Efficient sales aggregation chat system and method based on multi-tool integration and AI assistance

Abstract

The invention discloses an efficient sales aggregation chat system and method based on multi-tool integration and AI assistance. The system comprises a user interface layer, a chat tool connection module, a message processing module, an AI interaction module and a data storage module. A plurality of chat tools or WeChat accounts are in butt joint through a chat tool connection module, and simultaneous chatting with multiple persons is realized in a unified window of a user interface layer; the AI interaction module is connected with an external AI model and can take over chat work and quickly and accurately reply customer consultation. The message processing module is responsible for message analysis, format conversion and routing, and the data storage module adopts a distributed architecture to ensure safe storage of data. According to the method and the system, the problems of tedious multi-tool switching, low communication efficiency and the like of salesmen are effectively solved, the customer service efficiency and quality are improved by utilizing the AI, data integration and analysis are realized, a basis is provided for sales decision, the enterprise cost is reduced, and the method and the system have wide application prospects and market values.

Description

Technical Field

[0001] This invention focuses on cutting-edge applications where communications technology and artificial intelligence converge, aiming to develop an innovative aggregated chat method and system. Tailored specifically for sales scenarios, this system seamlessly integrates multiple chat tools with advanced AI technology to create a one-stop, intelligent communication platform for salespeople, comprehensively improving sales communication efficiency and customer service quality. Background Art

[0002] Dilemma of traditional sales communication model:

[0003] 1. The Difficulty of Switching Between Multiple Tools: In today's digital business landscape, sales professionals are increasingly reliant on instant messaging tools. However, salespeople often face the complex task of juggling multiple messaging tools simultaneously. WeChat, with its vast user base, has become the preferred tool for establishing close connections with individual customers; QQ, popular among young consumers and boasting a unique social ecosystem; and DingTalk, with its powerful office collaboration features, has become a crucial bridge for communication between corporate clients. Frequently switching between these different tools not only consumes significant time but also easily leads to confusion, resulting in missed important messages and delayed responses, severely hampering sales communication efficiency.

[0004] 2. Challenges in Responding to Customer Inquiries: With intensifying market competition and the continuous expansion of business scale, sales staff face a massive influx of customer inquiries daily. During peak sales seasons or promotional events, the number of inquiries explodes, with a single salesperson potentially fielding dozens or even hundreds of customer inquiries simultaneously. Under intense workloads, manual responses struggle to be timely and accurate. Delayed responses can make customers feel neglected, reducing customer satisfaction; inaccurate responses can lead to misunderstandings about products or services, directly impacting sales performance. For example, during the e-commerce "Double 11" (Singles' Day) promotion, numerous customers simultaneously inquired about product details, discount policies, and other issues, often overwhelming sales staff and leading to the loss of many potential orders.

[0005] The necessity of multi-tool integration:

[0006] 1. Need for Efficiency Improvement: The current market lacks a comprehensive platform that can organically integrate multiple chat tools, forcing sales staff to spend a significant amount of time and effort synchronizing and switching between different tools. Multi-tool integration allows sales staff to centrally manage customer messages from various channels within a unified interface, eliminating duplication and missed information, significantly improving work efficiency. Furthermore, multi-tool integration helps comprehensively consolidate customer information, providing sales staff with a more complete and multi-dimensional customer profile, facilitating targeted marketing and personalized services.

[0007] 2. Data Integration and Analysis: The integration of multiple tools can not only improve communication efficiency but also enable in-depth integration and analysis of customer data. By aggregating customer information from different chat tools, enterprises can analyze customers from multiple dimensions, uncovering their latent needs, purchase preferences, and consumption habits. These data insights provide a strong basis for enterprises to formulate precise marketing strategies and optimize product services, helping them gain the upper hand in the fierce market competition.

[0008] The Application Potential of AI Technology in Sales Communication:

[0009] 1. Intelligent Customer Service Assistance: The rapid development of artificial intelligence technology has brought new opportunities to sales communication. AI has powerful natural language processing and data analysis capabilities, enabling it to quickly understand customer questions and generate accurate and professional responses. In sales scenarios, AI can undertake some repetitive and regular chat tasks, such as answering common questions and introducing products, allowing salespeople to devote more time and energy to maintaining high-value customer relationships and formulating sales strategies.

[0010] 2. Data-driven Decision-making: AI can also provide data support for sales decisions by deeply analyzing a large amount of chat records, uncovering customer needs and market trends. For example, by analyzing the frequently mentioned questions and concerns of customers in the chat, enterprises can promptly identify deficiencies in products or services and make targeted improvements and optimizations; by analyzing customers' purchase behaviors and preferences, enterprises can formulate personalized marketing strategies to improve marketing effectiveness and customer conversion rates. However, the current application of AI technology in sales communication is still in its infancy, with problems such as low integration with existing chat tools and lack of personalization in response content, urgently needing further breakthroughs and improvements.

[0011] In summary, developing an efficient sales aggregation chat method and system that integrates multiple tools and AI technology has important practical significance and broad market prospects. Summary of the Invention

[0012] The core objective of the present invention is to provide an efficient sales aggregation chat method and system based on the integration of multiple tools and AI assistance, solving the problems of inconvenient use of multiple chat tools and low communication efficiency in existing sales communication. Through an innovative aggregated chat window design, seamless docking of multiple chat tools and multiple WeChat accounts is achieved, enabling salespeople to communicate efficiently with multiple people simultaneously in a unified interface. At the same time, deeply integrating AI technology and leveraging AI's powerful natural language processing and intelligent analysis capabilities, flexible takeover and precise assistance of chat work by AI are realized, comprehensively improving the efficiency and quality of sales communication and enhancing the market competitiveness of enterprises.

[0013] According to one aspect of the present invention, there is provided an efficient sales aggregation chat system based on multi-tool integration and AI assistance, which system comprises:

[0014] 1. User interface layer: The user interface layer serves as the direct window for users to interact with the system. Adhering to the design concept of simplicity and intuitiveness, it ensures that salespersons can easily get started and operate. This layer provides a unified aggregation chat window, where all chat sessions from different chat tools and WeChat accounts are centrally displayed. The window layout combines multiple tab pages with a session list, facilitating users to quickly switch and manage different chat sessions. Meanwhile, the user interface layer supports personalized settings, and salespersons can adjust parameters such as window layout, font size, and message reminder methods according to their own usage habits to enhance the usage experience.

[0015] 2. Chat tool connection module: This is the core module for realizing multi-tool integration, responsible for establishing stable connections with various mainstream chat tools and ensuring secure data transmission. The module adopts a modular design, developing independent connection plugins for different chat tools, such as WeChat connection plugin, Enterprise WeChat connection plugin, Feishu connection plugin, DingTalk connection plugin, etc. Each connection plugin connects with the chat tool to achieve functions such as message reception and sending, and data transmission. During the connection process, the chat tool connection module adopts encryption transmission technology to ensure the security of user account information and chat data. In addition, the module has an automatic reconnection and fault detection function. When the connection is abnormal, it can automatically restore the connection in a timely manner to ensure communication stability.

[0016] 3. Message processing module: As the message center of the system, the message processing module undertakes key tasks such as message reception, sending, format conversion, and routing. When a new message arrives, the chat tool connection module transmits the message to the message processing module. The message processing module first parses the message to identify the message source, type, and content. Then, according to the message format and the requirements of the target chat tool, it performs format conversion on the message to ensure accurate transmission of the message between different chat tools. In terms of message routing, the message processing module accurately routes the message to the corresponding chat session window for display according to preset rules. For messages sent by users, the message processing module also performs reverse format encapsulation and routing operations to ensure that the messages are correctly sent to the target chat tool.

[0017] 4. AI Interaction Module: The AI interaction module is a key component for realizing AI-assisted chatting and is responsible for docking and interacting with external AI models. This module adopts a standardized interface design and can be easily integrated with various mainstream AI models, such as ChatGPT, DeepSeek, Doubao, Yuanbao, Tongyi Qianwen, etc. When the salesperson selects AI to take over the chat, the AI interaction module organizes the chat records of the user and the customer into a format acceptable to the AI model and sends them to the AI model for analysis and processing. Based on the received chat records, the AI model uses its powerful natural language processing capabilities and knowledge graph to generate accurate and professional response content. After receiving the response content returned by the AI model, the AI interaction module transmits it to the message processing module, which sends the response content to the customer. In addition, the AI interaction module has an intelligent learning function and can continuously optimize the response strategy of the AI model according to the actual chat situation, improving the accuracy and personalization of the response.

[0018] 5. Data Storage Module: The data storage module is used to store various types of data generated during the operation of the system, including chat records, user information, AI model training data, etc. This module adopts a distributed database architecture, integrating the advantages of relational databases and non-relational databases to meet the storage requirements of different types of data. For structured user information and system configuration data, a relational database (such as MySQL) is used for storage to ensure data consistency and integrity; for unstructured chat records and AI model training data, a non-relational database (such as MongoDB) is used for storage to improve data storage and query efficiency. At the same time, the data storage module has data backup and recovery functions, regularly backing up the data to prevent data loss. In terms of data security, strict access control and encryption technologies are adopted to ensure the security and privacy of the data.

[0019] According to another aspect of the present invention, there is provided an efficient sales aggregation chat method based on multi-tool integration and AI assistance, and the method includes:

[0020] 1. Initialization Step: When the user logs in to the aggregated chat system for the first time, the system guides the user through a series of initialization settings. First, the user needs to add the chat tool accounts and WeChat accounts to be connected in the system settings and complete the authorization operation. The chat tool connection module calls the corresponding connection plug-in according to the account information input by the user to perform an authorized login verification with the chat tool. During the authorization process, the system displays detailed authorization instructions and security prompts to the user to ensure that the user understands the authorization content and risks. After successful authorization, the system automatically obtains the contact list and chat records of the user in each chat tool and synchronizes them to the local data storage module. At the same time, the system generates a personalized aggregated chat window layout and message reminder settings for the user based on the user's historical usage habits and preference settings.

[0021] 2. Message Receiving Step: When a new message arrives, the chat tool connection module monitors the message queues of each chat tool in real time. Once a new message is detected, the chat tool connection module immediately transmits the message to the message processing module. The message processing module first decrypts and parses the message to extract the key information of the message, such as the sender, recipient, message content, sending time, etc. Then, the message processing module performs a unified format processing on the message according to the message source and type. For example, it converts the message formats of different chat tools into the unified message format within the system for subsequent storage and display. After processing, the message processing module routes the message to the corresponding chat session display in the aggregated chat window and sends a message reminder to the user according to the message reminder methods set by the user, such as sound, vibration, pop-up window, etc.

[0022] 3. Message Sending Step: After the user enters a message in the aggregated chat window and clicks the send button, the message is first sent to the message processing module. The message processing module checks the format and validates the content of the message entered by the user to ensure the legality and integrity of the message. Then, the message processing module encapsulates the message into the format acceptable to the target chat tool according to the target chat tool of the message. For example, for a message sent to WeChat, it is encapsulated according to the WeChat message format; for a message sent to Feishu, it is encapsulated according to the Feishu message format. After encapsulation, the message processing module sends the message to the chat tool connection module, and the chat tool connection module sends the message to the target chat tool. During the message sending process, the system displays the sending status of the message in real time, such as sending, sent successfully, sent failed, etc., so that the user can understand the message sending situation in a timely manner. If the message sending fails, the system prompts the user with the failure reason and provides corresponding solutions, such as network connection problems, account abnormalities, etc.

[0023] 4. AI Takeover Steps: When a salesperson encounters difficult questions during a chat with a customer or needs to quickly handle a large number of repetitive questions, they can click the AI takeover button in the aggregated chat window to temporarily hand over the chat work to AI for processing. After the AI takeover function is activated, the AI interaction module organizes the historical records of the current chat session (including the chat content between the user and the customer) into a specific format and sends it to an external AI model for analysis and processing. After receiving the chat records, the AI model uses its powerful natural language processing capabilities and knowledge graph to understand and analyze the customer's questions and generate corresponding response content. After receiving the response content returned by the AI model, the AI interaction module reviews and optimizes the response content. The review process mainly checks whether the response content complies with laws, regulations, ethical norms, and the business requirements of the enterprise to avoid inappropriate remarks or incorrect information. The optimization process mainly polishes the language and adjusts the format of the response content to make it more smooth and easy to understand. After the review and optimization are completed, the AI interaction module sends the response content to the message processing module, and the message processing module sends the response content to the customer. During the AI takeover of the chat, the salesperson can view the response content of the AI at any time and make adjustments and modifications according to the actual situation. If the salesperson believes that the response content of the AI does not meet the requirements, they can manually turn off the AI takeover function and take over the chat work again.

[0024] The present invention has the following application values:

[0025] 1. Improve sales communication efficiency: By connecting multiple chat tools and multiple WeChat accounts through the aggregated chat window, salespersons do not need to frequently switch between multiple applications and can chat with multiple people simultaneously on a unified interface. This greatly saves the time and energy of salespersons and improves communication efficiency. In addition, AI takeover can take over the conversations between salespersons and customers, significantly increasing the number of customers that a single salesperson can manage and improving management efficiency. According to actual tests, after using the aggregated chat system of the present invention, the communication efficiency of salespersons has increased by more than 30% on average, and they can handle more customer inquiries and business negotiations within the same time.

[0026] 2. Enhance customer service quality: With the powerful natural language processing capabilities and intelligent analysis capabilities of AI, the AI takeover of chat work can quickly and accurately reply to customer inquiries, avoiding problems of untimely and inaccurate replies caused by salespersons being busy or lacking knowledge. AI can provide personalized services and recommendations based on the customer's historical chat records and purchase behaviors, enhancing customer satisfaction and loyalty. For example, when a customer inquires about a certain product, AI can quickly query the customer's purchase history and preferences and recommend relevant product accessories or value-added services to enhance the customer's purchase experience.

[0027] 3. Data integration and analysis: The system centrally stores all chat records, facilitating comprehensive and in-depth analysis of customer data. By analyzing chat records, enterprises can understand customers' needs, pain points, and purchase intentions, providing a strong basis for sales decisions. For example, by analyzing the frequently mentioned problems of customers in the chat, deficiencies in products or services can be identified and timely improvements and optimizations can be made; by analyzing customers' purchase behaviors and preferences, precise marketing strategies can be formulated to improve marketing effectiveness. At the same time, data integration can also enable the sharing of customer information, and employees in different departments can view relevant customer information according to their permissions, providing more collaborative and efficient services to customers.

[0028] 4. Reducing enterprise costs: The aggregated chat system of the present invention can effectively reduce the labor costs and operating costs of enterprises. On the one hand, by improving the efficiency of sales communication and the quality of customer service, enterprises can handle more business without increasing the number of salespersons, thereby improving sales performance. On the other hand, the AI taking over chat work can reduce the repetitive labor of salespersons, reducing the labor costs of enterprises. In addition, the centralized management and data integration functions of the system can reduce the investment and management costs of enterprises on multiple chat tools, improving the operating efficiency of enterprises.

[0029] 5. Expanding business boundaries: The openness and scalability of the system provide the possibility for enterprises to expand their business boundaries. By integrating new chat tools or business systems, enterprises can quickly adapt to market changes and meet the needs of different customer groups. For example, with the rise of emerging social platforms, enterprises can quickly access these platforms through this system to expand customer sources and increase market share. At the same time, the integration of the system with other business systems (such as CRM systems, ERP systems) can achieve the automation and coordination of business processes, further enhancing the operating efficiency and competitiveness of enterprises. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 is the overall architecture diagram of the efficient sales aggregated chat system based on multi-tool integration and AI assistance in the embodiment of the present invention.

[0031] Figure 2 is the schematic diagram of the user interface of the aggregated chat window in the embodiment of the present invention.

[0032] Figure 3 is the flowchart of the AI taking over the work of salespersons in the embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0033] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0034] I. System Architecture and Implementation

[0035] Figure 1 It is the overall architecture diagram of the efficient sales aggregation chat system based on multi-tool integration and AI assistance in the embodiments of the present invention. This efficient sales aggregation chat system mainly consists of a user interface layer, a chat tool connection module, a message processing module, an AI interaction module, and a data storage module:

[0036] The user interface layer is located at the top of the system, directly interacting with users, and providing functions such as an aggregated chat window, message input and display, and personalized settings. The chat tool connection module is located on the left side of the system and is responsible for establishing connections with various chat tools (such as WeChat, Enterprise WeChat, DingTalk, Feishu, etc.) to achieve message reception and sending. The message processing module is located in the center of the system and is responsible for processing the received and sent messages, including operations such as parsing, format conversion, and routing. The AI interaction module is located on the right side of the system and is responsible for interacting with external AI models (such as ChatGPT, DeepSeek, etc.) to achieve AI assistance and takeover functions. The data storage module is located at the bottom of the system and is responsible for storing, backing up, and retrieving system data, supporting a distributed database architecture.

[0037] Data exchange and collaborative work are carried out between each module through standardized interfaces, forming an efficient and stable chat system to achieve the functions of multi-chat tool integration and AI-assisted sales.

[0038] (I) Implementation of the User Interface Layer

[0039] Figure 2Displays the user interface layout of the aggregated chat window, including four main areas: The first column on the left is the account list for sales management, and the second column is the conversation list area, which shows all chat conversations and categorizes them for display according to different types (such as individual customers, enterprise customers) and topics (such as product consultation, after-sales service). In the center is the chat content area, which shows the chat records of the currently selected conversation, including various types of messages such as text, pictures, and voice. The upper right side is the customer information area, which shows the basic information of the current chat object, customer source, intended product, customer level, follow-up status, purchase history, follow-up plan, and tags, etc.; the lower right side is the AI settings, where customers can select AI models, response tones, and brand scripts, etc. At the bottom is the message input area, which provides functions such as a text input box, emoji selection, and file upload, and includes an AI takeover button. There is a function menu bar at the top of the interface, which provides function entry points such as aggregated chat, mass sending management, moments, customer operation, function encyclopedia, and system settings. The overall interface design is simple and intuitive, and the operation is convenient, helping salespeople efficiently manage multiple chat conversations. The specific implementation process of the user interface layer is as follows:

[0040] 1. Construction of the aggregated chat window

[0041] Use front-end development technologies such as React and Vue.js frameworks to create a unified aggregated chat window interface. This window should have a message input area, a chat record display area, and a personalized setting entry.

[0042] Use HTML and CSS to design the window layout to ensure that the interface is beautiful and the operation is convenient.

[0043] 2. Implementation of the message input function

[0044] Bind an event listener to the message input box. When the user enters content and triggers the send operation, the message is passed to the message processing module for subsequent processing.

[0045] 3. Implementation of the chat record viewing function

[0046] Extract the chat record data from the data storage module and sort it according to the time sequence or other rules.

[0047] Render the sorted chat records to the chat record display area, supporting functions such as scrolling viewing and searching.

[0048] 4. Implementation of the personalized setting function

[0049] Develop a personalized setting panel that provides window layout adjustment options, such as column layout, single-column layout, etc.; font size adjustment options to set different font size levels; message reminder method options, including sound reminder, vibration reminder, pop-up reminder, etc.

[0050] After the user performs the setting operation, the setting information is saved to the data storage module, and the window display effect is updated in real time.

[0051] 5. Implementation of the intelligent conversation classification function

[0052] Define the classification rules for chat object types and chat topics. For example, determine the chat object type based on labels, remarks, etc. in the contact information; judge the chat topic by extracting keywords and performing semantic analysis on the message content.

[0053] Group the chat conversations according to the classification rules, and display them using different labels or grouping lists to facilitate users to quickly locate and manage.

[0054] (2) Implementation of the chat tool connection module

[0055] 1. Development of connection plugins

[0056] Develop independent connection plugins for mainstream chat tools such as WeChat, Enterprise WeChat, DingTalk, QQ, and Feishu respectively.

[0057] The plugin implements the message synchronization function. By polling or listening to the message queue, it can obtain new messages in the chat tool in real time, and synchronize the messages in the aggregated chat system to the corresponding chat tool.

[0058] 2. Implementation of the automatic reconnection function

[0059] Monitor the network connection status. When a connection interruption is detected, start the automatic reconnection mechanism.

[0060] Set the maximum number of retry attempts and the retry interval time. If the retry fails multiple times, record the error information and prompt the user.

[0061] 3. Implementation of the fault detection function

[0062] Periodically detect the connection status to check for abnormal situations such as message loss and connection timeout.

[0063] When a fault is detected, record the fault information and try to repair it automatically; if it cannot be repaired, send a fault prompt to the user.

[0064] 4. Implementation of the multi-account connection and switching function

[0065] Design an account management interface that allows users to add, delete, and manage multiple chat tool accounts.

[0066] Implement the function of quickly switching between different accounts of the same chat tool, save the login status and session information of the accounts, and quickly restore the chat interface when switching.

[0067] Supports the quick transfer of chat sessions among multiple WeChat accounts, and realizes the seamless docking of customer information by copying or moving chat records and contact information.

[0068] (3) Implementation of the message processing module

[0069] 1. Message reception and processing

[0070] Receives messages from the chat tool connection module and first performs decryption operations to ensure data security.

[0071] Adopts targeted parsing strategies according to the type of message (text, picture, voice, video, etc.). For text messages, directly extract the message content; for multimedia messages, download and save them to local storage, and display corresponding thumbnails or play buttons in the chat record.

[0072] Converts the message format to unify the message formats of different chat tools into the standard format within the aggregated chat system.

[0073] Routes the message to the corresponding chat session in the aggregated chat window for display according to the sender and receiver information of the message.

[0074] Sends message reminders according to the message reminder methods set by the user at the user interface layer.

[0075] 2. Message sending and processing

[0076] Checks the format and validates the content of the message entered by the user in the aggregated chat window to ensure that the message meets the requirements of the target chat tool.

[0077] Performs reverse format encapsulation on the message according to the message format specification of the target chat tool.

[0078] Sends the message to the target chat tool through the chat tool connection module and displays the sending status (sending, sent, sending failed, etc.) in real time.

[0079] When the sending fails, analyzes the failure reasons (such as network problems, account anomalies, etc.), and prompts the user with the reasons and provides solutions.

[0080] (4) Implementation of the AI interaction module

[0081] 1. Standardized interface design

[0082] Designs a unified interface specification for docking mainstream AI models such as ChatGPT, DeepSeek, Doubao, Yuanbao, Tongyi Qianwen, etc. The interface should include request parameters (such as chat records, user information, business rules, etc.) and response formats (AI-generated reply content, relevant suggestions, etc.).

[0083] 2. Data processing and transmission

[0084] When the salesperson clicks the AI takeover button, the current chat session history is organized into a format acceptable to the AI model (such as JSON format) and sent to the external AI model through a standardized interface.

[0085] Receive responses generated by the AI model, review them, and optimize them. During the review process, we factor in the company's pre-set brand messaging style, business practices, and customer profiles to ensure responses are consistent with the company's image and meet the customer's personalized needs.

[0086] 3. Implementation of intelligent learning function

[0087] Record the user's adjustments and feedback on the AI's reply content, and save this information as training data in the data storage module.

[0088] Regularly analyze and process training data, update the parameters and rules of the AI model, and realize intelligent learning functions.

[0089] 4. Implementation of customer problem summary generation function

[0090] In the AI takeover step, natural language processing technology (such as keyword extraction and text summarization algorithm) is used to automatically generate a summary of the customer's question based on the chat history.

[0091] Show summary information to sales staff to help them quickly understand the key points of customer needs.

[0092] (V) Data storage module implementation

[0093] 1. Database architecture construction

[0094] It uses a distributed database architecture that combines relational databases (such as MySQL) and non-relational databases (such as MongoDB). Relational databases are used to store structured data (such as user information and basic information about chat logs), while non-relational databases are used to store unstructured data (such as detailed chat log content and multimedia files).

[0095] 2. Data storage and compression

[0096] When storing data, data compression algorithms (such as Gzip) are used to compress and store chat records, AI model training data, etc. to save storage space.

[0097] When reading data, the compressed data is automatically decompressed without affecting the normal use of the data.

[0098] 3. Implementation of Data Backup and Recovery Function

[0099] Regularly perform backup operations on the database and store the backup data in a secure location.

[0100] When data recovery is needed, be able to quickly recover the database from the backup to the state at a specified point in time.

[0101] 4. Implementation of Data Cleaning and Archiving Function

[0102] Set data cleaning and archiving rules, and automatically archive and store expired or low-frequency accessed chat records, user information, etc.

[0103] Develop a data retrieval function to ensure that the required information can be quickly retrieved and recovered from the archived data when needed.

[0104] 5. Data Interaction and Sharing with Other Business Systems

[0105] Develop data interfaces to achieve data interaction and sharing with other enterprise business systems (such as CRM systems, ERP systems).

[0106] Through the interfaces, circulate customer information, sales data, etc. among different systems to promote the coordination and integration of business processes.

[0107] II. System Usage Process

[0108] (I) Initialization Steps

[0109] 1. The user opens the aggregated chat system, enters the login interface, and enters the account number and password to log in.

[0110] 2. After successful login, enter the system settings page, add and authorize the chat tool accounts or WeChat accounts to be connected. If there is no chat tool account during the first login, the system will prompt the user to add a chat tool account.

[0111] 3. The system obtains the contact list and chat records of the user in each chat tool through the chat tool connection module and synchronizes them to the local data storage module.

[0112] 4. Generate a personalized aggregated chat window layout and message reminder settings according to the user's historical usage habits and preferences (such as the previously set window layout, font size, message reminder method, etc.).

[0113] (II) Message Receiving Steps

[0114] 1. The chat tool connection module monitors the chat tool message queue in real time. When there is a new message, it transmits the message to the message processing module.

[0115] 2. The message processing module decrypts, parses, and unifies the format of the message, and routes the message to the corresponding chat session in the aggregated chat window for display according to the sender and recipient information of the message.

[0116] 3. Send message reminders (such as sound reminders, vibration reminders, pop-up reminders, etc.) according to the message reminder method set by the user at the user interface layer.

[0117] (III) Message Sending Steps

[0118] 1. The user enters a message in the message input box of the aggregated chat window and clicks the send button.

[0119] 2. The message processing module checks the format and validates the content of the message to ensure that the message meets the requirements of the target chat tool.

[0120] 3. Reverse format encapsulation is performed on the message according to the message format specification of the target chat tool.

[0121] 4. The message is sent to the target chat tool through the chat tool connection module, and the sending status (sending, sent, sending failed, etc.) is displayed in real time.

[0122] 5. If the sending fails, the message processing module analyzes the reason for the failure (such as network problems, account abnormalities, etc.), and prompts the user with the reason and provides a solution.

[0123] (IV) AI Takeover Steps

[0124] [[ID=२७]] Figure 3 The detailed process of AI taking over the work of salespersons is shown, including the following steps:

[0125] 1. The salesperson clicks the AI takeover button in the aggregated chat window.

[0126] 2. The AI interaction module collects and organizes the historical records of the current chat session and generates a format acceptable to the AI model.

[0127] 3. The AI interaction module sends the organized chat records to an external AI model through a standardized interface.

[0128] 4. The AI model generates a reply based on the received chat records and returns it to the AI interaction module.

[0129] 5. The AI interaction module reviews and optimizes the reply generated by the AI model.

[0130] 6. The system determines whether human intervention is required.

[0131] 7. If no intervention is required, send the reviewed and optimized response content to the customer through the message processing module and the chat tool connection module.

[0132] 8. If intervention is required, the system notifies the salesperson to handle it.

[0133] 9. The system records the entire process data for subsequent analysis and optimization.

[0134] The salesperson can view and adjust the AI response content at any time. When dissatisfied, manually turn off the AI takeover function and resume manual response. The flowchart shows different handling methods during the AI takeover process through a branch structure and demonstrates the system's automatic judgment and flexible intervention mechanism.

[0135] III. System Maintenance and Management

[0136] (I) Operation Log Recording and Analysis

[0137] 1. During the operation of the system, all operation behaviors of users within the system (login, message sending, AI takeover operation, data query, etc.) are recorded in detail, and the operation logs are saved to the data storage module.

[0138] 2. Regularly analyze the operation logs, generate reports and visual charts through data analysis tools (such as Tableau, PowerBI), to help the enterprise understand user usage habits, system performance and other information, and provide support for system optimization and business decision-making.

[0139] (II) System Update and Optimization

[0140] 1. Regularly update and optimize the system, including fixing system vulnerabilities, improving system performance, adding new functions, etc.

[0141] 2. According to user feedback and business requirements, improve and optimize the system functions and interfaces to enhance the user experience.

[0142] (III) Data Security and Privacy Protection

[0143] 1. Strengthen data security management, regularly conduct backup and recovery tests on the database to ensure data security and integrity.

[0144] 2. Comply with relevant laws, regulations and privacy policies to protect users' personal information and chat records from being leaked. Encrypt the storage and transmission of sensitive data, and take access control measures to limit access rights to the data.

[0145] IV. Integration of the System with Other Business Systems

[0146] The system supports data interaction and sharing with other business systems of the enterprise (such as CRM systems and ERP systems). By writing interface codes, data transmission and synchronization between the system and other business systems are achieved.

[0147] (I) Design of Data Interaction Interfaces

[0148] Standardized interface protocols (such as RESTful API and SOAP) are adopted to design data interaction interfaces, defining the request and response formats of the interfaces to ensure accurate data transmission. The interface design follows the principles of security, efficiency, and scalability, and conducts authentication and authorization management for the interfaces to prevent illegal access.

[0149] (II) Data Synchronization Mechanism

[0150] A data synchronization mechanism is established to synchronize customer information, sales data, etc. in the system to other business systems regularly or in real time, and at the same time synchronize relevant data in other business systems to this system. During the data synchronization process, data conflict detection and resolution strategies are adopted to ensure data consistency and accuracy.

[0151] (III) Business Process Collaboration

[0152] Through data interaction and sharing, business process collaboration and integration are achieved. For example, when a salesperson completes a sales order in this system, the system automatically synchronizes the order information to the ERP system, triggering subsequent business processes such as inventory management and logistics distribution; at the same time, synchronizes the customer feedback information to the CRM system to facilitate customer relationship management and the development of subsequent marketing activities.

[0153] Through the above specific implementation manners, the efficient sales aggregation chat method and system based on multi-tool integration and AI assistance of the present invention can realize the integration of multiple chat tools, improve the efficiency and quality of sales communication with the help of AI technology, and provide strong support for the sales business of the enterprise. At the same time, the system has good scalability and compatibility, and can be integrated with other business systems of the enterprise to achieve business process collaboration and integration.

Claims

1. An efficient sales aggregation chat system based on multi-tool integration and AI assistance, characterized in that It includes: User interface layer: Provides a unified aggregated chat window for displaying chat sessions from multiple chat tools, supporting users to input messages, view chat records, and perform personalized settings on the window. Chat tool connection module: Develops independent connection plugins for different chat tools to achieve message synchronization and data transmission with multiple chat tools or multiple WeChat accounts, and has functions such as automatic reconnection and fault detection. Message processing module: Receives messages from the chat tool connection module, parses, converts the format, and routes them, accurately displays the messages in the corresponding chat sessions of the aggregated chat window, and at the same time performs reverse format encapsulation and routing on the messages sent by users. AI interaction module: Adopts a standardized interface design to connect to external AI models, organizes the chat records of users and customers into a format acceptable to the AI model and sends them, receives the reply content generated by the AI model, audits and optimizes it, and then transmits it to the message processing module, and has an intelligent learning function. Data storage module: Adopts a distributed database architecture, combines relational databases and non-relational databases to store chat records, user information, AI model training data, etc., and has functions of data backup and recovery.

2. The efficient sales aggregation chat system according to claim 1, wherein The personalized settings of the user interface layer include adjusting the window layout, font size, and message reminder method.

3. The efficient sales aggregation chat system according to claim 1, wherein The connection plugins of the chat tool connection module support mainstream chat tools such as WeChat, WeCom, DingTalk, QQ, and Lark.

4. The efficient sales aggregation chat system according to claim 1, wherein The AI interaction module can connect to mainstream AI models such as ChatGPT, DeepSeek, Doubao, Yuanbao, and Tongyi Qianwen.

5. An efficient sales aggregation chat method based on multi-tool integration and AI assistance, which is applied to the efficient sales aggregation chat system described in any one of claims 1-4, characterized in that, It includes the following steps: Initialization step: The user logs in to the aggregated chat system, adds and authorizes the chat tool accounts or WeChat accounts to be connected in the system settings. The system obtains the contact lists and chat records of the user in each chat tool and synchronizes them to the local data storage module, and generates a personalized aggregated chat window layout and message reminder settings according to the user's historical usage habits and preferences. Message receiving step: The chat tool connection module monitors the chat tool message queue in real time. When there is a new message, it transmits it to the message processing module. The message processing module decrypts, parses, and unifies the format of the message, and then routes it to the corresponding chat session in the aggregated chat window for display, and sends message reminders according to the user settings. Message sending step: The user inputs a message in the aggregated chat window. The message processing module checks the format and validates the content, encapsulates the message format according to the target chat tool, and sends it through the chat tool connection module. The sending status is displayed in real time during the sending process. When the sending fails, the reason is prompted and a solution is provided. AI takeover step: The salesperson clicks the AI takeover button. The AI interaction module organizes the current chat session history records and sends them to the external AI model. The AI model generates reply content. After the AI interaction module audits and optimizes the reply content, it is sent to the customer through the message processing module and the chat tool connection module. The salesperson can view and adjust the AI reply content at any time and can manually turn off the AI takeover function when dissatisfied.

6. The efficient sales aggregation chat method according to claim 5, wherein: During the message processing, the message processing module adopts targeted parsing and format conversion strategies for different types of messages (text, pictures, voice, video, etc.) to ensure the accurate transmission and display of various messages among different chat tools.

7. The efficient sales aggregation chat system according to claim 1, characterized in that: When storing data, the system uses data compression algorithms to compress and store chat records, AI model training data, etc., in order to save storage space, and automatically decompresses when reading data without affecting the normal use of the data.

8. The efficient sales aggregation chat system according to claim 1, wherein: The user interface layer has an intelligent conversation classification function, which can automatically classify and display chat conversations according to the type of chat object (personal customers, enterprise customers, potential customers, etc.) and chat topics (product consultation, after-sales service, cooperation negotiation, etc.), facilitating users to quickly locate and manage.

9. The efficient sales aggregation chat system according to claim 1, wherein: When implementing multi-account connection, the chat tool connection module supports quick switching and collaborative operations between different accounts of the same chat tool. For example, it can quickly transfer chat conversations between multiple WeChat accounts to achieve seamless docking of customer information.

10. The efficient sales aggregation chat system according to claim 1, wherein: When auditing and optimizing the reply content, the AI interaction module processes it in combination with the brand speech style, business norms and customer portraits preset by the enterprise, so that the AI reply content not only conforms to the enterprise image but also meets the personalized needs of customers.

11. The efficient sales aggregation chat system according to claim 1, characterized in that: The system has an operation log recording function, which details all operation behaviors of users in the system (login, message sending, AI takeover operation, data query, etc.) for operation traceability and data analysis.

12. The efficient sales aggregation chat method according to claim 5, wherein: In the AI takeover step, the AI interaction module can automatically generate a summary of customer questions based on the chat history, helping salespersons quickly understand the key points of customer needs, so as to more accurately intervene in the AI reply when needed.

13. The efficient sales aggregation chat system according to claim 1, characterized in that: The data storage module supports the functions of regular data cleaning and archiving. For expired or infrequently accessed chat records, user information, etc., it can automatically archive and store them, and quickly retrieve and restore them when needed.

14. The efficient sales aggregation chat system according to claim 1, wherein: The system supports data interaction and sharing with other enterprise business systems (such as CRM systems, ERP systems), realizes the circulation of customer information, sales data, etc. between different systems, and promotes the coordination and integration of business processes.

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