Customer service processing method, device and equipment for express work order and storage medium

Abstract

The invention discloses a customer service processing method and device for an express work order, equipment and a storage medium. The method comprises the steps of obtaining a theme work order pushed by a third-party platform; analyzing the theme work order to obtain a target work order; a work order processing framework and a work order customer service processing flow corresponding to the work order processing framework are determined, the work order processing framework comprises multiple work order processing levels, and the next work order processing level in the multiple work order processing levels is used for receiving the overflow target work order of the previous work order processing level; executing a work order customer service processing flow on the target work order based on the work order processing architecture to obtain a customer service processing result; and feeding back a customer service processing result to the third-party platform. According to the method, the responsibility division of each level is defined by establishing the work order processing architecture, the work order can be matched with the processing flow to be distributed to the proper level for processing, the third-party platform docking system is introduced, the abnormal work order of multiple platforms can be acquired and processed in real time, the information transmission link is reduced, the processing flow is accelerated, and the overall processing efficiency is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of express logistics processing, and specifically relates to a customer service processing method, device, equipment and storage medium for express work orders. Background Art

[0002] With the rapid development of e-commerce, the global express logistics industry has experienced explosive growth. While this prosperity has brought numerous opportunities, it has also posed numerous severe challenges to logistics operations management, especially in work order management. These challenges are reflected in the following key areas: The surge in order volume has increased the complexity of work order management: The booming e-commerce industry has driven exponential growth in logistics orders. This massive influx of logistics orders has spurred a surge in after-sales, exception handling, and operational management requirements. This has resulted in a significant increase in the number of work orders, and their complexity and diversity have become increasingly complex. Traditional work order management models are struggling to cope with this massive and complex workload, severely impacting both processing efficiency and quality.

[0003] Under the existing work order management model, information transmission is delayed when unusual situations or customer requests arise, resulting in long response times for handling work orders. Customer issues aren't resolved promptly, leading to dissatisfaction and complaints, and damaging the brand image of logistics companies. Processing processes often lack standardization and efficiency, plagued by cumbersome steps and duplication of effort. Collaboration and information communication between departments are inefficient, leading to significant time-consuming work order circulation and further reducing processing efficiency. The order allocation method lacks scientific considerations, failing to fully consider factors such as the urgency of the order, the difficulty of handling it, and the skills and workload of the handlers. This can result in some urgent work orders not being promptly assigned to the appropriate handlers, and handlers experiencing backlogs or idleness due to uneven task allocation. There's a lack of effective monitoring and management of work order processing timelines, with reasonable processing deadlines not set based on the type and urgency of the order. This can hinder the smooth flow of the entire logistics process and increase operating costs due to the delayed handling of some work orders.

[0004] Furthermore, today's logistics operations involve numerous partners and service platforms, such as e-commerce platforms, warehousing systems, and distribution platforms. However, existing work order management systems often rely solely on their own internal work orders and lack effective data exchange and collaboration with these third-party platforms. When exceptions arise from multi-platform interactions, information cannot be shared between platforms, resulting in incomplete exception handling, impacting overall business flow and customer experience.

[0005] The original work order processing system primarily relied on a specific department at headquarters. As business scale continued to expand and the number of abnormal work orders increased, headquarters customer service faced enormous processing pressure, resulting in delayed responses and low processing efficiency. This single processing organizational structure lacked flexibility and scalability, and was unable to meet the needs of the rapidly growing logistics business.

[0006] To sum up, the existing work order management model can no longer adapt to the rapid development of the express logistics industry. Innovation and improvement are urgently needed to enhance the quality of logistics services and operational efficiency and meet the growing needs of customers. Summary of the Invention

[0007] In view of the shortcomings of the existing technology, the purpose of the present invention is to provide a customer service processing method, device, equipment and storage medium for express delivery work orders to solve the problem of low work order processing efficiency in the existing technology.

[0008] According to one aspect of the present application, a customer service processing method for an express work order is disclosed, the method comprising: Obtain the subject work order pushed by the third-party platform and parse the subject work order to obtain the target work order; Determine a work order processing architecture and a work order customer service processing flow corresponding to the work order processing architecture, wherein the work order processing architecture includes multiple work order processing levels, wherein a lower level in the multiple work order processing levels is used to receive overflow target work orders from an upper level; Execute the work order customer service processing process on the target work order based on the work order processing architecture to obtain a customer service processing result; Feedback the customer service processing results to the third-party platform.

[0009] In some embodiments, obtaining a topic work order pushed by a third-party platform includes: Capture the topic work orders pushed by the third-party platform based on Kafka message queue technology through the Kafka message listener; Determine target analysis tools and analysis keywords; Extract the parsing keywords in the subject work order based on the target parsing tool, The analyzed keywords are subjected to data conversion and standardization processing to obtain the target work order.

[0010] In some embodiments, executing a work order customer service processing process on the target work order based on the work order processing architecture to obtain a customer service processing result includes: Determine a target processing level corresponding to the target work order, where the target processing level is a current processing level corresponding to the target work order; Calling the target-level customer service corresponding to the target processing level to perform customer service processing on the target work order at the target processing level; If the target customer service of the target processing level does not handle the target work order within the level waiting time, the next level customer service of the next processing level is called to handle the target work order. The level waiting time is determined based on the attributes of each level in the work order processing architecture. Update the next processing level to the target processing level, and return to the step of calling the target level customer service corresponding to the target processing level to perform customer service processing on the target work order at the target processing level, until the work order customer service processing process is executed and the customer service processing result is obtained.

[0011] In some embodiments, the method further comprises: Obtaining a target processing result of customer service processing performed by a target-level customer service representative at the target processing level on the target work order within a level waiting time corresponding to the target processing level; The initial processing result is encapsulated as a Kafka message and fed back to the third-party platform, so that the target Kafka message serves as a topic work order of the next processing level of the target processing level.

[0012] In some embodiments, the method further comprises: When the next processing level is the final processing level, determining whether the final processing level performs customer service processing on the target work order within the level waiting time; If the final processing level fails to process the target work order through customer service within the level waiting time; Mark the target work order as an abnormal pending order; Feedback the abnormal pending orders to the target personnel through the third-party platform.

[0013] In some embodiments, the method further comprises: If, within the hierarchical waiting time, the target-level customer service corresponding to the target processing level performs customer service processing on the target work order, the target work order is updated and marked as a hierarchical attribute pending feedback order, wherein the hierarchical attribute is determined based on the hierarchical attribute of the target processing level in the work order processing architecture; Feedback the order with the hierarchical attribute to be fed back to the subsequent levels in the work order processing architecture for review in sequence; If the current review level of the subsequent level fails to approve the order feedback from the previous level, the order with the level attribute to be fed back will be returned to the upper target processing level, so that the target level customer service corresponding to the target processing level will re-review the target work order.

[0014] In some embodiments, the method further comprises: If the current review level is the final review level, determine whether the final review level has passed the order review of the level immediately above the final review level; When the review is passed, the target order is updated and marked as a completed order.

[0015] According to another aspect of the present application, a customer service processing device for express work orders is also disclosed, the device comprising: The target work order acquisition module is used to obtain the subject work order pushed by the third-party platform and parse the subject work order to obtain the target work order; A work order customer service processing flow determination module is used to determine a work order processing architecture and a work order customer service processing flow corresponding to the work order processing architecture. The work order processing architecture includes multiple work order processing levels, wherein the lower level of the multiple work order processing levels is used to receive overflow target work orders from the upper level. A customer service processing result determination module is used to execute the work order customer service processing process on the target work order based on the work order processing architecture to obtain a customer service processing result; The result feedback module is used to feed back the customer service processing result to the third-party platform.

[0016] According to another aspect of the present application, an electronic device is also disclosed, which includes a memory and at least one processor, wherein the memory stores instructions; the at least one processor calls the instructions in the memory so that the electronic device executes each step of the customer service processing method for express work orders as described in any one of the above items.

[0017] According to another aspect of the present application, a computer-readable storage medium is also disclosed, on which instructions are stored. When the instructions are executed by a processor, the various steps of the customer service processing method for express work orders as described in any of the above items are implemented.

[0018] The present invention includes but is not limited to the following beneficial effects: (1) This application clarifies the division of responsibilities at each level by establishing a work order processing architecture, so that work orders can be matched with the processing flow and assigned to the appropriate level for processing, and introduces a third-party platform docking system, which can obtain and process abnormal work orders from multiple platforms in real time, reduce information transmission links, speed up the processing flow, and improve overall processing efficiency; (2) By obtaining and processing the subject work orders pushed by the third-party platform, the cooperation and collaboration between logistics companies and third parties are strengthened, and real-time data sharing and business collaborative processing are achieved. All parties can jointly deal with logistics anomalies, optimize supply chain processes, improve the efficiency and competitiveness of the entire industrial chain, and promote the integrated development of the logistics industry and related industries; (3) By parsing the subject work orders to obtain the target work orders, determine the work order processing architecture and the corresponding processing flow, and standardize and normalize the entire work order processing process, reduce errors and delays caused by human factors, improve the accuracy and reliability of processing, and improve the operational stability of logistics business; (4) Using Kafka message queue technology and Kafka message listener to capture the subject work orders pushed by the third-party platform, Kafka It has the characteristics of high throughput, persistent storage, and distribution, and can efficiently and stably receive a large amount of work order data, reduce the occurrence of work order data loss and congestion, improve transmission reliability, and provide a solid data foundation for subsequent processing; (5) By clarifying the target parsing tools and parsing keywords, it can accurately extract the key information in the subject work order, reduce the interference of invalid data, make the acquired data more targeted and effective, and improve the accuracy and efficiency of work order data processing. Furthermore, the parsing keywords are converted and standardized, and the work order data from different sources and in various formats are unified and standardized, so as to improve the consistency of data format within the system, facilitate the smooth execution of the subsequent work order processing process, and reduce Reduce processing errors and delays caused by data format differences; (6) In this application, when a certain level is busy, the work order will be transferred to other levels in a timely manner, and the processing level can be dynamically adjusted according to the work order processing situation, which can optimize system resource utilization, avoid excessive concentration of resources in some levels, achieve reasonable allocation of resources, and improve overall processing efficiency; (7) By updating the next processing level to the target processing level and looping the processing until the work order customer service processing process is completed, the entire processing process is ensured to be fully executed, avoiding process interruptions, ensuring that each work order can be properly processed, and improving service quality; (8) This application encapsulates the target processing results of the target work order at the target processing level into Kafka messages, so that the target processing level is decoupled from the processing links of different levels such as the next processing level. Each level of processing is relatively independent, and different levels execute tasks asynchronously without relying closely on the status of other levels, reducing the system coupling, enhancing the independence and maintainability of each module, improving the concurrent processing capability of the logistics system, avoiding the blocking and waiting that may be caused by synchronous processing, and improving the overall processing efficiency;(9) In this application, when the final processing level fails to process a work order within the specified time, it will be marked as an abnormal pending order, which clearly defines the abnormal situation of work order processing, helps management personnel to promptly discover problem work orders in the processing process, and realizes accurate monitoring of the work order processing status. By marking the abnormalities, these special work orders can be centrally managed, which is convenient for subsequent targeted allocation of resources for processing, avoiding abnormal work orders being ignored or omitted in the system, and improving the integrity and accuracy of work order processing; (10) Feedback orders are reviewed in order by level in the work order processing architecture, and an orderly review mechanism is established. The latter level reviews based on the processing results of the previous level, ensuring that the problem is checked layer by layer, so that complex problems can be handled more professionally at a higher level, improving the processing quality. If the latter level fails the review, it will be returned to the upper target processing level for re-review, forming a quality control closed loop, which can promptly discover and correct errors or unreasonableness in the processing, avoid the outflow of erroneous results, ensure the accuracy and reliability of the final processing results, and improve customer recognition of the processing results. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for describing the embodiments or the prior art.

[0020] Figure 1 This is a flow chart of a customer service processing method for an express work order according to an embodiment of the present application; Figure 2 This is another flow chart of the customer service processing method for the express work order of the embodiment of the present application; Figure 3 This is another flow chart of the customer service processing method for the express work order of the embodiment of the present application; Figure 4 This is another flow chart of the customer service processing method for the express work order of the embodiment of the present application; Figure 5 This is another flow chart of the customer service processing method for the express work order of the embodiment of the present application; Figure 6 This is another flow chart of the customer service processing method for the express work order of the embodiment of the present application; Figure 7 This is a schematic diagram of a customer service processing method for an express work order according to an embodiment of the present application; Figure 8 This is a structural block diagram of a customer service processing device for an express work order according to an embodiment of the present application; Figure 9 It is a structural diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0021] The embodiment of the present invention provides and discloses a customer service processing method, apparatus, equipment and storage medium for express work orders, the method comprising obtaining a subject work order pushed by a third-party platform; parsing the subject work order to obtain a target work order; determining a work order processing architecture and a work order customer service processing flow corresponding to the work order processing architecture, the work order processing architecture comprising a multi-layer work order processing hierarchy, wherein the lower level in the multi-layer work order processing hierarchy is used to receive overflow target work orders from the upper level; executing the work order customer service processing flow for the target work order based on the work order processing architecture to obtain a customer service processing result; and feeding back the customer service processing result to the third-party platform. This application clarifies the division of responsibilities of each level by establishing a work order processing architecture, so that work orders can be matched with the processing flow to be assigned to the appropriate level for processing, and introduces a third-party platform docking system, which can obtain and process abnormal work orders from multiple platforms in real time, reduce information transmission links, speed up the processing flow, and improve overall processing efficiency.

[0022] The terms "first," "second," "third," "fourth," and so on (if any) in the description and claims of the present invention and in the accompanying drawings are used to distinguish similar objects and are not necessarily used to describe a particular order or precedence. It should be understood that the terms used in this manner are interchangeable where appropriate, so that the embodiments described herein can be implemented in an order other than that shown or described herein. In addition, the terms "including" or "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or apparatus that includes a series of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, product, or apparatus.

[0023] For ease of understanding, the specific process of the embodiment of the present invention is described below. Specifically, Figure 1 This is a flow chart of a customer service processing method for an express work order according to an embodiment of the present application. This method is executed based on a customer service operation system. Figure 1 As shown, the following steps are included: S100: Obtain a subject work order pushed by a third-party platform, and parse the subject work order to obtain a target work order.

[0024] In one example, Figure 2 This is another flow chart of the customer service processing method of the express work order embodiment of the present application. The flow chart is the specific steps of step S100, see Figure 2 Step S100 of obtaining the subject work order pushed by the third-party platform includes the following steps: S200. Capture topic work orders pushed by a third-party platform based on Kafka message queue technology through a Kafka message listener.

[0025] Specifically, third-party platforms include, but are not limited to, e-commerce platforms, warehousing systems, and delivery platforms. Leveraging Kafka message queuing technology, third-party platforms push messages containing information related to the target work order to the customer service operations system. As you can see, Kafka's high throughput, persistent storage, and distributed nature allow it to efficiently and stably receive large amounts of work order data, reducing data loss and congestion, improving transmission reliability, and providing a solid data foundation for subsequent processing. It's important to note that key parameters such as the topic and format for message transmission can be agreed upon in advance before actual operation. Message formats typically use structured data formats such as JSON to clearly encapsulate detailed information such as the work order number, content, creation time, and the business involved. For example, when an e-commerce platform generates a work order regarding a lost courier package, it encapsulates the relevant information into a Kafka message according to a predefined format and pushes it to a designated topic. In one example, by gaining a deep understanding of the customer service process for courier work orders, it can clearly identify the different sources (e-commerce platform, corporate customer, etc.), types (complaint, inquiry, exception, etc.), and processing levels (branch, provincial company, headquarters). For example, e-commerce platforms handle a large volume of work orders in diverse formats, and complaints require rapid response. Based on this, we can determine the topic requirements for different business scenarios. We can also select a topic classification method based on business needs, either by single dimensions such as source, type, and processing level, or by combining multiple dimensions. For example, the "E-commerce - Complaint - Outlet" topic combines source, type, and processing level dimensions to facilitate precise management of specific types of work orders.

[0026] In the customer service operations system, a Kafka consumer is configured based on a Spring configuration file. This configuration requires specifying the topic to monitor (the topic from which the third-party platform pushes work order messages), as well as setting parameters such as the consumer group. A Kafka message listener is created to monitor the specified topic. Once a work order message is pushed from the third-party platform, the listener quickly captures it and prepares for subsequent processing.

[0027] S202: Determine target analysis tools and analysis keywords.

[0028] S204: Extracting parsing keywords from the subject work order based on the target parsing tool.

[0029] Specifically, after capturing a message, the Kafka message listener parses it. Parsing tools, such as libraries like Jackson and Gson, can be used in a Java environment to parse JSON data. By writing a parser, you can extract key information from a work order according to pre-defined rules. For example, you can accurately extract fields such as the work order number and content from JSON data and organize it into a format that meets the processing requirements of the customer service operations system.

[0030] S206: Perform data conversion and standardization on the parsed keywords to obtain a target work order.

[0031] Specifically, the extracted data is verified to check whether required fields exist and are formatted correctly. If the work order number is empty or the format does not comply with regulations, appropriate action is required, such as logging an error and returning an error message to the third-party platform. The data is standardized according to system requirements. Tracking numbers are converted to uppercase, and address information is standardized, removing extra spaces and special characters to ensure data consistency and accuracy within the system.

[0032] Furthermore, the parsed work order can be passed to the Controller layer, which calls the Service layer interface. The Service layer performs business logic processing on the work order data, including data validation to check whether required fields are complete and the format is correct. It also determines the initial status of the work order based on business rules, such as marking it as "10 pending." Next, the Service layer calls the DAO layer and inserts the work order information into the work order table in the MySQL database through MyBatis. During the insertion process, tools such as Navicat are used to monitor database operations to ensure that the data is written correctly. In addition, relevant operation logs are recorded in the processing record table to facilitate subsequent tracing of the work order processing process.

[0033] In another example, data format conversion can also be achieved in advance by establishing a correspondence between the source data and the target data. When processing work order data, it is necessary to pre-define the mapping rules between the third-party platform data format and the system's unified standard format. For fields with different names but the same meaning in third-party platforms, such as some platforms use "express delivery number" and some use "waybill number", they are uniformly mapped to the system standard "express delivery number" field in the mapping rules. These correspondences can be recorded in detail with the help of special mapping configuration files, such as XML or JSON format files. During data processing, the system accurately fills the field values ​​in the source data into the corresponding positions in the target format according to the mapping rules, completes the unified conversion of the data format, and ensures the consistency and accuracy of the data.

[0034] Furthermore, ETL tools (Extract, Transform, Load) can be used to extract data from various data sources and perform transformation and loading operations. When processing third-party work order data, ETL tools can extract work order data from various third-party platforms. Leveraging their rich transformation capabilities, data can be cleaned, formatted, and field reorganized. For date fields with irregular formats, the ETL tool's date formatting function can be used to uniformly convert them to the system's standard date format. Missing values ​​can be filled according to pre-set rules, such as using default values ​​or values ​​calculated from other relevant data. After the transformation is complete, the processed data is loaded into the target database or data storage of the customer service operations system to achieve standardized processing of work order data and provide high-quality data support for subsequent business processes.

[0035] Furthermore, the data standardization engine can be used as a tool to handle data standardization tasks. Based on pre-set standards and rules, various formats of input data can be automatically processed. In the work order data processing scenario, standardization rules for work order data from different third-party platforms can be configured in the engine. In response to the various expressions of address fields in e-commerce platform work order data, the engine can use the built-in address standardization algorithm to unify them into a standard address format, including hierarchical structures such as province, city, district, and street. Through machine learning algorithms, the data standardization engine can also continuously learn and optimize processing rules to adapt to emerging data formats and changes, improve the accuracy and efficiency of data standardization, and ensure the efficient flow and processing of work order data within the system.

[0036] It is understandable that by obtaining and processing the subject work orders pushed by the third-party platform, the cooperation and collaboration between logistics companies and third parties is strengthened, and real-time data sharing and business collaborative processing are achieved. All parties can jointly deal with logistics anomalies, optimize supply chain processes, improve the efficiency and competitiveness of the entire industrial chain, and promote the integrated development of the logistics industry and related industries; further, by parsing the subject work orders to obtain the target work orders, determine the work order processing architecture and the corresponding processing flow, and standardize and normalize the entire work order processing process, reducing errors and delays caused by human factors, improving the accuracy and reliability of processing, and improving the operational stability of logistics business; further, using Kafka message queue technology and Kafka message listener to capture the subject work orders pushed by the third-party platform, Kafka It has the characteristics of high throughput, persistent storage, and distribution. It can efficiently and stably receive large amounts of work order data, reduce the occurrence of work order data loss and congestion, improve transmission reliability, and provide a solid data foundation for subsequent processing. Furthermore, by clarifying the target parsing tools and parsing keywords, it can accurately extract key information from the subject work order, reduce invalid data interference, make the acquired data more targeted and effective, and improve the accuracy and efficiency of work order data processing. Furthermore, the parsing keywords are converted and standardized to unify work order data from different sources and in various formats, improve the consistency of data format within the system, facilitate the smooth execution of subsequent work order processing, and reduce processing errors and delays caused by data format differences.

[0037] S102: Determine a work order processing architecture and a work order customer service processing flow corresponding to the work order processing architecture.

[0038] Specifically, the work order processing architecture includes multiple layers of work order processing levels, and the lower level in the multiple layers of work order processing levels is used to receive overflow target work orders from the upper level. The work order processing architecture can be pre-built, and the architecture can include multiple layers of work order processing levels, for example, including two or three or four layers or other layers. In this example, a three-layer work order processing architecture is used as an example for explanation. Specifically, the three-layer work order processing architecture can include an outlet processing level, a provincial company processing level, and a headquarters processing level. The work order customer service processing process can be predetermined. For example, in the three-layer work order processing architecture of this example, the work order customer service processing process can be that the outlet processing level is the basic processing level, the provincial company processing level is the intermediate processing level, and the headquarters processing level is the ultimate processing level. When a certain target work order meets the outlet processing level, the provincial company processing level and the headquarters processing level can serve as substitute processing levels for the upper processing level in turn, but the previous processing level cannot serve as a substitute processing level for the subsequent processing level.

[0039] S104: Execute the work order customer service processing process for the target work order based on the work order processing architecture to obtain a customer service processing result.

[0040] Specifically, in one example, Figure 3 This is another flow chart of the customer service processing method of the express work order embodiment of the present application. This flow chart is an exemplary introduction to step S104. Figure 3 , including the following steps: S300: Determine the target processing level corresponding to the target work order.

[0041] Specifically, the target processing level is the current processing level corresponding to the target work order. It's understandable that the level of the topic work orders pushed by third-party platforms using Kafka message queue technology, captured by the Kafka message listener, could be any level within the work order processing architecture. Therefore, it's necessary to first determine the target processing level for the target work order. In this example, the target processing level is the branch processing level.

[0042] S302: Call the target-level customer service corresponding to the target processing level to perform customer service processing on the target work order at the target processing level.

[0043] S304. If the target level customer service corresponding to the target processing level does not perform customer service processing on the target work order within the level waiting time corresponding to the target processing level, the next level customer service corresponding to the next processing level is called to perform customer service processing on the target work order.

[0044] Specifically, the hierarchical waiting time is determined based on the attributes of each hierarchical level in the work order processing architecture. For example, in the three-tier work order processing architecture in this example, the hierarchical waiting time corresponding to the branch processing level can be 10 minutes, or 15 minutes, or 20 minutes, etc., and when the target processing level is the provincial company processing level, the corresponding hierarchical waiting time can be 15 minutes, or 20 minutes, or 25 minutes, etc. When the target processing level is the headquarters processing level, the corresponding hierarchical waiting time can be 20 minutes, or 25 minutes, or 30 minutes, etc. Specifically, the hierarchical waiting time can be set based on actual needs, which will not be elaborated here.

[0045] S306. Update the next processing level to the target processing level, and return to the step of calling the target level customer service corresponding to the target processing level to perform customer service processing on the target work order at the target processing level, until the work order customer service processing flow is completed and the customer service processing result is obtained.

[0046] It is understandable that when a certain level of business is busy, the work order will be transferred to other levels in a timely manner, and the processing level can be dynamically adjusted according to the work order processing situation, which can optimize the utilization of system resources, avoid excessive concentration of resources at some levels, achieve reasonable allocation of resources, and improve overall processing efficiency; and by updating the next processing level to the target processing level and processing it in a loop until the work order customer service processing process is completed, the entire processing process is ensured to be fully executed, avoiding process interruptions, ensuring that each work order can be properly handled, and improving service quality.

[0047] S106. Feedback the customer service processing results to the third-party platform.

[0048] Furthermore, in another example, Figure 4 Another flow chart of the customer service processing method of the express work order embodiment of this application, see Figure 4 , including the following steps: S400 , obtaining a target processing result of customer service processing performed by the target level customer service corresponding to the target processing level on the target work order within the level waiting time corresponding to the target processing level.

[0049] S402: Encapsulate the target processing result as a target Kafka message and feed it back to the third-party platform, so that the target Kafka message serves as a topic work order of the next processing level of the target processing level.

[0050] Specifically, when the target-level customer service corresponding to the target processing level performs customer service processing on the target work order within the level waiting time corresponding to the target processing level, the target processing result is obtained, and the target processing result is further encapsulated as a target Kafka message and fed back to the third-party platform, so that the target Kafka message serves as the topic work order of the next processing level of the target processing level.

[0051] It is understandable that encapsulating the target processing results of the target work order at the target processing level into Kafka messages decouples the target processing level from the next processing level and other processing links at different levels. Each level processes relatively independently, and different levels execute tasks asynchronously without relying closely on the status of other levels. This reduces the system coupling, enhances the independence and maintainability of each module, improves the concurrent processing capabilities of the logistics system, avoids the blocking and waiting that may be caused by synchronous processing, and improves overall processing efficiency.

[0052] Furthermore, in another example, Figure 5 Another flow chart of the customer service processing method of the express work order embodiment of this application, see Figure 5 , including the following steps: S500: When the next processing level is the final processing level, determine whether the final processing level performs customer service processing on the target work order within the level waiting time.

[0053] S502: If the final processing level does not perform customer service processing on the target work order within the level waiting time.

[0054] S504: Mark the target work order as an abnormal pending order.

[0055] S506: Feedback the abnormal pending orders to the target personnel through the third-party platform.

[0056] Specifically, the target personnel can be managers of the customer service operations system. It's understandable that when the final processing level doesn't handle a work order within the specified timeframe, it's marked as an exception pending order. This clearly defines the exceptions to work order processing, helping managers promptly identify problematic work orders in the process and accurately monitor the status of work order processing. Furthermore, by marking exceptions, these special work orders can be centrally managed, facilitating the targeted allocation of resources for subsequent processing. This prevents abnormal work orders from being overlooked or omitted in the system, and improves the completeness and accuracy of work order processing.

[0057] Furthermore, in another example, Figure 6 Another flow chart of the customer service processing method of the express work order embodiment of this application, see Figure 6 , including the following steps: S600: If, within the hierarchical waiting time, the target-level customer service corresponding to the target processing level performs customer service processing on the target work order, the target work order is updated and marked as a hierarchical attribute awaiting feedback order.

[0058] Specifically, the hierarchical attributes are determined based on the hierarchical attributes of the target processing level in the work order processing architecture; for example, in this example, the hierarchical attributes can be outlets, provincial companies, or headquarters, and the hierarchical attributes of pending feedback orders can be outlet pending feedback orders, provincial company pending feedback orders, or headquarters pending feedback orders.

[0059] S602: Feedback the order with the hierarchical attribute to be fed back to the subsequent levels in the work order processing architecture for review in sequence.

[0060] S604. If the current review level of the subsequent level fails to approve the order feedback from the previous level, the level attribute pending feedback order is returned to the upper target processing level, so that the target level customer service corresponding to the target processing level re-reviews the target work order.

[0061] It is understandable that feedback orders are reviewed in sequence according to the levels in the work order processing architecture, and an orderly review mechanism is established. The latter level reviews based on the processing results of the previous level to ensure that problems are checked layer by layer, so that complex problems can be handled more professionally at a higher level, improving the processing quality. When the latter level fails the review, it will be returned to the upper target processing level for re-review, forming a quality control closed loop, which can promptly discover and correct errors or unreasonable aspects in the processing, avoid the outflow of erroneous results, ensure that the final processing results are accurate and reliable, and improve customer recognition of the processing results.

[0062] Furthermore, if the current review level is the final review level, it is determined whether the final review level has passed the order review of the upper level of the final review level; when the review is passed, the target order is updated and marked as a completed order.

[0063] Further, for ease of understanding, this application is combined with Figure 7 The schematic diagram of the customer service processing method for express work orders is given as an example using the three-tier work order processing architecture: The customer service operations system assigns work orders based on pre-defined order splitting rules, combined with the order distribution network and channel rules. These rules take into account various factors, such as the delivery address, the region of the courier number, and the type of business. The system uses MyBatis to retrieve relevant network information from the database and accurately assigns work orders to the corresponding network based on the delivery address's regional classification. The work order status is then marked as "20 Networks Pending." This distribution method ensures that work orders are quickly delivered to the network closest to customers and frontline operations, facilitating timely processing and improving efficiency.

[0064] If branch customer service fails to accept a work order with the status "20 Branch Pending" within the corresponding level's waiting time, the system triggers a timeout mechanism using a timer and business logic. The system changes the work order's status to "21 Provincial Company Pending" and automatically transfers the work order to the provincial branch. This mechanism ensures that work orders are not stalled due to branch delays, ensuring timely processing. For example, during peak business periods, branches may be overwhelmed and unable to process all work orders promptly. The timeout mechanism allows work orders to be appropriately allocated to higher-level processing levels, ensuring smooth business operations. Furthermore, provincial branch customer service will process work orders with the status "21 Provincial Company Pending" or overflowed work orders from branches. If the processing requires cross-branch coordination, the provincial branch can leverage system functions to allocate resources and integrate regional human and material resources to better resolve the issue. Upon completion, the provincial branch customer service changes the work order's status to "31 Provincial Company Pending Feedback." This process demonstrates the provincial company's coordinating and management role in work order processing, effectively resolving complex regional issues. Furthermore, if the provincial company's customer service team fails to accept the order within the specified timeframe, the order will time out and be transferred to headquarters. Headquarters customer service will receive the order as "22 Headquarters Pending Order" and process it, updating the status to "32 Headquarters Pending Feedback." As the highest-level processing organization, headquarters is primarily responsible for handling cross-regional, complex, and multi-departmental work orders. Leveraging its extensive resources and expertise, it ensures that complex issues are properly resolved.

[0065] After handling a ticket, customer service at each level must submit feedback through the system interface. For example, provincial customer service reviews a ticket submitted by a branch with the status "30 Branch Awaiting Feedback." During the review process, they use data comparisons and express order details to determine the rationality and completeness of the feedback. If the review passes, the ticket status is updated to "41 Provincial Company Awaiting Review" and submitted to headquarters. If it fails, the ticket is returned to the branch and the status is changed back to "20 Branch Awaiting Order." If the provincial customer service fails to complete the review within the specified time, the ticket status changes to "42 Headquarters Awaiting Review" and is transferred to headquarters. Headquarters customer service conducts a final review of tickets submitted by provincial branches with the status "41 Provincial Company Awaiting Review" or timed-out tickets with the status "42 Headquarters Awaiting Review." If the review passes, the ticket status is marked as "100 Completed." If it fails, it is returned to the provincial company or branch for reprocessing, depending on the situation. This rigorous review process ensures the accuracy and reliability of ticket processing results, ensuring that customer issues are effectively resolved.

[0066] After completing work order processing and review, the system transmits the results in a specified format to the third-party platform via an interface. Reliable data transmission protocols, such as HTTP / HTTPS, ensure accurate communication of results, enabling closed-loop management of business processes. Upon receiving the results, the third-party platform can perform subsequent actions based on them, such as updating order status and providing feedback to customers, thereby improving customer satisfaction and the overall quality of logistics services.

[0067] Further, Figure 8 This is a structural diagram of the customer service processing device for express work orders, such as Figure 8 As shown, the device includes: The target work order acquisition module is used to obtain the subject work orders pushed by the third-party platform and parse the subject work orders to obtain the target work orders; A work order customer service processing flow determination module is used to determine the work order processing architecture and the work order customer service processing flow corresponding to the work order processing architecture. The work order processing architecture includes multiple work order processing levels, and the lower level in the multi-level work order processing level is used to receive overflow target work orders from the upper level. The customer service processing result determination module is used to execute the customer service processing process for the target work order based on the work order processing architecture and obtain the customer service processing result; The result feedback module is used to feed back customer service processing results to the third-party platform.

[0068] The application introduction of the relevant modules of the device in this example can refer to the relevant introduction of the above method principles, which will not be repeated here.

[0069] According to another aspect of the present application, the present application also discloses an electronic device, which includes a memory and at least one processor, wherein instructions are stored in the memory; at least one processor calls the instructions in the memory to enable the electronic device to execute each step of the customer service processing method for the express work order as described above.

[0070] above Figure 8 The customer service processing device for the express work order in the embodiment of the present invention is described in detail from the perspective of modular functional entities, and the electronic device in the embodiment of the present invention is described in detail from the perspective of hardware processing.

[0071] Figure 9is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. The electronic device 900 may vary significantly due to different configurations or performance, and may include one or more central processing units (CPUs) 910 (e.g., one or more processors), a memory 920, and one or more storage media 930 (e.g., one or more mass storage devices) storing application programs 933 or data 932. The memory 920 and storage medium 930 may be either transient or persistent storage. The program stored in the storage medium 930 may include one or more modules (not shown), each of which may include a series of instruction operations on the electronic device 900. Furthermore, the processor 910 may be configured to communicate with the storage medium 930 to execute the series of instruction operations in the storage medium 930 on the electronic device 900.

[0072] The electronic device 900 may further include one or more power supplies 940, one or more wired or wireless network interfaces 950, one or more input and output interfaces 960, and / or one or more operating systems 931, such as Windows Server, Mac OS X, Unix, Linux, FreeBSD, etc. It will be understood by those skilled in the art that Figure 9 The illustrated electronic device structure does not constitute a limitation on the electronic device, and may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently.

[0073] The present invention also provides a computer-readable storage medium, which may be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium. The computer-readable storage medium stores instructions, which, when executed on a computer, cause the computer to execute the steps of a customer service processing method for an express work order.

[0074] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described systems, devices, and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0075] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the various embodiments of the method of the present invention. The aforementioned storage medium includes various media that can store program code, such as a USB flash drive, a mobile hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0076] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that the technical solutions described in the above embodiments can still be modified, or some of the technical features thereof can be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A customer service processing method for express delivery work orders, characterized in that: The method comprises: Obtain the subject work order pushed by the third-party platform and parse the subject work order to obtain the target work order; Determine a work order processing architecture and a work order customer service processing flow corresponding to the work order processing architecture, wherein the work order processing architecture includes multiple work order processing levels, wherein a lower level in the multiple work order processing levels is used to receive overflow target work orders from an upper level; Execute the work order customer service processing process on the target work order based on the work order processing architecture to obtain a customer service processing result; Feedback the customer service processing results to the third-party platform.

2. The customer service processing method for express work orders according to claim 1, characterized in that: Obtaining thematic work orders pushed by third-party platforms includes: Capture the topic work orders pushed by the third-party platform based on Kafka message queue technology through the Kafka message listener; Determine target analysis tools and analysis keywords; Extract the parsing keywords in the subject work order based on the target parsing tool, The analyzed keywords are subjected to data conversion and standardization processing to obtain the target work order.

3. The customer service processing method for express work orders according to claim 1, characterized in that: Executing the work order customer service processing flow for the target work order based on the work order processing architecture, obtaining a customer service processing result includes: Determine a target processing level corresponding to the target work order, where the target processing level is a current processing level corresponding to the target work order; Calling the target-level customer service corresponding to the target processing level to perform customer service processing on the target work order at the target processing level; If the target level customer service of the target processing level does not handle the target work order within the level waiting time corresponding to the target processing level, the next level customer service of the next processing level is called to handle the target work order. The level waiting time is determined based on the attributes of each level in the work order processing architecture. Update the next processing level to the target processing level, and return to the step of calling the target level customer service corresponding to the target processing level to perform customer service processing on the target work order at the target processing level, until the work order customer service processing process is executed and the customer service processing result is obtained.

4. The customer service processing method for express work orders according to claim 3, characterized in that: The method further comprises: Obtaining a target processing result of customer service processing performed by a target-level customer service representative at the target processing level on the target work order within a level waiting time corresponding to the target processing level; The target processing result is encapsulated as a target Kafka message and fed back to the third-party platform, so that the target Kafka message serves as a topic work order of the next processing level of the target processing level.

5. The customer service processing method for express work orders according to claim 1, characterized in that: The method further comprises: When the next processing level is the final processing level, determining whether the final processing level performs customer service processing on the target work order within the level waiting time; If the final processing level fails to process the target work order through customer service within the level waiting time; Mark the target work order as an abnormal pending order; Feedback the abnormal pending orders to the target personnel through the third-party platform.

6. The customer service processing method for express work orders according to claim 1, characterized in that: The method further comprises: If, within the hierarchical waiting time, the target-level customer service corresponding to the target processing level performs customer service processing on the target work order, the target work order is updated and marked as a hierarchical attribute pending feedback order, wherein the hierarchical attribute is determined based on the hierarchical attribute of the target processing level in the work order processing architecture; Feedback the order with the hierarchical attribute to be fed back to the subsequent levels in the work order processing architecture for review in sequence; If the current review level of the subsequent level fails to approve the order feedback from the previous level, the order with the level attribute to be fed back will be returned to the upper target processing level, so that the target level customer service corresponding to the target processing level will re-review the target work order.

7. The customer service processing method for express work orders according to claim 1, characterized in that: The method further comprises: If the current review level is the final review level, determine whether the final review level has passed the order review of the level immediately above the final review level; When the review is passed, the target order is updated and marked as a completed order.

8. A customer service processing device for express delivery work orders, characterized in that: The device comprises: The target work order acquisition module is used to obtain the subject work order pushed by the third-party platform and parse the subject work order to obtain the target work order; A work order customer service processing flow determination module is used to determine a work order processing architecture and a work order customer service processing flow corresponding to the work order processing architecture. The work order processing architecture includes multiple work order processing levels, wherein the lower level of the multiple work order processing levels is used to receive overflow target work orders from the upper level. A customer service processing result determination module is used to execute the work order customer service processing process on the target work order based on the work order processing architecture to obtain a customer service processing result; The result feedback module is used to feed back the customer service processing result to the third-party platform.

9. An electronic device, characterized in that: The electronic device includes a memory and at least one processor, wherein the memory stores instructions; the at least one processor calls the instructions in the memory so that the electronic device executes each step of the customer service processing method for the express work order as described in any one of claims 1-7.

10. A computer-readable storage medium having instructions stored thereon, characterized in that: When the instructions are executed by the processor, the steps of the customer service processing method for the express work order according to any one of claims 1 to 7 are implemented.

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