CN113869576A - Order processing method, device, equipment and storage medium - Google Patents
Order processing method, device, equipment and storage medium Download PDFInfo
- Publication number
- CN113869576A CN113869576A CN202111126951.XA CN202111126951A CN113869576A CN 113869576 A CN113869576 A CN 113869576A CN 202111126951 A CN202111126951 A CN 202111126951A CN 113869576 A CN113869576 A CN 113869576A
- Authority
- CN
- China
- Prior art keywords
- evaluation
- order
- user
- indication information
- feedback result
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000003672 processing method Methods 0.000 title claims abstract description 35
- 238000011156 evaluation Methods 0.000 claims abstract description 259
- 238000012545 processing Methods 0.000 claims abstract description 45
- 230000004044 response Effects 0.000 claims abstract description 18
- 238000004458 analytical method Methods 0.000 claims description 16
- 238000000034 method Methods 0.000 abstract description 18
- 230000006872 improvement Effects 0.000 description 15
- 230000008569 process Effects 0.000 description 8
- 238000010586 diagram Methods 0.000 description 6
- 238000004590 computer program Methods 0.000 description 5
- 238000004422 calculation algorithm Methods 0.000 description 4
- 230000008878 coupling Effects 0.000 description 3
- 238000010168 coupling process Methods 0.000 description 3
- 238000005859 coupling reaction Methods 0.000 description 3
- 238000007405 data analysis Methods 0.000 description 3
- 230000000694 effects Effects 0.000 description 3
- 238000007726 management method Methods 0.000 description 3
- 230000006399 behavior Effects 0.000 description 2
- 238000004891 communication Methods 0.000 description 2
- 230000006870 function Effects 0.000 description 2
- 230000008439 repair process Effects 0.000 description 2
- 238000012935 Averaging Methods 0.000 description 1
- 206010048669 Terminal state Diseases 0.000 description 1
- 230000006978 adaptation Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 239000002131 composite material Substances 0.000 description 1
- 230000001186 cumulative effect Effects 0.000 description 1
- 238000013500 data storage Methods 0.000 description 1
- 230000004069 differentiation Effects 0.000 description 1
- 230000005059 dormancy Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000002349 favourable effect Effects 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/20—Natural language analysis
- G06F40/279—Recognition of textual entities
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/06—Buying, selling or leasing transactions
- G06Q30/0601—Electronic shopping [e-shopping]
- G06Q30/0633—Lists, e.g. purchase orders, compilation or processing
- G06Q30/0635—Processing of requisition or of purchase orders
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/06—Buying, selling or leasing transactions
- G06Q30/0601—Electronic shopping [e-shopping]
- G06Q30/0641—Shopping interfaces
- G06Q30/0643—Graphical representation of items or shoppers
Abstract
The disclosure provides an order processing method, an order processing device and a storage medium, which are applied to intelligent equipment. The method comprises the following steps: in response to the received first indication information, determining an order type of a completed order indicated by the first indication information, wherein the first indication information is used for indicating order completion; acquiring an evaluation record of a completed order, wherein the evaluation record is used for representing the evaluation content of the completed order filled by a user and comprises a score and character evaluation; based on the evaluation record, generating a user feedback result corresponding to the order type, wherein the user feedback result comprises a comprehensive score obtained based on the score and a comprehensive evaluation obtained based on the character evaluation; and determining a pertinence adjustment strategy corresponding to the order type based on the user feedback result. The technical scheme disclosed by the invention realizes the purpose of effectively utilizing the opinions fed back by the user and realizing the targeted adjustment of specific services.
Description
Technical Field
The present disclosure relates to the field of order management technologies, and in particular, to an order processing method, an order processing apparatus, an order processing device, and a storage medium.
Background
Along with the popularization of the online business handling platform, more and more offline businesses or simple services can be applied and handled on the online business handling platform, so that the business handling efficiency can be improved, and a user can conveniently and quickly apply for business handling.
The existing online service handling platform usually sets a feedback evaluation function corresponding to service handling, but generally needs to manually identify specific feedback opinions, and is difficult to perform targeted adjustment on specific services through the feedback opinions.
Disclosure of Invention
The present disclosure provides an order processing method, apparatus, device and storage medium, so as to effectively utilize the opinion fed back by the user to realize the targeted adjustment of specific services.
In a first aspect, the present disclosure provides an order processing method applied to an intelligent device, where the order processing method includes:
in response to the received first indication information, determining an order type of a completed order indicated by the first indication information, wherein the first indication information is used for indicating order completion;
acquiring an evaluation record of a completed order, wherein the evaluation record is used for representing the evaluation content of the completed order filled by a user and comprises a score and character evaluation;
based on the evaluation record, generating a user feedback result corresponding to the order type, wherein the user feedback result comprises a comprehensive score obtained based on the score and a comprehensive evaluation obtained based on the character evaluation;
and determining a pertinence adjustment strategy corresponding to the order type based on the user feedback result.
Optionally, in response to the received first indication information, determining an order type of the completed order indicated by the first indication information includes: and in response to the received first indication information, determining an 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 where the user is located, wherein the order type is used for pushing the order selected by the user to a processing person of the corresponding order type.
Optionally, obtaining an 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; when second indication information from the client is received, an initial evaluation page corresponding to the order type is pushed to the client, the initial evaluation page comprises a form for grading and filling in character evaluation, and the second indication information is used for indicating that a user selects to agree with the evaluation; and receiving a target evaluation page uploaded by the client, and acquiring the evaluation record of the user on the completed order based on the target evaluation page.
Optionally, based on the evaluation record, generating a user feedback result corresponding to the order type, including: determining the average value of the scores corresponding to the order types; determining whether the average value of the scores is larger than a set reference value; and when the average value of the scores is smaller than or equal to the reference value, generating a user feedback result corresponding to the order type based on the character evaluation.
Optionally, based on the text evaluation, generating a user feedback result corresponding to the order type, including: performing keyword analysis on the character evaluation based on a preset word bank; determining evaluation keywords of the order types according to the occurrence frequency of the keywords and the matching degree of the keywords and a preset word bank; and combining the evaluation keywords with the character evaluation to obtain a user feedback result of the order type.
Optionally, determining an average value of scores corresponding to the order types includes: removing records which only contain character evaluation or only contain scores from the evaluation records; determining the average value of the scores corresponding to the order types based on the scores in the rejected evaluation records; correspondingly, based on the character evaluation, a user feedback result corresponding to the order type is generated, and the method comprises the following steps: respectively marking character evaluations corresponding to different grades based on the grades in the rejected evaluation records; and generating a user feedback result corresponding to the order type based on the marked character evaluation.
Optionally, determining a targeted adjustment policy corresponding to the order type based on the user feedback result includes: when the average value of the scores is larger than the reference value, determining that the pertinence adjustment strategy corresponding to the order type does not need to be adjusted; and when the average value of the scores is smaller than or equal to the reference value, outputting the user feedback result of the order type to related personnel as a targeted adjustment strategy.
In a second aspect, the present disclosure provides an order processing apparatus comprising:
the obtaining module is used for responding 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 for indicating the order completion; acquiring an evaluation record of the completed order, wherein the evaluation record is used for representing the evaluation content of the completed order filled by the user and comprises a score and character evaluation;
the processing module is used for generating a user feedback result corresponding to the order type based on the evaluation record, wherein the user feedback result comprises a comprehensive score obtained based on the score and a comprehensive evaluation obtained based on the character evaluation; and determining a pertinence adjustment strategy corresponding to the order type based on the user feedback result.
Optionally, the obtaining module is specifically configured to, in response to the received first indication information, determine an order type of a completed order indicated by the first indication information based on an order service type selected by the user on the order issuing platform and/or a group in which the user is located, where the order type is used to push the order selected by the user to a handler of the corresponding order type.
Optionally, the obtaining module is specifically configured to, in response to receiving the first indication information, send an evaluation request to a client corresponding to the user; when second indication information from the client is received, an initial evaluation page corresponding to the order type is pushed to the client, the initial evaluation page comprises a form for grading and filling in character evaluation, and the second indication information is used for indicating that a user selects to agree with the evaluation; and receiving a target evaluation page uploaded by the client, and acquiring the evaluation record of the user on the completed order based on the target evaluation page.
Optionally, the processing module is specifically configured to determine an average value of scores corresponding to the order types; determining whether the average value of the scores is larger than a set reference value; and when the average value of the scores is smaller than or equal to the reference value, generating a user feedback result corresponding to the order type based on the character evaluation.
Optionally, the processing module is specifically configured to perform keyword analysis on the word evaluation based on a preset lexicon; determining evaluation keywords of the order types according to the occurrence frequency of the keywords and the matching degree of the keywords and a preset word bank; and combining the evaluation keywords with the character evaluation to obtain a user feedback result of the order type.
Optionally, the processing module is specifically configured to remove records that only contain text evaluation or only contain scores from the evaluation records; determining the average value of the scores corresponding to the order types based on the scores in the rejected evaluation records; correspondingly, based on the character evaluation, a user feedback result corresponding to the order type is generated, and the method comprises the following steps: respectively marking character evaluations corresponding to different grades based on the grades in the rejected evaluation records; and generating a user feedback result corresponding to the order type based on the marked character evaluation.
Optionally, the processing module is specifically configured to determine that a targeted adjustment policy corresponding to the order type does not need to be adjusted when the average value of the scores is greater than the reference value; and when the average value of the scores is smaller than or equal to the reference value, outputting the user feedback result of the order type to related personnel as a targeted adjustment strategy.
In a third aspect, the present disclosure provides an electronic device comprising:
at least one processor;
and a memory communicatively coupled to the at least one processor;
wherein the memory stores instructions executable by the at least one processor, the instructions being executable by the at least one processor to cause the electronic device to perform the order processing method according to any of the first aspect.
In a fourth aspect, the present disclosure also provides a computer-readable storage medium having stored therein computer-executable instructions for implementing the order processing method according to any one of the first aspect of the present disclosure when executed by a processor.
According to the order processing method, the order processing device, the order processing equipment and the storage medium, the order type corresponding to the completed order is determined according to the received first indication information of order completion, the evaluation record corresponding to the order type is obtained, and then the corresponding user feedback result is generated based on the evaluation record so as to determine the pertinence adjustment strategy of the business corresponding to the order type.
Drawings
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 disclosure.
Fig. 1 is an application scenario diagram of an order processing method according to an embodiment of the present disclosure;
FIG. 2 is a flow chart of an order processing method provided by an embodiment of the present disclosure;
FIG. 3 is a flow chart of an order processing method according to another embodiment of the present disclosure;
FIG. 4 is a schematic structural diagram of an order processing apparatus according to another embodiment of the present disclosure;
fig. 5 is a schematic structural diagram of an electronic device according to yet another embodiment of the present disclosure.
With the foregoing drawings in mind, certain embodiments of the disclosure have been shown and described in more detail below. These drawings and written description are not intended to limit the scope of the disclosed concepts in any way, but rather to illustrate the concepts of the disclosure to those skilled in the art by reference to specific embodiments.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the exemplary embodiments below are not intended to represent all implementations consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present disclosure, as detailed in the appended claims.
The following describes the technical solutions of the present disclosure and how to solve the above technical problems in specific embodiments. The following several specific embodiments may be combined with each other, and details of the same or similar concepts or processes may not be repeated in some embodiments. Embodiments of the present disclosure will be described below with reference to the accompanying drawings.
A plurality of existing online business handling platforms or telephone business handling systems provide users with a fast channel for directly handling various businesses online by presetting different business types. After the preset service type is completed, the online service handling platform usually provides a feedback opinion page, for example, through user evaluation, to know the completion of the specific service, and accordingly improve the service. However, in the prior art, the page corresponding to the feedback opinions is usually screened manually, and part of representative feedback evaluations are selected for processing, so that a large amount of feedback is wasted, and the selected result is difficult to ensure that all feedback opinions are effectively represented, so that it is difficult to perform targeted adjustment on specific services through the feedback opinions in actual processing.
In order to solve the above problem, an embodiment of the present disclosure provides an order processing method, which performs processing based on an evaluation record of a specific order type, and automatically generates a comprehensive user feedback result, so that a pertinence adjustment policy for a service corresponding to the order type can be directly generated, and a pertinence improvement effect on the specific service is improved.
The following explains an application scenario of the embodiment of the present disclosure:
fig. 1 is an application scenario diagram of an order processing method according to an embodiment of the present disclosure. As shown in fig. 1, in the process of processing an order, after the server 100 collects an order sent by the user equipment 110, a feedback evaluation page is sent to the user equipment 110 when the order is completed, and a specific evaluation opinion of the user is determined according to an uploaded result after the user fills in the feedback evaluation page.
It should be noted that, in the scenario shown in fig. 1, the user equipment and the server are illustrated as an example, but the disclosure is not limited thereto, that is, the number of the user equipment and the server may be any.
The order processing method provided by the present disclosure is explained in detail by specific embodiments below. It should be noted that the following specific embodiments may be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments.
Fig. 2 is a flowchart of an order processing method according to an embodiment of the present disclosure. As shown in fig. 2, the order processing method provided by this embodiment is applied to a server, and includes the following steps:
step S201, in response to the received first indication information, determining an order type of the completed order indicated by the first indication information.
The first indication information is used for indicating order completion.
Specifically, the platform for issuing the order may be an online service handling platform, such as an online business hall of a network provider, or a telephone service handling system, such as an after-sales telephone service system, capable of selecting a service according to an input number after dialing a telephone number.
The order can be a service which can be automatically completed by a server or a client, such as inquiring broadband arrearages, or a service which needs manual service or goes to the field for processing, such as problem consultation or network equipment failure processing service.
In some embodiments, the first indication information is generated after a service corresponding to the order is completed, and when the service is a service automatically completed by the mobile device, such as a recharge payment or an inquiry order, the first indication information is automatically generated content; when the service needs to be processed by a specific worker, such as the installation of a broadband network service, the completion of the service is generated by the specific worker through the corresponding terminal, and if the specific worker takes a picture through the mobile terminal application and uploads a record, the mobile terminal application automatically sends first indication information to the server.
The order type may only include a specific service type, such as a specific service type that a user may select to click in the online service transaction platform; the method can also comprise specific service types and user types, because for some types of services, specific classification differences can be generated according to different user types, such as broadband fault reimbursement in a telephone service handling system, broadband fault repair of enterprise VIP customers and broadband fault repair of common family customers can be simultaneously included, but the processing speed and the processing difficulty are usually obviously different, different workers are required to process the services, and the user types and the specific service types need to be combined to determine the specific order types.
The completed orders may have one or more types, but the type of the order to which the completed orders belong is configured in advance by the system, and when the completed orders are received by the server, the completed orders are automatically classified into the corresponding order types.
Step S202, obtaining the evaluation record of the completed order.
The evaluation records are used for representing the evaluation content of the completed orders filled by the user, and the evaluation records comprise scores and character evaluation.
The evaluation records need to be sent to the client for filling after the service corresponding to the order is completed, because the purpose is to know the evaluation of the user on the service completion condition.
For different types of services or types of orders, evaluation pages with different specific contents may be generated, such as questions including corresponding to specific service types or scores corresponding to aspects of specific service staff.
Generally, the evaluation record comprises two aspects of rating and text evaluation, and in the telephone, when the user does not give the highest favorable rating, the user generally knows the specific evaluation opinions of the user by means of telephone return visit, converts the voice information fed back by the user into text evaluation and records the text evaluation.
The acquisition mode generally has no time requirement, and the acquisition mode is sent after the service is completed, and in some cases, field workers can assist the user in filling, such as indicating which contents need to be filled or suggesting to be filled.
And step S203, generating a user feedback result corresponding to the order type based on the evaluation record.
And the user feedback result comprises a comprehensive score obtained based on the score and a comprehensive evaluation obtained based on the character evaluation.
Specifically, the comprehensive score is a total score obtained by processing the scoring results in the plurality of evaluation records, and the total score is used as the evaluation result corresponding to the order type, or the specific processing personnel, or the specific scoring aspect. Such as by averaging, or by a set algorithm.
The composite score is generally a score in a total evaluation record of a cumulative statistic for a time period or from a time point, such as a monthly score or a score after an improved version of the business system is brought online.
The comprehensive evaluation is generally an evaluation result corresponding to the order type obtained by comprehensively processing character evaluation in a plurality of evaluation records, and generally a big data analysis method can be adopted to obtain a character evaluation result after all the evaluation records of the order type are integrated.
In some embodiments, the text evaluation and the score may be combined, and the evaluation of different segments may be processed comprehensively, or the evaluation of a specific segment may be processed, for example, the text evaluation of an order type below 80 scores, so as to avoid a situation where the user merely praise an order or service when the score is too high, and thus cannot provide an improvement suggestion.
And step S204, determining a pertinence adjustment strategy corresponding to the order type based on the user feedback result.
Specifically, the determined user feedback result usually has more contents, such as a comprehensive evaluation result of multiple aspects obtained after big data analysis, and also includes a score, but actually, the adjustment needs to be improved, which is usually started from the most important point, and therefore, the most core point is generally found from the user feedback result and then is taken as the direction of the targeted adjustment.
In some embodiments, the user feedback result and the preset lexicon can be combined for analysis through the preset lexicon, so that the targeted adjustment direction in the user feedback is found, and a targeted adjustment strategy is obtained. If the preset word bank contains all common improvement directions corresponding to a certain order type, the preset word which is closest to the user feedback result is determined through comparing the user feedback result with the preset word bank, namely the preset word is the direction of the targeted adjustment, and if the operation response time is too long, the targeted adjustment strategy is to shorten the operation response time.
Illustratively, a preset word bank is provided with a plurality of preset improvement strategies corresponding to certain services, such as improving contact time of workers, reducing delay arrival time of the workers and the like, and when the comprehensive evaluation obtained through analysis of big data of user feedback results indicates that the contact time of the workers with customers is too long, the improvement of contact efficiency of the workers can be used as a targeted adjustment strategy.
According to the order processing method, the order type corresponding to the completed order is determined according to the received first indication information of order completion, the evaluation record corresponding to the order type is obtained, and the corresponding user feedback result is generated based on the evaluation record so as to determine the pertinence adjustment strategy of the business corresponding to the order type.
FIG. 3 is a flow chart of an order processing method provided by the present disclosure. As shown in fig. 3, the order processing method provided in this embodiment includes the following steps:
step S301, in response to the received first indication information, determining an order type of a completed order indicated by the first indication information based on an order service type selected by a user on an order issuing platform and/or a group where the user is located.
The order type is used for pushing the order selected by the user to a processing person corresponding to the order type.
The order type is determined when a user places an order through the online service transaction platform or the order publishing platform.
Specifically, the order type may be changed, but generally, the user is required to place an order again on the order issuing platform, and the order cannot be modified in real time in the processing process, so the order type placed on the order issuing platform is generally used as the standard, for example, the original order type is installed in a network, but actually, only the network equipment needs to be overhauled, and at this time, the order is generally placed again.
When the server receives the first indication information, the order type is the determined type.
And step S302, sending an evaluation request to a client corresponding to the user.
In some embodiments, the user may not be willing to spend time feedback for rating, and even if a rating form is sent to the user, valuable ratings are generally not available, such as the user simply filling in a simple "good comment" type of conversation. Therefore, it is usually determined that the user is willing to perform service evaluation on the completed order by sending an evaluation request, and then sending a corresponding specific evaluation result.
Step S303, when receiving the second indication information from the client, pushing an initial evaluation page corresponding to the order type to the client.
The initial evaluation page comprises a form for grading and filling in character evaluation, and the second indication information is used for indicating that the user chooses to agree with the evaluation.
Specifically, the initial evaluation page may be stored at a device side corresponding to the user, for example, when the user accesses the online service management platform through the client application, the server only sends a command for calling the page at this time; when the user accesses the evaluation page in other modes, such as telephone access or network browser access, the evaluation page can be sent through the server; in the scene of handling business by voice, the user can be guided to complete the evaluation content of the form by voice through the inquiry of the call visitor.
Further, the scoring may be only for the whole service, or may be for a specific aspect of the service, such as scoring the staff and the service processing result respectively; similarly, the text evaluation can be specific to the whole business, and also can be used for knowing the evaluation of the user on different aspects of the business, such as the evaluation on the staff and the evaluation on the service system, in a questioning mode.
And step S304, receiving a target evaluation page uploaded by the client, and acquiring the evaluation record of the completed order by the user based on the target evaluation page.
The evaluation record is used for representing the evaluation of the user on the completed order collected by the server.
Specifically, by means of page analysis, a score and a character evaluation result are extracted from an initial evaluation page fed back by a user, so that an evaluation record of the user on the completed order is obtained.
And step S305, determining the average value of the scores corresponding to the order types.
In some embodiments, for multiple evaluations of the same order type, the overall evaluation of the service by the user can be known by directly calculating the average value of the evaluations.
In some embodiments, the advanced data such as the standard deviation may also be calculated during further subsequent analysis, so as to understand the evaluation differentiation condition of the user, thereby providing a better analysis for effective utilization of the evaluation.
Further, still include:
removing records which only contain character evaluation or only contain scores from the evaluation records; and determining the average value of the scores corresponding to the order types based on the scores in the rejected evaluation records.
In this case, the result of simple scoring without text evaluation is likely to be the case where the user is only evaluating the expression property. Since such evaluations make it difficult to distinguish whether the user has an impression evaluation, the calculation of the actual rating for the order type is affected by confusion that may cause the user to rate. Therefore, such scores are typically removed first.
And step S306, determining whether the average value of the scores is larger than a set reference value.
In some embodiments, when the service itself is well completed, no improvement is needed, or no improvement is needed for a while, in this case, even if the user fills in the text evaluation, it is generally simply praised. Such evaluations lack advice on business improvement.
Consider that such evaluations are focused primarily on high scoring segments, such as the common full score. Therefore, by setting the reference value, the expressive evaluation is concentrated on the sections with the reference value or more, and the character evaluation with the reference value or more is eliminated, so that the analysis efficiency can be improved, and the accuracy and pertinence of the analysis can be improved.
And step S307, when the average value of the scores is larger than the reference value, determining that the pertinence adjustment strategy corresponding to the order type does not need to be adjusted.
When the score is above a baseline value, further analysis of such traffic is generally not required.
In some embodiments, when an advanced analysis is required, low score rating records in such order types may be extracted to determine if there are points that need improvement. If 200 of 10000 evaluations are low score evaluation records and all point to specific behavior of a specific worker, targeted improvement on the behavior of the specific worker is needed.
And S308, when the average value of the scores is smaller than or equal to the reference value, performing keyword analysis on the character evaluation based on a preset word bank.
Specifically, a word bank is preset in the server to store the categories of character evaluations, such as 'staff'/'master'/'worker'/'person' is used for indicating staff who process orders, and 'loud', 'sound' and 'alarm' are used for indicating that noise of the staff in the field processing process is large.
In some embodiments, meaningless contents in the text evaluation may also be screened out through a preset lexicon, for example, "do it well", and then a specific direction in the text evaluation is extracted through an algorithm such as a regular expression, so as to obtain an aspect targeted by the text evaluation, for example, an element on an online business handling platform relating to a "button", "interface", or "icon", and the sentence is extracted as a whole as the specific direction.
Further, marking character evaluations corresponding to different grades respectively based on the grades in the evaluation records after the evaluation records without character evaluations are removed; and generating a user feedback result corresponding to the order type based on the marked character evaluation.
By removing the evaluation records classified by pure evaluation, the obtained evaluation records are effectively guaranteed to be the contents filled by the user in time, and the usability of the evaluation records is further guaranteed.
The evaluation of various different evaluation segments is separately extracted, suggestions can be effectively obtained in a targeted manner, if the low segments are possibly more pure complaint type evaluation sets, the middle segments can indicate specific problematic aspects, at the moment, the evaluation of the pure complaint type is screened out after the text evaluation of the different scores and the segments is separately extracted, and then the final text evaluation set is obtained through big data analysis, such as word frequency analysis and the like, on the remaining text evaluation, and is used as a user feedback result, so that the usability of the user feedback result is effectively ensured.
And S309, determining the evaluation keyword of the order type according to the occurrence frequency of the keyword and the matching degree of the keyword and a preset word bank.
Because the types of words in the preset word bank are simple, the length of the words is fixed, and the word condition of all character evaluations can not be covered obviously, the preset word bank for reversely rejecting worthless comments can be set, and if the core point or the core word in the character evaluations after the keyword analysis can be found through a matching algorithm, the aspect which can not be improved is rejected. Such as a customer complaining about a sex problem of a service person or an excessive number of persons going to the process, such problems are generally pure complaints and are difficult to solve by improving the service or system.
And S310, combining the evaluation keywords with the character evaluation to obtain a user feedback result of the order type.
In some embodiments, after segmenting the word evaluation by using a regular expression or other word processing algorithms, taking sentences containing keywords as evaluation conclusions, for example, sentences containing "staff" as evaluation conclusions, and combining the word evaluations in different evaluation records to obtain keyword sentences for repetition comparison, so as to finally obtain a core evaluation, which can be used as a user feedback result of the order type.
In some embodiments, there are multiple core evaluations, so that multiple core evaluations may be arranged in a frequency order as a final order type corresponding to the user feedback result.
And step S311, outputting the user feedback result of the order type to related personnel as a pertinence adjustment strategy.
In some embodiments, according to the preset, multiple user feedback results may be used as a targeted adjustment policy, or only the core evaluation with the highest frequency of occurrence may be used as the targeted adjustment policy and output.
Typically, the relevant personnel may be system maintenance personnel, such as a system whose evaluation is directed to automatically completing the order, or a manager of the relevant business, such as a business whose evaluation is directed to requiring the participation of a worker.
The order processing method comprises the steps of determining the order type according to the service type and the user group selected by a user on an order issuing platform when first indication information of order completion is received, sending an evaluation request like the user, sending nighttime dormancy for evaluating the order when the user agrees, obtaining a corresponding evaluation record after the user uploads evaluation, extracting an average score in the evaluation record, determining whether the service of the order type needs to be improved or not according to the comparison of the average score and a preset reference value, obtaining a corresponding user feedback result by processing corresponding character evaluation content when the improvement is needed, and obtaining a targeted adjustment strategy based on the user feedback result and outputting the targeted adjustment strategy. Therefore, user evaluation can be effectively utilized, a specific improvement direction in the user evaluation is obtained through data processing, and the method is used for processing all services of the same order type, so that the finally obtained targeted adjustment strategy can be effectively ensured to be in line with the opinion tendency fed back by the user integrally, the improvement effect on the online service handling platform is effectively improved, and the user experience of the online service handling platform can be effectively improved.
Fig. 4 is a schematic structural diagram of an order processing apparatus provided in the present disclosure. As shown in fig. 4, the order processing apparatus 400 includes: an acquisition module 410 and a processing module 420. Wherein:
an obtaining module 410, configured to determine, in response to the received first indication information, an order type of a completed order indicated by the first indication information, where the first indication information is used to indicate that the order is completed; acquiring an evaluation record of the completed order, wherein the evaluation record is used for representing the evaluation content of the completed order filled by the user and comprises a score and character evaluation;
the processing module 420 is configured to generate a user feedback result corresponding to the order type based on the evaluation record, where the user feedback result includes a comprehensive score obtained based on the score and a comprehensive evaluation obtained based on the text evaluation; and determining a pertinence adjustment strategy corresponding to the order type based on the user feedback result.
Optionally, the obtaining module 410 is specifically configured to, in response to the received first indication information, determine an order type of a completed order indicated by the first indication information based on an order service type selected by the user on the order issuing platform and/or a group in which the user is located, where the order type is used to push the order selected by the user to a handler of the corresponding order type.
Optionally, the obtaining module 410 is specifically configured to, in response to receiving the first indication information, send an evaluation request to a client corresponding to the user; when second indication information from the client is received, an initial evaluation page corresponding to the order type is pushed to the client, the initial evaluation page comprises a form for grading and filling in character evaluation, and the second indication information is used for indicating that a user selects to agree with the evaluation; and receiving a target evaluation page uploaded by the client, and acquiring the evaluation record of the user on the completed order based on the target evaluation page.
Optionally, the processing module 420 is specifically configured to determine an average value of scores corresponding to the order types; determining whether the average value of the scores is larger than a set reference value; and when the average value of the scores is smaller than or equal to the reference value, generating a user feedback result corresponding to the order type based on the character evaluation.
Optionally, the processing module 420 is specifically configured to perform keyword analysis on the word evaluation based on a preset lexicon; determining evaluation keywords of the order types according to the occurrence frequency of the keywords and the matching degree of the keywords and a preset word bank; and combining the evaluation keywords with the character evaluation to obtain a user feedback result of the order type.
Optionally, the processing module 420 is specifically configured to remove records that only contain text evaluation or only contain scores from the evaluation records; determining the average value of the scores corresponding to the order types based on the scores in the rejected evaluation records; correspondingly, based on the character evaluation, a user feedback result corresponding to the order type is generated, and the method comprises the following steps: respectively marking character evaluations corresponding to different grades based on the grades in the rejected evaluation records; and generating a user feedback result corresponding to the order type based on the marked character evaluation.
Optionally, the processing module 420 is specifically configured to, when the average value of the scores is greater than the reference value, determine that the targeted adjustment policy corresponding to the order type does not need to be adjusted; and when the average value of the scores is smaller than or equal to the reference value, outputting the user feedback result of the order type to related personnel as a targeted adjustment strategy.
In this embodiment, the order processing apparatus can obtain an improvement suggestion corresponding to the service order type based on the user feedback evaluation through the combination of the modules, thereby effectively ensuring that the targeted improvement can be performed in the field of the user feedback evaluation, and not only improving the service processing capability of the online service handling platform or the order issuing platform, but also gradually providing the user experience.
Fig. 5 is a schematic structural diagram of an electronic device provided in the present disclosure, and as shown in fig. 5, the electronic device 500 includes: a memory 510 and a processor 520.
Wherein the memory 510 stores computer programs that are executable by the at least one processor 520. The computer program is executed by the at least one processor 520 to cause the electronic device to implement the user terminal state management method as provided in any of the embodiments above.
Wherein the memory 510 and the processor 520 may be connected by a bus 530.
The related descriptions may be understood by referring to the related descriptions and effects corresponding to the method embodiments, which are not repeated herein.
One embodiment of the present disclosure provides a computer-readable storage medium on which a computer program is stored, the computer program being executed by a processor to implement the order processing method according to any of the embodiments corresponding to fig. 2 to 3.
The computer readable storage medium may be, among others, ROM, Random Access Memory (RAM), CD-ROM, magnetic tape, floppy disk, optical data storage device, and the like.
An embodiment of the present disclosure provides a computer program product comprising computer executable instructions, which when executed by a processor, are used for implementing the order processing method according to any of the embodiments corresponding to fig. 2 to 3, and/or when executed by a processor, are used for implementing the order processing method according to the embodiment corresponding to fig. 4.
In the several embodiments provided in the present disclosure, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, a division of modules is merely a division of logical functions, and an actual implementation may have another division, for example, a plurality of modules or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or modules, and may be in an electrical, mechanical or other form.
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This disclosure is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
It will be understood that the present disclosure is not limited to the precise arrangements 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 (10)
1. An order processing method, characterized in that the order processing method comprises:
in response to the received first indication information, determining an order type of a completed order indicated by the first indication information, wherein the first indication information is used for indicating order completion;
acquiring an evaluation record of the completed order, wherein the evaluation record is used for representing the evaluation content of the completed order filled by a user, and the evaluation record comprises a score and a character evaluation;
generating a user feedback result corresponding to the order type based on the evaluation record, wherein the user feedback result comprises a comprehensive score obtained based on the score and a comprehensive evaluation obtained based on the character evaluation;
and determining a targeted adjustment strategy corresponding to the order type based on the user feedback result.
2. The order processing method of claim 1, wherein the determining the order type of the completed order indicated by the first indication information in response to the received first indication information comprises:
and in response to the received first indication information, determining an order type of a completed order indicated by the first indication information based on an order service type selected by a user on an order issuing platform and/or a group where the user is located, wherein the order type is used for pushing the order selected by the user to a processing person of the corresponding order type.
3. The order processing method of claim 1, wherein said obtaining an evaluation record of said completed order comprises:
in response to receiving the first indication information, sending an evaluation request to a client corresponding to the user;
when second indication information from a client is received, an initial evaluation page corresponding to the order type is pushed to the client, the initial evaluation page comprises a form used for grading and filling in character evaluation, and the second indication information is used for indicating a user to select to agree with the evaluation;
and receiving a target evaluation page uploaded by the client, and acquiring the evaluation record of the completed order by the user based on the target evaluation page.
4. The order processing method according to any of claims 1 to 3, wherein the generating a user feedback result corresponding to the order type based on the evaluation record comprises:
determining the average value of the scores corresponding to the order types;
determining whether the average value of the scores is larger than a set reference value;
and when the average value of the scores is smaller than or equal to the reference value, generating a user feedback result corresponding to the order type based on the character evaluation.
5. The order processing method of claim 4, wherein generating a user feedback result corresponding to the order type based on the textual evaluation comprises:
performing keyword analysis on the character evaluation based on a preset word bank;
determining evaluation keywords of the order types according to the occurrence frequency of the keywords and the matching degree of the keywords and the preset word bank;
and combining the evaluation keywords with the character evaluation to obtain a user feedback result of the order type.
6. The order processing method of claim 4, wherein the determining an average value of the scores corresponding to the order types comprises:
removing records which only contain character evaluation or only contain scores from the evaluation records;
determining the average value of the scores corresponding to the order types based on the scores in the rejected evaluation records;
correspondingly, the generating of the user feedback result corresponding to the order type based on the text evaluation includes:
respectively marking character evaluations corresponding to different grades based on the grades in the rejected evaluation records; and generating a user feedback result corresponding to the order type based on the marked character evaluation.
7. The order processing method according to claim 5, wherein the determining a targeted adjustment policy corresponding to the order type based on the user feedback result comprises:
when the average value of the scores is larger than the reference value, determining that the targeted adjustment strategy corresponding to the order type does not need to be adjusted;
and when the average value of the scores is smaller than or equal to the reference value, outputting a user feedback result of the order type to related personnel as a targeted adjustment strategy.
8. An order processing apparatus, comprising:
the obtaining module is used for responding to 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 for indicating the order completion; acquiring an evaluation record of the completed order, wherein the evaluation record is used for representing the evaluation content of the completed order filled by a user, and comprises a score and a character evaluation;
the processing module is used for generating a user feedback result corresponding to the order type based on the evaluation record, wherein the user feedback result comprises a comprehensive score obtained based on the score and a comprehensive evaluation obtained based on the character evaluation; and determining a targeted adjustment strategy corresponding to the order type based on the user feedback result.
9. An electronic device, comprising:
at least one processor;
and a memory communicatively coupled to the at least one processor;
wherein the memory stores instructions executable by the at least one processor to cause the electronic device to perform the order processing method of any of claims 1 to 7.
10. A computer-readable storage medium having computer-executable instructions stored thereon for implementing the order processing method of any one of claims 1 to 7 when executed by a processor.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111126951.XA CN113869576A (en) | 2021-09-26 | 2021-09-26 | Order processing method, device, equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111126951.XA CN113869576A (en) | 2021-09-26 | 2021-09-26 | Order processing method, device, equipment and storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113869576A true CN113869576A (en) | 2021-12-31 |
Family
ID=78994278
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111126951.XA Pending CN113869576A (en) | 2021-09-26 | 2021-09-26 | Order processing method, device, equipment and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113869576A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115099707A (en) * | 2022-07-27 | 2022-09-23 | 江苏银承网络科技股份有限公司 | Order evaluation data evaluation system, method, electronic device and storage medium |
-
2021
- 2021-09-26 CN CN202111126951.XA patent/CN113869576A/en active Pending
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115099707A (en) * | 2022-07-27 | 2022-09-23 | 江苏银承网络科技股份有限公司 | Order evaluation data evaluation system, method, electronic device and storage medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US10171668B2 (en) | Methods of AI based CRM | |
| KR102163081B1 (en) | Interactive voice bot server and unmanned counsel system | |
| US8983055B1 (en) | Quality review of contacts between customers and customer service agents | |
| CN107784593A (en) | Settlement of insurance claim interactive approach and system | |
| CN110598008A (en) | Data quality inspection method and device for recorded data and storage medium | |
| CN112364035A (en) | Processing method and device for call record big data, electronic equipment and storage medium | |
| CN111831875A (en) | Data processing method, device, equipment and storage medium | |
| CN113869576A (en) | Order processing method, device, equipment and storage medium | |
| CN111126071A (en) | Method and device for determining questioning text data and data processing method of customer service group | |
| JP2016143909A (en) | Telephone conversation content analysis display device, telephone conversation content analysis display method, and program | |
| CN110472852B (en) | Experience evaluation implementation management method for power service application | |
| CN115221892A (en) | Work order data processing method and device, storage medium and electronic equipment | |
| CN111050001A (en) | Telephone traffic distribution method and related device | |
| CN113723974A (en) | Information processing method, device, equipment and storage medium | |
| JPWO2019220520A1 (en) | Analysis program, analysis method, and analysis device | |
| WO2023272833A1 (en) | Data detection method, apparatus and device and readable storage medium | |
| CN112527991A (en) | Information processing method, apparatus and medium | |
| CN113506585A (en) | Quality evaluation method and system for voice call | |
| CN113609271A (en) | Service processing method, device and equipment based on knowledge graph and storage medium | |
| CN112260933A (en) | Communication method, communication device, electronic equipment and medium | |
| US9116980B1 (en) | System, method, and computer program for determining a set of categories based on textual input | |
| KR102163067B1 (en) | Unmanned receiving bot server and unmanned receiving method using the same | |
| KR102206206B1 (en) | Event outsourcing service Delivery System | |
| WO2022208711A1 (en) | Information processing device, information processing system, information processing method, and program | |
| KR20050109823A (en) | System and method for appraising quality of telephone call of call center |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |