Enterprise consultation service management system based on Internet

Abstract

The invention relates to the technical field of enterprise consultation, and discloses an internet-based enterprise consultation service management system, which is used for performing theme extraction and induction on customer consultation requirements, quickly calling and integrating related data from a database and matching consultation consultants in related fields according to the consultation fields. According to the system, rapid butt joint and efficient communication between enterprise customers and consulting consultants are achieved, the whole process of consulting service is effectively monitored and managed through application of the service progress tracking module and the service quality evaluation module, and meanwhile, the service quality of the consulting service is effectively improved through analysis and feedback of customer evaluation data in combination with service evaluation analysis of the system. The service process and method can be continuously optimized according to the service bias of a consulting company in a targeted manner, and through big data analysis and data acquisition, latest information of related projects and fields is pushed to an enterprise client in a targeted manner in an information pushing manner, and related suggestions are provided. And the client is helped to know the latest dynamic state of the related field in time and make related plans.

Description

Technical Field

[0001] The present invention relates to the technical field of enterprise consulting, and in particular to an enterprise consulting service management system based on the Internet. Background Art

[0002] With the popularization of enterprise informatization and e-commerce knowledge, the awareness of enterprise informatization has been greatly improved, the demand for enterprise consulting services has been increasing day by day, and service management of enterprises through the Internet has been paid attention to. In order to adapt to the highly competitive market environment, enterprises need to continuously improve and optimize management methods to enhance competitiveness and efficiency. With the rise of technologies such as the Internet, big data, and artificial intelligence, enterprise consulting management has become more scientific and efficient. The management consulting service system can help enterprises understand and comply with relevant laws and regulations, reduce legal risks, and provide solutions and guidance for specific problems through professional management consulting services to help enterprises improve operations and enhance performance.

[0003] With the rapid development of Internet technology, however, the traditional consulting service model has many limitations, such as poor timeliness and accuracy of consulting response information, low communication efficiency, lack of transparency in the service process, and difficulty in effectively evaluating service quality. These limitations not only affect the effectiveness of consulting services, but also reduce customer satisfaction with consulting. For this reason, an Internet-based enterprise consulting service management system is proposed. Summary of the invention

[0004] The purpose of the present invention is to provide an Internet-based enterprise consulting service management system to solve the problems raised in the above-mentioned background technology.

[0005] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: An Internet-based enterprise consulting service management system includes a user management unit, a consulting service unit, a service evaluation unit, a cloud service unit and a service push unit;

[0006] The user management unit is used for customer registration, login and security management, and includes a user terminal, a user management module and a login security management module;

[0007] The consulting service unit provides comprehensive service management for enterprise consulting services by calling cloud service unit data. The consulting service unit includes an intelligent demand matching module, an online communication and collaboration module, and a service progress tracking module;

[0008] The service evaluation unit is used for comprehensive evaluation and analysis after the enterprise consulting service to improve the service system, and the service evaluation unit includes an analysis and evaluation module and an evaluation feedback module;

[0009] The cloud service unit is used as the core of the system to store and manage various types of data. The cloud service unit includes a cloud database, a cloud server and a data security protection module;

[0010] The service push unit comprehensively analyzes the user's consultation content and provides the user with relevant and latest information push. The service push unit includes a demand analysis module and an information push module.

[0011] Preferably, the above-mentioned user terminal is a network interaction port between the system and the customer, and the user terminal includes login entries for multiple roles. The user management module is used for classified management of registered and logged-in user information. The user management module summarizes and organizes the information of newly registered users and uploads it to the cloud service unit, classifies and manages customers according to their value, industry, and scale factors, defines different customer categories, and adds corresponding tags to customers to facilitate targeted customer service and marketing activities.

[0012] Preferably, the login security management module is used for verifying user login information and managing permissions after login. When working, the login security management module verifies user information by calling and checking user data in the cloud database, sets different data access levels according to user roles and permissions, and ensures that only authorized users can access sensitive data.

[0013] As a preferred embodiment, the intelligent demand matching module extracts and summarizes the customer's consulting needs, quickly retrieves and integrates relevant information from the database according to the customer's consulting needs, and matches consultants in related fields according to the consulting field, as follows:

[0014] Demand analysis: When a corporate customer submits a consulting request, the system first performs natural language processing and semantic analysis on the request to extract key information;

[0015] Consultant matching: Based on the extracted key information, the intelligent matching algorithm is used to call relevant data from the cloud database and select the most suitable consultant from the consulting consultant database, as follows:

[0016] Using a matching algorithm based on content similarity, first, the enterprise's consulting demand text Q and the consultant's professional field description text P i (i=1,2,…,n,)where n is the number of consultants, vectorized representation, and word vector model is used to calculate Q and P i The cosine similarity Sim(Q,P i ), the formula is:

[0017]

[0018] where q j and p ijRepresents text Q and P respectively i The word vector value of the jth dimension in the word vector is m, and then all consultants are sorted according to the similarity score, and the consultant with the highest score is selected as the matching result. At the same time, combined with the collaborative filtering algorithm, the similarity between the company's historical consulting records and other companies is considered to further optimize the matching accuracy.

[0019] Task assignment: After a successful match, the system automatically assigns the consulting task to the selected consultant and sends a notification to remind the consultant to handle it in a timely manner. At the same time, it generates a unique project number for the corporate customer to facilitate subsequent tracking and management.

[0020] Preferably, the online communication and collaboration module is used for information assistance during consultation, specifically as follows:

[0021] Real-time communication: The system has built-in instant messaging function, which supports real-time text, voice and video communication between corporate customers and consultants. No matter where the two parties are, they can communicate conveniently and quickly to solve problems that arise during the consultation process in a timely manner;

[0022] File sharing: In order to facilitate the sharing of data and information between the two parties, the system provides file upload and download functions. Corporate customers can upload relevant materials so that consultants can better understand the company's situation. Consultants can also share relevant files with customers to ensure timely transmission and sharing of information;

[0023] Data visualization display: Build an intuitive and easy-to-use data visualization interface, support the display of multiple types of visualization charts, so that users can more intuitively understand the relevant parameter information during the consultation process, and realize the dynamic interaction function of data. Users can deeply understand the detailed information behind the data through operations such as clicking, filtering, and drilling, thereby improving the efficiency and effect of data analysis;

[0024] Task discussion area: A dedicated task discussion area is set up for each consulting project system, where enterprises and consultants can discuss and exchange ideas on the specific content, progress, and problems encountered in the project. The chat records in the discussion area will be automatically saved for subsequent reference and review.

[0025] Preferably, the service progress tracking module is used for overall management of consulting service progress, as follows:

[0026] Project plan formulation: After receiving the task, the consultant will formulate a detailed project plan based on the consulting needs and the actual situation of the enterprise and enter the project plan into the system;

[0027] Real-time progress update: During the project implementation process, consultants need to regularly update the project progress in the system. The system will automatically generate progress reports based on the updated information and present them to enterprises and consultants in the form of visual charts, so that they can intuitively understand the progress of the project;

[0028] Early warning mechanism: When the project progress deviates or is about to exceed the scheduled time node, the system will automatically issue an early warning notification to remind relevant personnel to take timely measures to make adjustments and improvements.

[0029] Preferably, the analysis and evaluation module combines the recorded data in the consultation process with the customer's later evaluation to make an overall analysis, as follows:

[0030] Multi-dimensional evaluation indicators: In order to comprehensively and objectively evaluate the quality of consulting services, the system has established a set of multi-dimensional evaluation indicators, including the feasibility, innovation, practicality of consulting solutions, consultants' professional level, communication skills, service attitude and the final effect of services, as follows:

[0031] Key indicator evaluation formula: K = ω1×P+ω2×C+ω3×Q;

[0032] Where: K: comprehensive evaluation value of key indicators;

[0033] w1, w2, w3: weight coefficients of consulting project progress, process time, and performance evaluation respectively;

[0034] P: Project consultation progress score;

[0035] C: process time score;

[0036] Q: Performance evaluation score;

[0037] Customer evaluation: After the consulting service is completed, corporate customers can evaluate and score the consultant and the entire service process based on their actual experience, as follows:

[0038] Determine the customer satisfaction evaluation index set: X = {x1, x2, ..., x r};

[0039] Among them, x r represents the rth evaluation index;

[0040] Collect customer evaluation data matrix: D = (d ij ) s×r ;

[0041] Where: d ij represents the score of the i-th customer on the j-th indicator, s is the number of evaluated customers, and r is the number of evaluation indicators;

[0042] Calculate the information entropy H of each indicator j , information entropy H j The uncertainty used to measure each indicator is calculated as follows:

[0043]

[0044] Among them, p ij is the probability of the i-th customer scoring the j-th indicator, and the calculation formula is:

[0045]

[0046] The constant k is defined as:

[0047]

[0048] Calculate the weight w of each indicator j , according to information entropy, we can calculate the weight w of each indicator j :

[0049]

[0050] Calculate the comprehensive customer satisfaction rating S, using the calculated weight w j and customer evaluation data matrix

[0051] D, we can calculate the comprehensive score S of customer satisfaction:

[0052]

[0053] After that, fill in detailed evaluation opinions and suggestions based on the comprehensive score S. The system will collect and organize the customer's evaluation data as an important basis for consultant performance evaluation and service improvement;

[0054] The evaluation feedback module analyzes and mines a large amount of customer evaluation data. The system can identify problems and deficiencies in consulting services, provide consulting companies with targeted improvement suggestions and decision-making support, and improve the consulting system.

[0055] Preferably, the cloud database is an online data storage structure for centralized storage of various parameter data of the system. The cloud server is used for analysis, calculation and decision-making of system data. The data security protection module builds a multi-level network security protection system to prevent external network attacks and malware intrusions, and regularly performs network security vulnerability scanning and repair work to promptly discover and resolve security risks in the system, and encrypts data transmission inside and outside the system to ensure the confidentiality and integrity of the data and prevent the data from being stolen or tampered with during transmission.

[0056] Preferably, the demand analysis module comprehensively analyzes the enterprise consulting content to understand the client's enterprise's later operational needs. The information push module collects, summarizes and analyzes relevant data through big data analysis, and pushes the latest information on related projects and fields to the enterprise client in a targeted manner and provides relevant suggestions, so as to help customers keep abreast of the latest developments in related fields and make relevant plans.

[0057] Preferably, the information push module collects relevant data through a knowledge recommendation formula based on association rule mining, as follows:

[0058] Assume that the item set in the knowledge base is: I = {i1, i2, ..., i m};

[0059] The transaction data set is: T = {t1, t2, ..., t n};

[0060] Suppose the support of item set X in the transaction data set is:

[0061]

[0062] The frequent item set threshold is minSup. If the support of an item set is greater than or equal to the threshold, it is considered a frequent item set. For the association rule X→Y, its confidence is:

[0063]

[0064] The threshold of strong association rule is minConf. If the confidence is greater than or equal to the threshold, it is considered to be a strong association and can be used for knowledge recommendation.

[0065] Compared with the prior art, the present invention adopts the above technical solution and has the following technical effects:

[0066] 1. The system extracts and summarizes customer consulting needs through the intelligent demand matching module and the online communication and collaboration module, quickly retrieves and integrates relevant information from the database based on customer consulting needs, and matches consultants in related fields based on consulting fields, thereby achieving rapid connection and efficient communication between corporate customers and consultants, reducing time waste in the intermediate links, and greatly improving the efficiency of consulting services.

[0067] 2. Through the application of service progress tracking module and service quality assessment module, the whole process of consulting service is effectively monitored and managed, ensuring the quality and effect of service. At the same time, through the analysis and feedback of customer evaluation data combined with the system's own service evaluation analysis, the service process and methods can be optimized according to the service preferences of the consulting company, and the overall service level can be improved. The system also centrally stores and manages the historical data of consulting services, which is convenient for consulting companies to summarize and analyze past cases and accumulate valuable knowledge and experience. This knowledge and experience can be reused and shared in subsequent service projects to improve the overall level of consulting services.

[0068] 3. Comprehensively analyze and focus on related fields based on the consulting content of the enterprise. Through big data analysis and data collection, push the latest information of related projects and fields to the enterprise clients in a targeted manner and provide relevant suggestions, help customers to keep abreast of the latest developments in related fields and make relevant plans, improve post-service work, maintain good communication and interaction with customers, and improve customers' service experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0070] Figure 1 It is a schematic diagram of the overall working unit composition of the system of the present invention;

[0071] Figure 2 It is a schematic diagram of the overall working modules of the system of the present invention;

[0072] Figure 3 It is a schematic diagram of the overall working steps of the system of the present invention. DETAILED DESCRIPTION

[0073] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0074] It should be noted that the structures, proportions, sizes, etc. illustrated in the drawings of this specification are only used to match the contents disclosed in the specification for people familiar with this technology to understand and read, and are not used to limit the conditions under which this application can be implemented. Therefore, they have no substantive technical significance. Any structural modification, change in proportional relationship or adjustment of size should still fall within the scope of the technical content disclosed in this application without affecting the effects and purposes that can be achieved by this application.

[0075] Example

[0076] See also Figure 1-3 The present invention provides a technical solution: an Internet-based enterprise consulting service management system, including a user management unit, a consulting service unit, a service evaluation unit, a cloud service unit, and a service push unit, specifically:

[0077] User Management Unit:

[0078] Used for customer registration, login and security management, the user management unit includes a user terminal, a user management module and a login security management module;

[0079] User side: including login portals for different roles such as corporate customers and consultants. When using, corporate customers and consultants register on the user side of the system respectively, fill in personal information, corporate information (for corporate customers) or professional fields, work experience and other information (for consultants). After successful registration, use the account and password to log in to the system. Corporate customers can submit consulting needs, view service progress, evaluate service quality, etc. through this port, while consultants can receive task assignments, upload service results, communicate with customers, etc.;

[0080] User management module: used for classification management of registered and logged-in user information. The user management module summarizes and organizes the information of newly registered users and uploads it to the cloud service unit. It classifies and manages customers according to their value, industry, and scale factors, defines different customer categories, and adds corresponding tags to customers, so as to facilitate targeted customer service and marketing activities;

[0081] Login security management module: used for verifying user login information and managing permissions after login. When working, the login security management module verifies user information by calling and checking user data in the cloud database, sets different data access levels according to user roles and permissions, and ensures that only authorized users can access sensitive data, thereby ensuring the security of user information access.

[0082] Consulting service unit:

[0083] By calling the cloud service unit data, we provide comprehensive service management for enterprise consulting services. The consulting service unit includes intelligent demand matching module, online communication and collaboration module and service progress tracking module. Specifically:

[0084] Intelligent demand matching module: After the enterprise customer logs in to the system, he / she enters the consulting demand submission page, describes the enterprise's consulting problems, goals and expectations in detail, and uploads relevant information. After the system conducts preliminary verification and classification of the submitted requirements, it adds them to the demand pool and waits for matching. The system extracts and summarizes the customer's consulting needs through themes, quickly retrieves and integrates relevant information from the database according to the customer's consulting needs, and matches consultants in related fields according to the consulting field. The details are as follows:

[0085] Demand analysis: When a corporate customer submits a consulting request, the system first performs natural language processing and semantic analysis on the request to extract key information, such as the type of question, industry field, and degree of urgency;

[0086] Consultant matching: Based on the extracted key information, the intelligent matching algorithm is used to call relevant data from the cloud database and select the most suitable consultant from the consulting consultant database. For example, for a manufacturing company's consulting needs on production process optimization, the system will give priority to matching consultants with rich experience and good reputation in the manufacturing field. The specific matching algorithm is as follows:

[0087] Using a matching algorithm based on content similarity, first, the enterprise's consulting demand text Q and the consultant's professional field description text P i (i=1,2,…,n,)where n is the number of consultants, vectorized representation, and word vector model is used to calculate Q and P i The cosine similarity Sim(Q,P i ), the formula is:

[0088]

[0089] where q j and p ij Represents text Q and P respectively i The word vector value of the jth dimension in the word vector is m, and then all consultants are sorted according to the similarity score, and the consultant with the highest score is selected as the matching result. At the same time, combined with the collaborative filtering algorithm, the similarity between the company's historical consulting records and other companies is considered to further optimize the matching accuracy.

[0090] Task assignment: After a successful match, the system automatically assigns the consulting task to the selected consultant and sends a notification to remind the consultant to handle it in a timely manner. At the same time, it generates a unique project number for the corporate customer to facilitate subsequent tracking and management. The system uses the intelligent demand matching module and the online communication and collaboration module to extract and summarize the customer's consulting needs. According to the customer's consulting needs, the system can quickly retrieve and integrate relevant information from the database and match consultants in related fields according to the consulting field, thereby achieving rapid connection and efficient communication between corporate customers and consultants, reducing time waste in the intermediate links, and greatly improving the efficiency of consulting services.

[0091] Online communication and collaboration module: used for information assistance during consultation, as follows:

[0092] Real-time communication: The system has built-in instant messaging function, which supports real-time text, voice and video communication between corporate customers and consultants. No matter where the two parties are, they can communicate conveniently and quickly to solve problems that arise during the consultation process in a timely manner;

[0093] File sharing: To facilitate the sharing of data and information between the two parties, the system provides file upload and download functions. Corporate customers can upload relevant documents, pictures, videos and other materials so that consultants can better understand the company's situation. Consultants can also share analysis reports, solutions and other files with customers to ensure timely transmission and sharing of information;

[0094] Data visualization display: Build an intuitive and easy-to-use data visualization interface, support the display of multiple types of visualization charts, so that users can more intuitively understand the relevant parameter information during the consultation process, and realize the dynamic interaction function of data. Users can deeply understand the detailed information behind the data through operations such as clicking, filtering, and drilling, thereby improving the efficiency and effect of data analysis;

[0095] Task discussion area: For each consulting project, the system sets up a special task discussion area, where enterprises and consultants can discuss and exchange ideas on the specific content, progress, problems encountered, etc. of the project. The chat records in the discussion area will be automatically saved for easy reference and review. In the storage and processing of sensitive customer information (such as ID card numbers, business secrets, etc.), data desensitization technology is used to encrypt, hide or replace sensitive data to ensure that the customer's privacy information is not leaked. The data desensitization algorithm is regularly evaluated and updated to adapt to changing security needs;

[0096] Service progress tracking module: used for the overall management of consulting service progress, as follows:

[0097] Project plan formulation: After receiving the task, the consultant will formulate a detailed project plan based on the consulting needs and the actual situation of the enterprise, including the task objectives, time nodes, responsible persons and other information of each stage, and enter the project plan into the system;

[0098] Real-time progress update: During the project implementation process, consultants need to regularly update the project progress in the system. The system will automatically generate progress reports based on the updated information and present them to enterprises and consultants in the form of visual charts, so that they can intuitively understand the progress of the project;

[0099] Early warning mechanism: When the project progress deviates or is about to exceed the scheduled time node, the system will automatically issue an early warning notification to remind relevant personnel to take timely measures to make adjustments and improvements. For example, if the completion time of a task exceeds a certain percentage of the planned time, the system will send early warning messages to consultants and corporate customers at the same time, prompting them to pay attention to the project progress.

[0100] Service Evaluation Unit:

[0101] It is used for comprehensive evaluation and analysis after consulting services for enterprises to improve the service system. The service evaluation unit includes analysis and evaluation module and evaluation feedback module. Specifically:

[0102] Analysis and evaluation module: Combine the recorded data in the consultation process with the customer's later evaluation for an overall analysis, as follows:

[0103] Multi-dimensional evaluation indicators: In order to comprehensively and objectively evaluate the quality of consulting services, the system has established a set of multi-dimensional evaluation indicators, including the feasibility, innovation, practicality of consulting solutions, consultants' professional level, communication skills, service attitude and the final effect of services. The specific evaluation formula is as follows:

[0104] Key indicator evaluation formula: K = w1×P+w2×C+w3×Q;

[0105] Where: K: comprehensive evaluation value of key indicators;

[0106] w1, w2, w3: weight coefficients of consulting project progress, process time, and performance evaluation respectively;

[0107] P: Project consultation progress score;

[0108] C: process time score;

[0109] Q: Performance evaluation score;

[0110] Customer evaluation: After the consulting service is completed, corporate customers can evaluate and score the consultant and the entire service process based on their actual experience, as follows:

[0111] Determine the customer satisfaction evaluation index set: X = {x1, x2, ..., x r};

[0112] Among them, x r represents the rth evaluation index;

[0113] Collect customer evaluation data matrix: D = (d ij ) s×r ;

[0114] Where: d ij represents the score of the i-th customer on the j-th indicator, s is the number of evaluated customers, and r is the number of evaluation indicators;

[0115] Calculate the information entropy H of each indicator j , information entropy H j The uncertainty used to measure each indicator is calculated as follows:

[0116]

[0117] Among them, p ij is the probability of the i-th customer scoring the j-th indicator, and the calculation formula is:

[0118]

[0119] The constant k is defined as:

[0120]

[0121] Calculate the weight w of each indicator j , according to information entropy, we can calculate the weight w of each indicator j :

[0122]

[0123] Calculate the comprehensive customer satisfaction rating S, using the calculated weight w j and customer evaluation data matrix

[0124] D, we can calculate the comprehensive score S of customer satisfaction:

[0125]

[0126] After the consulting service is completed, the corporate customer will evaluate and score the consultant and the entire service process, and then fill in detailed evaluation opinions and suggestions based on the comprehensive score S. The system will collect and organize the customer's evaluation data, and analyze and process it. The consulting company will conduct performance appraisal of the consultant based on the evaluation results, and reward consultants with outstanding performance, which will serve as an important basis for consultant performance appraisal and service improvement;

[0127] Evaluation and feedback module: Through the analysis and mining of a large amount of customer evaluation data, the system can discover problems and deficiencies in consulting services, and provide training and guidance to consultants with problems. At the same time, the system will feed back the evaluation results to consultants to help them understand their service performance and deficiencies so that they can improve them in future work, provide consulting companies with targeted improvement suggestions and decision-making support, and improve the consulting system. Through the application of service progress tracking module and service quality evaluation module, the whole process of consulting services is effectively monitored and managed to ensure the quality and effectiveness of the services. At the same time, through the analysis and feedback of customer evaluation data combined with the system's own service evaluation analysis, the service process and methods can be continuously optimized according to the service preferences of the consulting company to improve the overall service level.

[0128] Cloud service unit:

[0129] As the core of the system, it is responsible for storing and managing various types of data. The cloud service unit includes cloud database, cloud server and data security protection module. Specifically:

[0130] Cloud database: It is an online data storage structure used for centralized storage of various parameter data of the system;

[0131] Cloud server: used for analysis, calculation and decision-making of system data;

[0132] Data security protection module: Build a multi-level network security protection system to prevent external network attacks and malware intrusions, and regularly scan and repair network security vulnerabilities to promptly discover and resolve security risks in the system. It also encrypts data transmission inside and outside the system to ensure data confidentiality and integrity and prevent data from being stolen or tampered with during transmission.

[0133] Service push unit:

[0134] Comprehensively analyze the user's consultation content and provide the user with the latest relevant information push. The service push unit includes the demand analysis module and the information push module. Specifically:

[0135] Demand analysis module: Comprehensively analyze and understand the client's future operational needs based on the company's consulting content;

[0136] Information push module: collects and summarizes relevant data through big data analysis, and pushes the latest information of relevant projects and fields in a targeted manner. The information push module collects relevant data through the knowledge recommendation formula based on association rule mining, as follows:

[0137] Assume that the item set in the knowledge base is: I = {i1, i2, ..., i m};

[0138] The transaction data set is: T = {t1, t2, ..., t n};

[0139] Suppose the support of item set X in the transaction data set is:

[0140]

[0141] The frequent item set threshold is minSup. If the support of an item set is greater than or equal to the threshold, it is considered a frequent item set. For the association rule X→Y, its confidence is:

[0142]

[0143] The threshold of strong association rules is minConf. If the confidence is greater than or equal to the threshold, it is considered to be a strong association and can be used for knowledge recommendation. It will then be pushed to the enterprise client and relevant suggestions will be provided to help customers keep abreast of the latest developments in related fields and make relevant plans. Through big data analysis and data collection, the latest information on related projects and fields is pushed to the enterprise client in a targeted manner through information push, and relevant suggestions will be provided to help customers keep abreast of the latest developments in related fields and make relevant plans. The post-service work will be improved to maintain good communication and interaction with customers and improve customer service experience.

[0144] In summary, the system extracts and summarizes customer consulting needs through the intelligent demand matching module and the online communication and collaboration module, quickly retrieves and integrates relevant information from the database according to customer consulting needs, and matches consultants in related fields according to consulting fields, thereby achieving rapid docking and efficient communication between corporate customers and consultants, reducing time waste in the middle links, and greatly improving the efficiency of consulting services. Through the application of the service progress tracking module and the service quality evaluation module, the entire consulting service process is effectively monitored and managed, ensuring the quality and effect of the service. At the same time, through the analysis and feedback of customer evaluation data combined with the system's own service evaluation analysis, it can be targeted and continuously optimized according to the service preferences of the consulting company. Streamline service processes and methods, improve the overall service level, and the system centrally stores and manages historical data of consulting services, which is convenient for consulting companies to summarize and analyze past cases and accumulate valuable knowledge and experience. These knowledge and experience can be reused and shared in subsequent service projects to improve the overall level of consulting services. According to the comprehensive analysis of the consulting content of the enterprise and focus on related fields, through big data analysis and data collection, the latest information of related projects and fields is pushed to the enterprise client in a targeted manner through information push, and relevant suggestions are provided, so as to help customers keep abreast of the latest developments in related fields and make relevant plans, improve the post-service work, maintain good communication and interaction with customers, and improve customers' service experience.

[0145] It will be appreciated by those skilled in the art that the features described in the various embodiments and / or claims of the present invention may be combined and / or combined in various ways, even if such combinations and / or combinations are not explicitly described in the present invention. In particular, the features described in the various embodiments and / or claims of the present invention may be combined and / or combined in various ways without departing from the spirit and teachings of the present invention. All of these combinations and / or combinations fall within the scope of the present invention.

Claims

1. An Internet-based enterprise consulting service management system, including a user management unit, a consulting service unit, a service evaluation unit, a cloud service unit and a service push unit, characterized in that: The user management unit is used for customer registration, login and security management, and includes a user terminal, a user management module and a login security management module; The consulting service unit provides comprehensive service management for enterprise consulting services by calling cloud service unit data. The consulting service unit includes an intelligent demand matching module, an online communication and collaboration module, and a service progress tracking module; The service evaluation unit is used for comprehensive evaluation and analysis after the enterprise consulting service to improve the service system, and the service evaluation unit includes an analysis and evaluation module and an evaluation feedback module; The cloud service unit is used as the core of the system to store and manage various types of data. The cloud service unit includes a cloud database, a cloud server and a data security protection module; The service push unit comprehensively analyzes the user's consultation content and provides the user with relevant and latest information push. The service push unit includes a demand analysis module and an information push module.

2. The Internet-based enterprise consulting service management system according to claim 1, characterized in that: The user end is the network interaction port between the system and the customer. The user end includes login entries for multiple roles. The user management module is used for classified management of registered and logged-in user information. The user management module summarizes and organizes the information of newly registered users and uploads it to the cloud service unit. It classifies and manages customers according to their value, industry, and scale factors, defines different customer categories, and adds corresponding tags to customers to facilitate targeted customer service and marketing activities.

3. The Internet-based enterprise consulting service management system according to claim 2, characterized in that: The login security management module is used for verifying user login information and managing permissions after login. When working, the login security management module verifies user information by calling and checking user data in the cloud database, sets different data access levels according to the user's role and permissions, and ensures that only authorized users can access sensitive data.

4. The Internet-based enterprise consulting service management system according to claim 1, characterized in that: The intelligent demand matching module extracts and summarizes the customer's consulting needs, quickly retrieves and integrates relevant information from the database according to the customer's consulting needs, and matches consulting consultants in related fields according to the consulting fields, as follows: Demand analysis: When a corporate customer submits a consulting request, the system first performs natural language processing and semantic analysis on the request to extract key information; Consultant matching: Based on the extracted key information, the intelligent matching algorithm is used to call relevant data from the cloud database and select the most suitable consultant from the consulting consultant database, as follows: Using a matching algorithm based on content similarity, first, the enterprise's consulting demand text Q and the consultant's professional field description text P i (i=1,2,…,n,)where n is the number of consultants, vectorized representation, and word vector model is used to calculate Q and P i The cosine similarity Sim(Q,P i ), the formula is: where q j and p ij Represents text Q and P respectively i The word vector value of the jth dimension in the word vector is m, and then all consultants are sorted according to the similarity score, and the consultant with the highest score is selected as the matching result. At the same time, the algorithm based on collaborative filtering is combined to consider the similarity between the company's historical consulting records and other companies to further optimize the matching accuracy. Task assignment: After a successful match, the system automatically assigns the consulting task to the selected consultant and sends a notification to remind the consultant to handle it in a timely manner. At the same time, it generates a unique project number for the corporate customer to facilitate subsequent tracking and management.

5. The Internet-based enterprise consulting service management system according to claim 4, characterized in that: The online communication and collaboration module is used for information assistance during consultation, as follows: Real-time communication: The system has built-in instant messaging function, which supports real-time text, voice and video communication between corporate customers and consultants. No matter where the two parties are, they can communicate conveniently and quickly to solve problems that arise during the consultation process in a timely manner; File sharing: In order to facilitate the sharing of data and information between the two parties, the system provides file upload and download functions. Corporate customers can upload relevant materials so that consultants can better understand the company's situation. Consultants can also share relevant files with customers to ensure timely transmission and sharing of information; Data visualization display: Build an intuitive and easy-to-use data visualization interface, support the display of multiple types of visualization charts, so that users can more intuitively understand the relevant parameter information during the consultation process, and realize the dynamic interaction function of data. Users can deeply understand the detailed information behind the data through operations such as clicking, filtering, and drilling, thereby improving the efficiency and effect of data analysis; Task discussion area: A dedicated task discussion area is set up for each consulting project system, where enterprises and consultants can discuss and exchange ideas on the specific content, progress, and problems encountered in the project. The chat records in the discussion area will be automatically saved for subsequent reference and review.

6. The Internet-based enterprise consulting service management system according to claim 5, characterized in that: The service progress tracking module is used for the overall management of the consulting service progress, as follows: Project plan formulation: After receiving the task, the consultant will formulate a detailed project plan based on the consulting needs and the actual situation of the enterprise and enter the project plan into the system; Real-time progress update: During the project implementation process, consultants need to regularly update the project progress in the system. The system will automatically generate progress reports based on the updated information and present them to enterprises and consultants in the form of visual charts, so that they can intuitively understand the progress of the project; Early warning mechanism: When the project progress deviates or is about to exceed the scheduled time node, the system will automatically issue an early warning notification to remind relevant personnel to take timely measures to make adjustments and improvements.

7. The Internet-based enterprise consulting service management system according to claim 1, characterized in that: The analysis and evaluation module combines the recorded data of the consultation process with the customer's post-evaluation for an overall analysis, as follows: Multi-dimensional evaluation indicators: In order to comprehensively and objectively evaluate the quality of consulting services, the system has established a set of multi-dimensional evaluation indicators, including the feasibility, innovation, practicality of consulting solutions, consultants' professional level, communication skills, service attitude and the final effect of services, as follows: Key indicator evaluation formula: K = w1×P+w2×C+w3×Q; Where: K: comprehensive evaluation value of key indicators; w1, w2, w3: weight coefficients of consulting project progress, process time, and performance evaluation respectively; P: Project consultation progress score; C: process time score; Q: Performance evaluation score; Customer evaluation: After the consulting service is completed, corporate customers can evaluate and score the consultant and the entire service process based on their actual experience, as follows: Determine the customer satisfaction evaluation index set: X = {x1, x2, ..., x r }; Among them, x r represents the rth evaluation index; Collect customer evaluation data matrix: D = (d ij ) s×r ; Where: d ij represents the score of the i-th customer on the j-th indicator, s is the number of evaluated customers, and r is the number of evaluation indicators; Calculate the information entropy H of each indicator j , information entropy H j The uncertainty used to measure each indicator is calculated as follows: Among them, p ij is the probability of the i-th customer scoring the j-th indicator, and the calculation formula is: The constant k is defined as: Calculate the weight w of each indicator j , according to information entropy, we can calculate the weight w of each indicator j : Calculate the comprehensive customer satisfaction rating S, using the calculated weight w j and customer evaluation data matrix D, we can calculate the comprehensive score S of customer satisfaction: After that, fill in detailed evaluation opinions and suggestions based on the comprehensive score S. The system will collect and organize the customer's evaluation data as an important basis for consultant performance evaluation and service improvement; The evaluation feedback module analyzes and mines a large amount of customer evaluation data. The system can identify problems and deficiencies in consulting services, provide consulting companies with targeted improvement suggestions and decision-making support, and improve the consulting system.

8. The Internet-based enterprise consulting service management system according to claim 1, characterized in that: The cloud database is an online data storage structure used for centralized storage of various parameter data of the system. The cloud server is used for analysis, calculation and decision-making of system data. The data security protection module builds a multi-level network security protection system to prevent external network attacks and malware intrusions, and regularly performs network security vulnerability scanning and repair work to promptly discover and resolve security risks in the system, and encrypts data transmission inside and outside the system to ensure the confidentiality and integrity of the data and prevent the data from being stolen or tampered with during transmission.

9. The Internet-based enterprise consulting service management system according to claim 1, characterized in that: The demand analysis module conducts a comprehensive analysis based on the enterprise consulting content to understand the client's enterprise's future operational needs. The information push module collects, summarizes and analyzes relevant data through big data analysis, and pushes the latest information on related projects and fields to the enterprise client in a targeted manner and provides relevant suggestions, helping customers to keep abreast of the latest developments in related fields and make relevant plans.

10. The Internet-based enterprise consulting service management system according to claim 9, characterized in that: The information push module collects relevant data through a knowledge recommendation formula based on association rule mining, as follows: Assume that the item set in the knowledge base is: I = {i1, i2, ..., i m }; The transaction data set is: T = {t1, t2, ..., t n }; Suppose the support of item set X in the transaction data set is: The frequent item set threshold is minSup. If the support of an item set is greater than or equal to the threshold, it is considered a frequent item set. For the association rule X→Y, its confidence is: The threshold of strong association rule is minConf. If the confidence is greater than or equal to the threshold, it is considered to be a strong association and can be used for knowledge recommendation.

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