Complaint work order processing method and device, equipment and medium
By analyzing complaint data to generate and accurately distribute work orders, the problem of inaccurate work order distribution has been solved, improving processing quality and efficiency and meeting regulatory requirements.
Patent Information
- Application Number
- CN202510887976.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-06-27
- Publication Date
- 2025-11-07
AI Technical Summary
The current technology for dispatching complaint work orders is not accurate enough, resulting in low quality and efficiency in complaint handling. It is unable to address the needs of users who file complaints that go beyond the appropriate level in a timely manner, and it cannot meet the regulatory requirements of higher-level regulatory agencies.
By acquiring complaint data, analyzing attribute information, generating work order content, determining candidate handlers based on work order type, and selecting target handlers based on the current task intensity of candidate handlers, the accurate dispatch of complaint work orders can be achieved.
This improved the accuracy of complaint work order dispatch, enhanced the quality and efficiency of complaint handling, and met the regulatory requirements of higher-level regulatory agencies.
Smart Images
Figure CN120911809A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The present application relates to the technical field of Internet, in particular to a complaint work order processing method, device, equipment and medium. BACKGROUND
[0002] At present, users can complain about the services provided by operators, most users complain through the internal channels of operators, and some users directly bypass the level to the regulatory department of the operator, which leads to a series of subsequent examination index requirements, resulting in the complication of the entire complaint process.
[0003] In the prior art, a complaint work order is usually generated directly according to the complaint content, and then the complaint work order is assigned to a processing personnel for processing, but this way is not accurate enough for the assignment of the complaint work order, and cannot process the demand of the bypass-level complaint user in the first time, and at the same time meet the regulatory requirements of the superior regulatory agency, thereby resulting in low processing quality and processing efficiency of the complaint. SUMMARY
[0004] In view of the above problems, a complaint work order processing method, device, equipment and medium are provided to overcome the above problems or at least partially solve the above problems, comprising:
[0005] A complaint work order processing method, the method comprising:
[0006] Obtaining complaint data and analyzing the complaint data to obtain attribute information;
[0007] Generating work order content according to the attribute information, and creating a complaint work order according to the work order content; wherein the attribute information includes complaint urgency, and the work order content includes work order type, and the work order type corresponds to the complaint urgency;
[0008] Determining a candidate processing personnel object according to the work order type;
[0009] Determining the current task intensity of the candidate processing personnel object, and determining a target processing personnel object from the candidate processing personnel object according to the current task intensity;
[0010] Assigning the complaint work order to the target processing personnel object.
[0011] Optionally, the complaint data is analyzed to obtain attribute information, comprising:
[0012] Determining product value, user label and user level according to the complaint data;
[0013] Determining importance according to the product value, user label and user level;
[0014] determine the complaint urgency level according to the importance and the user historical traffic usage.
[0015] Optionally, the attribute information further comprises a region where the user is located, and the candidate handler object is determined according to the work order type, comprising:
[0016] determine the handler object in the corresponding region according to the region where the user is located;
[0017] determine the capability label of the handler object in the corresponding region; wherein the capability label is used to indicate the work order type that the handler object has processing capability;
[0018] match the capability label with the work order type, and determine the candidate handler object from the handler object in the corresponding region according to the matching result.
[0019] Optionally, the current task intensity of the candidate handler object is determined, comprising:
[0020] determine the unprocessed completed work order of each candidate handler object, and determine the timeliness requirement coefficient, product value coefficient and processed time length coefficient of each unprocessed completed work order;
[0021] determine the current task intensity of each unprocessed completed work order according to the timeliness requirement coefficient, product value coefficient and processed time length coefficient;
[0022] determine the current task intensity of the candidate handler object according to the current task intensity of all unprocessed completed work orders of each candidate handler object.
[0023] Optionally, the current task intensity of each unprocessed completed work order is determined according to the timeliness requirement coefficient, product value coefficient and processed time length coefficient, comprising:
[0024] determine the weight of the timeliness requirement coefficient, product value coefficient and processed time length coefficient, and perform weighted summation on the timeliness requirement coefficient, product value coefficient and processed time length coefficient by using the corresponding weight to obtain the current task intensity of each unprocessed completed work order.
[0025] Optionally, further comprising:
[0026] determine the time difference between the current time and the order issuing time for each unprocessed completed work order;
[0027] perform early warning processing on the unprocessed completed work order according to the time difference.
[0028] Optionally, further comprising:
[0029] According to the processing scheme of the processed completed work order, experience knowledge data is generated and stored.
[0030] A processing device of a complaint work order, the device is used for:
[0031] Obtaining complaint data, and analyzing the complaint data to obtain attribute information;
[0032] Generating work order content according to the attribute information, and creating a complaint work order according to the work order content; wherein the attribute information includes complaint urgency, and the work order content includes work order type, and the work order type corresponds to the complaint urgency;
[0033] Determining a candidate processing personnel object according to the work order type;
[0034] Determining the current task intensity of the candidate processing personnel object, and determining a target processing personnel object from the candidate processing personnel object according to the current task intensity;
[0035] Assigning the complaint work order to the target processing personnel object.
[0036] An electronic device, comprising a processor, a memory, and a computer program stored on the memory and capable of running on the processor, the computer program being implemented when executed by the processor to realize the method described above.
[0037] A computer readable storage medium, the computer readable storage medium stores a computer program, the computer program is executed by a processor to realize the method described above.
[0038] The embodiments of the present application have the following advantages:
[0039] In the embodiments of the present application, by obtaining complaint data, and analyzing the complaint data to obtain attribute information, generating work order content according to the attribute information, and creating a complaint work order according to the work order content; wherein the attribute information includes complaint urgency, and the work order content includes work order type, and the work order type corresponds to the complaint urgency; determining a candidate processing personnel object according to the work order type; determining the current task intensity of the candidate processing personnel object, and determining a target processing personnel object from the candidate processing personnel object according to the current task intensity; assigning the complaint work order to the target processing personnel object, the optimization of the complaint work order assignment is realized, the accuracy of the complaint work order assignment is improved, and the processing quality and efficiency of the complaint are improved. BRIEF DESCRIPTION OF DRAWINGS
[0040] In order to more clearly illustrate the technical solutions of the present application, the drawings needed to be used in the description of the present application will be briefly introduced as follows. Obviously, the drawings in the following description are only some embodiments of the present application, and all other drawings obtained by those skilled in the art without creative labor on the basis of these drawings also belong to the protection scope of the present application.
[0041] Figure 1a is a schematic diagram of a system architecture provided by some embodiments of the present application;
[0042] Figure 1b is a schematic diagram of a module operation relationship provided by some embodiments of the present application;
[0043] Figure 2 is a step flow chart of a processing method of a complaint work order provided by some embodiments of the present application;
[0044] Figure 3a is a schematic diagram of a data import analysis module provided by some embodiments of the present application;
[0045] Figure 3b is a schematic diagram of a cross-level work order creation module provided by some embodiments of the present application;
[0046] Figure 3c is a schematic diagram of a work order monitoring module provided by some embodiments of the present application;
[0047] Figure 4 is a step flow chart of another processing method of a complaint work order provided by some embodiments of the present application. DETAILED DESCRIPTION
[0048] In order to make the above-mentioned purposes, features and advantages of the present application more apparent and easy to understand, the present application will be further described in detail below with reference to the drawings and specific embodiments. Obviously, the described embodiments are some embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor also belong to the protection scope of the present application.
[0049] For cross-level complaint work orders, if there is a more accurate assignment and more effective processing flow, the needs of cross-level complaint customers can be processed in the first time, and the regulatory requirements of the superior regulatory agencies can be met. On the one hand, enterprises need to identify the complaint content as soon as possible when facing complaint work orders, and assign work orders according to the emergency attribute of the work order and the situation of the corresponding city processing personnel. On the other hand, effective work order monitoring means are also needed to upgrade the work order processing level and prioritize the processing of related cross-level complaints.
[0050] In the embodiment of the present application, by identifying the single overstep complaint content, combining the characteristics of the user, such as city, package value, traffic condition, etc., there will be an emergency degree determination of the work order, such as high and low value users, user traffic, star level, etc. User characteristics determine classification, default three categories: urgent, medium and ordinary, and the characteristics are transmitted to the work order creation module to generate corresponding work orders.
[0051] After the overstep work order is generated, the dispatch personnel is selected in the city dimension, combined with the existing work order number of the processing personnel, the progress of the received work order, the processing level, etc. The most suitable work order processing object is matched to perform the work order dispatch process. The generated work order is automatically dispatched to the processing post personnel of the corresponding city, providing an effective and accurate work order dispatch method.
[0052] In the embodiment of the present application, a work order whole process monitoring method is provided, including work order processing process monitoring, timeout warning, and processing scheme integration after work order processing is completed. The dispatched work order is put into the dispatch work order pool, and the whole life cycle of the work order is controlled.
[0053] Specifically, different levels of alarms are performed by the difference between the work order dispatch time and the current time, reminding different levels of management personnel to process and supervise the work order. For example, if an overstep work order is not processed within the specified time, a timeout warning reminder of the next level is performed. Secondly, the processing scheme of the completed work order is combined to analyze the related conclusions and add them to the overstep work order processing knowledge base to form historical experience knowledge, providing relevant reference for subsequent other overstep complaint work orders.
[0054] For example Figure 1a , Figure 1b , mainly includes: data import analysis module, overstep work order creation module, work order processing module, work order monitoring module. The overall scheme flow is:
[0055] The complaint data source mainly has two ways, one is to provide data offline, and the overstep complaint management personnel imports the received overstep complaint list, and the other is to directly transmit to the overstep complaint processing system through the API interface. Then, the system analyzes the complaint content, combines the historical complaint solution data, and transmits the data downward to the work order creation module to generate corresponding work order content. Then, the work order is dispatched to different front-end processing personnel by combining the work order type, the city of the work order user, and the current responsible work order of the corresponding city overstep complaint processing personnel. At the same time, the work order monitoring module monitors the work order in the work order pool, upgrades the overtime work order, archives the processed work order, and summarizes and combines the related processing scheme for subsequent similar overstep complaint problem processing.
[0056] Specifically, the content of the user's over-level complaint is combined with natural language processing technology for data recognition and analysis, and two types of data are combined: one is the user's own relevant feature data, and the other is the historical solution data of the user's complaint content. The above data is output to the over-level work order generation model to create a related complaint type work order. After generating the over-level complaint work order, combined with the work order distribution method, first, according to the urgency of the work order, whether the processing personnel has the processing label is considered when selecting the processing personnel. For a city with multiple personnel with the same emergency processing capacity, the selection method will combine the task intensity result of the complaint work order processing personnel of the city node at the current time point, and select the person in charge with the smallest task intensity to distribute the order, and he will process the corresponding subsequent complaint content.
[0057] The application will be further described below:
[0058] Referring to Figure 2 , a step flowchart of a complaint work order processing method provided by some embodiments of the application is shown, which can specifically include the following steps:
[0059] Step 201, obtaining complaint data and analyzing the complaint data to obtain attribute information.
[0060] In actual application, complaint data sources are various, which can be complaint information submitted by users directly through online channels, or user complaint content recorded and sorted by customer service personnel. These complaint data contain user's basic information, complaint specific content, complaint time and other key elements.
[0061] The process of analyzing the complaint data is mainly to use natural language processing, data mining and other technical means to extract useful information in the complaint data, i.e. attribute information. These attribute information includes but is not limited to complaint urgency, user's region, product value, user label, user level, etc., which plays a crucial role in subsequent work order creation and distribution.
[0062] For example Figure 3a , the data import analysis module includes a data import module and a complaint content analysis module.
[0063] The data import module provides offline data import function and also supports API interface data transmission capability. In actual use, most of the over-level complaint data is offline provided by the superior supervisory agency, and then the subsequent complaint processing arrangement is made by the provincial management personnel of the enterprise. By setting the API interface, the transmission capability of the API can provide the superior supervisory agency with over-level complaint digital management capability.
[0064] The complaint content analysis module mainly performs natural language processing on the text content of the user's over-level complaint, identifies the involved content and related complaint categories, provides relevant data support for subsequent work order generation, and queries the processing scheme of similar problems from the historical experience knowledge base to provide certain reference for the relevant processing personnel. Specifically, it includes text splitting and data classification, identifying the involved content and related complaint categories, and extracting user data, including but not limited to city, package value, package agreement, package validity period, etc. Finally, the attribute information of the over-level complaint work order user is provided, including but not limited to: user over-level complaint content classification, complaint urgency, user city, historical complaint handling method and other data.
[0065] In some embodiments of the present application, the complaint data is analyzed to obtain attribute information, including: determining the product value, user label and user level according to the complaint data; determining the importance according to the product value, user label and user level; and determining the complaint urgency according to the importance and historical traffic usage of the user.
[0066] In actual application, the determination of complaint urgency is crucial for the priority handling of work orders. By comprehensively considering the product value, user label, user level and historical traffic usage of the user, the urgency of the complaint can be more accurately evaluated. For example, complaints submitted by high-value users or users with high historical traffic usage may be considered as urgent complaints and need to be handled in priority. This determination method helps to ensure that important user complaints are responded to in a timely manner and improves user satisfaction.
[0067] In some examples, the urgency of over-level complaints is classified into three categories: urgent, medium and ordinary, which can be classified using the characteristics of the sign function, as follows:
[0068] 1. The package value (i.e. product value) P of the over-level complaint user, P = sign (sign (p-m) + 1), where m is a set package boundary value. For example, m = 129, if the user package p = 169, then P = 1; if the user package p = 129, then P = 1; if the user package p = 99, then p = 0.
[0069] 2. Important customer label (i.e. user label) L, L = {0, 1}, the value of this label comes from the user system.
[0070] 3. Star level (i.e. user level) S, S = {0, 1}, calculated by the sign function, same as the package value calculation principle, where n is the star level boundary value.
[0071] 4. Near 1 month traffic usage (i.e. historical traffic usage) Y, Y = {0, 1}, calculated by sign function, same as the principle of calculating the value of the package, where o is the traffic demarcation value.
[0072] The above parameters, demarcation values m, n, and o, are dynamically adjusted by the business system in actual use according to different time periods and different customer service cycles.
[0073] In some examples, the emergency level determination method is as follows:
[0074] Importance C = sum (P + L + S)
[0075]
[0076] Step 202, generating a work order content according to the attribute information, and creating a complaint work order according to the work order content; wherein the attribute information includes complaint emergency level, and the work order content includes work order type, and the work order type corresponds to the complaint emergency level.
[0077] After obtaining the attribute information, the specific work order content can be generated according to these attribute information, and then the complaint work order is created. Among them, the work order content contains the work order type, which is determined according to the emergency level of the complaint, to ensure that the emergency complaint can be responded and processed faster. For example, if the complaint is determined to be an emergency category, the generated work order type will also be an emergency work order, which will be marked as high priority in the system, prompting the processing personnel to handle as soon as possible.
[0078] As Figure 3b The bypass work order creation module mainly includes a work order generation model and a strategy distribution model.
[0079] The work order generation model receives the relevant analysis and disassembly results of each complaint data from the data import analysis module, combines historical problem handling schemes, and generates a handling work order for this complaint data for subsequent processing personnel to use in the whole process.
[0080] The strategy distribution model mainly combines the emergency level of the bypass complaint work order, the city where the user is located, the post of the city complaint handling center, and the handling level of the complaint handling personnel to perform different assignment methods. One is equal in quantity, and the other is different in level of handling personnel, and the level of work order assigned is different, such as general work order for primary handling personnel and company customers, important customers, etc. for senior handling personnel.
[0081] Step 203, determining a candidate handling personnel object according to the work order type.
[0082] In practical applications, different types of work orders may require processing personnel with different professional skills and experience. Therefore, after determining the type of work order, the system can filter personnel from the preset personnel database that meet the processing requirements of the type of work order as candidate processing personnel objects. In some examples, these candidate processing personnel objects can be filtered according to professional skills, experience in processing similar work orders, current workload, and other factors to ensure that the work order can be processed efficiently and accurately.
[0083] In some embodiments of the present application, the attribute information further includes a region where the user is located, and determining the candidate processing personnel object according to the type of work order includes:
[0084] According to the region where the user is located, determining the processing personnel object of the corresponding region; determining the ability tag of the processing personnel object of the corresponding region; wherein the ability tag is used to indicate the type of work order that the processing personnel object has processing ability; matching the ability tag and the type of work order, and determining the candidate processing personnel object from the processing personnel object of the corresponding region according to the matching result.
[0085] In practical applications, each processing personnel will have an ability tag representing whether he / she can process urgent, medium, or ordinary type of work orders. When selecting the object, for urgent type of work order, the selected object should have the ability tag of processing urgent type of work order; for medium type of work order, the selection method is the same, and for ordinary type of work order, the subsequent processing personnel selection process is directly performed, and the subsequent dispatching process is performed.
[0086] Step 204, determining the current task intensity of the candidate processing personnel object, and determining the target processing personnel object from the candidate processing personnel object according to the current task intensity.
[0087] In related technologies, for the dispatching of work orders, relevant work order data can be generated directly in combination with the complaint content and other work order details, and then the dispatching action is performed through the work order data such as work order category, work order attribute, and work order level. Among them, the selection of the dispatching object mainly has two ways: one is to determine the processing personnel object selected when the work order is generated (i.e., directly specifying the processing personnel of the work order when creating the work order), and the other is to select the processing personnel object by the dispatching system according to the work order data.
[0088] However, in the dispatching process of related technologies, the dispatching is based on the work order attribute and other work order data, such as the city where the work order belongs, which ignores the personnel order receiving situation of processing work orders, which may lead to the situation that a certain processing personnel receives a large number of work orders, and the dispatching of some work orders is accumulated. However, in the process of handling the cross-level complaint work order, the priority of most work orders is high, and it needs to be processed as soon as possible. The processing efficiency of the order receiving personnel or the order closing channel often determines whether the cross-level complaint work order can be processed on time.
[0089] In the embodiments of the present application, on the basis of combining work order data, the order receiving processing team personnel is combined in real time, the order distribution strategy is dynamically adjusted, the defect problem of inaccurate work order distribution is solved, and the distribution of step-by-step complaint work orders is quickly, effectively and accurately distributed to different regional complaint processing positions.
[0090] In actual application, the work load of the processing personnel is also an important factor affecting the efficiency and quality of work order processing. Therefore, after determining the candidate processing personnel object, the system needs to further evaluate the current task intensity of these candidate personnel, i.e. the number and difficulty of the work orders currently being processed, to ensure that the selected target processing personnel object has enough time and energy to process new work orders.
[0091] After obtaining the current task intensity, the system determines the target processing personnel object from the candidate processing personnel object according to the calculated current task intensity value. Specifically, the system can select a processing personnel with a low current task intensity value and the ability to process this type of work order as the target processing personnel object to ensure that the work order can be processed in a timely and effective manner.
[0092] In some embodiments of the present application, determining the current task intensity of the candidate processing personnel object includes: determining unprocessed completed work orders of each candidate processing personnel object, and determining a time limit requirement coefficient, a product value coefficient and a processed time length coefficient of each unprocessed completed work order; determining the current task intensity of each unprocessed completed work order according to the time limit requirement coefficient, the product value coefficient and the processed time length coefficient; and determining the current task intensity of the candidate processing personnel object according to the current task intensity of all unprocessed completed work orders of each candidate processing personnel object.
[0093] In actual application, the time limit requirement coefficient of each unprocessed completed work order can be determined according to the urgency of the work order and the preset time limit standard, the higher the urgency, the greater the time limit requirement coefficient; the product value coefficient can be determined according to the product value involved in the work order, the higher the product value, the greater the product value coefficient; and the processed time length coefficient can be determined according to the length of time the work order has been processed, the longer the processed time length, the smaller the processed time length coefficient.
[0094] By comprehensively considering these three coefficients, the current task intensity of each unprocessed completed work order can be more accurately evaluated, and the work order can be more reasonably distributed. After determining the target processing personnel object, the system distributes the work order to the processing personnel, who performs subsequent processing work. At the same time, the system also records the processing progress and processing result of the work order, so as to perform subsequent analysis and evaluation.
[0095] In some embodiments of the application, the current task intensity of each unprocessed completed work order is determined according to the time limit requirement coefficient, the product value coefficient and the processed time length coefficient, comprising: determining the weights of the time limit requirement coefficient, the product value coefficient and the processed time length coefficient, and performing weighted summation on the time limit requirement coefficient, the product value coefficient and the processed time length coefficient by using the corresponding weights to obtain the current task intensity of each unprocessed completed work order.
[0096] In some examples, how to select the complaint processing personnel of the city and whether to assign work orders to the complaint processing personnel depend on the current task intensity S. The distribution of each new work order is performed by comparing the task intensity S of the processing personnel of the city node where the user is located, and a worker with the smallest task intensity S is selected for work order distribution. The calculation process is simplified and summarized as the following formula:
[0097]
[0098] 1. S is the intensity of the work order already responsible by the employee. It is assumed that there are currently n work orders;
[0099] 2. T is the time limit requirement coefficient of the work order, which is in units of 24 hours. If the current time limit requirement is 24 hours, then T = 1; if the current time limit requirement is 48 hours, then T = 0.5; if the current time limit requirement is 8 hours, then T = 3. The smaller the time limit requirement, the larger T is, and the larger the intensity of the tasks already responsible by the employee is.
[0100] 3. P is the package value coefficient of the work order, which is generally based on 58 units. If the current package is 58, then P = 1; if the current package is 38, then P = 38 / 58; if the current package is 128, then P = 128 / 58. The higher the package value, the larger P is, and the larger the intensity of the tasks already responsible by the employee is.
[0101] 4. D is the processed time length coefficient of the work order, which is calculated in the same way as the time limit requirement coefficient, in units of 24 hours. If the current work order distribution time has passed 24 hours, then D = 1; if the current work order distribution time has passed 48 hours, then D = 0.5; if the current work order distribution time has passed 8 hours, then D = 3. The larger D is, the larger the intensity of the tasks already responsible by the employee is.
[0102] In the actual method model, different weight values Ki (i = 1, 2, 3) can be set for the above three parameters, which can be equal to 1 or can be dynamically adjusted in combination with the service time period, service target city of the actual enterprise. The more important a certain item is, the larger the weight K value is, and the larger the final S value is. The larger the task intensity of the processing personnel of the post is, the fewer the work orders are assigned, and the more time the processing personnel has to process the complaint content. In combination with the subsequent work order monitoring module, important and high-priority complaints are effectively handled in an emergency.
[0103] In some examples, the optimization scheme model is for the weights of the above three values, respectively:
[0104]
[0105] Step 205, the complaint work order is assigned to the target processing personnel object.
[0106] In practical applications, the system will assign the complaint work order that has been determined to the target processing personnel object, ensuring that the work order can be accurately delivered to the person responsible for processing.
[0107] In some examples, the system will record the time of assignment, the identity information of the target processing personnel, and other key data, in order to subsequently track and evaluate the work order processing process. It will also remind the target processing personnel through an internal notification mechanism that there is a new work order to be processed, ensuring that they can respond and carry out processing work in a timely manner. After the work order is assigned, the target processing personnel will analyze and process the work order in detail according to their professional knowledge and experience, ensuring that the problem is effectively solved, thereby improving user satisfaction.
[0108] The work order processing module is mainly processed by the complaint processing center personnel of different cities, and provides a work order pool for the whole cross-level complaint management method and system to provide work order whole process management ability. The construction of the work order pool also provides a work order data source for the subsequent work order monitoring module, which includes the work order time, work order time limit, work order latest progress, etc.
[0109] In some embodiments of the present application, it also includes:
[0110] For each unprocessed completed work order, determine the time difference between the current time and the assignment time; according to the time difference, the unprocessed completed work order is processed.
[0111] In related technologies, there are mainly two ways to monitor the work order that has been assigned. One is to conduct special OA notification for manually assigned work orders and to process related work orders within a fixed time. The other is to enter related work orders into the maintenance system for separate judgment. There is no good system monitoring system, and there is no processing overtime warning and serious overtime cross-level overtime warning capability for urgent work orders.
[0112] In practical applications, in order to ensure that all work orders can be processed within the specified time, the system monitors each unprocessed completed work order. Specifically, the system determines the time difference between the current time and the order time, which can reflect the processing progress of the work order and whether there is a risk of delay. Once the time difference exceeds the preset threshold, the system will perform early warning processing on the unprocessed completed work order. The early warning processing can include sending an early warning notification to the relevant processing personnel, or displaying the early warning information in a prominent way on the interface of the system to remind the processing personnel to pay attention and speed up the processing progress, which can effectively avoid the problem of user complaint escalation or satisfaction decrease caused by delayed processing of work orders. At the same time, this also provides an effective monitoring means for the managers of the complaint processing center, so that they can discover problems in time and take corresponding measures to intervene and adjust.
[0113] As Figure 3c , the work order monitoring module mainly includes a progress monitoring module and a work order archiving module.
[0114] In the work order monitoring module, the current time is combined with the order time of each work order to dynamically scan the work order situation in the work order pool, and an alarm is given when the time exceeds the specified time to prompt the superior of the processing personnel to pay attention, so that the over-level work order can be processed in time, a satisfactory reply is given to the customer, and a better digital management means is provided for the enterprise to handle over-level complaints.
[0115] The progress monitoring module provides an effective guarantee mechanism for the progress monitoring of over-level complaint work orders. When a work order is not completed within the specified time, it will be upgraded for processing, providing a better service experience for customers and improving the complaint processing efficiency of the enterprise.
[0116] The timer task management is executed by scanning at regular intervals, the state and order time of the work order are extracted, and for the unprocessed work order, the time difference D between the current time and the order time is judged, and D is compared with the first, second and third time differences set by the system in advance, and different early warning processing is performed, as follows:
[0117] If the time difference D is less than the first level, the work order is not early warned.
[0118] If the time difference D is greater than or equal to the first level and less than the second level, the work order is early warned at the first level.
[0119] If the time difference D is greater than or equal to the second level and less than the third level, the work order is early warned at the second level.
[0120] If the time difference D is greater than or equal to the third level, the work order is early warned at the third level.
[0121] In some embodiments of the present application, it further includes:
[0122] According to the processing scheme of the processed completed work order, experience knowledge data is generated and stored.
[0123] In the related art, for the work order that has been processed and completed, the archiving of the processing scheme of the work order requires human intervention to judge whether the work order is processed and completed, and the processing solution is not formed into effective knowledge experience.
[0124] In practical applications, in the process of processing complaint work orders, processing personnel often encounter various situations and problems, and the problems and corresponding solutions often have certain universality and reusability. Therefore, in the embodiments of the present application, the system analyzes and summarizes the work orders that have been processed and completed, extracts the processing scheme and experience lessons, and then generates experience knowledge data and stores it. These experience knowledge data can include the type of work order, problem description, processing steps, solution, processing result and other key information, as well as the problems encountered by the processing personnel in the processing process, the measures taken, the experience and lessons learned, and other subjective feelings and experience sharing. Through accumulation and arrangement of these experience knowledge data, a rich knowledge base can be formed to provide reference for subsequent processing of similar work orders. In practical applications, when processing personnel encounter similar problems, they can quickly find relevant solutions and experience sharing by searching the knowledge base, thereby improving processing efficiency and accuracy.
[0125] The work order archiving module mainly archives the work order after the work order is processed, and extracts and summarizes the processing scheme of the over-level complaint work order to form experience knowledge, which provides a certain reference for subsequent other problems, and provides a realistic reference for customer service management, customer package planning and customer whole cycle management of each department in the enterprise, and promotes the enterprise to better create value for customers.
[0126] Specifically, for the work order that has been processed and completed, the work order archiving module performs subsequent work, mainly archives the work order data, and extracts and summarizes the processing scheme of the over-level complaint work order to form experience knowledge, which provides a certain reference for subsequent other problem processing.
[0127] In the embodiment of the application, by acquiring complaint data, analyzing the complaint data, obtaining attribute information, generating work order content according to the attribute information, and creating a complaint work order according to the work order content, the complaint work order is dispatched to the target processing personnel object, the optimization of the complaint work order dispatch is realized, the accuracy of the complaint work order dispatch is improved, and the processing quality and efficiency of the complaint are improved.
[0128] Referring to Figure 4 , another step flowchart of a processing method of a complaint work order provided by some embodiments of the application is shown, which can specifically include the following steps:
[0129] Step 401, complaint data is acquired, and the complaint data is analyzed to obtain attribute information.
[0130] Step 402, work order content is generated according to the attribute information, and a complaint work order is created according to the work order content; wherein the attribute information includes complaint urgency and a user's region, and the work order content includes a work order type, and the work order type corresponds to the complaint urgency.
[0131] Step 403, a processing personnel object of a corresponding region is determined according to the user's region.
[0132] Step 404, an ability tag of the processing personnel object of the corresponding region is determined; wherein the ability tag is used to indicate a work order type that the processing personnel object has processing ability for.
[0133] Step 405, the ability tag and the work order type are matched, and a candidate processing personnel object is determined from the processing personnel object of the corresponding region according to a matching result.
[0134] Step 406, a current task intensity of the candidate processing personnel object is determined, and a target processing personnel object is determined from the candidate processing personnel object according to the current task intensity.
[0135] Step 407, the complaint work order is dispatched to the target processing personnel object.
[0136] It should be noted that, for the method embodiments, the series of acts complement each other to achieve the purpose of this embodiment, therefore, the sequence of the acts should not be construed as a limitation of the embodiments of this application. In addition, those skilled in the art should understand that the acts of the embodiments described in the specification are only preferred acts, and not all acts are necessary for the embodiments of this application.
[0137] Some embodiments of the present application provide a complaint work order processing device, which can be specifically used for:
[0138] Obtaining complaint data and analyzing the complaint data to obtain attribute information;
[0139] Generating work order content according to the attribute information, and creating a complaint work order according to the work order content; wherein the attribute information includes complaint urgency, and the work order content includes work order type, and the work order type corresponds to the complaint urgency;
[0140] Determining a candidate handler object according to the work order type;
[0141] Determining the current task intensity of the candidate handler object, and determining a target handler object from the candidate handler object according to the current task intensity;
[0142] Assigning the complaint work order to the target handler object.
[0143] Optionally, the attribute information obtained by analyzing the complaint data includes:
[0144] Determining product value, user label and user level according to the complaint data;
[0145] Determining importance according to the product value, user label and user level;
[0146] Determining complaint urgency according to the importance and user historical traffic usage.
[0147] Optionally, the attribute information further includes a user region, and determining a candidate handler object according to the work order type includes:
[0148] Determining a handler object of a corresponding region according to the user region;
[0149] Determining a capability label of the handler object of the corresponding region; wherein the capability label is used to indicate a work order type that the handler object has processing capability for;
[0150] The capability tag and the work order type are matched, and a candidate handler object is determined from handler objects in the corresponding region according to a matching result.
[0151] Optionally, the current task intensity of the candidate handler object is determined by:
[0152] An unprocessed completed work order of each candidate handler object is determined, and a time limit requirement coefficient, a product value coefficient, and a processed duration coefficient of each unprocessed completed work order are determined.
[0153] The current task intensity of each unprocessed completed work order is determined according to the time limit requirement coefficient, the product value coefficient, and the processed duration coefficient.
[0154] The current task intensity of the candidate handler object is determined according to the current task intensities of all unprocessed completed work orders of the candidate handler object.
[0155] Optionally, the current task intensity of each unprocessed completed work order is determined according to the time limit requirement coefficient, the product value coefficient, and the processed duration coefficient by:
[0156] The weights of the time limit requirement coefficient, the product value coefficient, and the processed duration coefficient are determined, and the time limit requirement coefficient, the product value coefficient, and the processed duration coefficient are weighted and summed according to the corresponding weights to obtain the current task intensity of each unprocessed completed work order.
[0157] Optionally, the method further comprises:
[0158] For each unprocessed completed work order, a time difference between a current time and an order time is determined.
[0159] The unprocessed completed work order is processed according to the time difference.
[0160] Optionally, the method further comprises:
[0161] According to a processing scheme of a completed work order, experience knowledge data is generated and stored.
[0162] In the embodiment of the present application, by acquiring complaint data and analyzing the complaint data, attribute information is obtained, work order content is generated according to the attribute information, and a complaint work order is created according to the work order content; wherein the attribute information includes complaint urgency, the work order content includes work order type, and the work order type corresponds to the complaint urgency; a candidate processing personnel object is determined according to the work order type; the current task intensity of the candidate processing personnel object is determined, and a target processing personnel object is determined from the candidate processing personnel object according to the current task intensity; and the complaint work order is assigned to the target processing personnel object, which realizes optimization of complaint work order assignment, improves the accuracy of complaint work order assignment, and further improves the processing quality and efficiency of complaints.
[0163] Some embodiments of the present application also provide an electronic device, including a processor, a memory, and a computer program stored on the memory and capable of running on the processor, and the computer program is executed by the processor to implement the method as above.
[0164] Some embodiments of the present application also provide a computer readable storage medium, and the computer readable storage medium stores a computer program, and the computer program is executed by the processor to implement the method as above.
[0165] Some embodiments of the present application also provide a computer program product, including a computer program, and the computer program is executed by the processor to implement the method as above.
[0166] For the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the related parts are referred to the part of the method embodiment.
[0167] It should be noted that the user information (including but not limited to user equipment information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in the present application are all information and data authorized by the user or authorized by all parties, and the collection, use and processing of related data need to comply with relevant laws, regulations and standards of relevant countries and regions, and provide corresponding operation portal for user to choose authorization or refusal.
[0168] Each embodiment in the specification is described in a progressive manner, and each embodiment focuses on the difference from other embodiments, and the same and similar parts of each embodiment can be referred to each other.
[0169] Those skilled in the art will appreciate that embodiments of the present application can be readily used as a method, apparatus, or computer program product. Accordingly, embodiments of the present application can take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, embodiments of the present application can take the form of a computer program product on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROMs, optical storage devices, and the like) embodying computer readable program code.
[0170] Embodiments of the present application are described herein with reference to the drawings, which are as follows:
[0171] These computer program instructions can also be stored in a computer- readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instructions which implement the function specified in the flowchart or block diagram block or blocks.
[0172] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart or block diagram block or blocks.
[0173] While preferred embodiments of the present application have been described, additional variations and modifications can be made to these embodiments by those skilled in the art once they have the benefit of the foregoing description. Therefore, the appended claims are intended to encompass within their scope all such variations and modifications as are included within the scope of the embodiments of the present application.
[0174] Finally, it is to be understood that the phraseology or terminology such as "first" and "second" etc. used herein is merely intended to differentiate one entity or operation from another entity or operation, without necessarily requiring or implying any actual such relationship or order between such entities or operations. Moreover, the terms "comprises", "comprising", or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but can also include other elements not expressly listed or inherent to such process, method, article, or apparatus. An element proceeded by "comprises... a" does not, without more constraints, exclude the existence of additional identical elements in the process, method, article, or apparatus that comprises the aforesaid element.
[0175] The above provides a complaint ticket processing method, device, equipment and medium, has carried on the detailed introduction, the principle and implementation mode of the application are set forth in this paper by applying specific examples, the above example is only for helping to understand the method and core idea of the application; At the same time, for the general technical personnel in the art, according to the idea of the application, the specific implementation mode and application range will have the change, on the basis of the above, the content of the specification should not be understood as the limitation of the application.
Claims
1. A method for processing complaint work orders, characterized in that, The method comprises: obtaining complaint data and analyzing the complaint data to obtain attribute information; generating a work order content according to the attribute information and creating a complaint work order according to the work order content; wherein the attribute information comprises complaint urgency, and the work order content comprises a work order type corresponding to the complaint urgency; determining a candidate handler object according to the work order type; determining a current task intensity of the candidate handler object and determining a target handler object from the candidate handler object according to the current task intensity; assigning the complaint work order to the target handler object.
2. The method of claim 1, wherein analyzing the complaint data to obtain attribute information comprises: determining product value, user label, and user level according to the complaint data; determining importance according to the product value, user label, and user level; determining complaint urgency according to the importance and user historical traffic usage. The attribute information further comprises a user region, and determining a candidate handler object according to the work order type comprises:
3. The method of claim 1, wherein, determining a handler object of a corresponding region according to the user region; determining a capability label of the handler object of the corresponding region; wherein the capability label indicates a work order type that the handler object has processing capability for; matching the capability label and the work order type, and determining a candidate handler object from the handler object of the corresponding region according to a matching result.
4. The method of any one of claims 1-3, wherein determining a current task intensity of the candidate handler object comprises: determining an unprocessed completed work order of each candidate handler object, and determining a time limit requirement coefficient, a product value coefficient, and a processed time length coefficient of each unprocessed completed work order; determining a current task intensity of each unprocessed completed work order according to the time limit requirement coefficient, the product value coefficient, and the processed time length coefficient; determining a current task intensity of the candidate handler object according to the current task intensities of all unprocessed completed work orders of each candidate handler object.
5. The method of claim 4, wherein determining a current task intensity of each unprocessed completed work order according to the time limit requirement coefficient, the product value coefficient, and the processed time length coefficient comprises: determining weights of the time limit requirement coefficient, the product value coefficient, and the processed time length coefficient, and performing weighted summation on the time limit requirement coefficient, the product value coefficient, and the processed time length coefficient by using corresponding weights to obtain a current task intensity of each unprocessed completed work order. Further comprising: determining a time difference between a current time and an assignment time for each unprocessed completed work order; performing early warning processing on the unprocessed completed work order according to the time difference.
6. The method according to any one of claims 1 to 3, characterized in that, Further comprising: generating and storing experience knowledge data according to a processing scheme of a completed work order. The device is used for:
7. The method according to any one of claims 1 to 3, characterized in that, obtaining complaint data and analyzing the complaint data to obtain attribute information; 8. A complaint ticket processing apparatus, characterized by comprising: generating a work order content according to the attribute information, and creating a complaint work order according to the work order content; wherein the attribute information comprises a complaint urgency level, and the work order content comprises a work order type corresponding to the complaint urgency level; determining a candidate handler object according to the work order type; determining a current task intensity of the candidate handler object, and determining a target handler object from the candidate handler object according to the current task intensity; assigning the complaint work order to the target handler object.
9. An electronic device, comprising: A computer program product comprising a processor, a memory, and a computer program stored on the memory and executable on the processor, the computer program, when executed by the processor, implementing the method according to any one of claims 1 to 7.
10. A computer-readable storage medium, characterized in that, A computer program product comprising a processor, a memory, and a computer program stored on the memory and executable on the processor, the computer program, when executed by the processor, implementing the method according to any one of claims 1 to 7.