CN115623131B - Shunt system based on voice customer service - Google Patents
Shunt system based on voice customer service Download PDFInfo
- Publication number
- CN115623131B CN115623131B CN202211381857.3A CN202211381857A CN115623131B CN 115623131 B CN115623131 B CN 115623131B CN 202211381857 A CN202211381857 A CN 202211381857A CN 115623131 B CN115623131 B CN 115623131B
- Authority
- CN
- China
- Prior art keywords
- data
- customer service
- data set
- demand
- association
- 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.)
- Active
Links
Images
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04M—TELEPHONIC COMMUNICATION
- H04M3/00—Automatic or semi-automatic exchanges
- H04M3/42—Systems providing special services or facilities to subscribers
- H04M3/50—Centralised arrangements for answering calls; Centralised arrangements for recording messages for absent or busy subscribers ; Centralised arrangements for recording messages
- H04M3/51—Centralised call answering arrangements requiring operator intervention, e.g. call or contact centers for telemarketing
- H04M3/523—Centralised call answering arrangements requiring operator intervention, e.g. call or contact centers for telemarketing with call distribution or queueing
- H04M3/5232—Call distribution algorithms
-
- 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
- G06F40/284—Lexical analysis, e.g. tokenisation or collocates
-
- 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
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06311—Scheduling, planning or task assignment for a person or group
- G06Q10/063112—Skill-based matching of a person or a group to a task
-
- 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
- G06Q30/01—Customer relationship services
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04M—TELEPHONIC COMMUNICATION
- H04M3/00—Automatic or semi-automatic exchanges
- H04M3/42—Systems providing special services or facilities to subscribers
- H04M3/50—Centralised arrangements for answering calls; Centralised arrangements for recording messages for absent or busy subscribers ; Centralised arrangements for recording messages
- H04M3/51—Centralised call answering arrangements requiring operator intervention, e.g. call or contact centers for telemarketing
- H04M3/5141—Details of processing calls and other types of contacts in an unified manner
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management
Landscapes
- Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Human Resources & Organizations (AREA)
- Theoretical Computer Science (AREA)
- Marketing (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- Signal Processing (AREA)
- Entrepreneurship & Innovation (AREA)
- Development Economics (AREA)
- Educational Administration (AREA)
- General Business, Economics & Management (AREA)
- Quality & Reliability (AREA)
- Tourism & Hospitality (AREA)
- Operations Research (AREA)
- Game Theory and Decision Science (AREA)
- Accounting & Taxation (AREA)
- Finance (AREA)
- Health & Medical Sciences (AREA)
- Artificial Intelligence (AREA)
- Audiology, Speech & Language Pathology (AREA)
- Computational Linguistics (AREA)
- General Health & Medical Sciences (AREA)
- General Engineering & Computer Science (AREA)
- Telephonic Communication Services (AREA)
Abstract
The invention relates to the field of data processing, in particular to a diversion system based on voice customer service, which classifies received demand requests by arranging a data storage module, a data receiving module, a switching module, a data processing module and a data supporting module, determines the optimal processing category of each customer service end, provides short consultation content by a demand party when receiving the demand requests, converts the received consultation content into text information, adjusts the switching mode according to the text information, distributes the demand requests to the customer service end with highest processing efficiency of the type of demand requests, accurately classifies the demand requests, and matches the demand requests to the customer service end with highest processing efficiency by using a specific matching mode, thereby improving the service processing efficiency, increasing the circulation rate of the customer service system, and simultaneously, accurately calling a database in the customer service answering consultation process, providing data support, assisting the customer service, improving the service processing efficiency, and further improving the service efficiency of the whole customer service system.
Description
Technical Field
The invention relates to the field of data processing, in particular to a diversion system based on voice customer service analysis.
Background
The customer service system plays an important role in the production and operation activities of enterprises, is a service window for closely contacting the enterprises with users, plays a very important role in the aspects of product sales, after-sales service, technical support, consultation and complaint, and has a large burden on the customer service system for the enterprises with large service volume and large coverage, so that the customer service diversion system is arranged, and the improvement of customer service answering efficiency is very important;
chinese patent publication No.: CN111556208A discloses a customer service online switching method and device, relating to the technical field of customer service systems. Wherein the method comprises the following steps: distributing remote customer service for a customer accessing a customer service system and switching to the remote customer service; when the service performed by the client is determined to relate to an operation service, determining the seat customer service corresponding to the operation service; and switching to the seat customer service by a remote customer service so that the seat customer service processes the operation service. By utilizing the method, the service on the site of the call center can be split.
However, the prior art has the following problems,
1. the consultation contents of the demand end are distributed after being briefly known without technical means, and different consultation demands are automatically distributed to customer service ends familiar with the type of service so as to improve the operation efficiency of the customer service;
for application scenes with wider service areas, the more stringent the requirements on the operators are, the lack of a system for automatically extracting keywords and pushing related data support to the operators by analyzing voice information is lacking in the prior art.
Disclosure of Invention
In order to solve the above problems, the present invention provides a diversion system based on voice customer service analysis, comprising:
the data storage module is internally stored with a plurality of data sets, and for any data set, the data storage module comprises common information and a plurality of keywords, wherein the keywords are different from each other, and the data storage module determines the association level between the data sets;
the data receiving module is used for receiving a demand request sent by a demand end and consultation contents corresponding to the demand request;
the switching module is used for switching the demand request to the customer service end for processing;
the data processing module is connected with the data storage module, the data receiving module and the switching module and completes data exchange, after receiving the data of the data receiving module, the data processing module classifies demand requests, calls the processed demand request data records of all customer service ends, and determines the optimal processing category of all the customer service ends and the data set associated with all the customer service ends;
the data processing module converts the consultation content into text information, extracts keywords in the text information, judges a data set matched with the text information, judges whether to allocate calculation or not, randomly transfers the demand request to a current non-busy line customer service end when allocation calculation is not performed, and determines a transfer mode according to the association level of the data set matched with the text information and the non-busy line customer service end association data set when allocation calculation is performed;
the data support module is connected with the data storage module, extracts voice data during conversation of the customer service end, judges a data set matched with the voice data, and transmits the data set to the customer service end.
Further, the data storage module determines the association level between the data sets, wherein the data storage module extracts keywords in the data sets and calculates an association coefficient K between the data sets according to the following formula,
wherein, E represents the superposition number of keywords in the two data sets, E0 represents the total number of keywords in the two data sets, N represents the difference value of the number of keywords in the two data sets, N0 represents the difference value parameter of the number of preset keywords, P0 represents the total data amount of the two data sets, and alpha represents the conversion coefficient.
Further, a first association relation comparison parameter K1 and a second association relation comparison parameter K2 are preset in the data storage module, the data storage module compares the association relation coefficient K corresponding to the data sets with the K1 and the K2 to judge the association grade between the data sets, wherein,
when K is more than or equal to K2, the data storage module judges that the data sets are of a first association level;
when K1 is less than or equal to K2, the data storage module judges that the data sets are of a second association level;
and when K is smaller than K1, the data storage module judges that the data sets are in a third association level.
Further, when the data receiving module receives a demand request of a demand party, prompting the demand party to send consultation content, and after the data receiving module converts the consultation content into text information, extracting keywords in the text information and recording the keywords to a demand keyword data set; the data processing module determines a set of data that matches the demand request, wherein,
when the association relation coefficient K between a demand keyword data set generated by the text information of the consultation content corresponding to the demand request and any data set in the data storage module is more than or equal to K3, the data processing module judges that the demand request is matched with the data set, wherein K3 is a third association relation comparison parameter, and K3 is more than K2.
Further, when the data processing module determines that the data set is matched with the requirement request, when the association coefficient K of a requirement keyword data set generated by text information of a plurality of data sets and corresponding consultation content of the requirement request exists in the data storage module is larger than or equal to K3, a data set with the largest association coefficient K of the requirement keyword data set is selected as the matched data set of the requirement request.
Further, a sample number parameter R is preset in the data processing module, after the data receiving module receives the demand request, information is sent to the data processing module, the data processing module determines whether to perform allocation calculation, wherein,
when the number of the transferred demand requests is smaller than the preset sample number parameter R, the data processing module judges that distribution calculation is not performed, the demand requests are randomly transferred to a currently not busy line customer service end, and when the customer service end completes the demand request processing, the time length information T of the customer service end for processing the demand requests is recorded;
when the number of the transferred demand requests is greater than or equal to the preset sample number parameter R, the data processing module judges that distribution calculation is needed.
Further, the data processing module determines an optimal processing category of each customer service end, wherein the data processing module calls a data record of a processed demand request of each customer service end to classify the demand request, wherein a corresponding relation between a data set and a category is preset in the data processing module, different data sets correspond to different categories, the demand request is classified according to the corresponding relation, the average duration delta T of the customer service end for processing the demand request of each category is calculated, the average duration delta T is ordered, the category of the demand request with the shortest required average duration is used as the optimal processing category of the customer service end, and the customer service end is marked to be associated with the data set corresponding to the demand request with the shortest required average duration.
Further, the data processing module judges that distribution calculation is needed, and determines a transfer mode according to the data set matched with the text information, wherein the data set matched with the text information is corresponding to the consultation content of the demand request, the data set is marked, the demand request is classified according to the marked data set, the category of the demand request is determined, and the demand request is transferred to a customer service end with the optimal processing category as the category;
and when the optimal processing category is all busy line of the customer service end of the category, the data processing module determines a data set associated with the customer service end of the remaining non-busy line, judges the association level of the marked data set and the data set, determines a transfer mode,
if a data set with the association level of the marked data set being the first association level exists, the data processing module calls the history record of all customer service side processing demand requests associated with the data set, calculates the average duration delta T of all customer service side processing the category demand requests corresponding to the marked data set, and transfers the demand requests to the customer service side with the minimum average duration delta T required for processing the category demand requests;
if a data set with the association level of the marked data set being a second association level exists, the data processing module transfers the demand request to any customer service end associated with the data set;
and if the association level of the data set associated with the remaining non-busy line customer service end and the marked data set is a third association level, the data processing module transfers the demand request to any customer service end in the remaining non-busy line customer service end.
Further, the common information includes data, and after the data set is transmitted to the customer service end, the display device of the customer service end obtains and displays the data.
Further, when the data support module judges that the voice data are matched with the data set, the voice data are converted into text information, keywords in the text information are extracted, the keywords are recorded to the voice data set, an association relation coefficient K between the voice data set and the data set in the data storage module is calculated, when K is more than or equal to K0, the data processing module judges that the voice data are matched with the data set, and K0 represents a preset voice matching coefficient.
Compared with the prior art, the invention classifies and calls the demand request data records processed by each customer service end through the data storage module, the data receiving module, the switching module, the data processing module and the data supporting module, determines the optimal processing category of each customer service end, provides short consultation content when receiving the demand request, converts the received consultation content into text information, extracts keywords in the text information, judges a data set matched with the text information, determines a switching mode according to the association level of the data set matched with the text information and the associated data set of the customer service end without busy line, distributes the demand request to the customer service end with highest processing efficiency of the type demand request.
In particular, the invention sets a plurality of data sets through the data storage module, the data sets can be increased and decreased according to the service field required to provide the consultation service in actual conditions, and the data sets and related keywords related to the data sets are established for different service fields, so that the corresponding type of service can be accurately identified for distribution in the consultation distribution, the consultation type of the demander can be effectively represented through the form of keyword comparison, the reliability and the data identification precision of the system distribution are improved, and the false distribution is avoided.
In particular, the invention receives the demand request of the demand party through the data receiving module, and simultaneously the demand party can provide brief consultation content when sending the demand request, which can be voice or text, extracts keywords and a preset data set based on the voice or text to perform association degree calculation, calculates an association relation coefficient K, has better characterization on the association of the data set, determines the data set matched with the consultation content, and classifies the demand request.
In particular, the invention records the data of the processing demand requests of each client by setting the preset sample quantity parameter R, for the previous R times of switching, the system automatically counts the data, determines what type of demand requests the client processes is more skilled, in the practical situation, for the customer service system with wider service surface, customer service personnel accurately grasp all consultation knowledge, the speed and efficiency of each customer service processing each service are different, the system automatically counts the data, further determines the type of the demand requests with highest processing efficiency of each customer service end, establishes the association relation with the data set, facilitates the subsequent split calculation and identification, distributes the corresponding type of demand requests to the customer service end with highest processing efficiency, and further improves the customer service processing efficiency.
In particular, the invention sets the association level between the data sets, when the service is busy, the current demand request is distributed to the customer service end with higher processing communication according to the association level between the remaining unconnected customer service end association data sets and the current marked data sets, and different association levels correspond to different transfer methods.
In particular, the invention sets the data support module, extracts the key words in the process of the voice dialogue between the customer service and the demander, accurately extracts the data information related to the conversation content from the database, transmits the data information to the customer service end for display, reduces the operation of the customer service personnel, has more accurate data calculation precision, and assists the customer service personnel, thereby improving the customer service efficiency.
Drawings
FIG. 1 is a schematic diagram of a diversion system based on voice customer service analysis according to an embodiment of the present invention;
FIG. 2 is a diagram illustrating a data structure of a data set according to an embodiment of the present invention.
In the figure, 1: and (5) data collection.
Detailed Description
In order that the objects and advantages of the invention will become more apparent, the invention will be further described with reference to the following examples; it should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are merely for explaining the technical principles of the present invention, and are not intended to limit the scope of the present invention.
It should be noted that, in the description of the present invention, terms such as "upper," "lower," "left," "right," "inner," "outer," and the like indicate directions or positional relationships based on the directions or positional relationships shown in the drawings, which are merely for convenience of description, and do not indicate or imply that the apparatus or elements must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as limiting the present invention.
Furthermore, it should be noted that, in the description of the present invention, unless explicitly specified and limited otherwise, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be either fixedly connected, detachably connected, or integrally connected, for example; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the above terms in the present invention can be understood by those skilled in the art according to the specific circumstances.
Referring to fig. 1, which is a diagram illustrating a diversion system based on voice customer service analysis according to an embodiment of the present invention, the diversion system based on voice customer service analysis of the present invention includes,
the data storage module is internally stored with a plurality of data sets, and for any data set, the data storage module comprises common information and a plurality of keywords, wherein the keywords are different from each other, and the data storage module determines the association level between the data sets;
the data receiving module is used for receiving a demand request sent by a demand end and consultation contents corresponding to the demand request;
the switching module is used for switching the demand request to the customer service end for processing;
the data processing module is connected with the data storage module, the data receiving module and the switching module and completes data exchange, after receiving the data of the data receiving module, the data processing module classifies demand requests, calls the processed demand request data records of all customer service ends, and determines the optimal processing category of all the customer service ends and the data set associated with all the customer service ends;
the data processing module converts the consultation content into text information, extracts keywords in the text information, judges a data set matched with the text information, judges whether to allocate calculation or not, randomly transfers the demand request to a current non-busy line customer service end when allocation calculation is not performed, and determines a transfer mode according to the association level of the data set matched with the text information and the non-busy line customer service end association data set when allocation calculation is performed;
the data support module is connected with the data storage module, extracts voice data during conversation of the customer service end, judges a data set matched with the voice data, and transmits the data set to the customer service end.
Specifically, for setting the data set, the data set can be modified according to the scope of specific consultation services, the invention does not limit the specific form, one data set is set for each type of service, and corresponding supporting data is set, and keywords associated with pre-corresponding services are selected to be associated with the data set.
Specifically, referring to fig. 2, the data storage module determines the association level between the data sets, wherein the data storage module extracts keywords in the data sets and calculates the association coefficient K between the data sets according to the following formula,
wherein, E represents the superposition number of keywords in the two data sets, E0 represents the total number of keywords in the two data sets, N represents the difference value of the number of keywords in the two data sets, N0 represents the difference value parameter of the number of preset keywords, P0 represents the total data amount of the two data sets, and alpha represents the conversion coefficient.
Specifically, a first association relation comparison parameter K1 and a second association relation comparison parameter K2 are preset in the data storage module, the data storage module compares the association relation coefficient K corresponding to the data sets with the K1 and the K2 to judge the association grade between the data sets, wherein,
when K is more than or equal to K2, the data storage module judges that the data sets are of a first association level;
when K1 is less than or equal to K2, the data storage module judges that the data sets are of a second association level;
and when K is smaller than K1, the data storage module judges that the data sets are in a third association level.
Specifically, a plurality of data sets are arranged through the data storage module, the data sets can be increased or decreased according to the service field required to provide the consultation service in actual situations, and related data sets and related keywords are established for different service fields, so that the corresponding type of service can be accurately identified for distribution in consultation distribution, the consultation type of a demander can be effectively represented through the form of keyword comparison, the reliability and the data identification precision of system distribution are improved, and the false distribution is avoided.
Specifically, when the data receiving module receives a demand request of a demand party, prompting the demand party to send consultation content, and after the data receiving module converts the consultation content into text information, extracting keywords in the text information and recording the keywords to a demand keyword data set; the data processing module determines a set of data that matches the demand request, wherein,
when the association relation coefficient K between a demand keyword data set generated by the text information of the consultation content corresponding to the demand request and any data set in the data storage module is more than or equal to K3, the data processing module judges that the demand request is matched with the data set, wherein K3 is a third association relation comparison parameter, and K3 is more than K2.
Specifically, the consultation content can be in a voice form or a text form, and after the demand party sends out a demand request, the data receiving module sends out a prompt to the terminal of the demand party, and the demand party can input voice or input text information on the terminal of the demand party and send the voice or input text information to the data receiving module.
Specifically, when the data processing module determines that the data set is matched with the demand request, when the association coefficient K of a demand keyword data set generated by text information of a plurality of data sets and corresponding consultation content of the demand request exists in the data storage module is larger than or equal to K3, a data set with the largest association coefficient K of the demand keyword data set is selected as the matched data set of the demand request.
Specifically, through setting up the data receiving module, receive the demand request of demand side, simultaneously the demand side can provide brief consultation content when sending the demand request, it can be the pronunciation and can be the text, extract the keyword and carry out the association degree calculation with preset data set based on this, calculate association relation coefficient K, association relation coefficient K has better characterization nature to data set's association, and confirm the data set that matches with the consultation content, and then classify the demand request, above-mentioned scheme is comparatively accurate, reliable to the discernment of demand request category, the follow-up operation distribution of being convenient for, and then the reliability of whole business system has been improved.
Specifically, the data processing module is preset with a sample number parameter R, after receiving the demand request, the data receiving module sends information to the data processing module, and the data processing module determines whether to perform distribution calculation, wherein,
when the number of the transferred demand requests is smaller than the preset sample number parameter R, the data processing module judges that distribution calculation is not performed, the demand requests are randomly transferred to a currently not busy line customer service end, and when the customer service end completes the demand request processing, the time length information T of the customer service end for processing the demand requests is recorded;
when the number of the transferred demand requests is greater than or equal to the preset sample number parameter R, the data processing module judges that distribution calculation is needed.
Specifically, through setting a preset sample number parameter R, recording data of processing demand requests of all clients, for the former R times of switching, automatically counting data by a system, determining what type of demand requests are processed by the clients to be more skilled, in actual conditions, accurately grasping all consultation knowledge by customer service personnel for a customer service system with wider service surface, and enabling the speed and efficiency of processing all services of all customer service terminals to be different, automatically counting the data by the system, further determining the type of demand requests with highest processing efficiency of all customer service terminals, establishing an association relation with a data set, facilitating subsequent split calculation and identification, and distributing the corresponding type demand requests to the customer service terminals with highest processing efficiency, thereby improving customer service processing efficiency.
Specifically, the data processing module determines an optimal processing category of each customer service end, wherein the data processing module calls a data record of a processed demand request of each customer service end to classify the demand request, wherein corresponding relations between a preset data set and categories in the data processing module correspond to different categories, the demand request is classified according to the corresponding relations, average duration delta T of the customer service end for processing the demand request of each category is calculated, the average duration delta T is ordered, the category of the demand request with the shortest required average duration is used as the optimal processing category of the customer service end, and the customer service end is marked to be associated with the data set corresponding to the demand request with the shortest required average duration.
Specifically, the data processing module judges that distribution calculation is needed, and determines a transfer mode according to the data set matched with the text information, wherein the data set matched with the text information is corresponding to the consultation content of the demand request, the data set is marked, the demand request is classified according to the marked data set, the category of the demand request is determined, and the demand request is transferred to a customer service end with the optimal processing category as the category;
and when the optimal processing category is all busy line of the customer service end of the category, the data processing module determines a data set associated with the customer service end of the remaining non-busy line, judges the association level of the marked data set and the data set, determines a transfer mode,
if a data set with the association level of the marked data set being the first association level exists, the data processing module calls the history record of all customer service side processing demand requests associated with the data set, calculates the average duration delta T of all customer service side processing the category demand requests corresponding to the marked data set, and transfers the demand requests to the customer service side with the minimum average duration delta T required for processing the category demand requests;
if a data set with the association level of the marked data set being a second association level exists, the data processing module transfers the demand request to any customer service end associated with the data set;
and if the association level of the data set associated with the remaining non-busy line customer service end and the marked data set is a third association level, the data processing module transfers the demand request to any customer service end in the remaining non-busy line customer service end.
Specifically, the invention sets the association level between the data sets, when the service is busy, the current demand request is distributed to the customer service end with higher processing communication according to the association level between the remaining unconnected customer service end association data sets and the current marked data sets, and different association levels correspond to different transfer methods.
Specifically, the common information includes data, and after the data set is transmitted to the customer service end, the display device of the customer service end obtains and displays the data.
Specifically, when the data support module judges that the voice data is matched with the data set, the voice data is converted into text information, keywords in the text information are extracted, the keywords are recorded to the voice data set, an association relation coefficient K between the voice data set and the data set in the data storage module is calculated, when K is more than or equal to K0, the data processing module judges that the voice data is matched with the data set, and K0 represents a preset voice matching coefficient.
Specifically, a data support module is arranged, keywords are extracted in the voice dialogue process between customer service and a demander, data information related to the conversation content is accurately extracted from a database and is transmitted to a customer service end for display, the operation of customer service personnel is reduced, the data calculation accuracy is accurate, the customer service personnel is assisted, and further the customer service business efficiency is improved.
Specifically, the text keyword extraction is a mature prior art, and the extraction modes are various, and the invention is not limited to the text keyword extraction.
The data storage module only needs to be provided with a database and a data processing unit which can be called for storage, the data receiving module only needs to be connected with a cloud end to receive information sent by a user end, the transfer module is a data transfer platform only needs to be used for completing call transfer, the data transfer is only needed, the data processing module only needs to be used for completing data processing and data interaction, and the data support module only needs to be used for completing data processing and data interaction.
Thus far, the technical solution of the present invention has been described in connection with the preferred embodiments shown in the drawings, but it is easily understood by those skilled in the art that the scope of protection of the present invention is not limited to these specific embodiments. Equivalent modifications and substitutions for related technical features may be made by those skilled in the art without departing from the principles of the present invention, and such modifications and substitutions will be within the scope of the present invention.
Claims (10)
1. A voice customer service based distribution system comprising:
the data storage module is internally stored with a plurality of data sets, and for any data set, the data storage module comprises common information and a plurality of keywords, wherein the keywords are different from each other, and the data storage module determines the association level between the data sets;
the data receiving module is used for receiving a demand request sent by a demand end and consultation contents corresponding to the demand request;
the switching module is used for switching the demand request to the customer service end for processing;
the data processing module is connected with the data storage module, the data receiving module and the switching module and completes data exchange, after receiving the data of the data receiving module, the data processing module classifies demand requests, calls the processed demand request data records of all customer service ends, and determines the optimal processing category of all the customer service ends and the data set associated with all the customer service ends;
the data processing module converts the consultation content into text information, extracts keywords in the text information, judges a data set matched with the text information, judges whether to allocate calculation or not, randomly transfers the demand request to a current non-busy line customer service end when allocation calculation is not performed, and determines a transfer mode according to the association level of the data set matched with the text information and the non-busy line customer service end association data set when allocation calculation is performed;
the data support module is connected with the data storage module, extracts voice data during conversation of the customer service end, judges a data set matched with the voice data, and transmits the data set to the customer service end.
2. The voice customer service-based distribution system according to claim 1, wherein the data storage module determines a level of association between the data sets, wherein the data storage module extracts keywords in the data sets and calculates an association coefficient K between the data sets according to the following formula,
wherein, E represents the superposition number of keywords in the two data sets, E0 represents the total number of keywords in the two data sets, N represents the difference value of the number of keywords in the two data sets, N0 represents the difference value parameter of the number of preset keywords, P0 represents the total data amount of the two data sets, and alpha represents the conversion coefficient.
3. The voice customer service-based distribution system according to claim 2, wherein the data storage module is pre-provided with a first association comparison parameter K1 and a second association comparison parameter K2, and the data storage module compares the association coefficients K corresponding to the data sets with K1 and K2 to determine the association level between the data sets, wherein,
when K is more than or equal to K2, the data storage module judges that the data sets are of a first association level;
when K1 is less than or equal to K2, the data storage module judges that the data sets are of a second association level;
and when K is smaller than K1, the data storage module judges that the data sets are in a third association level.
4. The voice customer service-based distribution system according to claim 3, wherein the data receiving module prompts the demand party to send consultation contents when receiving a demand request of the demand party, and the data receiving module extracts keywords in the text information after converting the consultation contents into the text information, and records the keywords to a demand keyword data set; the data processing module determines a set of data that matches the demand request, wherein,
when the association relation coefficient K between a demand keyword data set generated by the text information of the consultation content corresponding to the demand request and any data set in the data storage module is more than or equal to K3, the data processing module judges that the demand request is matched with the data set, wherein K3 is a third association relation comparison parameter, and K3 is more than K2.
5. The voice customer service-based distribution system according to claim 4, wherein when the data processing module determines that the data set matches the demand request, if the association coefficient K of the demand keyword data set generated by the text information in which a plurality of data sets exist and the demand request corresponding to the consultation content in the data storage module is greater than or equal to K3, then selecting the data set with the association coefficient K maximum to the demand keyword data set as the matching data set of the demand request.
6. The voice customer service-based distribution system according to claim 5, wherein the data processing module presets a sample number parameter R, and when the data receiving module receives the request, the data processing module sends information to the data processing module, and the data processing module determines whether to perform distribution calculation, wherein,
when the number of the transferred demand requests is smaller than the preset sample number parameter R, the data processing module judges that distribution calculation is not performed, the demand requests are randomly transferred to a currently not busy line customer service end, and when the customer service end completes the demand request processing, the time length information T of the customer service end for processing the demand requests is recorded;
when the number of the transferred demand requests is greater than or equal to the preset sample number parameter R, the data processing module judges that distribution calculation is needed.
7. The voice customer service-based distribution system according to claim 6, wherein the data processing module determines an optimal processing category of each customer service end, wherein the data processing module invokes a data record of a demand request processed by each customer service end to classify the demand request, wherein a corresponding relation between a data set and a category is preset in the data processing module, different data sets correspond to different categories, the demand request is classified according to the corresponding relation, an average duration Δt of the customer service end for processing the demand request of each category is calculated, the average duration Δt is ordered, the category of the demand request with the shortest required average duration is used as the optimal processing category of the customer service end, and the customer service end is marked to be associated with the data set corresponding to the demand request with the shortest required average duration.
8. The voice customer service-based distribution system according to claim 7, wherein the data processing module determines that allocation calculation is required, determines a transfer mode according to the text information matched data set, determines a data set with matched text information corresponding to consultation content of a demand request, marks the data set, classifies the demand request according to the marked data set, determines a category of the demand request, and transfers the demand request to a customer service end with an optimal processing category of the category;
and when the optimal processing category is all busy line of the customer service end of the category, the data processing module determines a data set associated with the customer service end of the remaining non-busy line, judges the association level of the marked data set and the data set, determines a transfer mode,
if a data set with the association level of the marked data set being the first association level exists, the data processing module calls the history record of all customer service side processing demand requests associated with the data set, calculates the average duration delta T of all customer service side processing the category demand requests corresponding to the marked data set, and transfers the demand requests to the customer service side with the minimum average duration delta T required for processing the category demand requests;
if a data set with the association level of the marked data set being a second association level exists, the data processing module transfers the demand request to any customer service end associated with the data set;
and if the association level of the data set associated with the remaining non-busy line customer service end and the marked data set is a third association level, the data processing module transfers the demand request to any customer service end in the remaining non-busy line customer service end.
9. The voice customer service-based distribution system according to claim 1, wherein the general information includes data, and the display device of the customer service side obtains and displays the data after the data set is transmitted to the customer service side.
10. The voice customer service-based distribution system according to claim 1, wherein when the data support module determines that the voice data matches the data set, the voice data is converted into text information, keywords in the text information are extracted, the keywords are recorded into the voice data set, an association coefficient K between the voice data set and the data set in the data storage module is calculated, and when K is greater than or equal to K0, the data processing module determines that the voice data matches the data set, and K0 represents a preset voice matching coefficient.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211381857.3A CN115623131B (en) | 2022-11-07 | 2022-11-07 | Shunt system based on voice customer service |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211381857.3A CN115623131B (en) | 2022-11-07 | 2022-11-07 | Shunt system based on voice customer service |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN115623131A CN115623131A (en) | 2023-01-17 |
| CN115623131B true CN115623131B (en) | 2023-04-28 |
Family
ID=84878351
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211381857.3A Active CN115623131B (en) | 2022-11-07 | 2022-11-07 | Shunt system based on voice customer service |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115623131B (en) |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109040484A (en) * | 2018-07-16 | 2018-12-18 | 安徽信尔联信息科技有限公司 | A kind of Auto-matching contact staff method |
| CN109040486A (en) * | 2018-08-30 | 2018-12-18 | 中通天鸿（北京）通信科技股份有限公司 | A kind of position system of call center |
| CN111932144A (en) * | 2020-08-25 | 2020-11-13 | 腾讯科技（深圳）有限公司 | Customer service seat allocation method, customer service seat allocation device, server and storage medium |
| CN112615968A (en) * | 2019-12-05 | 2021-04-06 | 商客通尚景科技（上海）股份有限公司 | Shunting method and device for cloud call center telephone |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US11595525B2 (en) * | 2021-01-27 | 2023-02-28 | Dell Products L.P. | Assigning customer calls to customer care agents based on compatability |
-
2022
- 2022-11-07 CN CN202211381857.3A patent/CN115623131B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109040484A (en) * | 2018-07-16 | 2018-12-18 | 安徽信尔联信息科技有限公司 | A kind of Auto-matching contact staff method |
| CN109040486A (en) * | 2018-08-30 | 2018-12-18 | 中通天鸿（北京）通信科技股份有限公司 | A kind of position system of call center |
| CN112615968A (en) * | 2019-12-05 | 2021-04-06 | 商客通尚景科技（上海）股份有限公司 | Shunting method and device for cloud call center telephone |
| CN111932144A (en) * | 2020-08-25 | 2020-11-13 | 腾讯科技（深圳）有限公司 | Customer service seat allocation method, customer service seat allocation device, server and storage medium |
Non-Patent Citations (1)
| Title |
|---|
| 任虹林.四川移动公司农经信息呼叫系统的设计与实现.《中国优秀硕士学位论文全文数据库》.2016,全文. * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN115623131A (en) | 2023-01-17 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| KR920007142B1 (en) | Automatic operator assistance calls with voice processing | |
| US5181237A (en) | Automation of telephone operator assistance calls | |
| US8923502B2 (en) | Customer service system, method, and software program product for responding to queries using natural language understanding | |
| US6798877B2 (en) | Enhanced end user automatic call distributor control | |
| US5185781A (en) | Automation of telephone operator assistance calls | |
| US8976942B2 (en) | Method, system and software for implementing an automated call routing application in a speech enabled call center environment | |
| US20020196927A1 (en) | End user automatic call distributor network control | |
| CN110445942A (en) | A kind of outer paging system of intelligence and intelligent calling-out method | |
| US6801620B2 (en) | Enhanced agent automatic call distribution control | |
| KR102163081B1 (en) | Interactive voice bot server and unmanned counsel system | |
| US6813349B2 (en) | Communication of user data to an automatic call distributor agent | |
| KR101975320B1 (en) | Method and System For Providing Call Center Sharing Service Based On Big Data and Artificial Intelligence | |
| CN112801676A (en) | Express industry call center service method, device, equipment and system | |
| CN115623131B (en) | Shunt system based on voice customer service | |
| US7027572B2 (en) | System and method for associating interactive voice response unit data to a telephone call using automatic number identifiers | |
| CN116340482A (en) | Multi-skill customer service auxiliary product based on enterprise WeChat combined with NLP engine | |
| CN111310949A (en) | Method for feeding back user experience by intelligent hardware product, feedback device and service platform | |
| CN113518156B (en) | Telephone switching method and device and electronic equipment | |
| US8611526B2 (en) | CTIEX, system and method for channel associated data transmission between agent and automatic service | |
| CN113301213A (en) | Method for intelligently adjusting online queuing priority of customer service system | |
| CN103516917B (en) | Internet information treating method and apparatus | |
| KR101498045B1 (en) | Outbound system operated by selective call modes and the control method thereof | |
| US7606359B1 (en) | Methods and apparatus for automating the servicing of telephone calls including requesting directional and/or other types of information | |
| CN116033071A (en) | Telephone traffic item processing method, telephone traffic item processing device, electronic equipment and storage medium | |
| KR20210156684A (en) | Big Data-Based Call Center Shared Service Delivery Methods and Systems |
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 | ||
| TA01 | Transfer of patent application right | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20230413 Address after: 530013 No. 6, Minzhu Road, Xingning District, Nanning City, Guangxi Zhuang Autonomous Region Applicant after: GUANGXI POWER GRID Co.,Ltd. Address before: No. 372, 3rd floor, building 8, No. 663, Tianhe North Road, Tianhe District, Guangzhou, Guangdong 510000 Applicant before: Guangdong Yuantao Enterprise Management Consulting Co.,Ltd. |
|
| GR01 | Patent grant | ||
| GR01 | Patent grant |