natural language processing module 430 analyzes a text input based on an ontology model in the form of a vocabulary dictionary on the operation/comparison/control module 440, it may not be able to determine an appropriate service keyword. For example, the received text input does not include a predetermined word or phrase that is defined as being mapped to a specific service keyword, and by listing entity information that is completely irrelevant to a predetermined word or phrase, the desired service keyword is indirectly expressed. There may be cases, etc.

In other words, when the text input through the calculation/comparison/control module 440 is not direct product or quantity data, it is not easy to determine the service keyword through the natural language processing module 430.

To this end, the natural language processing module 430 to the calculation/comparison/control module 440 are learning basic data for machine learning, and include previous history, online dictionary data, direct input data, online seller data, and offline warehouse data. It can be used for the above decision by referring to data related to logistics.

Meanwhile, the service keyword determined in this way may be different from, for example, logistics-related data of an offline warehouse. These contents may be resolved by receiving related data in advance and referring to the dictionary definition of the service keyword, or processed in the form of a link.

For example, the text data is "Necklace Silver 1EA", "Necklace 1 Silver?", "Necklace Silver One?", "Rock 1 Silver", "Neck Class 1 Silver", "Necklace 1ea Silver It may be ", "one silver neck class", "one silver neck class", or the like. In this case, the natural language processing module 430 to the calculation/comparison/control module 440 finally, as the service keyword, accurately store the "one silver necklace" of the corresponding online seller 110 on the online warehouse 130. It can be determined by the article and its quantity.

The natural language processing module 430, on the other hand, determines an appropriate service keyword from the ontology model in the form of a vocabulary dictionary on the operation/comparison/control module 440, but when an error occurs, analyzes a plurality of entities present in the input. Based on this, an appropriate service keyword may be determined or a new service keyword may be generated and determined. For example, the natural language processing module 430 may determine that if an entity of the same type is repeated multiple times, such an input relates to a complaint or return request.

The natural language processing module 430 may secure various databases for words representing quality, such as size, color, performance, and price, among the received inputs, and refer to the service keyword determination.

The database 350 may store and manage history data including personalized data of the corresponding online seller 110. This may contribute to fast calculation and accurate processing/determination by referring to the processing or determination of the calculation/comparison/control module 440 to the natural language processing module 430 later. On the other hand, the personalization data included in the database 350 may include, for example, the seller's previous history, the seller's pronunciation, vocabulary preference, location, setting language, contact/friend list, and other personalization information of various sellers for each seller. I can.

As described above, the STT module 410 can obtain more accurate text data by referring to personalization data of each seller in the database 350, for example, pronunciation characteristics for each seller when converting the voice input into text data. have. In determining the service keyword, the natural language processing module 430 may determine a more accurate service keyword by referring to each seller personalization data of the database 350, for example, a personalization characteristic or context of each seller.

The database 350 may exist, for example, in the online seller terminal 110, or may be distributed and disposed in the online seller terminal 110 and the offline warehouse 130.

The operation/comparison/control module 440 may generate a series of operation flows corresponding to the service keyword determined by the natural language processing module 430. The operation/comparison/control module 440 may determine which operation and/or task to be performed in response to a service keyword received from the natural language processing module 430 and generate a detailed operation flow according thereto.

The TTS module 420 may receive a conversation response generated to be transmitted to the online seller terminal 110 by the conversation generating module 314. The conversation response received by the TTS module 420 may be a natural language having a text form or a sequence of words. The TTS module 420 may convert the received text input into a speech form according to various types of algorithms.

In addition, when determining each service keyword, the natural language processing module 430 to the operation/comparison/control module 440 may calculate a mapping or matching similarity and refer to it. Accordingly, when the calculated mapping or matching similarity is less than a predetermined threshold, the above-described process may be re-performed or returned to the online seller 110 to request confirmation, and may be determined accordingly. Meanwhile, the confirmation, that is, feedback of the online seller 110 may be reflected in the next calculation and keyword determination.

On the other hand, the natural language processing module 430 to the operation/comparison/control module 440 separately mark various text data, words, words, and associates that are not previously registered in the database 350, so that the mapping or matching similarity is applied. Can be reflected.

Next, an embodiment in which the full-filment service server 120 performs a full-filment service from an image is included in the order information received from the online seller 110 will be described.

3(a) to 3(c) and 4, a method for providing a full-filment service according to an embodiment of the present invention receives an image to be searched for a product from the online seller terminal 110.

The full-filment service server 120 classifies the received image of the online seller terminal 110 to be searched for products.

The full-filment service server 120 recognizes a product-related object from the classified online seller terminal 110's product search target image, and sets a product-related part in the object as a region of interest (ROI), The set region of interest (ROI) is cropped.

The full-filment service server 120 estimates the image similarity by calculating the cropped image data and the product image data stored in the database 350 using sub-networks included in a pre-learned network function. For example, the full-filment service server 120 performs a product search through estimation of an image-to-image method using a similarity estimation model for a portion of an ROI cropped from an image to be searched for a product.

The full-filment service server 120 transmits the corresponding product data to the terminal of the offline warehouse 130 as a result of the search based on the estimated image similarity.

The full-filment service server 120 communicates with the online seller terminal 110 shown in FIG. 1(a) to receive a variety of data from the online seller terminal 110, including product image data to be searched. Here, the image data to be searched received from the online seller terminal 110 may correspond to at least one of a captured or snapshot image, a captured image, a downloaded image, an image pre-stored in the online seller terminal 110, etc. have.

The full-filment service server 120 receives the received image data for product search of the online seller terminal 110.

The full-filment service server 120 classifies the image data to be searched for the received online seller terminal 110. Meanwhile, as described above, the full-filment service server 120 uses a deep learning-based multi-class classification model to classify the image to be searched for goods of the received online seller terminal 110 as described above. You can distinguish the types of. To this end, the full-filment service server 120 receives various types of product image data collected through the web, the product image of the manufacturer, the image provided by the online seller 110, and so on, through the deep learning model in advance. You can learn. The learned result may be stored in the database 350. Meanwhile, a deep learning-based multi-class classification model used in the full-filment service server 120 may be stored in the database 350 in advance.

The full-filment service server 120 performs object detection and cropping using a Faster Convolutional Neural Network Features (R-CNN) model. FIG. 3(a) shows a feature map pyramid extracted from FPN, and FIG. 3(b) shows an example of an R-CNN structure using a feature map pyramid extracted from FPN. A detailed description of the Faster R-CNN model and a description of (a) and (b) of FIGS. 3 to be described later refer to known contents, and a detailed description thereof will be omitted. However, not only the currently published R-CNN model but also the future developed and known R-CNN model is used in the process of detecting an object containing an item and automatically cropping the item-related item from the detection object in connection with the present invention. Can be.

First, the full-filment service server 120 is identified as a product image as a result of the above-described classification, and when the class is confirmed, the object related to the product image of the identified class in the search target image previously received from the terminal 110 Recognize.

In other words, in particular, a Faster R-CNN model that has been trained in advance by specializing in an item item is constructed, and by using the constructed model, among at least one or more objects in the image received from the online seller terminal 110, particularly related to the item item. Objects can be detected. In the case of the conventional object detection model, it was common to detect all objects included in the received image, but the present invention determines and detects only the objects necessary from the image as meaningful objects through an object detection model that is specialized for item items and learned in advance. By doing so, it is possible to increase the overall efficiency of the system by reducing the object detection time and computation time.

On the other hand, although not shown, for example, depending on the user's selection or setting, for example, it is a target that has been learned in advance by specializing only on the specific item(s) handled, excluding items that are not handled by the online seller 110 among the item items. By using an object detection model, the efficiency can be further improved.

Alternatively, product items may be randomly classified and multiple object detection models corresponding to the classified items may be used. In this case, the object detection model is applied sequentially or in parallel according to a criterion such as high user interest, high sales, or high priority due to the high level of sales or the type or number of products possessed, to determine objects related to the item items. Can be detected.

In addition, in the case of object detection, since the cropping process described later remains, it is not necessary to perform a complicated process such as critically classifying objects with item items, but to detect objects according to predetermined criteria and perform the cropping process. I can.

Meanwhile, when a plurality of objects related to an article item are detected as a result of object detection in the full-filment service server 120, it may be processed according to a setting. Here, according to the setting, for example, all objects detected to select a specific object among a plurality of objects in the cropping process are transferred to the cropping process, or a plurality of detection objects are determined in advance for convenience in the cropping process. Among them, it is possible to determine only the object containing the item item related to the desired item item and transfer it to the cropping process. On the other hand, it is preferable to group objects including item items belonging to the same classification among the detected objects and transmit them through a cropping process.

The full-filment service server 120 determines the product image part of the actually identified class from the recognized object as a region of interest, that is, a Region of Interest (ROI), and crops the corresponding part, that is, an ROI part, from the object. . As the object detection and cropping model used in the present invention, through the R-CNN model, the ROI is automatically cropped and can be used immediately for a corresponding article search described later.

In this way, a learning model specialized for an item item is used through the full-filment service server 120 according to the present invention, and through this, recognition accuracy is increased, and a number of cropped images for each object are stored in the image search step in the online seller terminal 110. It is possible to improve the user's convenience by inserting a single coordinated image and searching for a corresponding product without manually inputting it individually.

The above description was a process of performing object detection and cropping a part of an actual item item to be searched from the detected object from the ROI. However, the present invention is not necessarily limited thereto. For example, in the case of object detection, it is used for searching by cropping an item item to be searched from an image. Although not shown, detection of an object including the item item according to learning or through a pre-input item item The process can be omitted. That is, since the item item to be used for search is extracted from the image in the end, the detection process of the object including the object may be removed, and the process of detecting the item item may be substituted for it. By doing this, the detected item item can be cropped immediately and the processing speed or the amount of association can be reduced, thereby increasing the system efficiency.

The full-filment service server 120 calculates the similarity by comparing the cropped product image with the retained product image stored in the database 350 and image-to-image. The full-filment service server 120 may set the ranking of product candidates returned as a search result based on the similarity calculated as described above.

According to the present invention, the full-filment service server 120 calculates the cropped image data and the product image data stored in the database using sub-networks included in a pre-learned network function to estimate and search the image similarity. And search for the product through it. Here, the sub-networks may include a convolutional neural network (CNN) structure among deep neural network structures. As shown in FIG. 7, the sub-networks may constitute at least a part of a Siamese network. However, the present invention is not necessarily limited thereto. Meanwhile, as described above, a detailed description of a convolutional neural network (CNN), a Siamese network, and the like among the deep neural network structures will be omitted herein with reference to known techniques.

According to the present invention, when the image-to-image search method using the Siamese network shown in FIG. 7 is used, an index of similarity can be calculated numerically. Therefore, by arbitrarily adjusting or setting the calculated similarity index, the product search result value may be changed, and through this adjustment, it may be more suited to the intention or needs of the online seller 110.

In relation to this, in the present invention, a distribution ontology may be constructed through the above-described similarity estimation model and used for product search.

In (c) of FIG. 3, a learning model is shown, and an attribute value of the detected object can be extracted through the learning model. As an example, Google's Inception-V3 learning model is shown in FIG. 6, and related information is referred to, and a detailed description of the learning model is omitted herein.

For example, images having the same attribute as the detected attribute may be read from the database 350 and used as a search candidate group. After that, the ranking of the candidate group can be determined in connection with the similarity estimation model based on the Siamese network and determined/returned as the search result.

In addition, it is possible to use the online seller 110 as a filter function to perform detailed search by excluding/including items returned as a search result according to the detected attribute.

That is, conventionally, there has been a hassle of having to directly input accurate product attribute information through the online seller 110 or the offline warehouse 130 terminal, but in the present invention, the distribution ontology is built in advance and the attribute is automatically extracted from the input image. By tagging, not only can the service procedure be shortened, but also the online seller 110 can increase convenience.

On the other hand, between the online seller-full-filment service server-offline warehouse, the above-described process, that is, product search request-product search result determination/return, and selection of the online seller 110 or the offline warehouse 130 according to the provision of the search result. The efficiency can be further increased by reflecting it in learning and updating it.

If the full-filment service server 120 has information on an online seller or an offline warehouse terminal, a personalized product search and provision service customized to the terminal through learning is also possible. In this way, when personalization is performed, the factor values of the above-described various models can be more simply configured, efficiency can be further improved through learning, and results for desired products can be quickly provided.

Meanwhile, in relation to the present invention, the database 350 stores various data described above, such as received images, product information, and distribution ontology described above. Meanwhile, the database 350 does not necessarily have to be built in the computing device 120 (or the online seller terminal 110). This database 350 also stores data in the form of a cloud, and, if necessary, returns a uniform resource locator (url) to access the url returned from the full-filment service server 120 or the online seller terminal 110 to be related. It can also be built to be able to acquire data.

The control unit 340 controls the entire process of the full-filment service server 120 as a whole, and may appropriately control each configuration as necessary.

Meanwhile, in the case of the image comparison method described above, in general, it is possible to increase the accuracy of calculation or determination by collecting and referring to information in a variety of 3D forms on an article. For example, referring to images acquired for various fields of view or angles such as the front, rear, top, bottom, side, etc. of the article, it is possible to contribute to fast calculation and accurate determination in the process of determining the article.

Although not shown, in the case where the order information received from the online seller 110 in the full-filment service server 120 does not contain only text or images alone, but is combined, the above-described contents may be appropriately combined to solve the problem. Therefore, it can be seen that such a case is also included in the embodiments of the present invention. For example, if the data extracted from the order information and classified or classified by cropping is text, then the natural language processing method is used according to the text processing method, and if it is an image, the image processing method is used to obtain the final data from the processed data according to each method Full-filment service can be provided based on one data.

In addition, in the above case, if the information on the same item or the final full-filment service search data obtained therefrom do not match, repeat the process or full-filment service data on the items based on each different data. Can be generated and delivered to the online seller 110 to receive confirmation. Related data, such as experience acquired in this process, may be used as learning data of artificial intelligence-based data according to the present invention and may be updated later.

The full-filment service process in the full-filment service system 100 shown in FIG. 5(b) will be described with reference to FIGS. 6 and 7 as follows.

Referring to FIG. 6, the online seller 110 stocks a product that it can sell to the offline warehouse 130 in advance (S201).

When a customer places an order for a specific product with the online seller 110 (S202), the online seller 110 uploads the order information to the full-filment service server 120 (S203).

The full-filment service server 120 converts the order information into a database and transmits the order information to the offline warehouse 130 (S204).

The offline warehouse 130 picks up, packages, and releases the corresponding goods based on the transmitted order information (S205/S206).

The offline warehouse 130 uploads the invoice information to the full-filment service server 120 after the goods are released (S207).

The full-filment service server 120 provides the uploaded product invoice information to the online seller 110 (S208).

Referring to FIG. 7, a detailed processing process for the CS processing and return operation after FIG. 6 will be described.

When a customer requests a CS processing or return operation to the online seller 110 (S301), the online seller 110 transmits this to the full-filment service server 120 (S302).

The full-filment service server 120 determines the customer's CS processing/return job request information and transmits it to the offline warehouse 130 (S303).

After confirming this, the offline warehouse 130 transmits the feedback information to the online seller 110 through the full-filment service server 120 (S304, S305). In this case, the feedback information may include various data such as a restocking request according to a lack of quantity of goods, confirmation of whether another product is released, and data on a product delivery process according to a transfer request.

In addition, the offline warehouse 130 releases other items and delivers them to the customer (S306).

The offline warehouse 130 returns information on the reshipment to the online seller 110 through the full-filment service server 120 (S307, S308).

Thereafter, the online seller 110 receives the customer's feedback again. If the feedback is positive, the process ends. However, if the feedback is negative, the above-described procedure may be repeated or another procedure may be performed. The above other procedures may be the import and compensation of outgoing goods.

Meanwhile, in the above-described process, the full-filment service server 120 can continuously manage and control the full-filment service by converting and updating various types of data into a database in the form shown in FIG. 8.

Meanwhile, according to the present invention, it is possible to create a synergy effect in the online commerce market through sharing of inventory and distribution know-how. That is, in the present invention, as described above, not only a service platform for linking between online sellers and an offline warehouse is provided, but also various full-filment services are provided to help revitalize the commerce business.

11 is a flowchart illustrating a method of providing a full-filment service in a service server between a plurality of online sellers and an offline warehouse according to an embodiment of the present invention, and FIG. 12 is another embodiment of the present invention. Is a flow chart illustrating a method of providing a full-filment service in a service server between a plurality of online sellers and an offline warehouse according to the present invention, and FIG. 13 is a plurality of online sellers and stock items according to an embodiment of the present invention. It is a figure shown to explain the relationship between.

First, referring to FIGS. 11 and 2(a), the full-filment service server 120 acquires sales data of each online seller and inventory data of goods in the offline warehouse through the communication interface 310 (S701). .

The full-filment service server 120 generates first full-filment service data including proposal information related to the sale of inventory of goods in the offline warehouse based on the acquired data through the control unit 340 (S702), and the The generated first full-filment service data is transmitted to each of the online seller terminals (S703).

The full-filment service server 120 receives feedback data of the transmitted first full-filment service data (S704), and based on the received feedback data, a second full-filment service related to the sale of inventory of goods in the offline warehouse Data is generated (S705) and transmitted to corresponding online sellers (S706).

The full-filment service server 120 receives feedback data of the transmitted second full-filment service data (S707), and based on the received feedback data, 3 Full-filment service data is generated (S708) and transmitted to the offline warehouse terminal 130 (S709).

The full-filment service server 120 generates fourth full-filment service data for identification of the corresponding data based on the obtained sales data of each online seller and the product inventory data in the offline warehouse (S710), and It is transmitted to the seller terminal (S711).

In the above, the fourth full-filment service data may be implemented in the form of at least one of a number, a histogram, and a graph to help intuitive identification of online sellers.

On the other hand, as shown in Fig. 13, the proposal information related to the sale of the stock of goods in the offline warehouse in the generated first full-filment service data is, for a specific stock item, one online seller is a corresponding item of another online seller. Information on the right to sell all or part of the inventory of the online seller, information about the bundle sale of the inventory of that online seller and all or part of the inventory of the other online seller in a bundle to one online seller, and It may include at least one of information related to sales authority for all of the specific stock items in the offline warehouse.

Next, referring to FIGS. 12 and 2 (a), a method of providing a full-filment service in a service server between a plurality of online sellers and an offline warehouse according to another embodiment of the present invention will be described. same.

The full-filment service server 120 acquires sales data of each online seller and inventory data of goods in the offline warehouse 130 through the communication interface unit 310 (S801).

The full-filment service server 120 includes first full-filment service data including online sales training and community service data for each product type and price range for product inventory in the offline warehouse based on the data acquired through the control unit 340. And (S802), and transmits the generated first full-filment service data to each of the online seller terminals (S803).

In this case, the full-filment service server 120 may differentiate and generate the first full-filment service data for each online seller based on the acquired data.

The full-filment service server 120 receives the feedback data of the first full-filment service data through the control unit (S804), and based on the received feedback data and the acquired data, sells inventory of goods in the offline warehouse. The second full-filment service data including proposal information related to is generated (S805), and the generated second full-filment service data is transmitted to each of the online seller terminals (S806).

In the above, referring to FIG. 13, the proposal information related to the sale of the stock of goods in the offline warehouse in the generated second full-filment service data is, for a specific stock item, one online seller is the stock of the corresponding item of another online seller. Information on the right to sell all or part of the items, information on the bundled sale of all or part of the online seller's inventory and other online seller's heterogeneous or similar inventory to one online seller, and the offline It may include at least one of information related to sales authority for all specific inventory items in the warehouse.

Referring to FIG. 13, for example, the inventory status of goods for each online seller in the offline warehouse 130 can be viewed. Seller A has item 1 (10 items), item 2 (20 items) and item 3 (30 items) in stock, Seller B has item 1 (5 items), and item 4 (5 items) in stock, Seller C has item 1 (20 items), item 4 (5 items) and item 5 (10 items) in stock.

For example, each online seller (Seller A to Seller 3) must bear the distribution cost, such as storage cost for inventory items, to the offline warehouse 130, as shown in FIG. 18. When referring to the above-described sales data-this may be generated by the full-filment service server 120, or can be received from the corresponding online seller -, if the sales status of each online seller's inventory items is not good, continue to logistic costs. Must bear. From the point of view of online sellers, the rapid exhaustion of inventory after stocking can prevent an increase in logistics costs, thereby improving economic efficiency.

Accordingly, according to the present invention, the full-filment service server 120 includes the sales status and inventory status of each online seller, the sales trend of each online seller for other inventory items, the time until inventory is exhausted, and the cost according to the inventory. By comprehensively determining the possibility of exhaustion, etc., a full-filment service can be provided to each online seller to induce inventory exhaustion through sales promotion.

For example, referring to FIG. 13, Item 1 is in stock in both Seller A to Seller C, but Seller B has the lowest stock quantity. If Seller B's sales performance is the best for the product by referring to other subsidiary factors such as sales status, it is likely that Seller B will run out of inventory for the product, or it may take the shortest time to run out of inventory. On the other hand, from Seller B's point of view, while the sales performance of the item is good, sales may be sluggish due to a small inventory quantity, and if the item is restocked to solve this problem, the time and economic burden increases. Accordingly, in the present invention, the full-filment service server 120 learns this situation based on artificial intelligence, and transfers the sales authority for Seller A and Seller C's 1 (all or part of) to Seller B, thereby benefiting each seller. To this end, full-filment service data can be generated and provided to corresponding sellers. When appropriate feedback data is transmitted from each seller through feedback on this, full-filment service data including data such as incidental costs, fees, and settlement are generated and provided to induce inventory exhaustion.

Alternatively, referring to FIG. 13, seller A has 30 stocks of item 3, and seller C has 10 stocks of item 5. However, while sales of the corresponding products are sluggish, unlike the above-described embodiment, since other sellers do not own the corresponding product, it is difficult to transfer the sales authority to the other seller. In this case, full-filment service data may be generated and provided to the corresponding sellers so as to promote or induce inventory exhaustion by providing the product in the form of a bundle of other products of the own or other sellers.

Meanwhile, the two embodiments described above may be combined with each other. For example, if you want Seller B to have the right to sell all inventory of Item 1, it must be full to provide Seller A's Item 3 or Seller C's Item 5 in bundles to help promote sales of its Item 1. It is also possible to induce inventory exhaustion by generating and transmitting service data.

In addition, items that are unlikely to be sold for which sales status or inventory exhaustion is less than the threshold for the lapse of a predetermined period are formed, for example, through sellers with poor sales performance in recent years. Full-filment service data can be created and provided to prevent an increase in the economic burden of each seller.

On the other hand, unlike the above-described embodiment, not only the inventory exhaustion between sellers, but by referring to the above-described sales data and inventory quantity data, the full-filment service server 120 sells online such as by product type or/and price range. By creating and transmitting full-filment service data related to education-related and community services for know-how of the company, it is possible to induce increase in profits of sellers and offline warehouses by using the full-filment service.

For example, when the sales performance of a specific product is above a threshold and the inventory quantity is below a certain level, data on the sales know-how of the corresponding online seller may be collected and guide data based thereon may be used as full-filment service data. In this case, the collection of the data may be performed through comprehensive analysis and learning by collecting various information such as advertisement data, sales strategy sharing data, history, sales trend, etc. through various media related to the corresponding seller.

In addition, the full-filment service server 120 may provide a community service for sharing know-how between sellers and consulting on sales strategies as one of the full-filment services, which can be implemented through a chat window service or the like.

Hereinafter, various embodiments and scenarios related to logistics cost optimization according to the present invention will be described in FIGS. 14 and 15.

14 is a flowchart illustrating a full-filment service method for optimizing logistics cost according to an embodiment of the present invention, and FIG. 15 is a full-filment service method for optimizing logistics cost according to another embodiment of the present invention. It is a flow chart shown to explain.

Although, for convenience of description, in FIGS. 19 to 20, the full-filment service server 120 is described below, but the detailed configuration for each step or operation may be referred to FIG. 3.

First, a method of providing a full-filment service in a full-filment service server between a plurality of online sellers and an offline warehouse for optimizing distribution cost according to the present invention will be described with reference to FIG. 20.

The full-filment service server 120 acquires sales data including sales product data of each online seller and location information on a sales region, and product inventory data in the offline warehouse (S901).

The full-filment service server 120 receives order information from at least one online seller (S902).

The full-filment service server 120 calculates a distribution cost based on the received order information (S903), and determines whether the calculated distribution cost exceeds a threshold value (S904).

The full-filment service server 120, if the logistic cost exceeds the threshold value as a result of the determination in step S904, calculates the expected minimum logistics cost and the expected waiting time to reach the minimum logistics cost based on the acquired data (S905), First full-filment service data related to the calculated estimated minimum logistics cost and expected waiting time to arrive at the corresponding minimum logistics cost is generated (S906), and the generated first full-filment service data is transmitted to a corresponding online seller (S907). .

Here, the threshold is, for example, the logistics cost set in advance by the online seller 110, the average logistics cost of the corresponding offline warehouse to release the goods, the average logistics cost when referring to the previous history of the online seller, etc. It may correspond to at least one of or may be determined by an appropriate combination of the above. However, the present invention is not limited thereto.

In addition, in the above, the minimum logistics cost means the minimum logistics cost that can be calculated by referring to the delivery of goods to the order when various factors for calculating the logistics cost are comprehensively considered. For example, it is true that combined packaging or combined delivery is advantageous for reducing logistics costs, but attempting to reduce logistics costs through unlimited combination packaging or combined delivery may cause other problems due to delays in delivery, so appropriate timing should be taken. It is advisable to decide and follow it. Accordingly, when calculating the logistics cost in this regard, it is possible to refer to sales data including data of previously sold items of the online seller and location information about the sales regions of the products. For example, when a corresponding online seller frequently sells a specific product during a specific time period, the minimum distribution cost and the expected time to reach the minimum distribution cost may be calculated by referring to the online seller. The opposite is also true. In addition, by referring to the sales data including the sales data of the plurality of online sellers who have stock items in the corresponding offline warehouse and the sales data including the location information of the sales area of the goods, the minimum logistics cost can be calculated through combined delivery or combined packaging. I can.

In addition, if a plurality of online sellers with stock items in the corresponding offline warehouse sell items within a predetermined time, referring to the delivery location, combined delivery or combined packaging by referring to the delivery location information of the items sold by each online seller. It is possible to determine whether it is possible, and to calculate the minimum logistics cost based on it.

Meanwhile, the minimum logistics cost referred to in the present specification may be automatically calculated based on data learned by referring to the history in the full-filment service server 120 only, or may be determined according to the settings of online sellers.

In the present invention, various factors such as minimum logistics cost and minimum logistics cost arrival time are directly or/and It may be determined in consideration of at least one or more of various factors that may indirectly affect, and once set, this may be maintained unless there is special circumstances, or conversely, may be continuously changed and applied in real time based on the above factors. . For example, in the latter case, a threshold value is set for each factor, and if there is a variation exceeding the set threshold value, the change may be reflected in the determined value to change in real time.

Meanwhile, after the step S907, the full-filment service server 120 receives feedback information on the transmitted first full-filment service data from the corresponding online seller, and based on the received feedback information, the product in the offline warehouse It is possible to determine the generation time of the second full-filment service data related to the packing and delivery of inventory.

The feedback information may include a variety of information such as a decision on a logistics cost, a request to wait for delivery up to a minimum logistics cost, a request for immediate delivery, a request for maintenance/change of the expected arrival time of the minimum logistics cost, and the like.

At this time, when the determined second full-filment service data is generated or arrives before a predetermined time of the generation time, the logistics cost is calculated at that time and compared with the estimated minimum logistics cost previously calculated, and the comparison result, When the calculated logistics cost at the time point exceeds a predetermined threshold value, the calculated logistics cost at the time is calculated up to the cost within the threshold value of the estimated minimum logistics cost calculated at that time. It is also possible to recalculate the expected wait times that can be reached.

In this way, the estimated waiting time that can reach the cost within the threshold of the calculated estimated minimum logistics cost is transmitted back to the corresponding online seller, and the feedback may be received and the operation may be performed by referring to it.

In the above, the estimated waiting time for reaching the minimum logistics cost is at least one of the online seller, the product, and the location information based on the delivery forecast data generated by referring to at least one of the online seller, the product, and the location information including the sales area. It can be calculated based on

On the other hand, the logistics cost and the expected minimum logistics cost may be calculated by referring to the number of boxes for the stock item, not the space unit in which the stock item in the offline warehouse exists.

Next, referring to FIG. 15, a method of providing a full-filment service in a service server between a plurality of online sellers and an offline warehouse for optimizing distribution cost according to the present invention will be described as follows.

The full-filment service server 120 acquires sales data including sales product data of each online seller and location information about the product sales area, and product inventory data in the offline warehouse (S1001).

The full-filment service server 120 then receives order information from at least one online seller (S1002).

When receiving the order information in the step S1002, the full-filment service server 120 provides a first package and delivery of stock of goods in the offline warehouse according to the received order information based on the data obtained in the step S1001. Full-filment service data is generated (S1003), and the generated first full-filment service data is transmitted to the offline warehouse terminal (S1004).

The full-filment service server 120 may generate the first full-filment service data when the logistics cost calculated based on the received order information by referring to the acquired data is reduced to a threshold value or less or is the minimum logistics cost. I can.

When the calculated logistics cost exceeds a preset logistics cost, the full-filment service server 120 refers to the acquired data to reduce the corresponding logistics cost, and the predictable minimum logistics cost data compared to the calculated cost. Can be calculated.

The full-filment service server 120 sets a reference time by referring to the acquired data, and reaches a minimum predictable logistics cost relative to the calculated cost within the reference time, or when the minimum logistics cost is elapsed. If it falls within the range less than the threshold, it is possible to control to generate the first full-filment service data.

Meanwhile, in the above, the reference time is adjusted based on at least one of the online seller, the product, and the location information based on the delivery forecast data generated by referring to at least one of the location information including the online seller, the product, and the sales area. Can be.

In addition, the contents of FIGS. 14 and 15 may be combined with at least one or more of the embodiments of FIGS. 1A to 13 described above to implement a new embodiment.

On the other hand, the above-described method can be written in a program that can be executed on a computer, and can be implemented in a general-purpose digital computer that operates the program using a computer-readable medium. In addition, the structure of the data used in the above-described method can be recorded on a computer-readable medium through various means. Computer-readable media storing executable computer code for performing various methods of the present invention include magnetic storage media (e.g., 　 ROM, 　 floppy disk, 　 hard disk, etc.), 　 optical reading medium (e.g., CD-ROM, DVD Etc.).

Those of ordinary skill in the technical field related to the embodiments of the present invention will appreciate that it may be implemented in a modified form without departing from the essential characteristics of the above description. Therefore, the disclosed methods should be considered from a descriptive point of view rather than a limiting point of view. The scope of the present invention appears in the claims rather than the detailed description of the invention, and all differences within the scope equivalent thereto should be construed as being included in the scope of the present invention.

Claims (19)

In a method for providing a full-filment service in a service server between a plurality of online sellers and an offline warehouse,
Acquiring sales data including sales product data of each online seller and location information on a sales region of the product, and product inventory data in the offline warehouse;
Receiving order information from at least one online seller;
Calculating a distribution cost based on the received order information;
Determining whether the calculated distribution cost exceeds a threshold value;
If the distribution cost exceeds a threshold, calculating an expected minimum distribution cost and an expected waiting time for reaching the minimum distribution cost based on the acquired data;
Generating first full-filment service data related to the calculated estimated minimum distribution cost and the expected waiting time to arrive at the corresponding minimum distribution cost; And
Transmitting the generated first full-filment service data to a corresponding online seller;
A method of providing a full-filment service in a service server comprising a. The method of claim 1,
Receiving feedback information on the transmitted first full-filment service data from the corresponding online seller; And
Determining a generation time of second full-filment service data related to packing and releasing inventory of goods in the offline warehouse based on the received feedback information;
Method for providing a full-filment service in a service server, characterized in that it further comprises a. The method of claim 2,
If the determined second full-filment service data is generated or arrives before a predetermined time of the generation time, calculating a logistics cost at that time and comparing it with the estimated minimum logistics cost; And
As a result of the comparison, if the difference between the calculated logistics cost at the time point and the calculated expected minimum logistics cost exceeds a predetermined threshold, the calculated minimum logistics cost is calculated based on the calculated logistics cost at the time point. Recalculating an expected waiting time reachable to a cost within a threshold;
Method for providing a full-filment service in a service server, characterized in that it further comprises a. The method according to claim 1 or 3,
The estimated waiting time to reach the corresponding minimum logistics cost above is,
Full-filled in a service server, characterized in that it is calculated based on at least one of the online seller, product, and location information based on the delivery forecast data generated by referring to at least one of location information including online seller, product, and sales area. How to provide payment services. The method according to any one of claims 1 to 4,
The above logistics costs and estimated minimum logistics costs are:
The method for providing a full-filment service in a service server, characterized in that the calculation is performed in a unit of the number of boxes for the stock item, not in a unit of space in which the stock item in the offline warehouse exists. In a method for providing a full-filment service in a service server between a plurality of online sellers and an offline warehouse,
Acquiring sales data including sales product data of each online seller and location information on a sales region of the product, and product inventory data in the offline warehouse;
Receiving order information from at least one online seller;
Generating first full-filment service data related to packing and releasing stock of goods in the offline warehouse according to the received order information based on the acquired data; And
Transmitting the generated first full-filment service data to the offline warehouse terminal;
A method of providing a full-filment service in a service server comprising a. The method of claim 6,
The first full-filment service data,
A method for providing a full-filment service in a service server, characterized in that generating when a distribution cost calculated based on the received order information is reduced to a threshold value or less or is a minimum distribution cost with reference to the acquired data. The method of claim 7,
When the calculated logistics cost exceeds a preset logistics cost,
A method for providing a full-filment service in a service server, characterized in that, in order to reduce a corresponding logistics cost, a minimum predictable logistics cost data is calculated relative to the calculated cost by referring to the acquired data. The method of claim 8,
The first full-filment service data,
To set a reference time by referring to the acquired data, and to generate when it reaches the minimum predictable logistics cost compared to the calculated cost within the reference time or falls within a range below the threshold of the minimum logistics cost at the elapse of the reference time. A method of providing full-filment service in a service server, characterized in that. The method of claim 9,
The reference time is,
Full fill in a service server, characterized in that the adjustment is made based on at least one of the online seller, product, and location information based on the delivery forecast data generated by referring to at least one of the location information including the online seller, the product, and the sales area. How to provide payment services. In a service server that provides a full-filment service between a plurality of online sellers and an offline warehouse,
A communication interface unit;
A database unit for storing various types of data; And
When the sales data including the sales data of each online seller and the location information of the product sales area and the product inventory data in the offline warehouse are obtained, and order information is received from at least one online seller, the received order information is Calculate the logistics cost based on the calculation, determine whether the calculated logistics cost exceeds the threshold, and if the logistics cost exceeds the threshold, the estimated minimum logistics cost and the expected waiting time to reach the minimum logistics cost based on the acquired data A controller configured to generate first full-filment service data related to the calculated estimated minimum distribution cost and expected waiting time to arrive at the corresponding minimum distribution cost, and control to transmit it to a corresponding online seller;
Service server comprising a. The method of claim 11,
The control unit,
When feedback information on the transmitted first full-filment service data is received from the corresponding online seller, the generation time of the second full-filment service data related to packing and shipping inventory of goods in the offline warehouse based on the received feedback information Service server, characterized in that to determine. The method of claim 12,
The control unit,
When the determined second full-filment service data is generated or arrives before a predetermined time of the generation time, the logistics cost is calculated at that time and compared with the estimated minimum logistics cost previously calculated, as a result of the comparison, the calculated If the difference between the calculated logistics cost and the estimated minimum logistics cost at that time exceeds a predetermined threshold, it is expected to reach a cost within the threshold of the estimated minimum logistics cost calculated based on the calculated logistics cost at that time. Service server, characterized in that recalculating the waiting time. The method of claim 11 or 13,
The control unit,
The estimated waiting time for reaching the minimum logistics cost is determined based on at least one of the online seller, the product, and the location information, based on the delivery forecast data generated by referring to at least one of the online seller, the product, and the location information including the sales area. Service server, characterized in that to calculate. The method according to any one of claims 11 to 14,
The control unit,
The service server, characterized in that the distribution cost and the estimated minimum distribution cost are calculated by referring to a unit of the number of boxes for the stock item, not a unit of space in which the stock item in the offline warehouse exists. In a service server that provides a full-filment service between a plurality of online sellers and an offline warehouse,
A communication interface unit;
A database unit for storing various types of data; And
When the sales data including the sales data of each online seller and the location information of the product sales area and the product inventory data in the offline warehouse are obtained, and order information is received from at least one online seller, the obtained data is based on the obtained data. A control unit configured to generate first full-filment service data related to packing and shipping of goods in the offline warehouse according to the received order information, and to transmit the generated first full-filment service data to the offline warehouse terminal;
Service server comprising a. The method of claim 16,
The control unit,
And generating the first full-filment service data when a distribution cost calculated based on the received order information is reduced to a threshold value or less or is a minimum distribution cost with reference to the acquired data. The method of claim 17,
The control unit,
When the calculated logistics cost exceeds a preset logistics cost,
A service server, characterized in that for calculating the minimum predictable logistics cost data compared to the calculated cost by referring to the acquired data to reduce the corresponding logistics cost. The method of claim 18,
The control unit,
If a reference time is set by referring to the acquired data, and the minimum predictable logistics cost compared to the calculated cost is reached within the reference time, or falls within a range below the threshold of the minimum logistics cost at the lapse of the reference time, the second 1 A service server for controlling to generate full-filment service data.

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