Method and system for evaluating feedback quality of customer appeal work order

Abstract

The invention provides a method and system for evaluating the feedback quality of a customer appeal work order, and the method comprises the steps: obtaining the feedback information of the customer appeal work order, and carrying out the disassembly of the feedback information according to a preset work order feedback framework, and obtaining the disassembly information; recognizing a sentence pattern filled after each field in the disassembled information, and determining whether the filled content is abnormal or not; and when it is determined that there is an abnormality, outputting a corresponding evaluation result. According to the invention, normalization, pertinence, compliance and disposal results of client appeal work order feedback contents are analyzed, abnormal conditions are reminded, workers are helped to check work order feedback quality before submission, and normalization, pertinence, compliance and satisfaction of work order feedback are improved.

Description

Technical Field

[0001] This invention relates to the field of evaluation technology for the feedback quality of customer request work orders, and in particular to a method and system for evaluating the feedback quality of customer request work orders. Background Technology

[0002] Customer request feedback forms are an important record of the handling results of customer requests and a crucial basis for responding to customers. Due to the diversity and personalization of customer requests, the handling status of customer request forms has always been reported in text form. The workload of customer request feedback is substantial, and issues with feedback quality are inevitable. Direct submission may affect the quality of customer service, even leading to customer complaints and damaging the company's image.

[0003] Customer request feedback involves a large workload and a wide range of content, making it difficult to detect some poorly filled or substandard work orders. Examples of risks include: non-standard work order content (e.g., missing key fields, typos, incoherent sentences, or missing words leading to ambiguity or contradictory meanings); work order feedback failing to address the customer's request; work order feedback containing content that violates policies or regulations; and customer dissatisfaction or disapproval of the processing results.

[0004] In the power industry, the rapid and accurate screening of work order feedback quality is a crucial factor affecting power supply and service. Therefore, how to quickly screen work order feedback quality and alert on abnormal situations is a significant technical challenge. Summary of the Invention

[0005] The purpose of this invention is to propose a method and system for evaluating the feedback quality of customer request work orders, and to solve the technical problem of how to quickly screen the feedback quality of work orders and alert to abnormal situations.

[0006] On the one hand, a method for evaluating the quality of feedback on customer request work orders is provided, including: Obtain feedback information from customer request work orders, and break down the feedback information according to the preset work order feedback framework to obtain the breakdown information; Identify the sentence structure filled in after each field in the disassembled information and determine whether there are any anomalies in the filled content; when an anomaly is determined, output the corresponding evaluation result.

[0007] Preferably, the work order feedback framework includes at least fixed field content corresponding to a preset information type, wherein the information type includes at least basic information items, initial contact items, on-site handling items, and customer feedback items.

[0008] Preferably, determining whether the filled content is abnormal includes at least judging whether the filled content of the work order meets the requirements of the work order feedback framework, and judging whether the content after each field conforms to the specifications, whether there are typos, missing words, and incoherent sentences.

[0009] Preferably, it also includes identifying customer requests recorded in the feedback information and determining whether the work order feedback content responds to the customer requests; When a work order is identified where the feedback content has not responded to the customer's request, a corresponding feedback content non-response prompt message is output.

[0010] Preferably, it also includes identifying whether the feedback information contains any content that violates laws and regulations; When a work order is identified whose feedback content is suspected of violating laws and regulations, the corresponding feedback content suspected of being illegal will be output.

[0011] Preferably, it also includes identifying whether there are corresponding keywords in the customer feedback information; If the corresponding keywords are found, it is determined that the customer is not satisfied with the handling result or has reservations, and there is a risk of continuing to complain or escalating the complaint. Once this type of work order is identified, a corresponding special attention reminder message will be output.

[0012] Preferably, the corresponding keywords include at least one or more of the following: not accepting, disagreeing, not evaluating, and having objections.

[0013] On the other hand, a system for evaluating the feedback quality of customer request work orders is also provided, for implementing the aforementioned method for evaluating the feedback quality of customer request work orders, including, The information acquisition module is used to acquire feedback information from customer request work orders and to break down the feedback information according to the preset work order feedback framework to obtain the breakdown information. The anomaly detection module is used to identify the sentence structure filled in after each field in the decomposed information and determine whether there are any anomalies in the filled content; when an anomaly is determined, the corresponding evaluation result is output.

[0014] In summary, implementing the embodiments of the present invention has the following beneficial effects: This invention provides a method and system for evaluating the quality of customer request work orders. It utilizes artificial intelligence technology to read and understand text, analyzes large amounts of text content, and filters out work orders with non-standard feedback. The system compares the feedback content with the customer's request to determine if the feedback addresses the customer's needs and whether it is irrelevant. It also compares the text with relevant laws and regulations to determine if the feedback violates any laws or regulations. Finally, it assesses customer satisfaction with the handling results and filters out work orders with high complaint risk due to customer dissatisfaction. This invention provides a method for analyzing the standardization, relevance, compliance, and handling results of customer request work order feedback, and alerts staff to anomalies, helping them check the quality of work order feedback before submission and improving the standardization, relevance, compliance, and satisfaction of work order feedback. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, obtaining other drawings based on these drawings without creative effort still falls within the scope of the present invention.

[0016] Figure 1 This is a schematic diagram of the main process of a method for evaluating the feedback quality of customer request work orders in an embodiment of the present invention.

[0017] Figure 2 This is a logical diagram illustrating a method for evaluating the feedback quality of customer request work orders in an embodiment of the present invention. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings.

[0019] like Figure 1 and Figure 2 The diagram shown is an embodiment of a method for evaluating the feedback quality of customer request work orders provided by the present invention. In this embodiment, the method includes the following steps: Step S1: Obtain feedback information from customer request work orders, and break down the feedback information according to a preset work order feedback framework to obtain broken down information; the work order feedback framework includes at least fixed field content corresponding to preset information types, wherein the information types include at least basic information items, initial contact items, on-site handling items, and customer opinions items; Step S2: Identify the sentence structure filled in after each field in the decomposed information and determine whether there are any abnormalities in the filled content; when an abnormality is determined, output the corresponding evaluation result.

[0020] In a specific embodiment, step S1 involves disassembling the work order feedback framework, such as including fixed fields that require basic information, initial contact, on-site handling, and customer feedback; analyzing the sentence structure to be filled in after each field, such as after the basic information field, it is necessary to fill in "bound account number *** (a fixed number of digits with a certain pattern)", "the customer is the owner / tenant", "the customer is powered by **station** line** transformer", etc.

[0021] In one specific embodiment, determining whether the filled-in content is abnormal includes at least judging whether the filled-in content of the work order meets the requirements of the work order feedback framework, and judging whether the content after each field conforms to the specifications, and whether there are typos, omissions, or incoherent sentences. That is, artificial intelligence technology is used to analyze whether the filled-in content of the work order meets the framework requirements and whether the content after each field conforms to the specifications, and whether there are typos, omissions, or incoherent sentences; when the work order is submitted, for work orders that do not conform to the specifications, a message "Work order feedback content is not standardized" is displayed.

[0022] In this embodiment, customer requests recorded in the feedback information are identified, and it is determined whether the work order feedback content addresses the customer requests. When a work order is identified where the feedback content does not address the customer requests, a corresponding "Feedback content does not address customer requests" message is output. This involves screening for unresponsive customer requests; analyzing customer requests recorded in the work order; using artificial intelligence technology to analyze whether the work order feedback content addresses the customer requests; and displaying a message "Feedback content does not address customer requests" for work orders submitted without addressing the customer requests.

[0023] This also includes identifying whether feedback information contains content that violates laws and regulations; when a work order is identified as potentially violating laws and regulations, corresponding information indicating suspected violation is output. This involves screening feedback content for policy and regulatory violations; using artificial intelligence technology to analyze work order feedback content to determine if it contains any content that violates laws and regulations; and displaying a message indicating "Feedback content is suspected of violating laws and regulations" when a work order is submitted.

[0024] This also includes identifying whether corresponding keywords exist in the customer feedback information; if corresponding keywords are found, it is determined that the customer is dissatisfied with the handling result or has reservations, and there is a risk of further complaints or escalation of complaints; after identifying such work orders, corresponding special attention reminder information is output. This addresses understandable situations where customers are dissatisfied with or do not accept the handling result, indicating a risk of complaints; after analyzing the customer opinion fields in the work order feedback content, if fields such as "unacceptable," "disagree," "no evaluation," or "objections exist," it indicates that the customer is dissatisfied with the handling result or has reservations, and there is a risk of further complaints or escalation of complaints, requiring special attention; when submitting such work orders, a message should be displayed stating "The customer is dissatisfied with the handling result or has reservations."

[0025] In a specific embodiment, Figure 2 The flowchart shown in this example illustrates the abnormal notification for customer request work order feedback.

[0026] Step S00: After completing the work order, click "Submit"; Step S01: Determine whether the work order feedback content is standardized; Step S10: If S01 determines "No", then output the "Feedback content is not standardized" field. Step S02: If S01 determines "yes", then continue to determine whether the work order feedback content responds to the customer's request. In step S20, if S02 determines "No", then output the "Unresponsive customer request" field. Step S03: If S02 determines "yes", then continue to determine whether the work order content violates laws and regulations; Step S30: If S03 determines "yes", then output the "suspected violation of laws and regulations" field; Step S04: If S03 determines "no", then continue to determine whether the customer accepts the processing result; In step S40, if the judgment in S04 is "no", then output "The customer is not satisfied with or does not accept the processing result"; Step S50: For work orders with output fields in steps S10, S20, S30, and S40 above, manually verify the work order feedback status. Step S60: After manual verification, determine whether the work order needs to be modified. Step S70: If S60 determines "yes", then modify the work order feedback content, resubmit after modification, and enter step S00 loop. If steps S05 and S04 are judged as "yes" and S60 is judged as "no", then the work order is successfully submitted.

[0027] In embodiments of the present invention, a feedback quality assessment system for customer request work orders is also provided, for implementing the aforementioned feedback quality assessment method for customer request work orders, including, The information acquisition module is used to acquire feedback information from customer request work orders and to break down the feedback information according to the preset work order feedback framework to obtain the breakdown information. The anomaly detection module is used to identify the sentence structure filled in after each field in the decomposed information and determine whether there are any anomalies in the filled content; when an anomaly is determined, the corresponding evaluation result is output.

[0028] It should be noted that the system described in the above embodiments corresponds to the method described in the above embodiments. Therefore, the parts of the system described in the above embodiments that are not described in detail can be obtained by referring to the content of the method described in the above embodiments, and will not be repeated here.

[0029] In summary, implementing the embodiments of the present invention has the following beneficial effects: This invention provides a method and system for evaluating the quality of customer request work orders. It utilizes artificial intelligence technology to read and understand text, analyzes large amounts of text content, and filters out work orders with non-standard feedback. The system compares the feedback content with the customer's request to determine if the feedback addresses the customer's needs and whether it is irrelevant. It also compares the text with relevant laws and regulations to determine if the feedback violates any laws or regulations. Finally, it assesses customer satisfaction with the handling results and filters out work orders with high complaint risk due to customer dissatisfaction. This invention provides a method for analyzing the standardization, relevance, compliance, and handling results of customer request work order feedback, and alerts staff to anomalies, helping them check the quality of work order feedback before submission and improving the standardization, relevance, compliance, and satisfaction of work order feedback.

[0030] The above description discloses only preferred embodiments of the present invention and should not be construed as limiting the scope of the present invention. Therefore, equivalent variations made in accordance with the claims of the present invention are still within the scope of the present invention.

Claims

1. A method for evaluating the feedback quality of customer request work orders, characterized in that, include: Obtain feedback information from customer request work orders, and break down the feedback information according to the preset work order feedback framework to obtain the breakdown information; Identify the sentence structure filled in after each field in the disassembled information, and determine whether there are any anomalies in the filled content; When an anomaly is identified, the corresponding evaluation result is output.

2. The method as described in claim 1, characterized in that, The work order feedback framework includes at least fixed field content corresponding to preset information types, wherein the information types include at least basic information items, initial contact items, on-site handling items, and customer feedback items.

3. The method as described in claim 2, characterized in that, The process of determining whether the filled content is abnormal includes at least judging whether the filled content of the work order meets the requirements of the work order feedback framework, and judging whether the content after each field conforms to the specifications, whether there are typos, missing words, and incoherent sentences.

4. The method as described in claim 3, characterized in that, It also includes identifying customer requests recorded in the feedback information and determining whether the work order feedback content addresses the customer requests; When a work order is identified where the feedback content has not responded to the customer's request, a corresponding feedback content non-response prompt message is output.

5. The method as described in claim 4, characterized in that, This also includes identifying whether the feedback information contains any content that violates laws and regulations; When a work order is identified whose feedback content is suspected of violating laws and regulations, the corresponding feedback content suspected of being illegal will be output.

6. The method as described in claim 5, characterized in that, This also includes identifying whether there are corresponding keywords in the customer feedback information; If the corresponding keywords are found, it is determined that the customer is not satisfied with the handling result or has reservations, and there is a risk of continuing to complain or escalating the complaint; Once this type of work order is identified, a corresponding special attention reminder message will be output.

7. The method as described in claim 6, characterized in that, The corresponding keywords include at least one or more of the following: not accepting, disagreeing, not commenting, and having objections.

8. A system for evaluating the feedback quality of customer request work orders, used to implement the method as described in any one of claims 1-7, characterized in that, include, The information acquisition module is used to acquire feedback information from customer request work orders and to break down the feedback information according to the preset work order feedback framework to obtain the breakdown information. The anomaly detection module is used to identify the sentence structure filled in after each field in the decomposed information and to determine whether there are any anomalies in the filled content; When an anomaly is identified, the corresponding evaluation result is output.

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