Dynamic field automatic processing method for intelligent customer service work order

Abstract

The invention discloses an intelligent customer service work order-oriented dynamic field automatic processing method, and belongs to the technical field of customer service work order automatic processing, and the method comprises the following steps: S1, form field configuration; s2, associating a field with a service and an interface; s3, a field association button; s4, configuring a form template; s5, associating the work order scene with the form template; and S6, rendering and interface calling. According to the method, the fields required by the work order scene can be dynamically displayed, the number of the fields of the page is reduced, and the processing efficiency of processing personnel and the processing accuracy of the work order are greatly improved; only the value interface of the field appearing in the work order scene is called, so that the order recording time and unnecessary errors and delays caused by calling the interface are reduced; the configuration mode is simple, the learning cost of the configuration is extremely low, codes do not need to be modified and versions do not need to be released, the stability and expansibility of the system are greatly improved, and non-perceptual online is supported.

Description

Technical Field

[0001] The present invention relates to the technical field of automated processing of customer service work orders, and in particular to an automated processing method for dynamic fields of intelligent customer service work orders. Background Art

[0002] With the development of customer service systems and the detailed differentiation of business scenarios, traditional work order systems can no longer meet the needs of current businesses. In particular, the classification of work order types and the automatic disposal of corresponding field scenarios require the dynamic display of different work order fields in different work order scenarios. This demand aims to improve the efficiency and accuracy of work order processing, thereby providing customers with a better service experience. Therefore, it is necessary to upgrade and optimize the existing work order system to meet the dynamic field display requirements in different scenarios. In order to improve the efficiency and accuracy of customer work order processing.

[0003] In the current business environment, there are a large number of data fields, among which there is a large amount of redundant information. This requires business personnel to filter out the valid data that is really needed from many irrelevant fields when processing data. This way of working is not only inefficient, but also prone to misjudgment during the screening process, causing unnecessary troubles and losses to the business. In the process of recording orders, since the fields share a system, unnecessary fields are also called interfaces, thereby increasing the recording time. This redundant operation not only affects work efficiency, but may also cause unnecessary errors and delays. In actual use, there are often demands for field type modification, field position adjustment, field modification, field value interface modification, etc. In this case, the traditional approach can only be to modify the code and release the version, which brings unstable factors to the operation of the system and increases the operating cost of the system.

[0004] In the traditional work order processing process, it is found that most page fields need to rely on the programming skills of developers and are implemented by manually writing codes. This not only increases development time and cost, but also limits processing efficiency. More importantly, the values ​​of many fields still need to be filled in manually by business processing personnel, lacking automated intelligent processing capabilities. This situation undoubtedly affects the efficiency and accuracy of work order processing and restricts the smooth operation of the entire process.

[0005] The above problems need to be solved urgently. To this end, an automatic processing method for dynamic fields of intelligent customer service work orders is proposed. Summary of the invention

[0006] The technical problem to be solved by the present invention is: how to improve the efficiency and accuracy of work order processing, thereby greatly improving the work quality of work order processing personnel, reducing the operating costs of enterprises and improving customer satisfaction. A method for automatic processing of dynamic fields for intelligent customer service work orders is provided. This method can dynamically display different work order fields according to different business scenarios, and can conveniently adjust the position of the field, the type of the field, and the field value interface without changing the code, thereby realizing non-perceptible online launch.

[0007] The present invention solves the above technical problems through the following technical solutions, and the present invention comprises the following steps:

[0008] S1: Form field configuration

[0009] Define each field in the work order processing system, including the field ID, title, type, and configure the background entity variables corresponding to the field;

[0010] S2: Field association services and interfaces

[0011] Associate the fields with the service, and then specify the interface that the service calls;

[0012] S3: Field association button

[0013] By configuring the JSON array format, add an operation button after setting the field to associate the field with the button;

[0014] S4: Form template configuration

[0015] Add different modules according to business needs. In each module, add fields for form configuration according to actual needs. Use visual drag and drop to adjust the position of the fields, modify the length of the fields, and set required and non-required attributes to configure the form template.

[0016] S5: Work order scenario association form template

[0017] Create a new configuration page to define the association between the work order scenario and the form template, and implement the association between the work order scenario and the form template;

[0018] S6: Rendering and API calls

[0019] When a work order scenario is opened, the associated form template is automatically matched and the module and field information in JSON format is returned. According to the returned module and field information, the corresponding content is rendered on the page. At the same time, after being processed by the Groovy script, the interface output parameters in key-value format are returned to the front end for rendering to form a form page.

[0020] Furthermore, in step S1, the field ID is used to provide a unique identifier for each field; the field title is used to provide a name for each field; and the field type is used to select the corresponding input type according to different business needs, including input box type, drop-down box type, and text field type.

[0021] Furthermore, in the step S1, for the field of the drop-down box type, predefined JSON format data or dictionary encoding of the associated dictionary table is selected as an option.

[0022] Furthermore, in step S2, associating fields with services means defining which fields need to be associated with services, and services support configuring multiple interfaces.

[0023] Furthermore, in step S2, when processing the interface return value, a Groovy script is used to process the data returned by the interface, and data in key-value format is returned through the Groovy script, where the key is consistent with the ID of the field, and the value is the value obtained by the interface corresponding to the field.

[0024] Furthermore, in step S3, when the button is clicked, the corresponding function or method will be triggered.

[0025] Furthermore, the method for automatic processing of dynamic fields of intelligent customer service work orders further includes the following steps:

[0026] S7: Using AI technology to learn from historical work order data

[0027] Collect historical work order data, train an AI model, use the trained AI model to predict new work order data, predict potential problems, and provide suggestions to business processing personnel based on the predicted problem types and the learned solution knowledge.

[0028] Furthermore, in step S7, the historical work order data includes work order content, problem description, and solution.

[0029] Compared with the prior art, the present invention has the following advantages: the method for automatic processing of dynamic fields of intelligent customer service work orders can dynamically display the fields required for the work order scenario, reduce the number of fields on the page, and greatly improve the processing efficiency of processing personnel and the processing accuracy of work orders; it only calls the value-taking interface of the fields appearing in the work order scenario, reducing the order recording time and unnecessary errors and delays caused by calling the interface; the configuration method is simple, the learning cost of the configuration is extremely low, and there is no need to modify the code and release the version, which greatly increases the stability of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 It is a flow chart of the method for automatic processing of dynamic fields of intelligent customer service work orders of the present invention;

[0031] Figure 2 This is a schematic diagram of the work order dynamic field configuration process in the second embodiment of the present invention;

[0032] Figure 3 It is a schematic diagram of the work order dynamic field page rendering process in the second embodiment of the present invention. DETAILED DESCRIPTION

[0033] The following is a detailed description of an embodiment of the present invention. This embodiment is implemented on the premise of the technical solution of the present invention, and a detailed implementation method and a specific operation process are given, but the protection scope of the present invention is not limited to the following embodiment.

[0034] Embodiment 1

[0035] This embodiment provides a technical solution: a method for automatically processing dynamic fields of intelligent customer service work orders, including the following steps:

[0036] Step 1: Configure the work order fields involved into the form field configuration table, storing the field title, type, HTML ID, background entity variables, associated services, and value access interfaces.

[0037] Step 2: Associate form fields in the form template to modify the field's position, width, required field, etc.

[0038] Step 3: Associate the work order scenario with the form template. After opening the work order usage scenario, you can associate the corresponding work order template, display the form fields managed in the template, and call the value interface associated with the form field.

[0039] Step 4: To improve work efficiency and reduce the workload of manual filling, develop an automatic filling script for standardized fields. This script will automatically complete the filling of common fields in a programmatic way, greatly reducing the burden on employees. The automatic filling script can ensure the accuracy and consistency of data, improve work efficiency, and free up human resources to handle more complex tasks, thereby reducing costs and increasing efficiency for the enterprise.

[0040] Step 5: Use AI technology to learn from historical work order data, predict common problems and solutions, and provide intelligent suggestions to business processing personnel.

[0041] Embodiment 2

[0042] like Figure 2 , 3 As shown, this embodiment provides a method for automatically processing dynamic fields of intelligent customer service work orders, including the following main processes:

[0043] 1. Form field configuration

[0044] 1) Define each field in the work order processing system, including field ID, title, type and other attributes; Field ID: provide a unique identifier for each field for subsequent data processing and identification; Field title: provide a clear and easy-to-understand name for the field to facilitate user understanding and operation; Field type: select the appropriate input type, such as text, number, date, etc., to meet different business needs.

[0045] 2) Configure the background entity variables corresponding to the fields, and ensure the consistency and accuracy of the data by configuring the correspondence between the fields and the background data entities.

[0046] 3) For a drop-down box type field, you can select predefined JSON format data or dictionary encoding of an associated dictionary table as an option.

[0047] 2. Field association services and interfaces

[0048] 1) Field association service configuration, defining which fields need to be associated with the service to ensure dynamic acquisition and update of data;

[0049] 2) Service association interface, which specifies the interface called by the service for data acquisition and post-processing;

[0050] 3) Processing of interface return values: Use Groovy scripts to process the data returned by the interface to ensure that the format is unified and meets business requirements. The script returns data in key-value format, where the key is consistent with the field ID and the value is the value obtained by the interface corresponding to the field. This processing method helps improve data processing efficiency and accuracy.

[0051] 3. Field association button

[0052] 1) By configuring the JSON array format, for example: [{"btnName":"btnName","fun":"functionName()"}], add an action button after a specific field. When the button is clicked, the functionName() method is triggered.

[0053] 2) When users click these buttons, the corresponding functions or methods will be triggered, such as data validation, data submission, etc.

[0054] 3) This configuration method provides users with a more convenient operating experience and improves work efficiency.

[0055] 4. Form template configuration

[0056] 1) Add different modules according to business needs, such as customer information module, acceptance information module, etc. Each module corresponds to a specific business area or function.

[0057] 2) In each module, add new form configuration fields according to actual needs to ensure the integrity and accuracy of the data.

[0058] 3) Use visual dragging to adjust the position of the field to make it more in line with the user's usage habits and operation process. At the same time, you can modify the length of the field and set required and non-required attributes to meet the needs of different business scenarios. This configuration method provides great flexibility and convenience, making the customization and adjustment of form templates more efficient and accurate.

[0059] 5. Work order scenario associated template

[0060] 1) Create a new configuration page to define the relationship between the work order scenario and the form template. In this way, you can quickly match different work order scenarios with corresponding templates to improve the efficiency and accuracy of work order processing.

[0061] 6. System rendering and interface calling

[0062] 1) When a work order scenario is opened, the system automatically matches the associated form template and returns the module and field information in JSON format. This real-time matching and return mechanism ensures the accuracy and consistency of the data.

[0063] 2) Based on the returned module and field information, the system renders the corresponding content on the page. This process involves traversing the fields in the form template, summarizing the interfaces involved, and calling these interfaces uniformly in the background. After being processed by the Groovy script, the interface output parameters in key-value format are returned to the front end and rendered, providing users with an intuitive and efficient operation interface. This series of processes helps to improve the system's response speed and user experience.

[0064] 7. Use AI technology to learn historical work order data

[0065] 1) Collect historical work order data, including work order content, problem description, solution and other information. This data is the basis for training AI models. Through in-depth analysis and learning of historical work order data, AI models can gradually grasp the correlation pattern between problems and solutions. As time goes by and data continues to accumulate, the prediction accuracy of AI models will gradually improve.

[0066] 2) Use the trained AI model to predict new work order data and identify potential common problems. Through machine learning and data analysis technology, the AI ​​model can automatically learn and identify problem patterns, providing strong support for business processing personnel. Based on the predicted problem type, the learned solution knowledge is used to provide targeted intelligent suggestions to business processing personnel. These suggestions are based on the analysis and learning results of historical data, which help to improve the speed and accuracy of problem solving. In practical applications, it is crucial to continuously collect new work order data and update the AI ​​model to adapt to business changes and improve prediction accuracy. At the same time, continuously optimizing the accuracy and practicality of intelligent suggestions based on feedback from business processing personnel is also a key link. In this way, the embodiments of the present invention can provide more intelligent support for business processing personnel and help them better deal with various problems and challenges.

[0067] To sum up, the above-mentioned embodiment of the method for automatic processing of dynamic fields of intelligent customer service work orders can dynamically display the fields required for the work order scenario, reduce the number of fields on the page, and greatly improve the processing efficiency of processing personnel and the processing accuracy of work orders; it only calls the value-taking interface of the fields appearing in the work order scenario, reducing the order recording time and unnecessary errors and delays caused by calling the interface; the configuration method is simple, the learning cost of the configuration is extremely low, and there is no need to modify the code and release the version, which greatly increases the stability of the system.

[0068] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present invention.

Claims

1. A method for automatically processing dynamic fields of intelligent customer service work orders, characterized in that: The following steps are involved: S1: Form field configuration Define each field in the work order processing system, including the field ID, title, type, and configure the background entity variables corresponding to the field; S2: Field association services and interfaces Associate the fields with the service, and then specify the interface that the service calls; S3: Field association button By configuring the JSON array format, add an operation button after setting the field to associate the field with the button; S4: Form template configuration Add different modules according to business needs. In each module, add fields for form configuration according to actual needs. Use visual drag and drop to adjust the position of the fields, modify the length of the fields, and set required and non-required attributes to configure the form template. S5: Work order scenario association form template Create a new configuration page to define the association between the work order scenario and the form template, and implement the association between the work order scenario and the form template; S6: Rendering and API calls When a work order scenario is opened, the associated form template is automatically matched and the module and field information in JSON format is returned. According to the returned module and field information, the corresponding content is rendered on the page. At the same time, after being processed by the Groovy script, the interface output parameters in key-value format are returned to the front end for rendering to form a form page.

2. According to claim 1, a method for automatically processing dynamic fields of intelligent customer service work orders is characterized in that: In step S1, the field ID is used to provide a unique identifier for each field; the field title is used to provide a name for each field; the field type is used to select the corresponding input type according to different business requirements, including input box type, drop-down box type, and text field type.

3. According to claim 1, a method for automatically processing dynamic fields of intelligent customer service work orders is characterized in that: In step S1, for a field of the drop-down box type, predefined JSON format data or a dictionary encoding of an associated dictionary table is selected as an option.

4. According to claim 1, a method for automatic processing of dynamic fields of intelligent customer service work orders is characterized in that: In step S2, associating fields with services means defining which fields need to be associated with services, and services support configuring multiple interfaces.

5. According to claim 1, a method for automatic processing of dynamic fields of intelligent customer service work orders is characterized in that: In step S2, when processing the interface return value, a Groovy script is used to process the data returned by the interface, and the data in key-value format is returned through the Groovy script, where the key is consistent with the ID of the field, and the value is the value obtained by the interface corresponding to the field.

6. The method for automatic processing of dynamic fields of intelligent customer service work orders according to claim 1, characterized in that: In step S3, when the button is clicked, the corresponding function or method will be triggered.

7. The method for automatic processing of dynamic fields of intelligent customer service work orders according to claim 1, characterized in that: The method for automatically processing dynamic fields of intelligent customer service work orders also includes the following steps: S7: Using AI technology to learn from historical work order data Collect historical work order data, train an AI model, use the trained AI model to predict new work order data, predict potential problems, and provide suggestions to business processing personnel based on the predicted problem types and the learned solution knowledge.

8. The method for automatic processing of dynamic fields of intelligent customer service work orders according to claim 7, characterized in that: In step S7, the historical work order data includes work order content, problem description, and solution.

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