Order processing method, device, equipment and storage medium

Abstract

The present disclosure provides an order processing method, device, equipment and storage medium, which are applied to smart devices. The method includes: in response to the received first indication information, determining the order type of the completed order indicated by the first indication information, the first indication information is used to indicate the order completion; obtaining the evaluation record of the completed order, the evaluation record is used to indicate the evaluation content of the completed order filled in by the user, and the evaluation record includes a score and a text evaluation; based on the evaluation record, generating a user feedback result corresponding to the order type, the user feedback result includes a comprehensive score based on the score and a comprehensive evaluation based on the text evaluation; based on the user feedback result, determining the targeted adjustment strategy corresponding to the order type. The technical solution of the present disclosure realizes the effective use of user feedback opinions and realizes targeted adjustments to specific businesses.

Description

Technical Field

[0001] The present disclosure relates to the technical field of order management, and in particular to an order processing method, device, equipment and storage medium. Background Art

[0002] With the promotion of online business processing platforms, more and more offline businesses or simple services can be applied for and processed through online business processing platforms, thereby improving business processing efficiency and facilitating users to quickly apply for business processing.

[0003] Existing online business processing platforms usually have a feedback and evaluation function for corresponding business processing, but generally require manual identification of specific feedback, making it difficult to make targeted adjustments to specific business through feedback. Summary of the invention

[0004] The present disclosure provides an order processing method, apparatus, device and storage medium to effectively utilize user feedback to achieve targeted adjustments to specific businesses.

[0005] In a first aspect, the present disclosure provides an order processing method, which is applied to a smart device. The order processing method includes:

[0006] In response to the received first indication information, determining the order type of the completed order indicated by the first indication information, the first indication information being used to indicate that the order is completed;

[0007] Get the evaluation record of the completed order. The evaluation record is used to indicate the evaluation content of the completed order filled in by the user. The evaluation record includes the rating and text evaluation;

[0008] Generate user feedback results for the corresponding order type based on the evaluation records. The user feedback results include a comprehensive score based on the rating and a comprehensive evaluation based on the text evaluation.

[0009] Based on user feedback, determine the targeted adjustment strategy corresponding to the order type.

[0010] Optionally, in response to the received first indication information, determining the order type of the completed order indicated by the first indication information, including: in response to the received first indication information, based on the order business type selected by the user on the order publishing platform and / or the group to which the user belongs, determining the order type of the completed order indicated by the first indication information, the order type is used to push the order selected by the user to the processing personnel of the corresponding order type.

[0011] Optionally, obtaining evaluation records for completed orders includes: in response to receiving a first indication message, sending an evaluation request to a client corresponding to the user; upon receiving a second indication message from the client, pushing an initial evaluation page for the corresponding order type to the client, the initial evaluation page including a form for scoring and filling in a text evaluation, and the second indication message is used to instruct the user to choose to agree to the evaluation; receiving a target evaluation page uploaded by the client, and obtaining the user's evaluation record for the completed order based on the target evaluation page.

[0012] Optionally, based on the evaluation records, user feedback results corresponding to the order type are generated, including: determining the average value of the scores corresponding to the order type; determining whether the average value of the scores is greater than a set benchmark value; when the average value of the scores is less than or equal to the benchmark value, generating user feedback results corresponding to the order type based on the text evaluation.

[0013] Optionally, based on the text evaluation, user feedback results corresponding to the order type are generated, including: performing keyword analysis on the text evaluation based on a preset vocabulary; determining evaluation keywords of the order type according to the frequency of keyword occurrence and the degree of match between the keywords and the preset vocabulary; combining the evaluation keywords with the text evaluation to obtain user feedback results of the order type.

[0014] Optionally, determining the average value of the ratings corresponding to the order types includes: eliminating the evaluation records that only contain text evaluations or only contain ratings; determining the average value of the ratings corresponding to the order types based on the ratings in the eliminated evaluation records; correspondingly, generating user feedback results for the corresponding order types based on the text evaluations, including: marking the text evaluations corresponding to different ratings based on the ratings in the eliminated evaluation records; and generating user feedback results for the corresponding order types based on the marked text evaluations.

[0015] Optionally, based on user feedback results, a targeted adjustment strategy corresponding to the order type is determined, including: when the average value of the score is greater than a benchmark value, determining that the targeted adjustment strategy corresponding to the order type does not require adjustment; when the average value of the score is less than or equal to the benchmark value, using the user feedback results of the order type as a targeted adjustment strategy and outputting it to relevant personnel.

[0016] In a second aspect, the present disclosure provides an order processing device, the order processing device comprising:

[0017] an acquisition module, configured to determine, in response to the received first indication information, the order type of the completed order indicated by the first indication information, the first indication information being used to indicate that the order is completed; and to acquire an evaluation record of the completed order, the evaluation record being used to indicate the evaluation content of the completed order filled in by the user, the evaluation record including a score and a text evaluation;

[0018] The processing module is used to generate user feedback results corresponding to the order type based on the evaluation records, the user feedback results including a comprehensive score based on the score and a comprehensive evaluation based on the text evaluation; and, based on the user feedback results, determine the targeted adjustment strategy corresponding to the order type.

[0019] Optionally, the acquisition module is specifically used to, in response to the received first indication information, determine the order type of the completed order indicated by the first indication information based on the order business type selected by the user on the order publishing platform and / or the group to which the user belongs, and the order type is used to push the order selected by the user to the processing personnel of the corresponding order type.

[0020] Optionally, the acquisition module is specifically used to, in response to receiving a first indication message, send an evaluation request to a client corresponding to the user; when receiving a second indication message from the client, push an initial evaluation page of the corresponding order type to the client, the initial evaluation page includes a form for scoring and filling in a text evaluation, and the second indication message is used to instruct the user to choose to agree to the evaluation; receive a target evaluation page uploaded by the client, and obtain the user's evaluation record for completed orders based on the target evaluation page.

[0021] Optionally, the processing module is specifically used to determine the average value of the score corresponding to the order type; determine whether the average value of the score is greater than a set benchmark value; when the average value of the score is less than or equal to the benchmark value, generate user feedback results for the corresponding order type based on text evaluation.

[0022] Optionally, the processing module is specifically used to perform keyword analysis on text reviews based on a preset vocabulary; determine evaluation keywords for order types based on keyword occurrence frequency and the degree of match between the keywords and the preset vocabulary; and combine the evaluation keywords with the text reviews to obtain user feedback results for the order types.

[0023] Optionally, the processing module is specifically used to eliminate records in the evaluation records that only contain text evaluations or only contain ratings; determine the average value of the ratings corresponding to the order type based on the ratings in the eliminated evaluation records; correspondingly, generate user feedback results of the corresponding order type based on the text evaluations, including: based on the ratings in the eliminated evaluation records, respectively marking the text evaluations corresponding to different ratings; and generating user feedback results of the corresponding order type based on the marked text evaluations.

[0024] Optionally, the processing module is specifically used to, when the average value of the score is greater than a benchmark value, determine that the targeted adjustment strategy corresponding to the order type does not require adjustment; when the average value of the score is less than or equal to the benchmark value, output the user feedback results of the order type as a targeted adjustment strategy to relevant personnel.

[0025] In a third aspect, the present disclosure provides an electronic device, the electronic device comprising:

[0026] at least one processor;

[0027] and a memory communicatively coupled to the at least one processor;

[0028] The memory stores instructions that can be executed by at least one processor, and the instructions are executed by at least one processor to enable the electronic device to perform any order processing method as described in the first aspect.

[0029] In a fourth aspect, the present disclosure further provides a computer-readable storage medium, in which computer execution instructions are stored. When the computer execution instructions are executed by a processor, they are used to implement any order processing method as described in the first aspect of the present disclosure.

[0030] The order processing method, apparatus, device and storage medium provided by the present invention determine the order type corresponding to the completed order according to the first indication information of the order completion received, and obtain the evaluation record corresponding to the order type, and then generate the corresponding user feedback result based on the evaluation record, so as to determine the targeted adjustment strategy of the business corresponding to the order type. In this way, the user evaluation is effectively utilized, and the corresponding business can be improved accordingly, which effectively improves the improvement effect of the online business processing platform and can effectively improve the user experience of the online business processing platform. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0032] Figure 1 An application scenario diagram of the order processing method provided in the embodiment of the present disclosure;

[0033] Figure 2 A flowchart of an order processing method provided by an embodiment of the present disclosure;

[0034] Figure 3 A flowchart of an order processing method provided by yet another embodiment of the present disclosure;

[0035] Figure 4 A schematic diagram of the structure of an order processing device provided by yet another embodiment of the present disclosure;

[0036] Figure 5 A schematic structural diagram of an electronic device provided in yet another embodiment of the present disclosure.

[0037] The above drawings show clear embodiments of the present disclosure, which will be described in more detail below. These drawings and text descriptions are not intended to limit the scope of the present disclosure in any way, but to illustrate the concepts of the present disclosure to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0038] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. Instead, they are merely examples of devices and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0039] The technical solution of the present invention and how the technical solution of the present invention solves the above-mentioned technical problems are described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present invention will be described below in conjunction with the accompanying drawings.

[0040] There are many online business processing platforms or telephone business processing systems that pre-set different business types to provide users with a quick channel to directly handle a variety of businesses online. After the pre-set business types are completed, the online business processing platform usually provides a feedback page, such as through user evaluation, to understand the specific business completion status and improve the business accordingly. However, in the prior art, the corresponding feedback page is usually manually screened, and some representative feedback evaluations are selected for processing, which results in a large amount of feedback being wasted, and the selection results are difficult to ensure that they effectively represent all feedback opinions. As a result, it is difficult to make targeted adjustments to specific businesses through feedback opinions in actual processing.

[0041] In order to solve the above problems, the embodiments of the present disclosure provide an order processing method, which processes the evaluation records of specific order types and automatically generates comprehensive user feedback results. As a result, it is possible to directly generate targeted adjustment strategies for the corresponding order type businesses, thereby improving the targeted improvement effects on specific businesses.

[0042] The application scenarios of the embodiments of the present disclosure are explained below:

[0043] Figure 1 This is an application scenario diagram of the order processing method provided by the embodiment of the present disclosure. Figure 1As shown, during the order processing process, after the server 100 collects the order issued by the user device 110, it will send a feedback evaluation page to the user device 110 when it is completed, and determine the user's specific evaluation opinion based on the result uploaded by the user after filling in.

[0044] It should be noted that Figure 1 In the scenario shown, only one user device and one server are used as an example for illustration, but the present disclosure is not limited thereto, that is, the number of user devices and servers can be arbitrary.

[0045] The order processing method provided by the present disclosure is described in detail below through specific embodiments. It should be noted that the following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments.

[0046] Figure 2 The following is a flowchart of an order processing method provided by an embodiment of the present disclosure. Figure 2 As shown, the order processing method provided in this embodiment is applied to the server, comprising the following steps:

[0047] Step S201: In response to the received first indication information, determine the order type of the completed order indicated by the first indication information.

[0048] The first indication information is used to indicate that the order is completed.

[0049] Specifically, the platform for placing orders can be an online business processing platform, such as an online business hall of a network provider, or a telephone business processing system that can select a service based on the input number after a phone call is made, such as an after-sales telephone customer service system.

[0050] An order can be a service that can be completed automatically through the server or client, such as checking broadband arrears, or it can be a service that requires manual service or on-site processing, such as problem consultation or network equipment failure handling.

[0051] In some embodiments, the first indication information is generated after the business corresponding to the order is completed. When the business is automatically completed by the mobile device, such as recharging or querying an order, the first indication information is automatically generated content; when the business requires specific staff to handle it, such as installing broadband network services, the completion of the business is generated by the specific staff through the corresponding terminal. For example, after the specific staff takes a photo and uploads the record through the mobile application, the mobile application automatically sends the first indication information to the server.

[0052] The order type may include only specific business types, such as the specific business types that users can choose to click on on the online business processing platform; or it may include both specific business types and user types. This is because for certain types of business, specific classifications will be made based on different user types. For example, broadband fault reimbursement in the telephone business processing system may include both broadband fault repairs for corporate VIP customers and broadband fault repairs for ordinary household customers. However, the processing speed and difficulty are usually significantly different, and different staff are required to handle them. In this case, the user type and the specific business type need to be combined to determine the specific order type.

[0053] There can be one or more completed orders, but the order type to which the completed order belongs is pre-configured by the system. When the server receives a completed order, it will automatically classify it into the corresponding order type.

[0054] Step S202: Obtain evaluation records of completed orders.

[0055] The evaluation record is used to indicate the evaluation content of the completed order filled in by the user, and the evaluation record includes the rating and text evaluation.

[0056] The evaluation record needs to be sent to the customer for filling out after the corresponding business of the order is completed, because the purpose is to understand the user's evaluation of the completion of the business.

[0057] Corresponding to different types of business or order types, evaluation pages with different specific contents may be generated, such as questions corresponding to specific types of business, or scores for corresponding aspects of specific business staff.

[0058] Usually the evaluation record will include both the rating and the text evaluation. During the phone call, usually when the user does not give the highest star rating, we will make a follow-up call to understand the customer's specific evaluation opinions, convert the customer's voice feedback into text evaluation, and record it.

[0059] There is generally no time requirement for obtaining the form, and it can be sent after the business is completed. In some cases, on-site staff will assist users in filling out the form, such as pointing out which content needs to be filled in or is recommended to be filled in.

[0060] Step S203: Generate user feedback results corresponding to the order type based on the evaluation records.

[0061] Among them, the user feedback results include a comprehensive score based on the score and a comprehensive evaluation based on the text evaluation.

[0062] Specifically, the comprehensive score is a total score obtained by processing the scoring results in multiple evaluation records, which is used as the evaluation result corresponding to the order type, or the specific processing personnel, or the specific scoring aspect. For example, a specific value is obtained by averaging or by a set algorithm.

[0063] The comprehensive score is generally the cumulative score of all evaluation records over a period of time or starting from a point in time, such as monthly score results, or score results after the improved version of the business system is launched.

[0064] The comprehensive evaluation is generally obtained by comprehensively processing the text evaluations in multiple evaluation records to obtain the evaluation result corresponding to the order type. Generally, the big data analysis method can be used to obtain the text evaluation result after comprehensive evaluation of all evaluation records of this order type.

[0065] In some embodiments, text evaluations and scores may also be combined to comprehensively process evaluations of different segments, or to process evaluations of specific segments, such as text evaluations of order types with scores below 80 points, to avoid situations where, when the score is too high, the user simply praises the order or business and is unable to provide suggestions for improvement.

[0066] Step S204: Based on the user feedback result, determine the targeted adjustment strategy corresponding to the order type.

[0067] Specifically, the confirmed user feedback results usually contain more content, such as comprehensive evaluation results from multiple aspects obtained through big data analysis, which also include scores. However, what actually needs to be improved and adjusted is generally started from the most important points. Therefore, it is generally necessary to find the most core point from the user feedback results, and then use it as the direction for targeted adjustments.

[0068] In some embodiments, the user feedback results can be combined with the preset word library for analysis through a preset word library, so as to find the targeted adjustment direction in the user feedback, and then obtain a targeted adjustment strategy. For example, if the preset word library contains all common improvement directions corresponding to a certain order type, then by comparing the user feedback results with the preset word library, the preset word closest to the user feedback results is determined, which is the targeted adjustment direction. For example, if the "operation response time" is "too long", the targeted adjustment strategy is to shorten the operation response time.

[0069] Exemplarily, the preset vocabulary library contains a variety of preset improvement strategies corresponding to certain businesses, such as increasing staff contact time, reducing staff delayed arrival time, etc. When the comprehensive evaluation obtained through big data analysis of user feedback results shows that the staff takes too long to contact customers, improving staff contact efficiency can be used as a targeted adjustment strategy.

[0070] The order processing method provided by the present invention determines the order type corresponding to the completed order according to the first indication information of the order completion received, obtains the evaluation record corresponding to the order type, and then generates the corresponding user feedback result based on the evaluation record, so as to determine the targeted adjustment strategy of the business corresponding to the order type. In this way, the user evaluation is effectively utilized, and the corresponding business can be improved in a targeted manner, which effectively improves the improvement effect of the online business processing platform and can effectively improve the user experience of the online business processing platform.

[0071] Figure 3 The following is a flowchart of an order processing method provided by the present disclosure. Figure 3 As shown, the order processing method provided in this embodiment includes the following steps:

[0072] Step S301: In response to the received first indication information, based on the order business type selected by the user on the order publishing platform and / or the group to which the user belongs, determine the order type of the completed order indicated by the first indication information.

[0073] Among them, the order type is used to push the order selected by the user to the processing personnel of the corresponding order type.

[0074] Among them, the order type is determined when the user places an order through the online business processing platform or the order publishing platform.

[0075] Specifically, the order type can be changed, but generally the user is required to place a new order on the order publishing platform, and it cannot be modified in real time during the processing. Therefore, the order type placed on the order publishing platform is generally used as the basis. For example, the original order type is network installation, but in fact only network equipment maintenance is required. In this case, it is generally necessary to place a new order.

[0076] When the server receives the first indication information, the order type is the determined type.

[0077] Step S302: Send an evaluation request to the client corresponding to the user.

[0078] In some embodiments, users may not be willing to spend time to provide feedback and evaluation. In this case, even if you send them an evaluation form, you generally cannot obtain valuable evaluation opinions, such as if the user just fills in a simple "like" or other clichés. Therefore, usually, you first send an evaluation request to confirm that the user is willing to provide business evaluation for the completed order, and then send the corresponding specific evaluation results.

[0079] Step S303: When receiving the second indication information from the client, push an initial evaluation page corresponding to the order type to the client.

[0080] The initial evaluation page includes a form for scoring and filling in text evaluation, and the second instruction information is used to instruct the user to choose to agree to the evaluation.

[0081] Specifically, the initial evaluation page can be saved on the device corresponding to the user. For example, when the user accesses the online business processing platform through a client application, the server only sends a command to call the page. When the user accesses it through other means, such as by phone or through a web browser, the evaluation page can be sent through the server. In the scenario of processing business through voice, the user can also be guided to complete the evaluation content of the form through voice through inquiries made by telephone return personnel.

[0082] Furthermore, the rating can be for the business as a whole, or for a specific aspect of the business, such as scoring the staff and business processing results separately; similarly, the text evaluation can be for the business as a whole, or through asking questions to understand the user's evaluation of different aspects of the business, such as the evaluation of the staff and the evaluation of the service system.

[0083] Step S304: receiving the target evaluation page uploaded by the client, and obtaining the user's evaluation record of the completed order based on the target evaluation page.

[0084] The evaluation record is used to indicate the user's evaluation of the completed order collected by the server.

[0085] Specifically, by means of page analysis, the rating and text evaluation results are extracted from the initial evaluation page of the user feedback, thereby obtaining the user's evaluation record of the completed order.

[0086] Step S305: Determine the average value of the scores corresponding to the order types.

[0087] In some embodiments, for multiple evaluations of the same order type, the user's overall evaluation of this type of business can be understood by directly calculating their average value.

[0088] In some embodiments, in subsequent further analysis, advanced data such as standard deviation may be calculated to understand the differentiation of user evaluations, thereby providing better analysis for the effective use of evaluations.

[0089] Furthermore, it also includes:

[0090] The evaluation records that only contain text evaluations or only contain ratings are eliminated; based on the ratings in the eliminated evaluation records, the average of the ratings corresponding to the order types is determined.

[0091] Among them, the results of simple ratings without textual evaluations are likely to show that users only give perfunctory evaluations. Since it is difficult to distinguish whether users have given perfunctory evaluations in this type of evaluation, it will cause confusion in user ratings and affect the calculation of the actual ratings of the order type. Therefore, this type of rating should generally be removed first.

[0092] Step S306: Determine whether the average value of the scores is greater than a set reference value.

[0093] In some embodiments, when the service itself is well completed, no improvement is needed or no improvement is needed temporarily. At this time, even if the user fills in a text evaluation, it is generally a simple praise. This type of evaluation lacks suggestions for service improvement.

[0094] Considering that this type of evaluation is mainly concentrated in high-score segments, such as the common full-score praise, therefore, by setting a benchmark value, the praise evaluation is concentrated in the segments above the benchmark value, and the text evaluation above the benchmark value is eliminated, thereby improving the analysis efficiency and increasing the accuracy and pertinence of the analysis.

[0095] Step S307: When the average value of the scores is greater than the reference value, it is determined that the targeted adjustment strategy corresponding to the order type does not require adjustment.

[0096] When the score is higher than the benchmark value, further analysis of such business is generally not required.

[0097] In some embodiments, when advanced analysis is required, low-scoring evaluation records in this type of order can be extracted to determine whether there are points that need improvement. For example, if 200 of the 10,000 evaluations are low-scoring evaluation records, and all of them point to specific behaviors of specific staff members, then targeted improvements need to be made to the behaviors of the specific staff members.

[0098] Step S308: When the average value of the ratings is less than or equal to the reference value, keyword analysis is performed on the text evaluation based on a preset vocabulary.

[0099] Specifically, a vocabulary library is preset in the server to store the categories of text evaluations, such as "staff" / "master" / "worker" / "person" is used to refer to the staff who handles orders, and "noisy", "loud" and "noisy" are used to refer to the loud noises made by the staff during the on-site processing process. Through the keyword recognition method, keywords are extracted from a single text evaluation to obtain the aspects it targets, such as the operational links that need to be improved during the on-site processing process of the staff.

[0100] In some embodiments, meaningless content in the text evaluation can also be filtered out through a preset vocabulary, such as "well done", and then specific references in the text evaluation can be extracted through regular expressions and other algorithms to obtain the aspects targeted by the text evaluation, such as components on the online business processing platform such as "buttons", "interfaces" or "icons", and the sentence as a whole can be extracted as a specific reference.

[0101] Furthermore, based on the ratings in the evaluation records after eliminating the evaluation records without textual evaluations, the textual evaluations corresponding to the different ratings are marked respectively; based on the marked textual evaluations, user feedback results of the corresponding order types are generated.

[0102] By eliminating pure rating evaluation records, we can effectively ensure that the evaluation records obtained are all content that users have spent time filling out, thereby ensuring the availability of the evaluation records.

[0103] By extracting reviews from multiple different rating segments separately, more effective and targeted suggestions can be obtained. For example, a low-score segment may be more likely to be composed of pure complaint-type reviews, while a medium-score segment will point out specific problematic aspects. At this time, after extracting text reviews from different ratings and segments separately, pure complaint-type reviews are filtered out, and then the remaining text reviews are analyzed through big data, such as word frequency analysis, to obtain the final text review set as the user feedback result, effectively ensuring the availability of the user feedback result.

[0104] Step S309: Determine evaluation keywords for the order type based on the frequency of keyword occurrence and the degree of matching between the keyword and the preset vocabulary.

[0105] Since the words in the preset word library are usually simple in type and fixed in length, it is obviously impossible to cover all the terms used in text reviews. Therefore, a preset word library can be set up to reversely eliminate worthless comments. For example, a matching algorithm can be used to find the core points or core words in the text reviews after keyword analysis, and then eliminate the aspects that cannot be improved. For example, if a user complains about the gender of the service staff or the excessive number of people who go to handle the problem, these problems are generally simple complaints and are difficult to solve by improving the service or system.

[0106] Step S310: Combine the evaluation keywords with the text evaluation to obtain user feedback results of the order type.

[0107] In some embodiments, after the text evaluation is segmented through regular expressions or other text processing algorithms, sentences containing keywords are used as evaluation conclusions, such as sentences containing "staff" as evaluation conclusions, and the keyword sentences obtained by combining the text evaluations in different evaluation records are compared for repetition, and finally a core evaluation can be obtained. This core evaluation can be used as the user feedback result of this order type.

[0108] In some embodiments, there are usually multiple core evaluations of this type, so the multiple core evaluations can be arranged according to frequency as the final user feedback result corresponding to the order type.

[0109] Step S311: Use the user feedback results of the order type as a targeted adjustment strategy and output it to relevant personnel.

[0110] In some embodiments, according to pre-settings, multiple user feedback results may be used as targeted adjustment strategies, or only the core evaluations with the highest frequency may be output as targeted adjustment strategies.

[0111] Generally, relevant personnel may be system maintenance personnel, if the evaluation is for a system that automatically completes orders, or they may be managers of related businesses, if the evaluation is for businesses that require staff participation.

[0112] The order processing method provided by the present disclosure determines the order type according to the business type and user group selected by the user on the order release platform when the first indication information of the order completion is received, and then sends an evaluation request to the user, and when the user agrees, sends a message for evaluating the order. After the user uploads the evaluation, the corresponding evaluation record is obtained, and the average score in the evaluation record is extracted. According to the comparison between the average score and the preset benchmark value, it is determined whether the business of the order type needs to be improved. When improvement is needed, the corresponding user feedback result is obtained by processing the corresponding text evaluation content, and then a targeted adjustment strategy is obtained based on the user feedback result and output. In this way, the user evaluation can be effectively utilized, and the specific improvement direction in the user evaluation can be obtained through data processing. Since the method processes all businesses of the same order type, it effectively ensures that the targeted adjustment strategy finally obtained can meet the overall feedback opinion tendency of the user, thereby effectively improving the improvement effect of the online business processing platform and effectively improving the user experience of the online business processing platform.

[0113] Figure 4 The following is a schematic diagram of the structure of an order processing device provided by the present disclosure. Figure 4 As shown, the order processing device 400 includes: an acquisition module 410 and a processing module 420. Among them:

[0114] The acquisition module 410 is used to determine, in response to the received first indication information, the order type of the completed order indicated by the first indication information, where the first indication information is used to indicate that the order is completed; and to acquire an evaluation record of the completed order, where the evaluation record is used to indicate the evaluation content of the completed order filled in by the user, and the evaluation record includes a score and a text evaluation;

[0115] Processing module 420 is used to generate user feedback results corresponding to the order type based on the evaluation records, the user feedback results including a comprehensive score based on the score and a comprehensive evaluation based on the text evaluation; and, based on the user feedback results, determine the targeted adjustment strategy corresponding to the order type.

[0116] Optionally, the acquisition module 410 is specifically used to determine, in response to the received first indication information, the order type of the completed order indicated by the first indication information based on the order business type selected by the user on the order publishing platform and / or the group to which the user belongs, and the order type is used to push the order selected by the user to the processing personnel of the corresponding order type.

[0117] Optionally, the acquisition module 410 is specifically used to, in response to receiving a first indication message, send an evaluation request to a client corresponding to the user; when receiving a second indication message from the client, push an initial evaluation page of the corresponding order type to the client, the initial evaluation page includes a form for scoring and filling in a text evaluation, and the second indication message is used to indicate that the user chooses to agree to the evaluation; receive a target evaluation page uploaded by the client, and obtain the user's evaluation record for the completed order based on the target evaluation page.

[0118] Optionally, the processing module 420 is specifically used to determine the average value of the score corresponding to the order type; determine whether the average value of the score is greater than a set benchmark value; when the average value of the score is less than or equal to the benchmark value, generate user feedback results for the corresponding order type based on text evaluation.

[0119] Optionally, the processing module 420 is specifically used to perform keyword analysis on text reviews based on a preset vocabulary; determine evaluation keywords for order types based on keyword occurrence frequency and the degree of match between the keywords and the preset vocabulary; and combine the evaluation keywords with the text reviews to obtain user feedback results for the order types.

[0120] Optionally, processing module 420 is specifically used to eliminate records in evaluation records that only contain text evaluations or only contain ratings; determine the average value of the ratings corresponding to the order type based on the ratings in the eliminated evaluation records; correspondingly, generate user feedback results of the corresponding order type based on the text evaluations, including: based on the ratings in the eliminated evaluation records, respectively marking the text evaluations corresponding to different ratings; and generating user feedback results of the corresponding order type based on the marked text evaluations.

[0121] Optionally, the processing module 420 is specifically used to, when the average value of the score is greater than a benchmark value, determine that the targeted adjustment strategy corresponding to the order type does not require adjustment; when the average value of the score is less than or equal to the benchmark value, output the user feedback results of the order type as a targeted adjustment strategy to relevant personnel.

[0122] In this embodiment, the order processing device can obtain improvement suggestions for corresponding business order types based on user feedback and evaluation through the combination of various modules, thereby effectively ensuring that targeted improvements can be made in the areas of user feedback and evaluation, which can not only improve the business processing capabilities of the online business processing platform or order publishing platform, but also gradually improve the user experience.

[0123] Figure 5 A schematic diagram of the structure of an electronic device provided by the present disclosure, such as Figure 5 As shown, the electronic device 500 includes: a memory 510 and a processor 520 .

[0124] The memory 510 stores a computer program that can be executed by at least one processor 520. The computer program is executed by at least one processor 520 to enable the electronic device to implement the user terminal state management method provided in any of the above embodiments.

[0125] The memory 510 and the processor 520 may be connected via a bus 530 .

[0126] The relevant instructions can be understood by referring to the relevant descriptions and effects corresponding to the method embodiments, which will not be repeated here.

[0127] An embodiment of the present disclosure provides a computer-readable storage medium having a computer program stored thereon, and the computer program is executed by a processor to implement the following Figures 2 to 3 The order processing method of any corresponding embodiment.

[0128] Among them, the computer-readable storage medium may be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like.

[0129] An embodiment of the present disclosure provides a computer program product, which includes computer-executable instructions. When the computer-executable instructions are executed by a processor, the computer-executable instructions are used to implement the following Figures 2 to 3 The order processing method of any embodiment corresponding to the present invention, and / or the computer-executable instruction is used to implement the following when executed by the processor: Figure 4 The order processing method of the corresponding embodiment.

[0130] In the several embodiments provided in the present disclosure, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of modules is only a logical function division, and there may be other division methods in actual implementation, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or modules, which can be electrical, mechanical or other forms.

[0131] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the disclosure disclosed herein. The present disclosure is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The description and examples are to be considered exemplary only, and the true scope and spirit of the present disclosure are indicated by the following claims.

[0132] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. An order processing method, characterized in that: The order processing method comprises: In response to the received first indication information, determining the order type of the completed order indicated by the first indication information, wherein the first indication information is used to indicate that the order is completed; Obtaining an evaluation record of the completed order, wherein the evaluation record is used to indicate the evaluation content of the completed order filled in by the user, and the evaluation record includes a score and a text evaluation; Based on the evaluation record, generating a user feedback result corresponding to the order type, the user feedback result including a comprehensive score obtained based on the score and a comprehensive evaluation obtained based on the text evaluation; Based on the user feedback results, determine a targeted adjustment strategy corresponding to the order type; The generating a user feedback result corresponding to the order type based on the evaluation record includes: Determine an average value of the scores corresponding to the order type; Determine whether the average value of the scores is greater than a set benchmark value; When the average value of the ratings is less than or equal to the reference value, a keyword analysis is performed on the text evaluation based on a preset word library, wherein the preset word library is used to reversely eliminate worthless comments; Determine the evaluation keywords of the order type according to the frequency of keyword occurrence and the matching degree between the keyword and the preset vocabulary; Segmenting the text evaluation, and taking sentences containing evaluation keywords as evaluation conclusions; Compare the repetition of the keyword sentences obtained by combining different text reviews to obtain multiple core reviews; The multiple core evaluations are arranged according to frequency as the user feedback results corresponding to the order type.

2. The order processing method according to claim 1, characterized in that: The step of determining, in response to the received first indication information, the order type of the completed order indicated by the first indication information comprises: In response to the first indication information received, based on the order business type selected by the user on the order publishing platform and / or the group to which the user belongs, the order type of the completed order indicated by the first indication information is determined, and the order type is used to push the order selected by the user to the processing personnel of the corresponding order type.

3. The order processing method according to claim 1, characterized in that: The obtaining of the evaluation record of the completed order includes: In response to receiving the first indication information, sending an evaluation request to a client corresponding to the user; Upon receiving the second indication information from the client, an initial evaluation page corresponding to the order type is pushed to the client, the initial evaluation page including a form for scoring and filling in a text evaluation, and the second indication information is used to instruct the user to select to agree to the evaluation; The target evaluation page uploaded by the client is received, and based on the target evaluation page, a user's evaluation record for the completed order is obtained.

4. The order processing method according to claim 1, characterized in that: Determining the average value of the scores corresponding to the order types includes: Eliminate the evaluation records that only contain text evaluations or only contain ratings; Determine an average value of the scores corresponding to the order type based on the scores in the evaluation records after elimination; Correspondingly, generating a user feedback result corresponding to the order type based on the text evaluation includes: Based on the ratings in the eliminated evaluation records, the text evaluations corresponding to the different ratings are marked respectively; based on the marked text evaluations, a user feedback result corresponding to the order type is generated.

5. The order processing method according to claim 1, characterized in that: Determining a targeted adjustment strategy corresponding to the order type based on the user feedback result includes: When the average value of the score is greater than the reference value, determining that the targeted adjustment strategy corresponding to the order type does not need to be adjusted; When the average value of the ratings is less than or equal to the benchmark value, the user feedback results of the order type are output to relevant personnel as a targeted adjustment strategy.

6. An order processing device, characterized in that: include: an acquisition module, configured to determine, in response to received first indication information, an order type of a completed order indicated by the first indication information, wherein the first indication information is used to indicate that an order is completed; and obtaining an evaluation record of the completed order, wherein the evaluation record is used to indicate the evaluation content of the completed order filled in by the user, and the evaluation record includes a score and a text evaluation; A processing module, configured to generate a user feedback result corresponding to the order type based on the evaluation record, wherein the user feedback result includes a comprehensive score obtained based on the score and a comprehensive evaluation obtained based on the text evaluation; And, based on the user feedback result, determining a targeted adjustment strategy corresponding to the order type; The processing module is specifically used to determine the average value of the score corresponding to the order type; determine whether the average value of the score is greater than a set reference value; when the average value of the score is less than or equal to the reference value, perform keyword analysis on the text evaluation based on a preset word library; determine the evaluation keyword of the order type according to the frequency of keyword occurrence and the matching degree of the keyword with the preset word library; The text evaluation is segmented, and sentences containing evaluation keywords are used as evaluation conclusions; keyword sentences obtained by combining different text evaluations are compared for repetition to obtain multiple core evaluations; the multiple core evaluations are arranged according to frequency as user feedback results corresponding to the order type; wherein the preset vocabulary is used to reversely eliminate worthless comments.

7. An electronic device, characterized in that: include: at least one processor; and a memory communicatively coupled to the at least one processor; The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the electronic device to perform the order processing method as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which are used to implement the order processing method according to any one of claims 1 to 5 when executed by a processor.

9. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the order processing method according to any one of claims 1 to 5 is implemented.

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