Automated device for cross-border e-commerce and method for controlling same

Abstract

An automated device for cross-border e-commerce and a method for controlling same are disclosed. The automated device according to one embodiment of the present invention comprises: a database that stores data; and a processor that controls the automated device, wherein the processor may, when a preset word representing a popular search term is identified while scraping a web page, extract keywords searched at a preset frequency or higher and store the keywords in the database, search a shopping platform using the extracted and stored keywords, store a shopping mall URL address searched on the shopping platform in the database, and store product data of the shopping mall in the database using the stored shopping mall URL address.

Description

Automation device for e-commerce cross-border and control method thereof

[0001] The present invention relates to an automation device for e-commerce cross-bordering and a control method thereof, and more specifically, to an automation device for e-commerce cross-bordering and a control method thereof that automates a series of processes that a seller must perform in the process of overseas purchasing agency.

[0002] E-commerce cross-border business, which involves overseas purchasing agency services in the e-commerce market, generally follows the processes of product sourcing, product processing, product listing, order collection, product delivery, and customer service. In other words, sellers locate products from overseas, translate their descriptions or modify their images, and register them on open marketplaces. The registered products are displayed to buyers (consumers), and when a buyer makes a purchase, the order is received by the seller. The seller purchases the goods on behalf of the buyer and ships them to the buyer's address. Furthermore, the seller must resolve buyer inquiries throughout this entire process.

[0003] However, the lack of solutions to automate each of these processes presents a problem in that sellers must resolve all difficulties themselves. For example, there are challenges such as the difficulty of finding marketable products during the sourcing process, the difficulty of creating new product introduction pages for domestic customers to recognize even after finding products, the difficulty of considering many factors like international shipping costs when setting prices, the difficulty of not being able to ship domestically immediately upon receiving an order, and the difficulty of responding to buyer inquiries.

[0004] The present invention aims to solve the aforementioned problems by providing an automation device and a control method thereof that can automate a series of processes that a seller must perform during the process of overseas purchasing agency.

[0005] An automation device for e-commerce cross-bordering according to an embodiment of the present invention for achieving the above objective includes a database for storing data and a processor for controlling the automation device. When a preset word representing a popular search term is identified while scraping a webpage, the processor extracts keywords that have been searched more than a preset frequency and stores them in the database. It then searches a shopping platform using the extracted and stored keywords, stores the shopping mall URL address found on the shopping platform in the database, and stores product data of the shopping mall in the database using the stored shopping mall URL address.

[0006] And when a preset word representing the popular search term is identified, the processor can analyze the scraped webpage to identify the linked search engine, and extract keywords searched more than a preset frequency through the identified search engine and store them in the database.

[0007] In addition, the processor may store product data of the shopping mall as first temporary data in the database using the stored shopping mall URL address, compare the stored first temporary data with infringement determination data, and if the comparison result shows that the first temporary data corresponds to the infringement determination data, determine that it is data that cannot be sold and delete it from the database.

[0008] And the above infringement determination data includes pre-set prohibited word data based on deleted data and trademarked words, and the processor can control the database to add the above first temporary data, which is determined to be data that cannot be sold, as the above deleted data.

[0009] Additionally, the processor can control the database to search for similar products using product images constituting the first temporary data, and to store the data for the searched similar products in the first temporary data as final product data.

[0010] And the processor can generate option data to be attached to each of a plurality of products searched in the first shopping mall and at least one shopping mall different from the first shopping mall using the stored final product data, and can generate an option page configured as different options of a single product using the generated option data.

[0011] In addition, the processor can compare the first temporary data of the stored final product data with the data for the searched similar product to extract differences between the first shopping mall and at least one shopping mall different from the first shopping mall, match the extracted differences with pre-set option classification criteria, and generate option data based on the matched option classification criteria.

[0012] And the processor generates an option page with a function to select a product corresponding to each option based on the generated option data, sets an option price for each product corresponding to each option based on the selling price at the shopping mall sourcing the product corresponding to each option, shipping costs by product category, exchange rates, margins, payment fees, and shipping agent information, and can determine the regular price and sales price to be entered on the option page based on the set option price.

[0013] In addition, the processor can select one of a plurality of fully trained translation models based on the category of the target product for which the option page was generated, translate the option page using the selected fully trained translation model, and generate and save a product detail page by combining the translated option page with a header content file, a footer content file, and a product page containing the saved final product data.

[0014] And the processor can identify an image or text related to the price existing on a product page included in the stored final product data, and the identified image or text.

[0015] Meanwhile, a control method for an automation device according to an embodiment of the present invention for achieving the above objective may include the steps of: scraping a webpage; when a preset word representing a popular search term is identified during the scraping, extracting and storing keywords that have been searched more than a preset frequency; searching on a shopping platform using the extracted and stored keywords; storing a shopping mall URL address found on the shopping platform; and storing product data of the shopping mall using the stored shopping mall URL address.

[0016] And the step of extracting and storing the searched keywords may include, when a preset word representing the popular search terms is identified, a step of analyzing the scraped webpage to identify the linked search engine, and a step of extracting and storing keywords that have been searched more than a preset frequency through the identified search engine.

[0017] Additionally, the step of storing product data of the shopping mall may include the step of storing the product data of the shopping mall as first temporary data using the stored shopping mall URL address, the step of comparing the stored first temporary data with infringement determination data, and the step of determining that the first temporary data is unsellable data and deleting it if, as a result of the comparison, the first temporary data corresponds to the infringement determination data.

[0018] And the above infringement determination data includes pre-set prohibited word data based on deleted data and trademarked words, and the above deletion step may further include the step of adding the above first temporary data, which is determined to be data that cannot be sold, to the above deleted data.

[0019] Additionally, the step of storing product data of the shopping mall may further include the step of searching for similar products using product images constituting the first temporary data, and the step of storing the first temporary data as final product data by including data regarding the searched similar products.

[0020] The method may further include the step of generating option data to be attached to each of a plurality of products searched in the first shopping mall and at least one shopping mall different from the first shopping mall using the stored final product data, and the step of generating an option page that configures the plurality of products searched as different options of a single product using the generated option data.

[0021] Additionally, the step of generating the option data may include comparing the first temporary data of the stored final product data with the data for the searched similar product to extract differences between a plurality of products searched in the first shopping mall and at least one shopping mall different from the first shopping mall, matching the extracted differences with a preset option classification standard, and generating option data based on the matched option classification standard.

[0022] And the step of generating the above option page may include: generating an option page with a function added to allow selecting a product corresponding to each option based on the generated option data; setting an option price for each product corresponding to each option based on the price sold at the shopping mall sourcing the product corresponding to each option, shipping costs by product category, exchange rates, margins, payment fees, and shipping agent information; and determining the regular price and sales price to be entered on the above option page based on the set option price.

[0023] Additionally, the method may further include the steps of selecting one of a plurality of completed translation models based on the category of the target product for which the option page was generated, translating the option page using the selected completed translation model, and generating and saving a product detail page by combining the translated option page with a header content file, a footer content file, and a product page containing the saved final product data.

[0024] And the step of creating and saving the product detail page may include the step of identifying an image or text related to the price existing on the product page included in the saved final product data, and the step of removing the identified image or text.

[0025] According to various embodiments of the present invention as described above, it is possible to source goods that are likely to be sold automatically and goods that do not cause problems when sold to sellers who intend to source products from overseas shopping mall platforms and sell them on domestic open markets.

[0026] In addition, for sellers who source products from overseas shopping mall platforms and intend to sell them on domestic open markets, it can automatically generate a page containing product information that can be uploaded to the open market.

[0027] In addition, it has the effect of automatically registering products for sale on open markets and periodically updating and registering new products, automatically processing orders collected from multiple open markets, and filtering out cases where the seller might incur losses.

[0028] FIG. 1 is a conceptual diagram illustrating the operation of an automation device for e-commerce cross-bordering according to an embodiment of the present invention,

[0029] FIG. 2 is a schematic block diagram for explaining the configuration of an automation device according to one embodiment of the present invention,

[0030] FIG. 3 is a conceptual diagram for explaining the operation of a sourcing module according to an embodiment of the present invention,

[0031] FIG. 4 is a conceptual diagram for explaining the operation of a processing module according to an embodiment of the present invention,

[0032] FIG. 5 is a conceptual diagram for explaining the operation of a registration module according to an embodiment of the present invention,

[0033] FIG. 6 is a conceptual diagram for explaining the operation of an order processing module according to an embodiment of the present invention,

[0034] FIG. 7 is a conceptual diagram for explaining the operation of a purchasing module according to an embodiment of the present invention,

[0035] FIG. 8 is a conceptual diagram for explaining the operation of a delivery module according to an embodiment of the present invention,

[0036] FIG. 9 is a conceptual diagram for explaining the operation of a CS module according to an embodiment of the present invention, and,

[0037] FIGS. 10 to 13 are flowcharts for explaining a control method of an automation device according to an embodiment of the present invention.

[0038] Various embodiments of this document are described below with reference to the accompanying drawings. However, this is not intended to limit the technology described in this document to specific embodiments and should be understood to include various modifications, equivalents, and / or alternatives to the embodiments of this document. Similar reference numerals may be used for similar components in connection with the description of the drawings.

[0039] In this document, expressions such as 'have,' 'can have,' 'include,' or 'can include' refer to the existence of the relevant feature (e.g., components such as numerical values, functions, actions, or parts) and do not exclude the existence of additional features.

[0040] In this document, expressions such as 'A or B', 'at least one of A and / or B', or 'one or more of A and / or B' may include all possible combinations of items listed together. For example, 'A or B', 'at least one of A and B', or 'at least one of A or B' may refer to cases including (1) at least one A, (2) at least one B, or (3) both at least one A and at least one B. Expressions such as 'first', 'second', 'first', or 'second' used in this document may modify various components regardless of order and / or importance, and are used only to distinguish one component from another and do not limit said components.

[0041] As used in this document, the expression 'configured to' may be replaced, depending on the context, with, for example, 'suitable for,' 'having the capacity to,' 'designed to,' 'adapted to,' 'made to,' or 'capable of.' The term 'configured to' does not necessarily mean 'specifically designed to' in hardware. Instead, in some situations, the expression 'device configured to' may mean that the device is 'capable of' doing something together with other devices or components.

[0042] The terms used in this specification are for the purpose of describing embodiments and are not intended to limit or / or restrict the invention. Singular expressions include plural expressions unless the context clearly indicates otherwise. In this specification, terms such as "comprising" or "having" are intended to indicate the existence of the features, numbers, actions, components, parts, or combinations thereof described in the specification, and should be understood as not precluding the existence or addition of one or more other features, numbers, actions, components, parts, or combinations thereof.

[0043] In the embodiments, a 'module' or 'part' performs at least one function or operation and may be implemented in hardware or software, or a combination of hardware or software. Additionally, a plurality of 'modules' or a plurality of 'parts' may be integrated into at least one module and implemented by at least one processor, except for a 'module' or 'part' that needs to be implemented in specific hardware.

[0044] The present invention will be described in detail below using the attached drawings.

[0045] FIG. 1 is a conceptual diagram illustrating the operation of an automation device (1000) for e-commerce cross-bordering according to an embodiment of the present invention. The automation device (1000) may operate in a SaaS form in a cloud environment or in an on-premises form. In the example of FIG. 1, for convenience in understanding each function and operation of the automation device (1000), it will be described by dividing it into a total of seven modules. Furthermore, the automation device (1000) will be described primarily in terms of operating in a SaaS-type cloud.

[0046] Referring to FIG. 1, the automation device (1000) can transmit and receive data with domestic and international open market servers (2000), delivery agency servers (3000), and shopping mall servers (4000) and perform overseas purchasing agency operations. Additionally, the automation device (1000) visualizes data related to products, purchases, payments, delivery, and customer inquiries so that it can be checked on a seller terminal (5000) and / or an administrator terminal (6000). Referring to FIG. 1, the terms used in this specification will be defined. A seller refers to a person who acts as an agent for a buyer's purchase of goods through overseas purchasing agency. A seller also refers to a user of the automation device (1000) who has obtained usage rights in the form of a subscription, etc. A buyer refers to a general consumer. An open market refers to a platform where a seller sells goods to a buyer. A shopping mall refers to a platform for a seller to source goods that a buyer has requested to purchase. Although an open market and a shopping mall may be the same platform, a shopping mall is used to mean a place where a seller sources goods, and an open market is used to mean a place where a seller sells the goods sourced.

[0047] Each function and operation of the automation device (1000) can be broadly divided into seven types, and these are named respectively as the sourcing module (1100), processing module (1200), registration module (1300), order processing module (1400), purchasing module (1500), delivery module (1600), and CS module (1700).

[0048] FIG. 2 is a schematic block diagram for explaining the configuration of an automation device (1000) according to an embodiment of the present invention. Referring to FIG. 2, the automation device (1000) may include a database (10), a communication unit (20), and a processor (30). In addition, it is obvious that it may include other components such as an input unit (not shown), a display (not shown), and a memory (not shown).

[0049] The database (10) can store data necessary to operate the automation device (1000). Additionally, the database (10) can perform operations such as moving, copying, or deleting previously stored data under the control of the processor (30). For example, the database (10) may include various data such as keyword data, shopping mall-related data, product data, infringement determination data, data on similar products, option data, order data, inventory data, and delivery data.

[0050] Memory (not shown) can be used as a concept including a database (10). Memory (not shown) can store various modules, software, functions, AI learning completed models, data, etc. for operating an automation device (1000). For example, a function that performs an operation to extract product data can be stored in memory (not shown), and at least one AI learning completed model for appropriately translating for each product category can be stored.

[0051] The communication unit (20) communicates with external servers and devices such as an open market server (2000), a delivery agency server (3000), a shopping mall server (4000), a seller terminal (5000), and an administrator terminal (6000). For example, the automation device (1000) can access a webpage on an external server through the communication unit (20) to scrape product data.

[0052] To this end, the communication unit (20) can use wired communication methods such as LAN, HDMI, etc., and wireless communication methods such as wireless LAN, NFC, IR communication, Zigbee communication, Bluetooth, etc.

[0053] The processor (30) can control the remaining configuration of the automation device (1000). For example, the processor (30) can control the database (10) to store the first temporary data as final product data, including data for similar products.

[0054] The processor (30) can be implemented as a single CPU to perform product sourcing, product information processing, product registration, order processing, etc., and may also be implemented as multiple processors and IPs that perform specific functions. The specific operation of the processor (30) will be described later.

[0055] FIG. 3 is a conceptual diagram for explaining the operation of a sourcing module (1100) according to an embodiment of the present invention. Referring to FIG. 3, the sourcing module (1100) may include a popular search term extraction function (1110), a product data extraction function (1120), a product filter function (1130), and a similar product extraction function (1140). Since these modules and functions are called and operated through a processor (30), for convenience of explanation, the names of the processor (30) and each module and function will be used interchangeably in the following description.

[0056] The processor (30) can call the popular search term extraction function (1110) to extract and store keywords that have been searched more than a preset frequency. This performs the function of finding keywords that match trends in order to source products likely to be sold in large quantities. The processor (30) can scrape web pages. And when the processor (30) detects a preset word indicating a popular search term during scraping, it can extract the keyword and store it in the database (10). For example, the processor (30) can extract and store popular keywords by using the detection of a word such as 'Popular Search Terms TOP 10' on the web page being scraped as a trigger.

[0057] More specifically, when a pre-set word representing popular search terms, such as 'Top 10 Popular Search Terms', is identified, the processor (30) can analyze the scraped webpage to identify the linked search engine. Then, the processor (30) can extract keywords that have been searched more than a pre-set frequency through the identified search engine and store them in the database (10). For example, the processor (30) can extract popular keywords through the trend analysis function of the search engine.

[0058] Next, the processor (30) can call the product data extraction function (1120) to collect information about shopping malls that are selling products corresponding to the extracted keywords. The processor (30) can search on the shopping platform using the keywords extracted and stored in the database (10). The shopping platform may be various overseas open markets or a company's own mall. The processor (30) can scrape the URL address, shopping mall name, etc. of the shopping mall searched on the shopping platform and store them in the database (10). In the following, actions such as receiving data from the shopping mall may be interpreted as receiving data from the shopping mall server (4000). For convenience of explanation, the shopping mall and the shopping mall server (4000) are used interchangeably.

[0059] And the processor (30) can call the product filter function (1130) to collect product data, and at the same time, delete product data for products that cannot be sold due to the risk of infringing intellectual property rights. The processor (30) can store the product data of the shopping mall in the database (10) using the collected shopping mall URL address.

[0060] Specifically, the processor (30) can scrape product data from a shopping mall using a stored shopping mall URL address. At this time, the processor (30) can store the product data from the shopping mall as first temporary data. Then, the processor (30) can compare the stored first temporary data with infringement judgment data.

[0061] The infringement determination data may include prohibited word data and deletion data. The prohibited word data may be a pre-set data set based on words registered as trademarks. The deletion data may be a data set in which the names, trademarks, names, etc. of products that are deleted as products that cannot be sold through the operation of the product filter function (1130) are collected.

[0062] If, as a result of comparison with the infringement determination data, it is determined that the first temporary data corresponds to the infringement determination data, the processor (30) can determine that the first temporary data is data regarding a product that cannot be sold and delete it. Then, the processor (30) can manage the first temporary data determined as data that cannot be sold by adding it as deleted data. Through this, the data set for determining the risk of intellectual property infringement can be continuously updated.

[0063] The processor (30) may call the similar product extraction module (1140) to search for and manage similar products together using the stored product data. The processor (30) may extract product images constituting the first temporary data. Then, the processor (30) may search for similar products using the extracted product images. Subsequently, the processor (30) may control the database (10) to include data regarding the similar products searched in the first temporary data and store them as final product data. Additionally, the processor (30) may prevent duplicate data collection when searching for similar product data by using the shopping mall name stored together when storing the shopping mall URL address.

[0064] FIG. 4 is a conceptual diagram for explaining the operation of a processing module (1200) according to an embodiment of the present invention. Referring to FIG. 4, the processing module (1200) may include an option page creation function (1210), an option translation function (1220), and a detail page creation function (1230). Since these modules and functions are called and operated through a processor (30), for convenience of explanation, the names of the processor (30) and each module and function will be used interchangeably in the following description.

[0065] The processor (30) calls the option page creation function (1210) to perform the task of creating multiple options for a single product from data of a product to be sold, specifically multiple similar products sourced from multiple shopping malls. Specifically, the processor (30) can classify the data for similar products stored through the sourcing module (1100) into options. The processor (30) can control the database (10) to store the product data of the first shopping mall from which the product is to be sourced as the first temporary data. The processor (30) can also search for similar products from at least one shopping mall different from the first shopping mall using the product images constituting the first temporary data. The data for the searched similar products can be stored as final product data along with the first temporary data.

[0066] The processor (30) can use the stored final product data to generate option data to be attached to each of the multiple products searched in the first shopping mall and at least one shopping mall different from the first shopping mall. The processor (30) can also use the generated option data to generate an option page that configures the searched 'multiple products' into 'other options of one product'.

[0067] More specifically, when generating option data, the processor (30) can compare the first temporary data of the stored final product data with data for similar products. The processor (30) can extract differences between these multiple products. The processor (30) can match the extracted differences with pre-set option classification criteria. By matching with option classification criteria having a certain standard, the creation of option pages can be done consistently. For example, the option classification criteria can be composed of standardized specifications such as color, size, dimensions, and length. The processor (30) can generate option data based on the matched option classification criteria.

[0068] Next, the processor (30) can generate an option page with a function added to select a product corresponding to each option based on the generated option data. In some cases, the number of option data may exceed one; in such cases, the option page is generated based on the first option, and options after the second option can be combined and displayed. When multiple option data exist, which option is set as the first option can be determined according to the option selection priority set according to the product category. For example, depending on the product category, the criteria for customer selection may be color or size.

[0069] The processor (30) can set different prices for each product corresponding to each option when creating an option page. Since products with different options are likely to be sourced from different shopping malls, prices may not be consistent. Setting option prices is intended to adjust for this price inconsistency.

[0070] Specifically, the processor (30) can set the option price for each product corresponding to each option based on the price at which the product corresponding to each option is sold at the shopping mall sourcing the product, shipping costs by product category, exchange rates, margins, payment fees, and shipping agency information.

[0071] And the processor (30) can determine the regular price and the selling price to be entered on the option page based on the set option price. For example, the regular price can be set to a price corresponding to 100% of the option price. The selling price is set to a price equal to or lower than the option price, and based on the data of each item used to set the option price, the processor (30) can set the selling price to a value between 100% and 50% of the option price by deriving an item that can lower the price.

[0072] The processor (30) can perform appropriate translations for each product category by calling the option translation function (1220). Specifically, the processor (30) can select one of a plurality of trained translation models based on the category of the target product for which the option page was created. The plurality of trained translation models may be artificial intelligence models that have learned the language, terminology, nuances, etc. commonly used in the field based on the category. The processor (30) can translate the option page using the selected trained translation model.

[0073] Next, the processor (30) can create a product detail page to be registered on the open market server (2000) by calling a detail page creation function (1230). Specifically, the processor (30) can create a product detail page by combining a translated option page, a header content file (image, audio, video, etc.), a footer content file (image, audio, video, etc.), and a product page containing the saved final product data. Then, the processor (30) can control the database (10) to save the created product detail page.

[0074] When generating a product detail page, the processor (30) can identify images or text related to prices present in the product page included in the stored final product data. For example, it identifies an image that has a portion of the image containing the overseas local selling price. Then, the processor (30) can remove the identified images or text. Of course, appropriate image processing can be performed so that the removed portion does not look awkward. Through this, it is possible to prevent price information different from the selling price set through the option price from being included in the product detail page.

[0075] FIG. 5 is a conceptual diagram for explaining the operation of a registration module (1300) according to an embodiment of the present invention. Referring to FIG. 5, the registration module (1300) may include a product registration function (1310) and a product initialization function (1320). Since these modules and functions are called and operated through a processor (30), for convenience of explanation, the names of the processor (30) and each module and function will be used interchangeably in the following description. In the following description, operations such as receiving data from an open market may be interpreted as receiving data from an open market server (2000). For convenience of explanation, the terms open market and open market server (2000) will be used interchangeably.

[0076] The processor (30) can register products on multiple open markets by calling the product registration function (1310). To register on each open market, data for product registration must be generated to meet the requirements of each open market. To this end, the processor (30) can generate a data format that meets the respective requirements for registering on at least one open market. The processor (30) can convert product data, including a previously stored product detail page, into a JSON format and apply the converted product data to the generated data format to generate data that can be used for product registration.

[0077] The processor (30) can register a product on behalf of the seller in a corresponding open market using the generated product registration data. At this time, authentication of the seller is required for product registration. To this end, when product registration data is generated, the processor (30) can control the communication unit (20) to transmit authentication for product registration to the seller's terminal (5000). When a key value is received from the seller terminal (5000) through the communication unit (20), the processor (30) can complete authentication by comparing the received key value with the key value stored in the database (10). Once authentication is completed, the processor (30) can proceed with product registration in the open market using the product registration data.

[0078] And when the processor (30) receives from the open market server (2000) via the communication unit (20) that product registration is complete, it can match the registered product with the seller and store it in the database (10). By matching the seller with the product, it is possible to request payment from the seller when an order for the product is placed, notify the seller when a CS occurs, and perform actions such as settling the sale to the seller when sales revenue is generated.

[0079] The processor (30) can call the product initialization function (1320) to initialize the product registration and proceed with new product registration. Since open markets are platforms where products reflecting trends sell well, it is not appropriate to register and sell the same product for a long period without change. This is especially true for sellers who generate revenue through overseas purchasing agency. For this reason, the processor (30) can execute product registration initialization after a preset period has elapsed following the completion of product registration. For example, initialization can be executed after one month has elapsed since product registration, or initialization can be executed on the 1st of every month.

[0080] Specifically, the processor (30) can delete all products for which product registration has been completed from the open market. It can also classify products stored in the database (10) to select products for new product registration. Even after product registration, products are continuously added to the database through the sourcing module (1100) and the processing module (1200). The processor (30) can classify products stored in the database (10) into products that have been sold, products that have not been sold, and new sourced products. Products that have been sold can be classified based on whether there is a history of sales. Products that have not been sold and new sourced products can be classified based on the date they were registered in the database (10).

[0081] Next, the processor (30) can adjust the ratio of products of each category through a distribution model. For example, the distribution model may be a fully trained model that takes at least one of the sales frequency, the set sales price, and the subscription period of the seller as input values ​​and outputs a product distribution ratio that maximizes the total sales amount. Once the optimal product distribution ratio is determined, the processor (30) can proceed with product registration again according to the adjusted ratio of products. The process of proceeding with product registration again is the same as the process of registering products on an open market by calling the product registration function (1310) described above.

[0082] FIG. 6 is a conceptual diagram for explaining the operation of an order processing module (1400) according to an embodiment of the present invention. Referring to FIG. 6, the order processing module (1400) may include an inventory check function (1410), a margin calculation function (1420), a personal customs clearance code check function (1430), and an order approval function (1440). Since these modules and functions are called and operated through a processor (30), for convenience of explanation, the names of the processor (30) and each module and function will be used interchangeably in the following description.

[0083] The processor (30) can collectively collect and process orders from various open markets operated through the order processing module (1400). In particular, it collects information on the inventory quantity and fluctuating prices of shopping malls from which products are sourced, and if the pre-set conditions are not met, it cancels the order to prevent the seller from suffering a loss.

[0084] When a processor (30) receives an order signal through a communication unit (20) from at least one open market server (2000) where a product is registered, it can call an inventory check function (1410) to determine whether the inventory quantity of the product corresponding to the received order signal is greater than or equal to the order quantity. Specifically, the processor (30) can transmit a signal to a shopping mall server (4000) that sources the product to check the inventory quantity of the product, and determine whether the order can be processed by comparing the product inventory quantity information received from the shopping mall server (4000) with the order quantity.

[0085] If it is determined that the inventory quantity of a product is greater than or equal to the order quantity, the processor (30) calls the margin calculation function (1420) to calculate the margin. At this time, the margin may be a margin expressed as a monetary amount or a margin rate expressed as a percentage. The processor (30) can control the communication unit (20) to receive product price information from the shopping mall that has verified the product inventory quantity. Then, the processor (30) can calculate the margin by comparing the received product price information with the sales price registered on the open market server (2000). Since there is a possibility that the shopping mall from which the product is sourced has changed the price, a new margin is calculated and compared with the margin set when the sales price was previously determined. The processor (30) can determine that the condition is satisfied if the current margin is equal to or higher than the margin set when the sales price was determined. Conversely, if the margin set when the sales price was determined is lower than the current margin, the processor can determine whether the condition is satisfied by determining whether it corresponds to an allowable margin.

[0086] If the calculated margin does not satisfy these preset conditions, the processor (30) can control the communication unit (20) to send a signal to the open market server (2000) that received the order signal to cancel the order corresponding to the received order signal. Conversely, if the calculated margin satisfies the preset conditions, the processor (30) can control the database (10) to change the state of the received order signal to an order-available state.

[0087] Next, the processor (30) can call the personal customs clearance code verification function (1430) to check whether information required for overseas direct purchase agency has been entered. When it is confirmed that the state stored in the database (10) has been changed to an orderable state, the processor (30) can determine whether a value corresponding to the personal customs clearance code exists. If it is determined that a value corresponding to the personal customs clearance code has been entered in advance, the processor (30) can control the database (10) to change the orderable state to a delivery ready state. Conversely, if there is no value corresponding to the personal customs clearance code, the processor (30) can wait until a value is entered.

[0088] When it is confirmed that the status has changed to a shipping preparation state, the processor (30) can call the order approval function (1440) to approve the order. Then, when the order is approved, the processor (30) can control the communication unit (20) to transmit information regarding the approved product to the seller terminal (4000). Although the seller does not need to directly approve the order through the automation system, this is to notify the seller of the details regarding the approved order.

[0089] FIG. 7 is a conceptual diagram for explaining the operation of a purchasing module (1500) according to an embodiment of the present invention. Referring to FIG. 7, the purchasing module (1500) may include a payment request function (1510), a payment approval function (1520), an order ordering function (1530), and an order details transmission function (1540). Since these modules and functions are called and operated through a processor (30), for convenience of explanation, the names of the processor (30) and each module and function will be used interchangeably in the following description.

[0090] The processor (30) can automate the batch processing of purchasing agency from various shopping malls according to the order history of multiple open market servers (2000) through the purchasing module (1500). The processor (30) can control the database (10) to change the status from the shipping preparation state to the order approval state when an order is approved. When it is confirmed that the status has been changed to the order approval state, the processor (30) can control the communication unit (20) to call the payment request function (1510) and send a payment request message regarding the details of the sale price to the seller terminal (4000). The processor (30) can also control the database (10) to change the status to the payment request state.

[0091] Subsequently, the processor (30) calls the payment approval function (1520) to proceed with the payment. When a payment request signal is received from the seller terminal (4000), the processor (30) can control the communication unit (20) to retrieve the details to be paid from the database (10) to configure the screen and transmit the configured screen to the seller terminal (4000). When a signal indicating that the payment has been approved is received from the seller terminal (4000), the processor (30) can control the database (10) to change the state to a payment approval state.

[0092] When it is confirmed that the payment approval status has changed, the processor (30) can order products by calling the order order function (1530). The processor (30) can retrieve a list of products in the payment approval status from the database (10), create an order form suitable for each shopping mall server (4000), and transmit it. Additionally, the processor (30) can proceed with payment by utilizing the payment method provided by each shopping mall server (4000). The processor (30) can control the database (10) to change the status to order order completed for products for which payment has been completed at the shopping mall.

[0093] Subsequently, the processor (30) can control the communication unit (20) to call the order details transmission function (1540) to transmit details of the completed shopping mall payment to the shipping agency server (3000). The content transmitted to the shipping agency server (3000) may include the origin country code, destination country code, shipping method, customs clearance classification, personal customs clearance unique code, recipient information, product information, inspection options, whether freight shipping fees have been paid, and whether customs duties and taxes have been paid. In response to this, the shipping agency server (3000) transmits the destination country tracking number of the transmitted product. The processor (30) can control the database (10) to store the destination country tracking number received through the communication unit (20).

[0094] FIG. 8 is a conceptual diagram for explaining the operation of a delivery module (1600) according to an embodiment of the present invention. Referring to FIG. 8, the delivery module (1600) may include a shipping label verification function (1610), a shipping label transmission function (1620), and a delivery tracking function (1630). Since these modules and functions are called and operated through a processor (30), for convenience of explanation, the names of the processor (30) and each module and function will be used interchangeably in the following description.

[0095] The processor (30) can check the shipping label in transit by calling the shipping label verification function (1610) at preset time intervals. The shipping label information can be received from the delivery agency server (3000). The processor (30) can also control the database (10) to update the verified information. The processor (30) can configure a screen displaying the delivery status and control the communication unit (20) to transmit the configured screen to the seller terminal (5000).

[0096] Next, the processor (30) can call the shipping label transmission function (1620) to transmit the destination country shipping label number to the open market server (2000) where the purchase occurred, thereby enabling domestic delivery tracking. While delivery is in progress overseas, delivery tracking is not possible through the open market server (2000), but after the cargo is transported to the domestic market, delivery tracking becomes possible through the open market server (2000).

[0097] The processor (30) calls the delivery tracking function (1630) to provide the delivery status to the seller terminal (5000). The processor (30) can visualize the delivery status of the database (10) in real time. The processor (30) can also control the communication unit (20) to transmit the visualized information to the seller terminal (5000). Since delivery tracking is not possible through the open market server (2000) when the product is being shipped overseas, when the processor (30) receives a signal from the seller terminal (5000) requesting that the buyer be notified about the product being shipped overseas, the processor (30) can control the communication unit (20) to transmit a notification message about the current delivery status overseas to the buyer.

[0098] FIG. 9 is a conceptual diagram for explaining the operation of a CS module (1700) according to an embodiment of the present invention. Referring to FIG. 9, the CS module (1700) may include a return processing function (1710), an exchange processing function (1720), a cancellation processing function (1730), an inquiry confirmation function (1740), and an inquiry processing function (1750). Since these modules and functions are called and operated through a processor (30), for convenience of explanation, the names of the processor (30) and each module and function will be used interchangeably in the following description.

[0099] The processor (30) can check the history of inquiries made to the seller through the open market server (2000) via the CS module (1700) and automatically take action.

[0100] The processor (30) may call the return processing function (1710) at preset intervals to request data of the product for which a return request has occurred from the open market server (2000). Based on the received data, the processor (30) updates the database (10). The product for which a return request is in progress may be visualized by the processor (30) and transmitted to the administrator terminal (6000). When a return approval signal is received from the administrator terminal (6000), the processor (30) may control the database (10) so that information indicating that the return has been approved is updated.

[0101] The processor (30) may call the exchange processing function (1720) at preset intervals to request data of the product for which an exchange request has occurred from the open market server (2000). Based on the received data, the processor (30) updates the database (10). The product for which an exchange request is in progress may be visualized by the processor (30) and transmitted to the administrator terminal (6000). When an exchange approval signal is received from the administrator terminal (6000), the processor (30) may control the database (10) so that information indicating that the exchange has been approved is updated.

[0102] The processor (30) may call the cancellation processing function (1730) at preset intervals to request data of the product for which a cancellation request has occurred from the open market server (2000). Based on the received data, the processor (30) processes the order cancellation through the following process. First, the processor (30) determines whether the order processing has already begun or has already begun. If the order processing has already begun, the processor (30) may control the database (10) to immediately cancel the order and update the product data. Conversely, if the order processing has already begun, the processor (30) rejects the cancellation request. The processor (30) may also control the communication unit (20) to send a notification message to the buyer stating that cancellation is difficult because the product purchase or delivery process is in progress, but that a return is possible in the future.

[0103] The processor (30) can collect inquiry history from the open market server (2000) by calling an inquiry confirmation function (1740) at preset intervals. The collected inquiry history is stored in the database (10), and the processor (30) can visualize the history and control the communication unit (20) to transmit the visualized history to the seller terminal (5000) and the administrator terminal (6000).

[0104] The inquiry processing function (1750) is called by the processor (30) when an operation signal is received from the administrator terminal (6000) through the communication unit (20). The processor (30) can use a chatbot to explore the context of the inquiry made by the buyer and classify it into simple inquiries and complex inquiries. If classified as a simple inquiry, the processor (30) can send a rule-based answer to the open market server (2000). If classified as a complex inquiry, the processor (30) can send the answer received from the administrator terminal (6000) to the open market server (2000).

[0105] According to various embodiments of the present invention as described above, a seller who sells products on an open market through overseas purchasing agency can reduce the effort required to find products, process products, register products, purchase products when an order is received, process delivery, and perform customer service including customer management, and can also reduce the costs incurred.

[0106] Furthermore, this cost-saving sales process allows buyers to quickly receive products at lower prices and enables prompt action regarding defective goods.

[0107] In the following, additional explanations will be provided through flowcharts to aid in understanding the various embodiments of the present invention described above. The specific control method of the automation device (1000) described through the flowchart corresponds to the contents of the automation device (1000) described above.

[0108] FIG. 10 is a flowchart for explaining a control method of an automation device (1000) according to an embodiment of the present invention. In particular, FIG. 10 describes a method for automating product sourcing. According to FIG. 10, the automation device (1000) can scrape web pages (S1010). If a preset word representing a popular search term is identified during scraping, the automation device (1000) can extract and store keywords that have been searched more than a preset frequency (S1020). Specifically, if a preset word representing a popular search term is identified, the automation device (1000) can analyze the scraped web page to determine what the linked search engine is. Then, through the identified search engine, keywords that have been searched more than a preset frequency can be extracted and stored. For example, keywords that have been searched more than a preset frequency can be extracted through the trend analysis function of the search engine.

[0109] Next, the automation device (1000) can search on a shopping platform using the extracted and stored keywords (S1030). Then, the automation device (1000) can store the shopping mall URL address found on the shopping platform (S1040). At this time, in addition to the shopping mall URL address, the shopping mall name, etc., can be additionally stored. For example, the shopping mall name can be used as a keyword to prevent duplicate searches when searching for similar products.

[0110] The automation device (1000) can store product data of a shopping mall using a stored shopping mall URL address (S1050). Specifically, the automation device (1000) can store the product data of the shopping mall as first temporary data. Then, it can determine whether the first temporary data is data regarding a product that can be sold by comparing it with infringement determination data. If it corresponds to the infringement determination data, the first temporary data can be determined as data that cannot be sold and deleted. The infringement determination data is divided into prohibited word data and deleted data, and the first temporary data that was deleted because it corresponded to the infringement determination data can be added to the deleted data. Through this, the effect of continuously updating the infringement determination data can be achieved.

[0111] Additionally, the automation device (1000) can search for similar products using product images constituting the first temporary data. Data regarding the searched similar products can be included in the first temporary data and stored as final product data.

[0112] FIG. 11 is a flowchart for explaining a control method of an automation device (1000) according to an embodiment of the present invention. In particular, FIG. 11 describes a method for automating product page processing. Referring to FIG. 11, the automation device (1000) can store product data from a first shopping mall to source products as first temporary data (S1110). Then, the automation device (1000) can search for similar products from at least one shopping mall different from the first shopping mall using product images constituting the first temporary data (S1120), and can store the data for the similar products searched in the first temporary data as final product data (S1130).

[0113] Next, the automation device (1000) can generate option data to be attached to each of a plurality of products searched in the first shopping mall and at least one shopping mall different from the first shopping mall using the stored final product data (S1140). Specifically, the automation device (1000) can compare the first temporary data of the stored final product data with the data for similar products searched, and extract the differences between the first shopping mall and the plurality of products searched in the at least one shopping mall different from the first shopping mall. Then, the extracted differences can be matched with pre-set option classification criteria to generate option data.

[0114] And the automation device (1000) can generate an option page that configures multiple searched products as different options of a single product using the generated option data (S1150). That is, it can generate an option page that includes a function to select a product corresponding to each option based on the generated option data.

[0115] And the automation device (1000) can generate an option page and determine and add a sales price. The automation device (1000) can set an option price for each product corresponding to each option based on the price at which the product corresponding to each option is sold in a shopping mall that sources the product, shipping costs by product category, exchange rates, margins, payment fees, and shipping agent information. Then, based on the set option price, the regular price and sales price to be entered on the option page can be determined, and the sales price can be set to be less than or equal to the option price.

[0116] Additionally, the automation device (1000) may also translate an option page. Specifically, the automation device (1000) may select one of a plurality of fully trained translation models based on the category of the target product for which the option page was created. Then, the option page may be translated using the selected fully trained translation model. The automation device (1000) may create and save a product detail page by combining a header content file (image, audio, video, etc.), a footer content file (image, audio, video, etc.), and a product page containing the saved final product data with the translated option page. When creating the product detail page, the automation device (1000) may identify and remove images or text related to prices present in the product page included in the saved final product data.

[0117] FIG. 12 is a flowchart for explaining a control method of an automation device (1000) according to an embodiment of the present invention. In particular, FIG. 12 describes a method for automating the process of registering a product on an open market. According to FIG. 12, the automation device (1000) can generate a data format in accordance with each requirement for registration on at least one open market (S1210). Then, the automation device (1000) converts product data including a previously stored product detail page into a JSON format (S1220), and applies the converted product data to the generated data format to generate data that can proceed with product registration (S1230).

[0118] Next, the automation device (1000) can register a product on a corresponding open market on behalf of the seller using the generated product registration data (S1240). Specifically, when the product registration data is generated, the automation device (1000) can transmit authentication for product registration to the seller's terminal. Then, it performs authentication by comparing the key value received from the seller's terminal with the key value stored in the database, and if authentication is completed, it can register the product on the open market. When it receives from the open market server that the product registration is complete, the automation device (1000) can match the registered product with the seller and store them (S1250).

[0119] Additionally, the automation device (1000) can perform product registration initialization after a preset period has elapsed following the completion of product registration. Specifically, the automation device (1000) can start the initialization by deleting all products for which product registration has been completed from the open market. Subsequently, the automation device (1000) can classify products stored in the database into products that have been sold, products that have not been sold, and newly sourced products. Then, the automation device (1000) can proceed with product registration again by adjusting the ratio of products in each category through a distribution model. For example, the distribution model may be a completed learning model that takes at least one of the sales frequency, the set sales price, and the subscription period of the seller as input values ​​and outputs a product distribution ratio that maximizes the total sales amount.

[0120] FIG. 13 is a flowchart for explaining a control method of an automation device (1000) according to an embodiment of the present invention. In particular, FIG. 13 describes a method for automating the operation of processing multiple orders received from multiple open markets. Referring to FIG. 13, when an order signal is received from at least one open market server, the automation device (1000) can determine whether the inventory quantity of a product corresponding to the received order signal is greater than or equal to the order quantity (S1310). If the inventory quantity is less than the order quantity, the automation device (1000) can cancel the order. Conversely, if it is determined that the inventory quantity of a product is greater than or equal to the order quantity, the automation device (1000) can calculate a margin (S1320). Specifically, the automation device (1000) can receive product price information sold at a shopping mall that has confirmed the product inventory quantity, and calculate a margin by comparing the received product price information with the sales price registered for the product. Then, the automation device (1000) can determine whether the calculated margin satisfies a preset condition.

[0121] If the calculated margin satisfies the preset conditions, the automation device (1000) can change the state of the received order signal to an orderable state (S1330). Conversely, if the calculated margin does not satisfy the preset conditions, the automation device (1000) can cancel the order corresponding to the received order signal.

[0122] When it is confirmed that the ordering status has been changed to an orderable state, the automation device (1000) can check whether a value corresponding to the personal customs clearance code exists. If it is determined that a value corresponding to the personal customs clearance code exists, the automation device (1000) can change the orderable state to a shipping preparation state. Conversely, if it is determined that a value corresponding to the personal customs clearance code does not exist, the automation device (1000) can wait until a value corresponding to the personal customs clearance code is entered. When it is confirmed that the status has been changed to a shipping preparation state, the automation device (1000) can approve the order and transmit information regarding the approved product to the seller terminal.

[0123] In addition, the method of automating the collection of orders from various open markets and purchasing products from each shopping mall, the method of automating the confirmation of product delivery, and the method of automating the processing of CS such as buyer's return requests and inquiries are replaced by the description of the automation device (1000) described above.

[0124] The methods described above may be implemented in the form of program instructions that can be executed through various computer means and recorded on a computer-readable medium. The computer-readable medium may include program instructions, data files, data structures, etc., either individually or in combination. The program instructions recorded on the medium may be those specifically designed and configured for the present invention, or they may be those known and available to those skilled in the art of computer software. Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks, and magnetic tapes; optical recording media such as CD-ROMs and DVDs; magneto-optical media such as floptical disks; and hardware devices specifically configured to store and execute program instructions, such as ROM, RAM, and flash memory. Examples of program instructions include machine code, such as that generated by a compiler, as well as high-level language code that can be executed by a computer using an interpreter, etc. The hardware devices may be configured to operate as one or more software modules to perform the operation of the present invention, and vice versa.

[0125] As described above, although the present disclosure has been explained by limited embodiments and drawings, the present disclosure is not limited to the above embodiments, and various modifications and variations are possible from this description by those skilled in the art to which the present disclosure belongs. Therefore, the scope of the present disclosure should not be limited to the described embodiments, but should be defined by the claims set forth below as well as equivalents thereof.

Claims

1. In an automation device for e-commerce cross-border, A database that stores data; and A processor that controls the above-mentioned automation device; and The above processor is, An automated device that, when a preset word representing a popular search term is identified while scraping a webpage, extracts keywords searched at a frequency greater than a preset frequency and stores them in the database, searches a shopping platform using the extracted and stored keywords, stores the shopping mall URL address found on the shopping platform in the database, and stores product data of the shopping mall in the database using the stored shopping mall URL address.

2. In Paragraph 1, The above processor is, An automated device that, when a preset word representing the above popular search term is identified, analyzes the above scraped webpage to identify the linked search engine, extracts keywords searched at a frequency greater than a preset frequency through the identified search engine, and stores them in the above database.

3. In Paragraph 1, The above processor is, An automated device that uses the stored shopping mall URL address to store product data of the shopping mall as first temporary data in the database, compares the stored first temporary data with infringement determination data, and if the comparison result shows that the first temporary data corresponds to the infringement determination data, determines that the data cannot be sold and deletes it from the database.

4. In Paragraph 3, The above infringement determination data is, Includes pre-set prohibited word data based on deleted data and trademarked words, and The above processor is, An automated device for controlling the database to add the first temporary data, which is determined to be unsellable data, as the deleted data.

5. In Paragraph 3, The above processor is, An automated device for controlling a database to search for similar products using product images constituting the first temporary data, and to store the data for the searched similar products in the first temporary data as final product data.

6. In Paragraph 5, The above processor is, An automated device that generates option data to be attached to each of a plurality of products searched in the first shopping mall and at least one shopping mall different from the first shopping mall using the stored final product data, and generates an option page configured as different options of a single product using the generated option data.

7. In Paragraph 6, The above processor is, An automated device that compares the first temporary data of the stored final product data with the data for the searched similar products, extracts differences between a plurality of products searched in the first shopping mall and at least one shopping mall different from the first shopping mall, matches the extracted differences with preset option classification criteria, and generates option data based on the matched option classification criteria.

8. In Paragraph 6, The above processor is, An automated device that generates an option page with a function to select a product corresponding to each option based on the above-mentioned generated option data, sets an option price for each product corresponding to each option based on the selling price at a shopping mall sourcing the product corresponding to each option, shipping costs by product category, exchange rates, margins, payment fees, and shipping agent information, and determines the regular price and sales price to be entered on the option page based on the set option price.

9. In Paragraph 6, The above processor is, An automated device that selects one of a plurality of fully trained translation models based on the category of the target product for which the above option page was generated, translates the above option page using the selected fully trained translation model, and generates and saves a product detail page by combining the above translated option page with a header content file, a footer content file, and a product page containing the above saved final product data.

10. In Paragraph 9, The above processor is, An automated device that identifies images or text related to prices existing on product pages included in the stored final product data and removes the identified images or text.

11. A method for controlling an automation device for e-commerce cross-border, The step of scraping web pages; If a preset word representing a popular search term is identified during the scraping process, a step of extracting and storing keywords searched at a frequency greater than a preset frequency; A step of searching on a shopping platform using the keywords extracted and stored above; A step of storing the shopping mall URL address found on the shopping platform above; and A control method for an automation device comprising the step of storing product data of the shopping mall using the stored shopping mall URL address.

12. In Paragraph 11, The step of extracting and storing the above-mentioned searched keywords is, When a preset word representing the above popular search term is identified, a step of analyzing the scraped webpage to identify the linked search engine; and A control method for an automated device comprising the step of extracting and storing keywords searched at a frequency greater than a preset frequency through the search engine identified above.

13. In Paragraph 11, The step of storing product data of the above shopping mall is, A step of storing product data of the shopping mall as first temporary data using the stored shopping mall URL address; A step of comparing the stored first temporary data with infringement judgment data; and A control method for an automated device comprising the step of determining that the first temporary data corresponds to the infringement determination data based on the comparison result above, and deleting it as data that cannot be sold.

14. In Paragraph 13, The above infringement determination data is, Includes pre-set prohibited word data based on deleted data and trademarked words, and The above deletion step is, A control method for an automated device further comprising the step of adding the first temporary data, which is determined to be unsellable data, as the deleted data.

15. In Paragraph 13, The step of storing product data of the above shopping mall is, A step of searching for similar products using product images constituting the first temporary data; and A control method for an automated device further comprising the step of storing the first temporary data as final product data by including data for similar products searched above in the first temporary data.

16. In Paragraph 15, A step of generating option data to be attached to each of a plurality of products searched in the first shopping mall and at least one shopping mall different from the first shopping mall using the stored final product data; and A control method for an automated device further comprising the step of generating an option page that configures multiple searched products into different options of a single product using the generated option data.

17. In Paragraph 16, The step of generating the above option data is, A step of comparing the first temporary data of the stored final product data with the data for the searched similar products to extract differences between a plurality of products searched in the first shopping mall and at least one shopping mall different from the first shopping mall; A step of matching the above-mentioned extracted differences with preset option classification criteria; and A control method for an automated device comprising the step of generating option data based on the above-mentioned matched option classification criteria.

18. In Paragraph 16, The step of creating the above option page is, A step of generating an option page with an added function to select a product corresponding to each option based on the above-mentioned option data; A step of setting an option price for each product corresponding to each option based on the selling price at a shopping mall sourcing products corresponding to each of the above options, shipping costs by product category, exchange rates, margins, payment fees, and shipping agent information; and A control method for an automated device comprising the step of determining the regular price and sales price to be entered on the option page based on the above-determined option price.

19. In Paragraph 16, A step of selecting one of a plurality of completed translation models based on the category of the target product for which the above option page was generated; A step of translating the option page using the selected completed translation model; and A control method for an automated device further comprising the step of creating and saving a product detail page by combining a header content file, a footer content file, and a product page containing the saved final product data with the above-mentioned translated option page.

20. In Paragraph 19, The step of creating and saving the above product detail page is, A step of identifying an image or text related to the price existing on a product page included in the above-mentioned stored final product data; and A method for controlling an automated device comprising the step of removing the identified image or text.

Images