CN108683818B - Method, system, equipment and storage medium for distributing seats in call center - Google Patents
Method, system, equipment and storage medium for distributing seats in call center Download PDFInfo
- Publication number
- CN108683818B CN108683818B CN201811019192.5A CN201811019192A CN108683818B CN 108683818 B CN108683818 B CN 108683818B CN 201811019192 A CN201811019192 A CN 201811019192A CN 108683818 B CN108683818 B CN 108683818B
- Authority
- CN
- China
- Prior art keywords
- user
- agent
- seat
- current
- current user
- 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
Landscapes
- Business, Economics & Management (AREA)
- Marketing (AREA)
- Engineering & Computer Science (AREA)
- Signal Processing (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
- Telephonic Communication Services (AREA)
Abstract
The invention provides a method, a system, equipment and a storage medium for allocating seats in a call center, which comprises the steps of identifying user tags for users according to historical behavior data of the users, dividing a plurality of seats into a plurality of seat groups according to service categories, geographic positions and service tags, firstly adding the current users into a queue of the seat group matched with service requirement selection data, the current geographic positions and the user tags of the current users, when the current users are not allocated with seats within the preset first threshold time, adding the current user into a queue of an agent group with the same service class and the same geographic position with the matched agent group, when the current user is not allocated with an agent within the preset second threshold time, the current user is added into the queue of other seat groups with the shortest expected waiting time, the seats are flexibly distributed, and the occurrence of dead rows is effectively avoided.
Description
Technical Field
The present invention relates to the field of communications technologies, and in particular, to a method, a system, a device, and a storage medium for allocating agents in a call center.
Background
The call center is a place or a system for realizing centralized user service based on modern communication technology, and can provide various information services such as inquiry, acceptance, consultation, complaint and the like of service products for various users. Modern call centers mostly adopt computer and communication integration technology, including queuing machines, packet switching systems (PBX) and seats, and the main working mode of the call center is as follows: the user is accessed from the PBX, and the queuing machine arranges the user to enter the queue to wait and timely allocates a seat to the user to finish the service.
Most of the existing call centers process user incoming calls in a first-in first-out queue mode according to service class groups, that is, a user accesses to the call center, first waits in a queue of a service class group according to service requirement classes, the user who is queued for waiting in the queue is firstly allocated with an agent, and then the subsequent user needs to continuously wait.
The user queuing process in the prior art is not high in flexibility, once a service class group is busy, the user can be arranged in a queue of the service class group in an inactive mode, namely, the user can continuously queue for a long time and cannot connect a corresponding seat, and when the waiting time is out, the user in the queue is hung up and quit, so that the user can find the corresponding seat for service by dialing for many times.
Disclosure of Invention
In order to solve the technical problems, the invention provides a method, a system, a device and a storage medium for allocating agents to a call center, which divide a plurality of agents into a plurality of agent groups, add a current user into an agent group queue with data selected according to service requirements, a current geographic position and user labels matched, and reallocate the agents to other agent groups when the user is not allocated with agents within a threshold time, thereby flexibly allocating the agents, improving the agent answering efficiency and effectively avoiding the occurrence of the dead line.
A first aspect of the present invention provides a method for allocating agents in a call center, comprising the steps of: s11, identifying a user tag for the user according to historical behavior data of the user, wherein the historical behavior data comprises user dialing frequency, user consumption data and a user character tag; s12, dividing the plurality of agents into a plurality of agent groups according to service types, geographic positions and service labels, wherein the service labels correspond to user labels; s13, accessing a user dial-in signal; s15, selecting data, a current geographic position and a user label to match with the seat group according to the service requirement of the current user, and adding the current user into a queue of the matched seat group; s16, when the current user is not allocated with an agent within the preset first threshold time, adding the current user into a queue of an agent group with the same service type and the same geographical position as the matched agent group and different service labels; and S17, when the current user is not allocated with the seat within the preset second threshold time, adding the current user into a queue of the seat group with the shortest expected waiting time in a plurality of seat groups with the same service type, different geographical positions and different service types and the same geographical positions as the matched seat group.
Preferably, step S14 is further included before step S15, and step S14 is performed to determine whether the current user has an intended seat, if not, step S15 is performed, if yes, it is further determined whether the intended seat is idle, if yes, the current user is accessed to the intended seat, and if not, step S15 is performed.
Preferably, the intended seat includes a seat corresponding to the current historical call of the current user or a seat corresponding to the current order of the current user.
Preferably, it is checked in step S16 periodically whether the current user is allocated with an agent, if so, the current user is connected to the allocated agent, otherwise, it is calculated whether the sum of the current user' S already waiting time and the expected waiting time exceeds a first threshold time, if so, the current user is added to the queue of the agent group of a different service tag in the same service category and the same geographical position as the matched agent group, otherwise, the current user continues to wait in the queue of the matched agent group.
Preferably, in step S17, it is periodically checked whether the current user is allocated with an agent, if so, the current user is connected with the allocated agent, otherwise, whether the sum of the waiting time of the current user in the queue of the current agent group and the estimated waiting time exceeds a second threshold time is calculated, if so, the current user is added to the queue of the agent group with the shortest estimated waiting time in the plurality of agent groups with the same service category, different geographical locations and different service categories and the same geographical locations as the matched agent group, and if not, the current user continues to wait in the queue of the current agent group.
Preferably, the expected waiting time t is calculated by the following formula: t ═ u ═ l/w) + (w ═ l-T)/w; wherein u is the number of queuing users, r is the user abandoning rate, l is the average call duration, w is the number of seats in the seat group, and T is the total call duration of the current calls of all the seats in the seat group.
Preferably, in step S11, the history call record and the satisfaction degree score data of the user are obtained, the history call record is voice-converted and the keyword is extracted, and the keyword and the satisfaction degree score data are input into a preset analysis model to obtain the user character tag.
A second aspect of the present invention provides a system for allocating agents to a call center, comprising: the user representation module is used for identifying a user tag for a user according to historical behavior data of the user, wherein the historical behavior data comprises user dialing frequency, user consumption data and a user character tag; the seat grouping module is used for dividing a plurality of seats into a plurality of seat groups according to service types, geographic positions and service labels, and the service labels correspond to the user labels; the queue allocation module is used for selecting data, a current geographical position and a user label matching seat group according to the service requirement of a current user when a user dial-in signal is accessed, adding the current user into the queue of the matching seat group, adding the current user into the queue of the seat group with the same service class and different service labels at the same geographical position when the current user is not allocated with a seat within a preset first threshold time, and adding the current user into the queue of the seat group with the same service class and different service classes as the matching seat group and with the shortest waiting time among a plurality of seat groups at the same geographical position when the current user is not allocated with a seat within a preset second threshold time.
The third aspect of the present invention also provides an agent allocation apparatus for a call center, comprising: a processor; a memory having stored therein executable instructions of the processor; wherein the processor is configured to perform the steps of the method of call center allocation of agents of the first aspect described above via execution of executable instructions.
A fourth aspect of the present invention also provides a computer-readable storage medium storing a program which, when executed, performs the steps of the method for allocating an agent in a call center of the first aspect.
The method, the system, the equipment and the storage medium for allocating the seats of the call center divide a user into a plurality of user labels according to the historical behavior data of the user, divide a plurality of seats into a plurality of seat groups according to the service types, the geographic positions and the service labels, firstly add the current user into a seat group queue matched with the service requirement selection data, the current geographic positions and the user labels when the seats are allocated to the current user, and redistribute the seats to other seat groups when detecting that the seats are not allocated to the user within the threshold time, thereby avoiding that all users in the prior art can queue in the seats of fixed service types only according to first-in first-out, improving the flexibility of seat allocation, improving the operation efficiency of the system and effectively reducing the occurrence of dead rows.
Drawings
Other features, objects and advantages of the present invention will become more apparent upon reading of the following detailed description of non-limiting embodiments thereof, with reference to the accompanying drawings.
Fig. 1 is a flowchart of a method for allocating agents in a call center according to a first embodiment of the present invention;
fig. 2 is a flowchart of a method for allocating agents to a call center according to a second embodiment of the present invention;
FIG. 3 is a schematic diagram of an agent group according to an embodiment of the invention;
FIG. 4 is a block diagram of a system including a call center for agent allocation according to one embodiment of the invention;
FIG. 5 is a schematic diagram of an apparatus for assigning agents to a call center according to an embodiment of the present invention; and
fig. 6 is a schematic structural diagram of a computer-readable storage medium according to an embodiment of the present invention.
Detailed Description
Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art. The same reference numerals in the drawings denote the same or similar structures, and thus their repetitive description will be omitted.
For allocating an agent to a call center, in the prior art, all users with the same service requirement are generally queued in a queue of a fixed service class group according to a first-in first-out principle, and the agent allocation mode has poor flexibility and cannot reasonably transfer agent resources, so that when the service class group is busy, the condition of user death is easily caused.
According to the invention, a plurality of seats are divided into a plurality of seat groups, the current user firstly joins the seat group queue matched with the service requirement selection data, the current geographic position and the user label, and when the user is not allocated with seats within the threshold time, the seats are reallocated to other seat groups, so that the seats are allocated flexibly, the seat answering efficiency is improved, and the occurrence of dead rows is effectively avoided.
Fig. 1 is a flowchart of a method for allocating an agent in a call center according to a first embodiment of the present invention. As shown in fig. 1, the method for allocating agents in a call center of the present invention includes the following steps:
and S11, identifying the user label for the user according to the historical behavior data of the user.
The historical behavior data includes at least user dialing frequency, user consumption data, and user personality tags. Wherein the frequency dialed by the user comprises the frequency that the user has historically dialed the call center. The user consumption data comprises the user account type, the account label and the user historical order quantity. In this embodiment, in order to improve the user classification accuracy, the user dialing frequency further includes a frequency at which the user dials the call center on the same day, and the user consumption data further includes a number of orders of the user on the same day. And (3) the user dialing frequency is obtained, each factor in the user consumption data is subjected to weighted calculation according to a respective preset weight value, and the user labels are divided according to a result value interval. In this embodiment, the user with high dialing frequency and high user consumption data is classified into a high urgency tag, and the user with low dialing frequency and low user consumption data is classified into a low urgency tag.
The user character labels are used for dividing the user labels according to different user character categories, so that the agent groups can be allocated in a targeted manner in the subsequent steps. Preferably, the predetermined analysis model, for example, a decision tree model or a Logistic regression model, is trained by using the artificial index and the reference data to complete the analysis model. The method comprises the steps of obtaining historical call records and satisfaction degree grading data of a user, carrying out voice conversion on the historical call records, extracting keywords, and inputting the keywords and the satisfaction degree grading data into a preset analysis model to obtain a user character label. In other embodiments the user personality tag may be invoked directly from an external system, such as a user analysis system, through an interface.
The invention uses multiple dimensions to carry out label division on the users, thereby being capable of pertinently distributing the corresponding seat groups in the subsequent steps, rapidly pairing the users with the proper seats and improving the system operation efficiency and the user satisfaction.
And S12, dividing the plurality of seats into a plurality of seat groups.
And evaluating service categories, character labels and skill labels of customer service personnel corresponding to the seats, and dividing the seats into a plurality of seat groups according to the service categories, the geographic positions and the service labels. The service category refers to a classification of service contents provided, such as a national hotel, a national ticket, and the like.
Fig. 3 is a schematic diagram of an agent group according to an embodiment of the present invention. As shown in fig. 3, the plurality of seats are divided into a seat group 1, a seat group 2, a seat group 3, and a seat group 4. The service category of the seats in the seat group 1 is domestic hotels, the position is Shanghai, and the service label is label 1. The service class of the seats in the seat group 2 is domestic hotels, the position is Shanghai, and the service label is label 2. The service category of the seat in the seat group 3 is a domestic air ticket, the position is Shanghai, and the service label is a label 1. The service category of the seats in the seat group 4 is domestic hotel, the position is Beijing, and the service label is label 1. The service classes of the agent group 1 and the agent group 2 are the same as the geographical location, and only the service labels are different. The seat group 1 and the seat group 3 have different service types and the same geographical position. The seat group 1 and the seat group 4 have the same service class and different geographical positions.
Different from the prior art, the invention uniformly plans and allocates the agents of all service classes and geographic positions, thereby increasing the flexibility of agent allocation. The service labels of the seat groups are divided by character labels and skill labels of customer service personnel, and the service labels correspond to the user labels.
And S13, accessing the user dial-in signal.
In this embodiment, an Interactive Voice Response (IVR) system is used to obtain a user dial-in signal, identify a current user according to a mobile phone number, a device number, or an IP address of the user, and further obtain a user tag. And acquiring the selection data of the current user for the service requirement from the IVR system. The service requirement selection data refers to service content which is selected by the user and needs to be provided, and the service requirement selection data corresponds to the service category.
And S15, matching the seat group, and adding the current user into the queue of the matched seat group.
Specifically, the completely matched seat group is obtained according to the service requirement selection data, the current geographic position and the user label of the current user, and the current user is added into the queue of the matched seat group.
And S16, when the current user is not allocated with the seat within the preset first threshold time, adding the current user into the queue of the seat group with different service labels of the same service type and the same geographic position as the matched seat group.
Step S16 includes step S161 of determining whether the current user is assigned with an agent within a preset first threshold time, and step S162 of adding the current user to a queue of an agent group with a different service tag of the same service category and the same geographical location as the matched agent group. Specifically, whether the current user is allocated with an agent is checked periodically, if yes, step S20 is executed to connect the current user with the allocated agent, if not, whether the sum of the waiting time of the current user and the expected waiting time exceeds a first threshold time is calculated, if yes, step S162 is executed to join the current user into a queue of an agent group of a different service tag in the same service class and the same geographic position as the matched agent group, otherwise, the current user continues to wait in the queue of the matched agent group, and step S161 is executed in a loop again.
Preferably, the predicted waiting time t is calculated by the following formula in the present embodiment:
t＝(u*(1-r)*l/w)+(w*l-T)/w；
wherein u is the number of queuing users, r is the user abandoning rate, l is the average call duration, w is the number of seats in the seat group, and T is the total call duration of the current calls of all the seats in the seat group. Wherein (u x (1-r) l/w) is the estimated demand time of the average processing of the seats in the queue of the current seat group for the existing queuing users, and (w x l-T)/w is the adjusted average value of the rated time of the seat processing and the actual occurrence time. Through the formula calculation, the predicted waiting time of the current user is effectively predicted, and the accuracy is high. Other methods of calculating the expected wait time may be used in other embodiments.
In other embodiments, step S162 may also be performed by directly determining whether the waiting time of the current user exceeds the threshold, if so. Or by determining whether the predicted wait time exceeds the first threshold time, if so, step S162 is performed. Compared with the two modes, the method adopted by the embodiment comprehensively considers the waiting time of the current user and the predicted waiting time, has high accuracy and good predictability, and further improves the agent allocation efficiency of the system.
And S17, when the current user is not allocated with the seat within the preset second threshold time, adding the current user into a queue of the seat group with the shortest expected waiting time in a plurality of seat groups with the same service type, different geographical positions and different service types and the same geographical positions as the matched seat group.
Step S17 includes step S171 of determining whether the current user is allocated with an agent within a preset second threshold time, and step S172 of adding the current user to the other agent group with the shortest expected waiting time. Specifically, whether the current user is allocated with an agent is checked regularly, if so, step S20 is executed to connect the current user with the allocated agent, otherwise, whether the sum of the waiting time of the current user in the queue of the current agent group and the estimated waiting time exceeds a second threshold time is calculated, if so, step S172 is executed to calculate the estimated waiting time of the agent group in the same service class and different geographical position as the matched agent group and the estimated waiting time of the agent group in the same geographical position as the matched agent group, and the service tags of the agent group are not distinguished in this step, that is, the estimated waiting time of the agent group of all the service tags in the above conditions is calculated. And adding the current user to the queue of the seat group with the shortest calculated predicted waiting time. If not, the current user continues to wait in the queue of the current seat group, and step S171 is executed in a loop again.
The calculation manner of the predicted wait time t in this step may be the same as that in step S16.
Taking the schematic diagram of the agent group in fig. 3 as an example, if the agent group matched by the current user in step S15 is the agent group 1, the current user is added into the queue of the agent group 1. If it is determined in step S16 that the current user is not allocated with an agent within the preset first threshold time, the current user is added to the agent group 2 with a different service tag in the same service category and the same geographical location as the agent group 1. If it is determined in step S17 that the current user is not assigned a seat within the preset second threshold time, the current user is added to the queue of the seat group with the shortest expected waiting time in the seat group 3 or the seat group 4.
The invention firstly adds the current user into the queue of the seat group matched with the service type, the geographic position and the service label so as to distribute proper seats and improve the service quality of the whole seats. And when the matched seat group is busy, reallocating the current user to the queue of the seat group with the same service class and geographic position but different service label as the matched seat group so as to reduce the queuing waiting time of the user on the basis of ensuring the service quality. And when the newly distributed agent group is still busy, the queues from the current user to other agent groups with the shortest expected waiting time are newly distributed, so that the queuing waiting time of the user is reduced, and the occurrence of dead queuing is avoided.
Fig. 2 is a flowchart of a method for allocating an agent to a call center according to a second embodiment of the present invention. As shown in fig. 2, the present embodiment is substantially the same as the first embodiment except that in the present embodiment, a step S14 is further included between step S13 and step S15 to determine whether the user currently has an intention seat.
Specifically, in step S13, a user dial-in signal is acquired by the IVR system, and the current user is identified according to the user' S mobile phone number, device number or IP address. Step S14 includes step S141 and step S142. Step S141 is first executed to determine whether there is an intended seat for the current user. In this implementation, the intended seat includes a seat corresponding to the current historical call of the current user on the day, or a seat corresponding to the current order of the current user. According to the current order and the current historical call of the user before the identified current user searches, the current order comprises the order in progress and the order not yet in progress, and in the embodiment, the current order further comprises the historical order of the completed day within 3 days. The seat corresponding to the historical call at the day or the seat processing the current order is the intention seat.
If it is determined that there is no intended seat, step S15 is executed to match the seat group and add the current user to the queue of the matched seat group. If it is determined that the intended seat exists, step S142 is executed to determine whether the intended seat is idle. If the intended seat is free, step S20 is executed to connect the assigned seat, i.e. to connect the current user with the intended seat. If the intended seat is not idle, step S15 is performed.
Through the setting of the step S14, the incoming calls before and after the user can be distributed to the same seat, and the seat can effectively track the user requirements, so that the seat is further reasonably distributed, and the service quality is improved.
As can be seen from the above description of the embodiments of the present invention, the present invention divides a plurality of seats into a plurality of seat groups, and first joins the current user to a seat group queue matched with the selected data according to the service requirement, the current geographical location and the user tag, and when the user is not allocated a seat within the first threshold time, reallocates the current user to a queue of a seat group having the same geographical location but different service tag as the service class of the matched seat group, and when the user is not allocated a seat within the second threshold time again, reallocates the current user to a queue of another seat group having the shortest expected waiting time. The agents in different geographic positions and service categories are managed in a unified mode, the agents are grouped, the users are distributed for many times, the agents are distributed flexibly, the agent service quality is guaranteed, the agent answering efficiency is improved, and the occurrence of death rows is effectively avoided.
The invention also provides a system for distributing the seats in the call center, which is used for queuing all users with the same service requirements in a queue of a fixed service class group according to the first-in first-out principle when the seats are distributed in the call center in the prior art, so that the flexibility is poor, the seat resources cannot be reasonably transferred, and when the service class group is busy, the problem of user deadlock is easy to occur.
Figure 4 is a block diagram of a system including a call center for agent allocation according to one embodiment of the invention. As shown in FIG. 4, the system 10 for call center agent allocation of the present invention includes a user representation module 11, an agent grouping module 12, and a queue allocation module 13.
The user profile module 11 is coupled to an external user database 20 for identifying user tags to users based on historical user behavior data in the external user database 20.
In this embodiment, the historical behavior data includes user dialing frequency, user consumption data, and user personality tags. The frequency of dialing by the user includes the frequency of dialing by the user history to the call center and the frequency of dialing by the user to the call center on the same day. The user consumption data comprises the user account type, the account label, the historical order quantity of the user and the order quantity of the user on the day. And (3) the user dialing frequency is obtained, each factor in the user consumption data is subjected to weighted calculation according to a respective preset weight value, and the user labels are divided according to a result value interval.
The agent grouping module 12 is configured to divide a plurality of agents into a plurality of agent groups according to service categories, geographic locations, and service tags, where the service tags correspond to user tags.
The queue allocation module 13 is configured to select data, a current geographic location, and a user tag matching an agent group according to a service requirement of a current user when the access user dials in a signal, and add the current user to a queue of the matching agent group. The queue allocation module 13 periodically monitors the queuing condition of the current user, and when the current user is not allocated with an agent within a preset first threshold time, adds the current user into a queue of an agent group with different service tags of the same service type and the same geographical position as the matched agent group. After the current user is redistributed, the queue distribution module 13 continues to monitor the queuing condition of the current user periodically, and when the current user is not distributed with an agent within the preset second threshold time, the current user is added into the queue of the agent group with the shortest waiting time, which is expected to be the shortest, among the plurality of agent groups in the same service category, different geographical positions, different service categories with the matched agent group, and the same geographical positions.
It will be appreciated that the call center agent assignment system 10 of the present invention also includes other existing functional modules that support the operation of the call center agent assignment system 10. The system 10 for assigning agents at a call center shown in fig. 4 is merely an example and should not impose any limitations on the functionality or scope of use of embodiments of the present invention.
The system 10 for allocating agents in the call center in this embodiment is used to implement the method for allocating agents in the call center, so for the specific implementation steps of the system 10 for allocating agents in the call center, reference may be made to the description of the method for allocating agents in the call center, and details are not described here again.
The system 10 for distributing the seats in the call center divides a user into a plurality of user labels according to the historical behavior data of the user, divides the plurality of seats into a plurality of seat groups according to the service types, the geographic positions and the service labels, firstly adds the current user into a seat group queue matched with the service requirement selection data, the current geographic positions and the user labels when distributing the seats to the current user, and redistributes the seats to other seat groups when detecting that the user is not distributed with the seats within the threshold time, thereby avoiding that all users in the prior art can only queue in the seats of fixed service types according to first-in first-out, improving the flexibility of seat distribution, improving the operation efficiency of the system and effectively reducing the occurrence of death row.
The embodiment of the invention also provides a device for distributing the seats in the call center, which comprises a processor. A memory having stored therein executable instructions of the processor. Wherein the processor is configured to perform the steps of the above-described method of call center agent allocation via execution of executable instructions.
As described above, in the embodiment, a plurality of agents are divided into a plurality of agent groups, the current user firstly joins the agent group queue with the data selected according to the service requirement, the current geographic position and the user tag matched, and when the user is not allocated an agent within the threshold time, the agent group queue is reallocated to other agent groups, so that the agents are flexibly allocated, the agent answering efficiency is improved, and the occurrence of the death row is effectively avoided.
As will be appreciated by one skilled in the art, aspects of the present invention may be embodied as a system, method or program product. Thus, various aspects of the invention may be embodied in the form of: an entirely hardware embodiment, an entirely software embodiment (including firmware, microcode, etc.) or an embodiment combining hardware and software aspects that may all generally be referred to herein as a "circuit," module "or" platform.
Fig. 5 is a schematic structural diagram of an agent allocation device of a call center according to an embodiment of the present invention. Call center assignment agent arrangement 600 according to this embodiment of the invention is described below with reference to fig. 5. The call center assignment agent device 600 shown in fig. 5 is only an example and should not impose any limitations on the functionality or scope of use of embodiments of the present invention.
As shown in fig. 5, the call center assignment agent device 600 is embodied in the form of a general purpose computing device. The components of the call center assignment agent apparatus 600 may include, but are not limited to: at least one processing unit 610, at least one memory unit 620, a bus 630 connecting the different platform components (including the memory unit 620 and the processing unit 610), a display unit 640, etc.
Wherein the storage unit stores program code executable by the processing unit 610 to cause the processing unit 610 to perform steps according to various exemplary embodiments of the present invention described in the above-mentioned electronic prescription flow processing method section of the present specification. For example, processing unit 610 may perform the steps as shown in fig. 1.
The storage unit 620 may include readable media in the form of volatile memory units, such as a random access memory unit (RAM)6201 and/or a cache memory unit 6202, and may further include a read-only memory unit (ROM) 6203.
The memory unit 620 may also include a program/utility 6204 having a set (at least one) of program modules 6205, such program modules 6205 including, but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which, or some combination thereof, may comprise an implementation of a network environment.
The call center assignment agent device 600 may also communicate with one or more external devices 700 (e.g., keyboard, pointing device, bluetooth device, etc.), with one or more devices that enable a user to interact with the call center assignment agent device 600, and/or with any device (e.g., router, modem, etc.) that enables the call center assignment agent device 600 to communicate with one or more other computing devices. Such communication may occur via an input/output (I/O) interface 650. Also, the call center assignment agent device 600 may also communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network, such as the internet) via a network adapter 660. The network adapter 660 may communicate with other modules of the call center distribution agent apparatus 600 via the bus 630. It should be appreciated that although not shown in the figures, other hardware and/or software modules may be used in conjunction with the call center assignment agent apparatus 600, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage platforms, to name a few.
The embodiment of the present invention further provides a computer-readable storage medium, which is used for storing a program, and when the program is executed, the steps of the method for allocating an agent in the call center in the above embodiments are implemented. In some possible embodiments, the aspects of the present invention may also be implemented in the form of a program product comprising program code for causing a terminal device to perform the steps according to various exemplary embodiments of the present invention described in the above-mentioned electronic prescription flow processing method section of this specification, when the program product is run on the terminal device.
As shown above, when the program of the computer-readable storage medium of this embodiment is executed, the multiple agents are divided into multiple agent groups, the current user is first added to the agent group queue with matching data selected according to service requirements, the current geographic location and the user tag, and when the user is not allocated an agent within the threshold time, the user is reallocated to another agent group, so that the agents are flexibly allocated, the agent answering efficiency is improved, and the occurrence of the dead line is effectively avoided.
Fig. 6 is a schematic structural diagram of a computer-readable storage medium according to an embodiment of the present invention. Referring to fig. 6, a program product 800 for implementing the above method according to an embodiment of the present invention is described, which may employ a portable compact disc read only memory (CD-ROM) and include program code, and may be run on a terminal device, such as a personal computer. However, the program product of the present invention is not limited in this regard and, in the present document, a readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
The program product may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
A computer readable storage medium may include a propagated data signal with readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A readable storage medium may also be any readable medium that is not a readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a readable storage medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., through the internet using an internet service provider).
The method, the system, the equipment and the storage medium for distributing the seats of the call center firstly add the current user into the queue of the seat group matched with the service class, the geographic position and the service label so as to distribute proper seats and improve the service quality of the whole seats. And when the matched seat group is busy, reallocating the current user to the queue of the seat group with the same service class and geographic position but different service label as the matched seat group so as to reduce the queuing waiting time of the user on the basis of ensuring the service quality. And when the newly distributed agent group is still busy, the queues from the current user to other agent groups with the shortest expected waiting time are newly distributed, so that the queuing waiting time of the user is reduced, and the occurrence of dead queuing is avoided.
The foregoing is a more detailed description of the invention in connection with specific preferred embodiments and it is not intended that the invention be limited to these specific details. For those skilled in the art to which the invention pertains, several simple deductions or substitutions can be made without departing from the spirit of the invention, and all shall be considered as belonging to the protection scope of the invention.
Claims (8)
1. A method for assigning agents to a call center, comprising the steps of:
s11, identifying a user label for the user according to historical behavior data of the user, wherein the historical behavior data comprises user dialing frequency, user consumption data and a user character label;
s12, dividing a plurality of agents into a plurality of agent groups according to service types, geographic positions and service labels, wherein the service labels correspond to the user labels;
s13, accessing a user dial-in signal;
s15, selecting data, a current geographic position and a user label to match with the seat group according to the service requirement of the current user, and adding the current user into a queue of the matched seat group;
s16, checking whether the current user is allocated with an agent regularly, if so, connecting the current user with the allocated agent, if not, calculating whether the sum of the waiting time of the current user and the estimated waiting time exceeds a first threshold time, if so, adding the current user into a queue of the agent group with the same service class and the same geographic position with the matched agent group and different service labels, otherwise, continuing waiting the current user in the queue of the matched agent group,
the predicted waiting time t is calculated by the following formula:
t＝(u*(1-r)*l/w)+(w*l-T)/w；
wherein u is the number of queuing users, r is the user abandoning rate, l is the average call duration, w is the number of seats in the seat group, T is the total call duration of the current calls of all the seats in the seat group,
when the current user is not allocated with an agent within the preset first threshold time, adding the current user into a queue of an agent group with the same service type and the same geographic position as the matched agent group and different service labels;
and S17, when the current user is not allocated with the seat within the preset second threshold time, adding the current user into a queue of the seat group with the shortest expected waiting time in a plurality of seat groups with the same service type, different geographical positions and different service types and the same geographical positions as the matched seat group.
2. The method for allocating an agent to a call center according to claim 1, further comprising a step S14 before the step S15, determining whether the current user has an intended agent, if not, performing the step S15, if so, further determining whether the intended agent is idle, if so, accessing the current user to the intended agent, otherwise, performing the step S15.
3. The method for allocating an agent to a call center according to claim 2, wherein the intended agent comprises an agent corresponding to a current user's current day history call or an agent corresponding to a current user's current order.
4. The method for allocating an agent in a call center according to claim 1, wherein in step S17, it is periodically checked whether the current user is allocated with an agent, if so, the current user is connected to the allocated agent, if not, it is calculated whether the sum of the waiting time of the current user in the queue of the current agent group and the predicted waiting time exceeds a second threshold time, if so, the current user is added to the queue of the agent group with the shortest predicted waiting time in the plurality of agent groups with the same service category, different geographical locations and different service categories, and the same geographical locations as the matched agent group, and if not, the current user continues to wait in the queue of the current agent group.
5. The method for allocating an agent to a call center according to claim 1, wherein in step S11, a history call record and satisfaction rating data of the user are obtained, the history call record is voice-converted and keywords are extracted, and the keywords and the satisfaction rating data are input into a preset analysis model to obtain a user personality label.
6. A system for assigning agents to a call center, comprising:
the user representation module is used for identifying a user tag for a user according to historical behavior data of the user, wherein the historical behavior data comprises user dialing frequency, user consumption data and a user character tag;
the seat grouping module is used for dividing a plurality of seats into a plurality of seat groups according to service types, geographic positions and service labels, and the service labels correspond to the user labels;
a queue distribution module, which is used for selecting data, the current geographic position and the user label to match the seat group according to the service requirement of the current user when accessing the user dial-in signal, adding the current user into the queue of the matched seat group,
checking whether the current user is allocated with the seat regularly, if so, connecting the current user with the allocated seat, otherwise, calculating whether the sum of the waiting time of the current user and the estimated waiting time exceeds a first threshold time, if so, adding the current user into a queue of the seat group with the same service class and the same geographic position as the matched seat group, otherwise, continuing waiting the current user in the queue of the matched seat group,
the predicted waiting time t is calculated by the following formula:
t＝(u*(1-r)*l/w)+(w*l-T)/w；
wherein u is the number of queuing users, r is the user abandoning rate, l is the average call duration, w is the number of seats in the seat group, T is the total call duration of the current calls of all the seats in the seat group,
when the current user is not allocated with the seat within the preset first threshold time, the current user is added into a queue of the seat group with the same service class and different service labels at the same geographical position as the matched seat group, and when the current user is not allocated with the seat within the preset second threshold time, the current user is added into a queue of the seat group with the same service class, different geographical position and different service class and expected waiting time of the plurality of seat groups at the same geographical position as the matched seat group.
7. An apparatus for assigning agents to a call center, comprising:
a processor;
a memory having stored therein executable instructions of the processor;
wherein the processor is configured to perform the steps of the method of call center assigning agents of any of claims 1 to 5 via execution of the executable instructions.
8. A computer-readable storage medium storing a program, wherein the program when executed implements the steps of the method of assigning agents for a call center of any of claims 1 to 5.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811019192.5A CN108683818B (en) | 2018-09-03 | 2018-09-03 | Method, system, equipment and storage medium for distributing seats in call center |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811019192.5A CN108683818B (en) | 2018-09-03 | 2018-09-03 | Method, system, equipment and storage medium for distributing seats in call center |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN108683818A CN108683818A (en) | 2018-10-19 |
| CN108683818B true CN108683818B (en) | 2020-10-23 |
Family
ID=63815642
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811019192.5A Active CN108683818B (en) | 2018-09-03 | 2018-09-03 | Method, system, equipment and storage medium for distributing seats in call center |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108683818B (en) |
Families Citing this family (20)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109657965A (en) * | 2018-12-13 | 2019-04-19 | 上海安吉星信息服务有限公司 | A kind of service resource allocation method, device, storage medium and processor |
| CN110062120B (en) * | 2019-04-29 | 2020-08-25 | 携程旅游信息技术（上海）有限公司 | Call center seat allocation method, system, device and storage medium |
| CN110070298B (en) * | 2019-04-29 | 2020-12-22 | 携程旅游信息技术（上海）有限公司 | Call center task allocation method, system, equipment and storage medium |
| CN110147905B (en) * | 2019-05-08 | 2022-03-25 | 联想(北京)有限公司 | Information processing method, device, system and storage medium |
| CN110213450B (en) * | 2019-05-14 | 2021-04-23 | 长沙手之声信息科技有限公司 | Multi-center-based sign language online customer service distribution management method, device and system |
| CN111263015A (en) * | 2019-07-11 | 2020-06-09 | 上海联逾信息技术有限公司 | Mobile phone outbound management system |
| CN110572524B (en) * | 2019-08-15 | 2022-12-09 | 中国平安财产保险股份有限公司 | User call processing method, device, storage medium and server |
| CN111246025B (en) * | 2020-02-27 | 2021-03-09 | 大连即时智能科技有限公司 | Man-machine mixed arrangement customer service method and system |
| CN113905136A (en) * | 2020-06-22 | 2022-01-07 | 马上消费金融股份有限公司 | Agent allocation method, electronic equipment and storage medium |
| CN111626648B (en) * | 2020-07-28 | 2021-02-26 | 太平金融科技服务（上海）有限公司 | Survey task scheduling method and device, computer equipment and storage medium |
| CN111866288A (en) * | 2020-08-05 | 2020-10-30 | 中国银行股份有限公司 | Client incoming call processing method and device |
| CN112200440A (en) * | 2020-09-30 | 2021-01-08 | 深圳前海微众银行股份有限公司 | Agent allocation method and device, electronic equipment and computer readable storage medium |
| CN112422748B (en) * | 2020-11-23 | 2021-09-07 | 深圳供电局有限公司 | Dispatching telephone system and intelligent response method thereof |
| CN112751976B (en) * | 2020-12-23 | 2022-10-21 | 携程旅游信息技术（上海）有限公司 | Agent association method, system, equipment and storage medium based on authentication log |
| CN113762691A (en) * | 2021-01-14 | 2021-12-07 | 北京沃东天骏信息技术有限公司 | Service distribution method and device |
| CN113660383A (en) * | 2021-08-18 | 2021-11-16 | 浙江百应科技有限公司 | Artificial agent distribution method and device based on intelligent routing and electronic equipment |
| CN113869739A (en) * | 2021-09-29 | 2021-12-31 | 联想(北京)有限公司 | Service data processing method and device and electronic equipment |
| CN114356485A (en) * | 2022-01-07 | 2022-04-15 | 北京微呼科技有限公司 | Intelligent queuing position method and system based on label attribute |
| CN116414955B (en) * | 2022-12-26 | 2023-11-07 | 杭州数令集科技有限公司 | Intelligent queuing method, device, equipment and medium based on client intention and intention |
| CN116137620B (en) * | 2023-02-27 | 2024-04-19 | 飞虎互动科技(北京)有限公司 | Call routing method, device, electronic equipment and computer readable storage medium |
Family Cites Families (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6130942A (en) * | 1998-10-30 | 2000-10-10 | Ericsson Inc. | Skills-based automatic call distribution system |
| US9712679B2 (en) * | 2008-01-28 | 2017-07-18 | Afiniti International Holdings, Ltd. | Systems and methods for routing callers to an agent in a contact center |
| CA2713476C (en) * | 2008-01-28 | 2017-10-03 | The Resource Group International Ltd | Routing callers from a set of callers in an out of order sequence |
| US9025757B2 (en) * | 2012-03-26 | 2015-05-05 | Satmap International Holdings Limited | Call mapping systems and methods using bayesian mean regression (BMR) |
| CN104243730A (en) * | 2013-06-24 | 2014-12-24 | 中兴通讯股份有限公司 | Telephone call access processing method and device and call center |
| CN104125349B (en) * | 2014-06-27 | 2016-03-02 | 国家电网公司 | A kind of interactive voice management method based on traffic forecast and system thereof |
| CN106603262A (en) * | 2015-10-19 | 2017-04-26 | 阿里巴巴集团控股有限公司 | Method and system of distribution of customer service modes |
| CN108093149A (en) * | 2017-12-25 | 2018-05-29 | 平安科技（深圳）有限公司 | Exclusive pond distribution method, electronic device and the computer readable storage medium of attending a banquet |
-
2018
- 2018-09-03 CN CN201811019192.5A patent/CN108683818B/en active Active
Also Published As
| Publication number | Publication date |
|---|---|
| CN108683818A (en) | 2018-10-19 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108683818B (en) | Method, system, equipment and storage medium for distributing seats in call center | |
| CN108989588B (en) | Call distribution method, call center, electronic device, and storage medium | |
| KR102121135B1 (en) | Optimized routing of interactions to contact center agents based on machine learning | |
| EP3335119B1 (en) | Multi-priority service instance allocation within cloud computing platforms | |
| CN102300012B (en) | One-to-one matching in contact center | |
| US8391465B1 (en) | Customer care call routing | |
| EP3449438A1 (en) | Customer experience analytics | |
| CN102223453B (en) | High performance queueless contact center | |
| US20080144803A1 (en) | Dynamic agent skill balancing | |
| US8843929B1 (en) | Scheduling in computer clusters | |
| US20070133781A1 (en) | Method and system for automatic assignment of work units to agents | |
| CN107944000B (en) | Flight freight rate updating method and device, electronic equipment and storage medium | |
| CN107786760B (en) | Call center, queuing management method and device thereof, electronic equipment and storage medium | |
| WO2019080415A1 (en) | Client incoming call assignment method and system, computer device and storage medium | |
| CN110070298B (en) | Call center task allocation method, system, equipment and storage medium | |
| GB2479646A (en) | Analysing and converting performance metrics of a queueless contact centre | |
| WO2021179634A1 (en) | Customer service dispatching method, apparatus and device, and storage medium | |
| WO2019062000A1 (en) | Incoming call assignment method for attendants, electronic device and computer readable storage medium | |
| CN111985786A (en) | Agent-based task allocation method and device, computer equipment and storage medium | |
| US20210120092A1 (en) | Adaptive data fetching from network storage | |
| BRPI1101806A2 (en) | automated mechanism to populate and maintain data structures in a queue-free call center | |
| WO2019080416A1 (en) | Customer incoming call allocation method and system, computer device and storage medium | |
| WO2019227623A1 (en) | Method and apparatus for processing data of call platforms, device, and storage medium | |
| CN111932099A (en) | Marketing business management system and marketing business management method | |
| US20160165052A1 (en) | Automatic contact center expansion and contraction |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |