Automatic consulting system for advancement of global expansion based on ai and data technology, and method thereof

Abstract

The present invention relates to an automatic consulting system for the advancement of global expansion based on AI and data technology, and a method thereof. The automatic consulting system for the advancement of global expansion based on AI and data technology, according to the present invention, comprises: a training unit for training an AI-based learning model by having, as input data, activity data for each target country for global expansion of a plurality of globally expanded companies inputted in a preset service platform, and having a solution as output data; an input unit for receiving, from a target company, company information, one or more export target countries, keywords of interest, and business item information; and a solution provision unit for applying the inputted company information, one or more export target countries, keywords of interest, and export item information to the learning model, and thus providing, for each country, at least one solution among an influencer recommendation, a marketing method recommendation, and a content type recommendation taking into account the business item for the corresponding export target country.

Description

An automated consulting system and method for advancing overseas expansion based on AI and data technology.

[0001] The present invention relates to an automatic consulting system and method for advancing overseas expansion based on AI and data technology, and more specifically, to an automatic consulting system and method for advancing overseas expansion based on AI and data technology, which can automatically suggest, based on artificial intelligence, an advanced strategy for overseas expansion for a company seeking to advance overseas or export.

[0002] Social commerce is a type of e-commerce that leverages social media and online platforms. Social commerce can be broadly categorized into four types: social linking, social web, group purchasing, and offline integration.

[0003] E-commerce, short for electronic commerce, refers to the buying and selling of goods and services through online networks. With the recent surge in mobile shopping, the share of e-commerce is growing even further.

[0004] The Chinese e-commerce market, which accounts for the largest share of the global market, continues to grow. While Korean brands have experienced rapid growth in China, fueled by the power of Korean culture, the increasing sophistication of the Chinese market is diminishing the power of Korean products. This appears to be due to a lack of understanding and data on the local market, leading to a decline in market share and investment difficulties.

[0005] Accordingly, data analysis strategies are needed to increase and enhance exports on global social commerce and e-commerce platforms.

[0006] Furthermore, most companies seeking to expand overseas have, to date, obtained only partial or limited information through limited channels, making it difficult to establish marketing strategies tailored to their products due to a lack of information on overseas local market networks and consumer preferences.

[0007] Therefore, a platform is needed that can assist companies seeking to expand overseas or export, offering customized strategies and solutions that take into account their business needs in the respective countries.

[0008] The technology underlying the present invention is disclosed in Korean Patent Publication No. 10-2000-0049787 (published on August 5, 2000).

[0009] The purpose of the present invention is to provide an automatic consulting system and method for advanced overseas expansion based on AI and data technology that can automatically suggest advanced strategies for overseas expansion of a company seeking to advance overseas or export, based on artificial intelligence.

[0010] The present invention relates to an automatic consulting system for advancing overseas expansion based on AI and data technology, comprising: a learning unit that trains an AI-based learning model using activity data for each country of overseas expansion of a plurality of overseas expansion companies input within a preset service platform as input data and a solution as output data; an input unit that receives corporate information, one or more export target countries, keywords of interest, and business item information from a target company; and a solution providing unit that applies the input corporate information, one or more export target countries, keywords of interest, and export item information to the learning model and provides at least one solution among influencer recommendation, marketing method recommendation, and content type recommendation for each country, taking into account business items in the corresponding export target country.

[0011] In addition, the activity data of the company advancing overseas may include at least one of the company advancing overseas' search keywords, countries of overseas expansion, main item information, favorite feature information, influencer collaboration history, content type, marketing method, annual sales, and annual profit.

[0012] In addition, the solution provider may additionally provide at least one of competitive brand information, competitive product information, and market analysis results for each country.

[0013] In addition, the above corporate information may include at least one of the target company's brand value information, main product information, price information, and past history of expansion into other overseas countries.

[0014] In addition, the marketing method may include at least one of online, SNS, influencer, and offline methods, and the content type may include at least one of content centered on expert explanations of business items, content centered on user reviews, and content centered on home shopping.

[0015] In addition, the above learning model is a reinforcement learning model, and can provide (+) compensation when the annual sales or profits of the overseas companies in the relevant country increase, and can provide (-) compensation when the annual sales and profits of the overseas companies in the relevant country decrease.

[0016] In addition, the solution provider may further provide, through the results output through the learning model, whether or not to recommend exporting business items for each country for one or more export target countries input by the target company.

[0017] In addition, the solution provider may use the learning model to recommend business items with high similarity for each country in addition to the business items input from the target company, and the business items with high similarity may include business items having at least one similarity among the main consumer age group, usage category, and price range to the business items input from the target company.

[0018] In addition, the solution provider can recommend one or more overseas expansion countries in addition to the input export target countries by applying the corporate information, keywords of interest, and business item information input from the target company to the learning model.

[0019] In addition, the solution provider can recommend the highest priority country for overseas expansion to the target company through the learning model, and recommend lower priority countries in order of ranking by considering the similarity between countries with the highest priority country.

[0020] In addition, the solution provider can determine the similarity between countries by applying at least one of population difference, geographical location, age composition ratio, sex ratio, market size, religion, climate, middle class ratio, and exchange rate information to the learning model.

[0021] And, the present invention relates to an automatic consulting method performed by an automatic consulting system for advanced overseas expansion based on AI and data technology, comprising the steps of: training an AI-based learning model using overseas expansion activity data of a plurality of overseas expansion companies by country as input data and a solution as output data within a preset service platform; receiving corporate information, one or more export target countries, keywords of interest, and business item information from a target company; and applying the input corporate information, one or more export target countries, keywords of interest, and export item information to the learning model to provide at least one solution among influencer recommendation, marketing method recommendation, and content type recommendation for each country, taking into account business items in the corresponding export target country.

[0022] According to the present invention, advanced strategies and solutions for overseas expansion can be automatically presented to companies seeking to enter the overseas market or export based on artificial intelligence.

[0023] Additionally, by receiving corporate information about target companies seeking to expand overseas, as well as information on export target countries and export items, we can provide advanced export strategy solutions, such as marketing content suggestions and influencer recommendations that consider business items in those countries.

[0024] In addition, by providing guidance on establishing initial entry strategies for export target countries, target companies can establish accurate entry strategies from the beginning, thereby minimizing opportunity costs.

[0025] Figure 1 is a diagram illustrating the configuration of an automatic consulting system for advanced overseas expansion based on AI and data technology according to an embodiment of the present invention.

[0026] Figure 2 is a drawing showing the configuration of the automatic consulting system of Figure 1 in more detail.

[0027] Figure 3 is a drawing explaining an automatic consulting method for improving overseas expansion using the system of Figure 1.

[0028] FIG. 4 is a diagram showing the concept of an optimal solution recommendation operation using an AI-based learning model according to an embodiment of the present invention.

[0029] Hereinafter, embodiments of the present invention will be described in detail with reference to the attached drawings so that those skilled in the art can easily implement the present invention. However, the present invention may be implemented in various different forms and is not limited to the embodiments described herein. In addition, in the drawings, parts irrelevant to the description have been omitted to clearly explain the present invention, and similar parts have been designated with similar drawing reference numerals throughout the specification.

[0030] Throughout the specification, when a part is said to be "connected" to another part, this includes not only the cases where the parts are "directly connected" but also the cases where the parts are "electrically connected" with other elements intervening. Furthermore, when a part is said to "include" a component, this does not exclude other components, but rather includes other components, unless otherwise stated.

[0031] Figure 1 is a diagram illustrating the configuration of an automatic consulting system for advanced overseas expansion based on AI and data technology according to an embodiment of the present invention.

[0032] As illustrated in FIG. 1, the automated consulting system (100) for advancing overseas expansion based on AI and data technology according to an embodiment of the present invention can be connected to a plurality of first and second user terminals (200, 300) via a wired, wireless, or wired / wireless combination network to exchange information with each other. The wireless network may include at least one of RF, WLAN, Wi-Fi, and Bluetooth, and various known wireless network methods may be used.

[0033] Each first user terminal (200) may correspond to a user terminal of a plurality of overseas expansion companies that have previously expanded overseas, and the second user terminal (300) may correspond to a user terminal of a target company that wishes to expand overseas.

[0034] For convenience of explanation, FIG. 1 illustrates a single second user terminal (300). However, the present invention is not necessarily limited to this. Specifically, if there are multiple target companies seeking advanced overseas expansion solutions, multiple second user terminals (300) may be network-connected to the proposed system (100).

[0035] In an embodiment of the present invention, companies expanding overseas can transition to the position of the target company at any time to receive advanced overseas expansion solutions for upgraded or modified products from existing overseas products, or newly developed or scheduled to be launched products. In other words, the first user terminal (200) corresponding to the overseas expansion company can transition to the position of the second user terminal (300) of the target company at any time. Of course, the second user terminal (300) can also transition to the position of the first user terminal (200) at any time after receiving consulting on optimal solutions through the proposal system and completing overseas expansion.

[0036] This automatic consulting system (100) can be implemented as an online / offline platform such as a web server or app server that provides an automatic consulting service for artificial intelligence-based advancement of overseas expansion to a second user terminal (300) of a target company connected to a network, or can be implemented in the form of an application program, application, etc. on a user terminal, etc.

[0037] That is, the automated consulting system (100) can provide an advanced overseas expansion consulting service platform implemented as an app or web to multiple network-connected user terminals (200, 300). The service platform may be an application program running in an app or web environment.

[0038] The automated consulting system (100) may be a platform server itself that provides advanced consulting services for overseas expansion, or may be implemented as an application program that runs and operates on a user terminal (200, 300). The user terminal (200, 300) can receive related services by connecting to the system (100) through a network while the related application program is running.

[0039] The first and second user terminals (200, 300) may include devices that can connect to a wired or wireless network and exchange information, such as a PC, desktop, smart phone, tablet, or notebook. The first and second user terminals (200, 300) may include an administrator terminal of the relevant company, a general user terminal, etc.

[0040] FIG. 2 is a diagram illustrating in more detail the configuration of the automatic consulting system of FIG. 1, and FIG. 3 is a diagram illustrating an automatic consulting method for enhancing overseas expansion using the system of FIG. 1. Furthermore, FIG. 4 is a diagram illustrating the concept of an optimal solution recommendation operation using an AI-based learning model according to an embodiment of the present invention.

[0041] Referring to FIGS. 2 and 3, the automatic consulting system (100) for advanced overseas expansion according to an embodiment of the present invention includes a learning unit (110), an input unit (120), and a solution providing unit (130). Here, the operation of each unit (110-130) and the data flow between each unit can be controlled by a control unit (not shown).

[0042] Such an automatic consulting system (100) may be implemented as a computer device that is physically configured and includes a processor, memory, a user interface input / output device and a storage device, a network input / output unit, etc., or may be implemented as an application program running on a computer device or a user terminal.

[0043] First, the learning unit (110) can train an AI-based learning model using the overseas activity data of multiple overseas companies entered into a pre-established service platform as input data and solutions as output data (S310). Here, the "overseas companies" can refer to companies with a history of overseas expansion through the proposed service platform.

[0044] This learning unit (110) can train an AI-based learning model based on past big data including past activity history data performed by overseas companies accessing the service platform through the first user terminal (200) and solution data actually provided to the companies.

[0045] Here, activities may include various actions such as data search, inquiry, information input, registration, and storage performed through user terminals within the service platform.

[0046] More specifically, in an embodiment of the present invention, the activity data of a company advancing overseas may include at least one of the company's search keywords (search keywords), countries of overseas expansion, main item information, favorite feature information, influencer collaboration history, content type, marketing method, annual sales, and annual profit.

[0047] Here, the favorite feature information may include the properties or characteristics of links registered as favorites by overseas companies within the service platform, and the main item information may correspond to the main product group information of the overseas company (e.g., mobile phone cases, mobile phone accessories).

[0048] Additionally, marketing methods may include at least one of the following: online, social media, influencer, or offline. Content types may include at least one of the following: expert explanations of the business item, user reviews, or home shopping. This consideration takes into account the fact that marketing methods most advantageous to a company may vary depending on factors such as the type of business item, the countries it operates in, its size, and its sales volume.

[0049] In an embodiment of the present invention, the learning model can be implemented as a reinforcement learning model. In this case, the reinforcement learning model can be trained to provide (+) compensation when the annual sales or profits of companies expanding overseas in the relevant country increase, and (-) compensation when the annual sales or profits of companies expanding overseas in the relevant country decrease.

[0050] Annual sales or profits in a given country can be indicators of the likelihood or even the success of overseas expansion into that country. Using reinforcement learning, countries with increasing sales or profits can be recommended, while countries with declining sales or profits can be excluded from recommendations.

[0051] Next, the input unit (120) can receive corporate information, one or more export target countries, keywords of interest, and business item information from the target company (S320). Here, the target company may refer to a company seeking to expand overseas or export.

[0052] This input unit (120) can receive corporate information, export target countries, keywords of interest, and business item information through a second user terminal (300) of the target company, and transmit the input values ​​to the solution provider (130).

[0053] Here, corporate information may include at least one of the following: brand value information, main product information, price information, and past overseas expansion history of the target company.

[0054] If your main product is a mobile phone case, pricing information may include the case's selling price and price range. Information on past overseas expansion into other markets is used to determine whether to recommend expansion into similar regions (e.g., English-speaking, Chinese-speaking, Asian, European, Arab, etc.) and the likelihood of success.

[0055] Next, the solution provider (130) can apply the corporate information, one or more export target countries, keywords of interest, and export item information input through the input unit (120) to a pre-learned learning model, thereby providing at least one solution among influencer recommendation, marketing method recommendation, and content type recommendation that takes into account business items in the export target country for each country (S330).

[0056] Here, the solution provider (130) can additionally provide at least one of the following for each country: information on competing brands, information on competing products, and market analysis results for the target company based on the information entered in the input unit (120).

[0057] The recommended solution for enhancing overseas expansion using this AI learning model can also be seen in Figure 4. As shown in Figure 4, utilizing AI and data technologies eliminates the need for individual analysis of massive amounts of data, saving human and time resources, thereby maximizing work efficiency and productivity. Furthermore, by providing guidance on establishing initial entry strategies for target export countries, target companies can establish accurate entry strategies early on, minimizing opportunity costs.

[0058] The accuracy of AI matching for these AI learning models can increase as customer data continues to accumulate. Furthermore, the solution strategies presented for each target company using the service and their activity history data can be used to update the AI ​​learning model in the future.

[0059] Meanwhile, the solution provider (130) can further provide whether to recommend or not to recommend exporting business items to one or more export target countries input by the target company through the results output through the learning model.

[0060] For example, it is possible to provide information on whether a business item (e.g., a mobile phone case) is recommended or not for export to overseas countries (e.g., Hong Kong, Taiwan) entered by the target company (e.g., recommended for Hong Kong, not recommended for Taiwan).

[0061] In addition, the solution provider (130) can use the learning model to recommend business items with high similarity to each country in addition to business items (e.g., mobile phone cases) input from the target company.

[0062] At this time, business items with high similarity may include business items (e.g., cell phone cases) input from the target company and business items (e.g., cell phone key rings, stands, grip toks) that are similar in at least one of the main consumer age groups, usage categories, and price ranges.

[0063] In addition, the solution provider (130) can apply corporate information, keywords of interest, and business item information input from the target company to the learning model to recommend one or more overseas expansion countries in addition to the input export target countries.

[0064] That is, in addition to the export target countries (e.g., Hong Kong, Taiwan) entered by the target company, the solution provider (130) may additionally recommend one or more overseas expansion countries (e.g., Thailand, Vietnam) with a high probability of success exceeding a preset threshold when exporting or expanding overseas based on existing big data. This probability of success may be determined probabilistically through deep learning analysis of annual sales and profit trends or patterns of companies that have expanded overseas, as described above, or may be derived through simple statistics.

[0065] In this way, the solution provider (130) is not limited to the export target countries designated in advance by the target company, but can additionally match countries for overseas expansion that are predicted to have a high possibility of success, and through this, can contribute to reducing business risks at the time of initial overseas expansion by additionally recommending other countries that are predicted to be advantageous for overseas expansion of the target company.

[0066] Here, in making these additional recommendations, the solution provider (130) may recommend the highest priority country for overseas expansion to the target company through a learning model, and may also recommend lower priority countries in order of ranking by considering the similarity between countries with the highest priority country.

[0067] At this time, the solution provider (130) can determine the similarity between countries by applying at least one of population difference, geographical location, age composition ratio, sex ratio, market size, religion, climate, middle class ratio, and exchange rate information to the learning model, and can recommend lower-ranked countries in order of ranking by considering the determined similarity between countries.

[0068] That is, the solution provider (130) can recommend a lower priority country by determining the similarity between countries by comparing the income level, geographical similarity, population and sex ratio information, religion, climate, etc. with the highest priority country.

[0069] According to the present invention as described above, advanced strategies and solutions for overseas expansion can be automatically presented to companies seeking to enter the overseas market or export based on artificial intelligence.

[0070] Additionally, by receiving corporate information about companies seeking to expand overseas, as well as information on export target countries and export items, we can provide advanced export strategy solutions, such as marketing content suggestions and influencer recommendations that take into account business items in those countries.

[0071] While the present invention has been described with reference to the embodiments illustrated in the drawings, these are merely exemplary, and those skilled in the art will understand that various modifications and equivalent alternative embodiments are possible. Therefore, the true scope of technical protection of the present invention should be determined by the technical spirit of the appended claims.

Claims

1. In the automated consulting system for advancing overseas expansion based on AI and data technology, A learning unit that trains an AI-based learning model using the overseas activity data of multiple overseas companies entered into a pre-established service platform as input data and the solution as output data; An input section for receiving corporate information, one or more export target countries, keywords of interest, and business item information from the target company; and An automatic consulting system including a solution provider that applies input corporate information, one or more export target countries, keywords of interest, and export item information to the learning model, and provides at least one solution among influencer recommendation, marketing method recommendation, and content type recommendation for each export target country, taking into account business items in the export target country.

2. In claim 1, The activity data of the above overseas expansion companies are as follows: An automated consulting system that includes at least one of the following: search keywords, countries of overseas expansion, main product information, favorite feature information, influencer collaboration history, content type, marketing method, annual sales, and annual profit of the above-mentioned overseas expansion company.

3. In claim 1, The above solution provider, An automated consulting system that additionally provides at least one country-specific information on competing brands, competing product information, and market analysis results.

4. In claim 1, The above corporate information is, An automated consulting system that provides at least one of the following: brand value information, main product information, price information, and past overseas expansion history information of the target company.

5. In claim 1, The above marketing method includes at least one of online, SNS, influencer, and offline methods. The above content type is an automatic consulting system that includes at least one of the following: content focused on expert explanations of business items, content focused on user reviews, and content focused on home shopping.

6. In claim 2, The above learning model is a reinforcement learning model. If the annual sales or profits of the companies advancing overseas increase in the relevant country, (+) compensation will be provided. An automatic consulting system that provides (-) compensation when the annual sales and profits of overseas companies in the relevant country decrease.

7. In claim 6, The above solution provider, An automatic consulting system that provides recommendations or non-recommendations for overseas export of business items for each country for one or more export target countries input by the target company through the results output through the above learning model.

8. In claim 3, The above solution provider, Using the above learning model, business items with high similarity are recommended for each country in addition to the business items input from the target company. The above business items with high similarity are an automatic consulting system that includes business items that are similar to the business items input from the target company in at least one of the main consumer age group, usage category, and price range.

9. In claim 1, The above solution provider, An automatic consulting system that applies corporate information, keywords of interest, and business item information entered from the target company to the learning model and recommends one or more overseas expansion countries in addition to the entered export target countries.

10. In claim 9, The above solution provider, Through the above learning model, we recommend the top priority countries for overseas expansion to the above target companies. An automatic consulting system that recommends lower-priority countries in order of rank, taking into account the similarity between countries with the highest-priority countries.

11. In claim 10, The above solution provider, An automatic consulting system that determines the similarity between countries by applying at least one of the following information to the learning model: population difference, geographical location, age composition ratio, sex ratio, market size, religion, climate, middle class ratio, and exchange rate information.

12. In the automatic consulting method performed by the automatic consulting system for the advancement of overseas expansion based on AI and data technology, A step of training an AI-based learning model using the overseas activity data of multiple overseas companies entered into a pre-established service platform as input data and the solution as output data; A step of receiving corporate information, one or more export target countries, keywords of interest, and business item information from the target company; and An automatic consulting method comprising a step of applying input corporate information, one or more export target countries, keywords of interest, and export item information to the learning model to provide at least one solution among influencer recommendation, marketing method recommendation, and content type recommendation for each country, considering business items in the export target country.

13. In claim 12, The activity data of the above overseas expansion companies are as follows: An automated consulting method that includes at least one of the following: search keywords, countries of overseas expansion, main product information, favorite feature information, influencer collaboration history, content type, marketing method, annual sales, and annual profit of the above-mentioned overseas expansion company.

14. In claim 12, The steps provided above are: An automated consulting method that additionally provides at least one country-specific information on competing brands, competing product information, and market analysis results.

15. In claim 12, The above corporate information is, An automatic consulting method that provides at least one of the following: brand value information, main product information, price information, and past overseas expansion history information of the target company.

16. In claim 12, The above marketing method includes at least one of online, SNS, influencer, and offline methods. The above content type is an automated consulting method that includes at least one of content focused on expert explanations of business items, content focused on user reviews, and content focused on home shopping.

17. In claim 13, The above learning model is a reinforcement learning model. If the annual sales or profits of the companies advancing overseas increase in the relevant country, (+) compensation will be provided. An automatic consulting method that provides (-) compensation when the annual sales and profits of overseas companies in the relevant country decrease.

18. In claim 17, The steps provided above are: An automatic consulting method that provides further information on whether to recommend or not to export business items to one or more export target countries input by the target company based on the results output through the above learning model.

19. In claim 14, The steps provided above are: Using the above learning model, business items with high similarity are recommended for each country in addition to the business items input from the target company. The above business items with high similarity are an automatic consulting method including business items having at least one similarity among the main consumer age group, usage category, and price range to the business items input from the target company.

20. In claim 12, The steps provided above are: An automatic consulting method that recommends one or more overseas expansion countries in addition to the input export target countries by applying corporate information, keywords of interest, and business item information input from the target company to the learning model.

21. In claim 10, The steps provided above are: Through the above learning model, we recommend the top priority countries for overseas expansion to the above target companies. An automatic consulting method that recommends lower-priority countries in order of rank, taking into account the similarity between countries with the highest-priority countries.

22. In claim 21, The steps provided above are: An automatic consulting method for determining similarity between countries by applying at least one of population differences, geographical location, age composition ratio, sex ratio, market size, religion, climate, middle class ratio, and exchange rate information to the learning model.

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