Enterprise overseas marketing automation service method based on multi-mode AI cooperation

Abstract

The invention discloses an enterprise overseas marketing automation service method based on multi-mode AI cooperation, and relates to the technical field of artificial intelligence and digital marketing. According to the method, enterprise multi-modal data is aggregated through an intelligent data center, an AI model is driven to automatically generate an independent station page and a marketing video adaptive to a target market, and the independent station page and the marketing video are synchronously published to a social media platform. A cross-platform intelligent customer service module is deployed in the system, user consultation is analyzed in real time, a preset notification rule is triggered, and response efficiency and compliance are guaranteed. And dynamically optimizing the display content of the master station based on a multi-modal AI scoring mechanism, and realizing accurate recommendation in combination with user behavior analysis. Compared with a traditional method, the system solves the problems of multi-platform operation splitting, manual response delay, poor content adaptability and the like through multi-AI model collaboration and automatic process integration, and remarkably improves the overseas marketing efficiency and precision.

Description

Technical Field

[0001] The present invention relates to the technical fields of artificial intelligence and digital marketing. Specifically, it is a service platform that realizes full-link automation by scheduling multiple AI model APIs, and is used for intelligent website building, content generation, customer service hosting, and precise recommendation in cross-border scenarios, especially suitable for the globalization promotion needs in the fields of cross-border e-commerce, industrial equipment, etc. Background Art

[0002] Traditional enterprises' overseas marketing relies on manual operation of multiple platform tools. The construction of independent websites, content generation, and customer service systems need to be managed separately, with defects such as data fragmentation, low response efficiency, and poor cross-cultural adaptability. In the prior art, the automation tools have single functions and cannot achieve multi-modal data collaborative processing. Content generation relies on manual adjustment of cultural elements, with a high error rate; customer service responses rely on manual polling, and the processing delay of cross-platform consultations is large; the recommendation algorithm does not combine multi-modal content understanding, and the user click-through conversion rate is low. The above problems lead to high costs and low efficiency in enterprises' cross-border marketing, and it is difficult to meet the rapidly changing overseas market demands.

[0003] Object of the Invention

[0004] The present invention aims to solve the problems of fragmented multi-platform operations, manual response delays, and poor content adaptability in traditional methods through the collaborative scheduling and programmatic integration of multiple AI model APIs, and realize the automation and intelligence of the entire marketing link. Specifically, it includes: realizing the unified processing and scheduling of multi-modal data through an intelligent data center; automatically generating cross-culturally adapted independent websites and marketing content based on AI models; deploying a cross-platform intelligent customer service system to improve response efficiency; and achieving precise recommendation by combining multi-modal content understanding and user behavior analysis. Compared with traditional methods, this system has improvements in the automation level of the entire marketing link, cross-platform collaboration efficiency, and content matching accuracy. Content of the Invention

[0005] The present invention relates to an enterprise overseas marketing automation service platform and method based on multi-modal AI collaboration, belonging to the technical fields of artificial intelligence and digital marketing. Specifically, it is an automated service system that integrates the collaboration of multiple AI model APIs, and is used for the full-link marketing services of intelligent website building, content generation, customer service hosting, and precise recommendation for Chinese enterprises in cross-border scenarios. Traditional overseas marketing methods have problems such as fragmented multi-platform operations, low manual response efficiency, poor cross-cultural adaptability of content, and insufficient recommendation accuracy. Compared with traditional methods,

[0006] The system realizes the fully automated flow from data aggregation to content distribution by programmatically scheduling multiple AI model APIs such as text generation, video understanding, and image analysis. The intelligent website building module calls the AI text generation API to parse enterprise information; the video generation module calls the AI video synthesis API to dynamically generate marketing content; the customer service module uses the natural language processing API to parse user inquiries in real time.

[0007] Through the programmatic collaboration of multiple AI models and the integration of automated processes, the website building efficiency, customer service response speed, and content adaptation accuracy are significantly improved, realizing the intelligent management of the entire marketing chain.

[0008] The system aggregates enterprise-uploaded marketing data, product structured data, multi-modal materials, and customer service Q&A libraries through an intelligent data center to form a unified data processing center. Based on this, the system calls the AI text generation large model API to parse enterprise information, generates a responsive layout independent website page in combination with a preset template, automatically assigns a secondary domain name, and deploys it to a cloud server. The preset template has a multi-language adaptation module and SEO keyword optimization function to ensure that the generated independent website page meets the language habits and search engine optimization requirements of the target market. For example, after a home appliance enterprise uploads product parameters, the system automatically generates an English independent website adapted to the mobile layout and optimizes the display logic of technical parameters.

[0009] In the content generation link, based on the multi-modal materials uploaded by the enterprise, the system generates marketing videos through a programmatic process and synchronously publishes them to the independent website and specified social media platforms. The video content is dynamically synthesized by the AI video large model to ensure cross-cultural adaptation of the picture, subtitles, and background music. For example, the product usage scenario video provided by the enterprise is processed by AI to generate a 30-second demonstration video and automatically published to platforms such as Facebook, significantly reducing the time cost of manual editing.

[0010] The cross-platform customer service hosting module realizes unified management of multiple channels by deploying AI intelligent customer service. The system embeds an intelligent customer service interface in the independent website and social media platforms, calls the AI text large model API to parse user inquiry content in real time, and generates accurate responses based on the enterprise knowledge base and preset response rules. When the user inquiry content involves high-risk keywords such as "after-sales disputes" and "technical failures", the system automatically pushes text messages and email notifications to the designated contacts and marks the need for knowledge base updates. This mechanism ensures response timeliness while avoiding compliance risks of overseas instant messaging tools.

[0011] The main station intelligent aggregation module dynamically displays the preferred promotional content of enterprises under the first-level domain name. The content selection rules comprehensively consider click-through rate, user stay duration, and multi-modal AI quality scores. The scores are calculated based on the output scores of the AI image understanding large model and the video understanding large model according to a preset weight ratio, ensuring the objectivity of content quality evaluation. For example, a certain enterprise's video meets the standards for indicators such as picture clarity and content relevance, enters the preferred display area of the main station, and improves the exposure efficiency.

[0012] The personalized recommendation module analyzes the user's browsing behavior through the AI video understanding large model, extracts content feature vectors, and calls the recommendation algorithm API to generate a dynamic recommendation list. The recommended content is updated in real time to the independent station and social media pages based on the matching results of user behavior data and multi-modal features, effectively improving the click-through conversion rate. The system realizes the full-automatic flow from data aggregation to content distribution by programmatic scheduling of AI model APIs such as text, video, and image understanding, eliminating the data island problem of multi-platform operations.

[0013] In a specific implementation, a certain home appliance enterprise uploads product parameters and usage scenario videos after registration. The system automatically generates an English independent station and publishes an AI-synthesized demonstration video. When a user consults about "voltage compatibility", the intelligent customer service triggers a preset rule to send a text message notification to the enterprise owner, and at the same time updates the knowledge base to improve subsequent responses. The enterprise's promotional content enters the preferred display area of the main station due to excellent multi-modal scores, achieving precise traffic import.

[0014] The innovation of the present invention lies in the multi-AI model collaboration mechanism, cross-platform hosting architecture, dynamic content optimization strategy, and compliance constraint design. By driving the construction of the independent station, content generation, and customer service response with a unified data source, it ensures the consistency of the entire marketing chain; realizes the automatic selection and display of content based on multi-modal AI scores, avoiding the subjective deviation of manual screening; limits traditional communication methods in the manual notification link, reducing the compliance risk of overseas operations. Compared with traditional methods, the present system has significantly improved in terms of website construction efficiency, response speed, and recommendation accuracy, and is suitable for the complex scenario requirements of cross-border marketing. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 is the system architecture diagram of the present invention, showing the collaborative relationship between the intelligent data center, the content generation module, and the customer service hosting module;

[0016] Figure 2 is the flow chart of the intelligent customer service trigger rule, describing the identification and notification mechanism for high-risk consultations;

[0017] Figure 3 is the schematic diagram of multi-modal content score calculation, presenting the weight distribution logic of the image and video models.

[0018] To more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce using the attached drawings. Obviously, the attached drawings in the following description are only some embodiments recorded in the present invention. For those of ordinary skill in the art, other attached drawings can also be obtained based on these attached drawings. Detailed implementation manners

[0019] The present invention relates to an enterprise overseas marketing automation service platform and method based on multi-modal AI collaboration. The detailed implementation manners are described as follows in combination with Figure 1 、 Figure 2 and Figure 3 as follows:

[0020] As Figure 1 shown, after the intelligent data center aggregates the enterprise's multi-modal data, it schedules the AI text generation model through a preset API interface, generates the independent station page code and deploys it to the cloud server; the video generation module calls the video synthesis API to automatically generate cross-culturally adapted marketing videos based on the materials uploaded by the enterprise; the customer service module analyzes the user's consultation content in real time through the natural language processing API and triggers the notification process according to the preset rules.

[0021] As Figure 1 shown, the system aggregates the enterprise's uploaded marketing data, product structured data and multi-modal materials through the intelligent data center to form a unified data processing center. The data center is linked with the intelligent website building module, calls the AI text generation large model to parse the enterprise information, generates a responsive layout independent station page in combination with the preset template, automatically assigns a secondary domain name and deploys it to the cloud server. The generated independent station page is built-in with a multi-language adaptation module to ensure that the content meets the language habits of the target market and the requirements of search engine optimization. The video generation module dynamically synthesizes marketing videos based on the materials uploaded by the enterprise through the AI video large model and synchronously publishes them to the independent station and the specified social media platforms to realize the automation of content distribution.

[0022] The cross-platform customer service hosting module, as Figure 2 shown, deploys intelligent customer service interfaces on the independent station and social media platforms to analyze the user's consultation content in real time. When the user enters high-risk keywords such as "after-sales dispute" and "technical failure", the system triggers the notification push mechanism to send text messages and email notifications to the specified contacts, and at the same time marks the need for knowledge base update to improve subsequent responses. For regular consultations, the system generates automatic replies based on the enterprise knowledge base and preset rules to ensure the response efficiency.

[0023] The main station intelligent aggregation module, as Figure 1 shown, dynamically displays the preferred promotional content under the first-level domain name. The content selection rules comprehensively consider the user behavior data and the multi-modal AI quality score, as Figure 3As shown, the score is calculated based on the output scores of the image understanding model and the video understanding model according to preset weights. For example, image clarity and content relevance are evaluated by the image understanding model, and video content coherence is evaluated by the video understanding model. The two are weighted to form the final score. Content that meets the score standard automatically enters the preferred display area, improving the exposure efficiency.

[0024] The personalized recommendation module analyzes users' browsing behaviors through the AI video understanding model, extracts content feature vectors, and generates a dynamic recommendation list. The recommendation results are updated in real time to the independent website and social media pages based on the matching of user behavior data and multi-modal features, significantly improving the user click-through conversion rate. The system realizes the fully automated flow from data aggregation to content distribution by programmatically scheduling multiple AI model APIs, eliminating the data silo problem of multi-platform operations.

[0025] Compared with traditional methods, this system realizes the intelligent management of the entire marketing chain through a multi-modal AI collaboration mechanism, with significant improvements in cross-platform response efficiency, content adaptation accuracy, and recommendation matching rate. In a specific implementation, after a home appliance enterprise uploads product parameters, the system automatically generates an English independent website adapted to mobile devices and publishes an AI-synthesized product demonstration video. When a user consults about "voltage compatibility", the intelligent customer service triggers a notification mechanism and optimizes the content of the knowledge base at the same time. The enterprise's promotional video enters the preferred area of the main website because the multi-modal score meets the standard, achieving precise traffic import.

[0026] The present invention ensures the consistency of marketing strategies by driving website building, content generation, and customer service responses with a unified data source; realizes the automated selection and display of content based on a dynamic scoring mechanism, avoiding the subjective bias of manual screening; limits traditional communication methods in the notification link, reducing the compliance risks of overseas operations. The synergistic effect of the above technical features significantly improves the efficiency and effectiveness of cross-border marketing.

Claims

1. An enterprise overseas marketing automation service method based on multi-modal AI collaboration, characterized in that Including: Aggregating marketing data, product structured data, and multi-modal materials uploaded by enterprises through an intelligent data center; Invoking the AI text generation API to parse enterprise information, generating an independent website page with a responsive layout and deploying it to a cloud server; Invoking the AI video synthesis API to programmatically generate marketing videos based on the multi-modal materials and synchronously publish them to the independent website and specified social media platforms; Deploying an intelligent customer service module on the independent website and social media platforms through the natural language processing API, real-time parsing user consultation content and generating responses, and triggering notification push when preset high-risk keywords are matched; Dynamically optimizing the main website display content based on user behavior data and the output results of the multi-modal AI scoring API; Invoking the recommendation algorithm API to analyze user browsing behavior, generating a dynamic recommendation list and updating it to the target page.

2. The enterprise overseas marketing automation service method based on multi-modal AI collaboration according to claim 1, wherein: The response content of the intelligent customer service module is generated based on the enterprise knowledge base and preset response rules, and the notification push methods are limited to text messages and emails.

3. The enterprise overseas marketing automation service method based on multi-modal AI collaboration according to claim 1, wherein: The multi-modal AI quality score is generated by weighted calculation of the output scores of the image understanding model and the video understanding model.

4. A method for enterprise overseas marketing automation service based on multi-modal AI collaboration according to claim 1, characterized in that: The dynamic recommendation list is updated to the target page in real time based on user behavior data and the matching results of multi-modal content features.

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