Risk control management system and management method for intelligent marketing service
Through the risk control management system of smart marketing services, using artificial intelligence models for data analysis and risk warning, the problem of lack of systematicity and standardization in power company service management has been solved, efficient risk control and service optimization have been achieved, and service quality has been improved. and risk management level.
Patent Information
- Application Number
- CN202411394052.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-10-08
- Publication Date
- 2025-01-10
AI Technical Summary
The service management of existing power companies relies on manual operations and simple digital tools, resulting in a lack of systematic and standardized service records and evaluation, lack of targeted training mechanisms, insufficient risk control, and ineffective improvement of service quality and risk management level.
Provide a risk control management system for smart marketing services, including data collection, storage, analysis, risk management and conclusion output modules, data analysis and risk warning are carried out through artificial intelligence models, feedback opinions, measures and reports are generated, and systematic Service optimization and risk control.
Through digital means, systematic management and data analysis are improved, data processing efficiency is eliminated, information silos are eliminated, data accuracy and completeness are ensured, service quality and risk management are significantly improved, and reliable data support and real-time monitoring are provided. Early warning function.
Smart Images
Figure CN119294813A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of power grid business marketing, and in particular to a risk control management system and a management method for smart marketing services. Background Art
[0002] With the rapid development of the power industry, customers' demands and expectations for power services continue to increase, which places higher demands on the service quality and risk management of power companies.
[0003] In the existing technology, the service management of power companies mainly relies on manual operations and simple digital tools. For example, many power companies use Excel spreadsheets to record and evaluate the service status of business handling, rate the service of salesmen, and store related videos, photos and other information in the form of folders.
[0004] However, this approach has many problems and defects, such as the lack of systematicness and standardization of existing service records and evaluation methods, the lack of specificity and effectiveness of existing training mechanisms and service improvement measures, and the obvious deficiencies in existing technologies in service risk management, which make it impossible to effectively improve service quality and risk management level. Summary of the invention
[0005] The present invention relates to a risk control management system and management method for smart marketing services, which can comprehensively improve the service capabilities and overall service quality of sales staff through systematic digital management and data analysis, and achieve efficient risk control and continuous service optimization. The technical solution is as follows: On the one hand, a risk management system for smart marketing services is provided, which includes a data collection module, a data storage module, a data analysis module, a risk management module, and a conclusion output module; The data acquisition module is connected with the data storage module; The data storage module is connected with the data analysis module; The data analysis module is connected to the risk management module and the conclusion output module respectively, and the risk management module is connected to the conclusion analysis module; The data collection module is used to collect service data; The data storage module is used to store service data; The data analysis module is used to analyze service data and obtain risk data and conclusion data; The risk management module is used to obtain and process risk data; The conclusion output module is used to perform at least one conclusion output action based on the conclusion data and the risk data. The conclusion output action includes a feedback generation action, a measure generation action and a summary report generation action.
[0006] In an optional embodiment, the conclusion output module includes a service optimization submodule, an improvement feedback submodule, and an evaluation summary submodule.
[0007] On the other hand, a risk management method for smart marketing services is provided, which is applied to any of the above risk management systems, and includes: The data acquisition module acquires service data; and sends the service data to the data storage module; The data storage module receives the service data, generates and stores structured data based on the service data; and sends the structured data to the data analysis module in response to receiving a data sending request; The data analysis module receives structured data; generates service data analysis results based on the structured data; and sends the data analysis results to the risk management module and the conclusion analysis module; The risk management module receives the data analysis results and generates risk data based on the data analysis results; The conclusion analysis module receives the data analysis results; based on the data analysis results and combined with the conclusion output action, generates conclusion data, which includes feedback data, measure data and report summary data.
[0008] In an optional embodiment, the data acquisition module acquires service data, including: The data collection module obtains the business handling service evaluation data in a tabular form; Generate service data based on business processing service evaluation data.
[0009] In an optional embodiment, the data storage module generates and stores structured data based on the service data, including: The data storage module obtains the audio and video data associated with the service data; Generate structured data based on service data and audio and video data; Store structured data.
[0010] In an optional embodiment, the data analysis module generates service data analysis results based on the structured data, including: The data analysis module inputs the structured analysis data into the service problem generation model, and outputs a service problem generation result corresponding to the structured analysis data. The service problem generation model is an artificial intelligence model. Generate service data analysis results based on the service problem generation results.
[0011] In an optional embodiment, the risk data includes risk warning rule data and risk response rule data; The risk management module generates risk data based on data analysis results, including: The risk management module generates risk data scores based on data analysis results; In response to the risk data score being greater than the warning threshold, generating risk response rule data; In response to the risk data score being less than the warning threshold, risk warning rule data is generated.
[0012] In an optional embodiment, the conclusion output module includes a service optimization submodule; The conclusion analysis module generates conclusion data based on the data analysis results and conclusion output actions, including: In response to the output action being a measure generation action, measure data is generated by the service optimization submodule.
[0013] In an optional embodiment, the conclusion output module includes an improvement feedback submodule; The conclusion analysis module generates conclusion data based on the data analysis results and conclusion output actions, including: In response to the output action being a feedback generating action, feedback data is generated by the improving feedback submodule.
[0014] In an optional embodiment, the conclusion output module includes an evaluation summary submodule; The conclusion analysis module generates conclusion data based on the data analysis results and conclusion output actions, including: In response to the output action being a summary report generation action, conclusion data is generated by the evaluation summary submodule.
[0015] The technical effects of various embodiments of the present invention include at least: Through digital means, the recorded data of business services are systematically sorted and analyzed. Compared with existing manual operations and simple digital tools, this system can efficiently classify, store and analyze data, eliminate information islands, and ensure the accuracy and integrity of data. It not only improves the efficiency of data processing, but also provides reliable data support for subsequent service optimization. BRIEF DESCRIPTION OF THE DRAWINGS
[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.
[0017] Figure 1 A schematic diagram of the structure of a risk control management system for intelligent marketing services provided by an exemplary embodiment of the present invention is shown.
[0018] Figure 2A schematic diagram of the structure of another risk control management system for intelligent marketing services provided by an exemplary embodiment of the present invention is shown.
[0019] Figure 3 A flow chart of a risk management method for intelligent marketing services provided by an exemplary embodiment of the present invention is shown. DETAILED DESCRIPTION
[0020] In order to make the objectives, technical solutions and advantages of the present invention more clear, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.
[0021] Figure 1 A schematic diagram of the structure of a risk control management system for a smart marketing service provided by an exemplary embodiment of the present invention is shown. The system includes a data acquisition module 110, a data storage module 120, a data analysis module 130, a risk management module 140 and a conclusion output module 150.
[0022] The data acquisition module is connected to the data storage module; the data storage module is connected to the data analysis module; the data analysis module is respectively connected to the risk management module and the conclusion output module, and the risk management module is connected to the conclusion analysis module; the data acquisition module is used to collect service data; the data storage module is used to serve service data; the data analysis module is used to analyze service data to obtain risk data and conclusion data; the risk management module is used to obtain and process risk data; the conclusion output module is used to perform at least one conclusion output action based on the conclusion data and risk data, and the conclusion output action includes feedback generation action, measure generation action and summary report generation action.
[0023] In an embodiment of the present invention, the data acquisition module, data storage module, data analysis module, risk management module and conclusion output module can be implemented as a distributed server, or as a combination of a distributed server and a computer device, or as multiple independent computer devices, or as a virtual module in the same server or unified computer device. The present invention does not limit the specific implementation method of each module.
[0024] It should be noted that, in some other embodiments of the present invention, the data acquisition module may be directly connected to the data analysis module, and the data analysis module may be directly connected to the conclusion output module.
[0025] In an alternative embodiment, please refer to Figure 2 Corresponding to actual needs, the conclusion output module 150 also includes a service optimization submodule 151, an improvement feedback submodule 152 and an evaluation summary submodule 153.
[0026] In combination Figure 1 as well as Figure 2 The system diagram shown in Figure 3 A flow chart of a risk management method for intelligent marketing services provided by an exemplary embodiment of the present invention is shown, and the method is applied to Figure 1 or Figure 2 Taking the system shown in FIG. 1 as an example, the method includes: Step 301: The data collection module obtains service data.
[0027] In the embodiment of the present invention, the service data is the data generated in the marketing service process.
[0028] Optionally, the service data is implemented as data in a tabular form. In one example, the data collection module obtains business processing service evaluation data in a tabular form; and generates service data based on the business processing service evaluation data.
[0029] Optionally, the table data shown in the embodiment of the present invention also corresponds to associated audio and video data.
[0030] Step 302: The data collection module sends the service data to the data storage module.
[0031] Step 303: The data storage module receives the service data.
[0032] Step 304: The data storage module generates service data analysis results based on the structured data.
[0033] In an embodiment of the present invention, corresponding to the case where the table data shown in step 301 corresponds to associated audio and video data, the data storage module obtains the audio and video data associated with the service data; generates structured data based on the service data and the audio and video data; and stores the structured data.
[0034] Step 305: The data storage module sends structured data to the data analysis module in response to receiving the data sending request.
[0035] Step 306: The data analysis module receives the structured data.
[0036] Step 307: The data analysis module generates service data analysis results based on the structured data.
[0037] In the embodiment of the present invention, the data analysis module inputs the structured analysis data into the service problem generation model, and outputs a service problem generation result corresponding to the structured analysis data, and the service problem generation model is an artificial intelligence model. That is, the data analysis module is implemented as an artificial intelligence model with intelligent semantic recognition function.
[0038] Step 308: The data analysis module sends the data analysis results to the risk management module and the conclusion analysis module.
[0039] Step 309: The risk management module receives the data analysis result.
[0040] Step 310: The risk management module generates risk data based on the data analysis results.
[0041] In an embodiment of the present invention, part of the content indicating risk in the data analysis results can be represented in numerical form. In this case, in response to the risk data score being greater than the warning threshold, risk response rule data is generated; in response to the risk data score being less than the warning threshold, risk warning rule data is generated.
[0042] Step 311, the conclusion analysis module receives the data analysis result; Step 312: The conclusion analysis module generates conclusion data based on the data analysis results and the conclusion output action.
[0043] In an embodiment of the present invention, the conclusion data includes feedback data, measure data, and report summary data. In the case of the corresponding conclusion data, in some embodiments of the present invention, there is a corresponding relationship between the submodules of the conclusion analysis module and the specific content of the conclusion data. Optionally, the conclusion output module includes a service optimization submodule; the conclusion analysis module generates conclusion data based on the data analysis results and the conclusion output action, including: in response to the output action being a measure generation action, generating measure data through the service optimization submodule; or, The conclusion output module includes an improvement feedback submodule; the conclusion analysis module generates conclusion data based on the data analysis results and in combination with the conclusion output action, including: generating feedback data through the improvement feedback submodule in response to the output action as a feedback opinion generation action; or, The conclusion output module includes an evaluation summary submodule; the conclusion analysis module generates conclusion data based on the data analysis results and in combination with the conclusion output action, including: in response to the output action being a summary report generation action, generating conclusion data through the evaluation summary submodule.
[0044] In summary, the method provided by the embodiment of the present invention systematically organizes and analyzes the recorded data of business handling services through digital means. Compared with the existing manual operation and simple digital tools, the system can efficiently classify, store and analyze data, eliminate information islands, and ensure the accuracy and integrity of data. It not only improves the efficiency of data processing, but also provides reliable data support for subsequent service optimization.
[0045] It should be noted that, in the actual application scenario of the risk control management method for marketing services involved in the embodiment of the present invention, the following steps may be included: Service record data collation: Classify and organize the Excel spreadsheet data of business service evaluation, and digitally store the service information and scoring results in the database. This step includes the classified storage and digital processing of videos, photos and other files to ensure the systematization and standardization of all data.
[0046] Screening of typical service cases: Screen out representative service cases from the sorted data, including excellent services and services that need improvement. Screen out representative service examples by counting and sorting the service scores of salesmen.
[0047] Service process data analysis: Use data analysis tools to conduct in-depth analysis of the selected service cases to extract key service indicators and problem points. This step can include using machine learning algorithms to predict and classify service problems, thereby more accurately discovering problems and improvement points in the service.
[0048] Targeted training development: Develop a detailed training plan based on the analysis results, focusing on training the salesperson’s weaknesses in service. The training plan includes personalized training plans and standardized training courses to ensure the targeting and effectiveness of the training content.
[0049] Training effect evaluation: After the training, the service ability of the salesperson is re-evaluated to ensure the training effect. By comparing and analyzing the service scores of the salesperson before and after the training, the actual effect of the training is evaluated and the evaluation results are fed back to the system.
[0050] Data feedback and optimization: Feedback training effect data to the system to further optimize training programs and service specifications. Establish a dynamically updated training and service specification database to ensure continuous improvement of the system and training content.
[0051] Real-time monitoring and early warning: Real-time monitoring is carried out during the service process, and abnormal situations are warned and recorded. Service quality reports are generated regularly to provide decision-making support for management.
[0052] The method provided by the embodiment of the present invention also has the following advantages: Systematic data management and analysis: The present invention uses digital means to systematically organize and analyze the recorded data of business handling services. Compared with existing manual operations and simple digital tools, the system can efficiently classify, store and analyze data, eliminate information islands, and ensure the accuracy and integrity of data. This not only improves the efficiency of data processing, but also provides reliable data support for subsequent service optimization.
[0053] Typical case screening and application: The present invention screens and analyzes typical cases in the service process, extracts representative service examples, and uses them to formulate targeted training plans. Different from the existing training mechanism, the training content of the present invention is based on actual data and analysis results, which can more specifically solve the problems encountered by sales staff in the service, significantly improving the effectiveness of training and the service level of sales staff.
[0054] Real-time monitoring and early warning mechanism: The present invention integrates real-time monitoring and early warning functions, which can monitor the service status of the salesperson in real time during the service process and issue timely early warnings for abnormal situations. This function effectively improves the ability to manage and control service risks, enabling the company to promptly discover and deal with potential problems, reduce service risks, and ensure customer satisfaction and company reputation.
[0055] Dynamic optimization and feedback mechanism: A dynamic optimization and feedback mechanism is set up to continuously optimize the training program and service specifications through the evaluation of training effects and data feedback. This dynamic optimization mechanism ensures the continuous improvement of the system and training content, helps sales staff continuously improve their service capabilities, and further promotes the improvement of service quality.
[0056] Comprehensive service quality assessment: Through systematic monitoring and data analysis of the service process, the present invention can comprehensively assess the service quality of the salesperson and generate a detailed service quality report. This not only helps the company to fully understand the service performance of the salesperson, but also provides a scientific decision-making basis for the management, effectively improving the overall management level of the company.
[0057] Improve work efficiency and accuracy: Using advanced data analysis tools and algorithms, the efficiency and accuracy of service record collation and analysis are improved, and the time and error rate of manual operations are reduced. Through automated data processing and analysis, sales staff can devote more energy to improving service quality and customer satisfaction.
[0058] Promoting service innovation: It helps to promote service innovation of power companies. Through systematic management and data analysis, it continuously discovers and solves weak links in services, stimulates sales staff's innovation awareness and service enthusiasm, and provides customers with a better service experience.
[0059] The above are only optional embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.
Claims
1. A risk control management system for smart marketing services, characterized in that: The risk management system of the smart marketing service includes a data collection module, a data storage module, a data analysis module, a risk management module and a conclusion output module; The data acquisition module is connected to the data storage module; The data storage module is connected to the data analysis module; The data analysis module is connected to the risk management module and the conclusion output module respectively, and the risk management module is connected to the conclusion analysis module; The data collection module is used to collect service data; The data storage module is used to store the service data; The data analysis module is used to analyze the service data to obtain risk data and conclusion data; The risk management and control module is used to obtain and process the risk data; The conclusion output module is used to perform at least one conclusion output action based on the conclusion data and the risk data, and the conclusion output action includes a feedback generation action, a measure generation action and a summary report generation action.
2. The risk control management system for smart marketing services according to claim 1, characterized in that: The conclusion output module includes a service optimization submodule, an improvement feedback submodule and an evaluation summary submodule.
3. A risk control management method for smart marketing services, characterized in that: The method is applied to the risk management system of the smart marketing service as claimed in claim 1 or 2, and the method comprises: The data acquisition module acquires service data; and sends the service data to the data storage module; The data storage module receives the service data, generates and stores structured data based on the service data; and sends the structured data to the data analysis module in response to receiving a data sending request; The data analysis module receives the structured data; generates service data analysis results based on the structured data; and sends the data analysis results to the risk management module and the conclusion analysis module; The risk management module receives the data analysis result; generates risk data based on the data analysis result; The conclusion analysis module receives the data analysis results; based on the data analysis results and in combination with the conclusion output action, generates conclusion data, wherein the conclusion data includes feedback data, measure data and report summary data.
4. The risk control management method for smart marketing services according to claim 3 is characterized in that: The data acquisition module acquires service data, including: The data collection module acquires the business processing service evaluation data in a tabular form; and generates the service data based on the business processing service evaluation data.
5. The risk control management method for smart marketing services according to claim 4 is characterized in that: The data storage module generates and stores structured data based on the service data, including: The data storage module acquires the audio and video data associated with the service data; generates the structured data based on the service data and the audio and video data; and stores the structured data.
6. The risk control management method for smart marketing services according to claim 3 is characterized in that: The data analysis module generates service data analysis results based on the structured data, including: The data analysis module inputs the structured analysis data into a service problem generation model, and outputs a service problem generation result corresponding to the structured analysis data, wherein the service problem generation model is an artificial intelligence model; The service data analysis result is generated based on the service problem generation result.
7. The risk control management method for smart marketing services according to claim 3, characterized in that; The risk data includes risk warning rule data and risk response rule data; The risk management module generates risk data based on the data analysis result, including: The risk management module generates a risk data score based on the data analysis result; In response to the risk data score being greater than the warning threshold, generating the risk response rule data; In response to the risk data score being less than a warning threshold, the risk warning rule data is generated.
8. The risk control management method for smart marketing services according to claim 3 is characterized in that: The conclusion output module includes a service optimization submodule; The conclusion analysis module generates conclusion data based on the data analysis results and the conclusion output action, including: In response to the output action being a measure generation action, the measure data is generated by the service optimization submodule.
9. The risk control management method for smart marketing services according to claim 3, characterized in that: The conclusion output module includes an improvement feedback submodule; The conclusion analysis module generates conclusion data based on the data analysis results and the conclusion output action, including: In response to the output action being a feedback generating action, the feedback data is generated by the improved feedback submodule.
10. The risk control management method for smart marketing services according to claim 3, characterized in that: The conclusion output module includes an evaluation summary submodule; The conclusion analysis module generates conclusion data based on the data analysis results and the conclusion output action, including: In response to the output action being a summary report generation action, the conclusion data is generated by the evaluation summary submodule.