WO2019200767A1 - 坐席任务分配方法、装置、计算机设备及存储介质 - Google Patents

坐席任务分配方法、装置、计算机设备及存储介质 Download PDF

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Publication number
WO2019200767A1
WO2019200767A1 PCT/CN2018/096469 CN2018096469W WO2019200767A1 WO 2019200767 A1 WO2019200767 A1 WO 2019200767A1 CN 2018096469 W CN2018096469 W CN 2018096469W WO 2019200767 A1 WO2019200767 A1 WO 2019200767A1
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Prior art keywords
agent
task
marketing
audience
marketing activity
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PCT/CN2018/096469
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English (en)
French (fr)
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李洋
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平安科技（深圳）有限公司
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    • 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
    • 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
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G06Q30/0207—Discounts or incentives, e.g. coupons or rebates

Definitions

  • the present invention relates to the field of task management technologies, and in particular, to a method, device, computer device and storage medium for assigning agent tasks of a call center agent.
  • the call center system plays an increasingly important role in product promotion, product sales, technical support, after-sales service, consulting and complaints, and plays a role in the business activities of enterprises. An increasingly important role.
  • the agent service is an important way for the call center system to provide services for customers.
  • the agent service refers to the process in which the agent provides the corresponding service to the customer through the support system of the call center.
  • the agent system will use different marketing campaign recommendations to obtain different types of customers to achieve accurate marketing.
  • the task that is issued is excessively manual, the task is bound to the client, and then the client is manually bound to the agent.
  • the intelligent distribution mode should be adopted as much as possible, and the customer should be allocated according to the actual customer volume, the task amount, and the actual daily processing capacity of the agent.
  • the purpose of the present application is to provide an agent task allocation method for solving the problems existing in the prior art.
  • the present application provides a method for assigning an agent task, which is applicable to a method for assigning an agent task in a marketing campaign such as insurance, including the following steps:
  • Step 01 Obtain a marketing activity task allocation request
  • Step 02 analyzing the marketing activity information, and extracting the number of tasks and the task time in the marketing activity information
  • Step 03 Obtain agent information of all agents who can perform a marketing campaign task
  • Step 04 determining whether the agents have a binding relationship with the customer corresponding to the marketing activity task, if yes, executing step 05, if not, executing step 06;
  • Step 05 Assign a marketing activity task of the customer with the binding relationship to the corresponding agent
  • Step 06 the marketing campaign task of the unbound relationship is equally distributed to all available agents
  • step 07 the amount of tasks per agent per day is established according to the number of tasks assigned to each agent and the task time.
  • the present application further provides a task distribution apparatus, including:
  • An analysis module for analyzing marketing activity information, extracting the number of tasks and task time in the marketing activity information
  • An agent acquisition module is configured to obtain agent information of all agents who can perform a marketing campaign task
  • a judging module configured to determine whether the obtained executable agent has a binding relationship with a client corresponding to the marketing activity task
  • An execution module configured to allocate a marketing activity task of a customer having a binding relationship to a corresponding agent, and distribute an marketing activity task of the unbounded customer to all available agents equally;
  • the task quantity management module is configured to establish the amount of tasks per agent per day according to the number of tasks assigned to each agent and the task time.
  • the present application further provides a computer device including a memory, a processor, and a computer program stored on the memory and operable on the processor, the processor implementing the agent task allocation method when the computer program is executed The following steps:
  • Step 01 Obtain a marketing activity task allocation request
  • Step 02 analyzing the marketing activity information, and extracting the number of tasks and the task time in the marketing activity information
  • Step 03 Obtain agent information of all agents who can perform a marketing campaign task
  • Step 04 determining whether the agents have a binding relationship with the customer corresponding to the marketing activity task, if yes, executing step 05, if not, executing step 06;
  • Step 05 Assign a marketing activity task of the customer with the binding relationship to the corresponding agent
  • Step 06 the marketing campaign task of the unbound relationship is equally distributed to all available agents
  • step 07 the amount of tasks per agent per day is established according to the number of tasks assigned to each agent and the task time.
  • the present application also provides a computer readable storage medium having stored thereon a computer program that, when executed by a processor, implements the following steps of the agent task assignment method:
  • Step 01 Obtain a marketing activity task allocation request
  • Step 02 analyzing the marketing activity information, and extracting the number of tasks and the task time in the marketing activity information
  • Step 03 Obtain agent information of all agents who can perform a marketing campaign task
  • Step 04 determining whether the agents have a binding relationship with the customer corresponding to the marketing activity task, if yes, executing step 05, if not, executing step 06;
  • Step 05 Assign a marketing activity task of the customer with the binding relationship to the corresponding agent
  • Step 06 the marketing campaign task of the unbound relationship is equally distributed to all available agents
  • step 07 the amount of tasks per agent per day is established according to the number of tasks assigned to each agent and the task time.
  • the task distribution device, the device, the computer device and the storage medium provided by the application provide a task management method for the agent based on intelligent management, allocation, and adjustment of the workload of the agent.
  • the system achieves precise marketing by acquiring different types of customers based on various marketing campaign recommendations.
  • the classifier the audience is classified into the audience, the class is classified according to the classifier, and the audience is matched with the agent, and then the distribution is performed, so that the accuracy of the task is high, and the binding task is adjusted and more humanized.
  • the feedback module is dynamically adjusted to the needs to make the assignment task more scientific.
  • Embodiment 1 is a flowchart of Embodiment 1 of a method for managing an agent task according to the present application;
  • FIG. 2 is a schematic diagram of a program module of Embodiment 1 of the agent task management apparatus of the present application;
  • Embodiment 3 is a schematic structural diagram of hardware of Embodiment 1 of an agent task management apparatus according to the present application;
  • Embodiment 4 is a flowchart of Embodiment 2 of a method for managing an agent task according to the present application;
  • FIG. 5 is a schematic diagram of a program module of Embodiment 2 of the agent task management apparatus of the present application.
  • the agent task allocation method, device, computer equipment and storage medium provided by the application are applicable to the insurance business field, and provide a task management method for the agent based on intelligent management, allocation, and adjustment of the workload of the agent.
  • the system achieves precise marketing by acquiring different types of customers based on various marketing campaign recommendations.
  • the classifier the audience is classified into the audience, the class is classified according to the classifier, and the audience is matched with the agent, and then the distribution is performed, so that the accuracy of the task is high, and the binding task is adjusted and more humanized.
  • the feedback module is dynamically adjusted to the needs to make the assignment task more scientific.
  • a method for assigning an agent task in the embodiment is applicable to a method for assigning an agent task to a marketing activity in a field such as insurance.
  • Step 01 Obtain a marketing activity task allocation request.
  • marketing activities include breakpoint tasks, IB (incoming) consulting tasks, service tasks, comprehensive sales tasks, insurance sales tasks, and after-sales tasks.
  • the marketing task assignment includes, but is not limited to, the marketing task category, the processing order is arranged in order of priority, the total number of tasks in a certain category of statistical marketing tasks, the number of tasks in a certain task cluster in the task allocation request, and the task.
  • the frequency limit for processing a category task in an allocation request includes, but is not limited to, the marketing task category, the processing order is arranged in order of priority, the total number of tasks in a certain category of statistical marketing tasks, the number of tasks in a certain task cluster in the task allocation request, and the task.
  • the frequency limit for processing a category task in an allocation request includes, but is not limited to, the marketing task category, the processing order is arranged in order of priority, the total number of tasks in a certain category of statistical marketing tasks, the number of tasks in a certain task cluster in the task allocation request, and the task.
  • step 02 the marketing activity information is analyzed, and the number of tasks and the task time in the marketing activity information are extracted.
  • the analyzing the marketing activity information includes, but is not limited to, analyzing the marketing audience, extracting demographic characteristics, formulating a marketing plan, and obtaining the number of tasks and the task time according to the marketing plan.
  • the marketing audience is classified according to the information obtained by the audience.
  • the classification can be classified according to the audience's resume, that is, according to the audience's age, gender, occupation, position, family situation, education, region, or according to the audience's browsing.
  • Information keyword classification is, that is, according to the audience's age, gender, occupation, position, family situation, education, region, or according to the audience's browsing.
  • step 03 the agent information of all agents who can perform the marketing activity task is obtained.
  • the agent information of all the agents is traversed, the agent who is consistent with the audience feature is found, and the agent is reserved; if the audience feature is inconsistent, the agent is deleted. Mark the traversed set of agents as the first set of seats.
  • the number of traversals is determined according to the number of demographics and the number of categories in which the agent is good at the field, and the agent is good at matching the domain with the audience classification two or three times.
  • the set of agents obtained in the last traversal is taken as all agents of the executable marketing campaign task.
  • step 04 it is determined whether the agents have a binding relationship with the client corresponding to the marketing activity task, if yes, step 05 is performed, and if not, step 06 is performed.
  • the agent does not belong to the traversed agent set, and further includes feedback binding the agent to the event, and the binding agent selects to continue. Bind or unbind. If the binding is continued, the process proceeds to step S05, and if the binding is released, the process proceeds to step S06.
  • the specific method for determining the binding relationship is: obtaining the marketing activity information from the database of the marketing activity task, using SQL to obtain the historical binding relationship column in the database, and querying the binding relationship between a marketing audience and a specific agent in the database.
  • SQL a program that specifies the binding relationship between a marketing audience and a specific agent in the database.
  • the records need to be arranged according to the time sequence of the timed record of the query binding relationship, and the most The agent corresponding to the binding time record in which the timestamp is located serves as the agent in the binding relationship with the client, and records the next step.
  • step 05 the marketing activity task of the customer with the binding relationship is assigned to the corresponding agent.
  • step 06 the marketing activity task of the unbounded customer is evenly distributed to all available agents.
  • the date is the planned completion period of the task, and the system selects the idle time period of the agent from the start date to the end date range. Select the time period to mark as the occupation time.
  • the system acquires and evenly distributes the tasks of MYC push.
  • the distribution rules are as follows:
  • task A has 300 total tasks completed in 6 days, involving 3 seats.
  • seat 1 should be divided into 100
  • seat 2 should be divided into 80
  • seat 3 should be divided into 120.
  • assign the tasks of different agents 1 point and 100 seats, 2 points and 90 seats, and 3 points and 110 seats.
  • step 07 the amount of tasks per agent per day is established according to the number of tasks assigned to each agent and the task time.
  • the amount of tasks per agent per day is established.
  • the daily task of the first agent the total task/task plan completion period of the first agent (100/6).
  • the integer is 17, and 17 tasks are assigned every day, and 15 are assigned on the last day.
  • the total task amount of each agent is established, the total task amount is made into a total task list, and the total task list is sorted according to the deadline time of the task, and the seat day calculated according to the above is calculated when the agent daily task is assigned.
  • the average task amount, the priority deadline is to arrange the task with the highest deadline.
  • the task can be uniformly distributed to each agent in the most scientific and reasonable condition without affecting the progress of the task, thereby improving the scientific, convenient and humanized management of the agent task.
  • an agent task assigning device 10 is illustrated.
  • the agent task assigning device 10 may include or be divided into one or more program modules, and one or more program modules are stored in The storage medium is executed by one or more processors to complete the application, and the above-described agent task management method can be implemented.
  • the program module referred to in the present application refers to a series of computer program instruction segments capable of performing a specific function, and is more suitable than the program itself to describe the execution process of the agent task distribution device 10 in the storage medium. The following description will specifically describe the functions of each program module of this embodiment:
  • the request obtaining module 11 is configured to obtain a marketing activity task allocation request
  • the analyzing module 12 is configured to analyze the marketing activity information, and extract the number of tasks and the task time in the marketing activity information;
  • An executable agent obtaining module 13 is configured to obtain agent information of all agents who can perform a marketing campaign task
  • the determining module 14 is configured to determine whether the obtained executable agent has a binding relationship with a client corresponding to the marketing activity task;
  • the execution module 15 is configured to allocate a marketing activity task of the customer with the binding relationship to the corresponding agent, and distribute the marketing activity task of the unbounded customer to all available agents equally;
  • the task quantity management module 16 is configured to establish the amount of tasks per agent per day according to the number of tasks assigned to each agent and the task time.
  • the method further includes a request matching module 17, wherein the request matching module is configured to match the processing capability of the system itself, and if the processing demand of the marketing activity task allocation request is greater than the processing capability of the system itself, rejecting the marketing activity task allocation request and receiving The next marketing activity task assignment request is then matched until the processing requirements for receiving the marketing activity allocation request match the system processing capabilities.
  • the request matching module is configured to match the processing capability of the system itself, and if the processing demand of the marketing activity task allocation request is greater than the processing capability of the system itself, rejecting the marketing activity task allocation request and receiving The next marketing activity task assignment request is then matched until the processing requirements for receiving the marketing activity allocation request match the system processing capabilities.
  • the analysis module comprises an audience analysis module, a feature extraction module, and a solution generation module.
  • the audience analysis module includes a classifier classified according to one or more categories of the age, gender, occupation, position, family situation, education, and region of the audience, and a classifier classified according to the browsing information keyword of the audience.
  • the task adjustment module 18 further automatically selects a customer category for the agent according to the feature matching degree, and preferentially assigns the remaining binding customer to the agent with a high degree of feature matching under the same idle degree, if the rated task When the quantity is full, it is marked as occupying the seat set, and the feedback is sent to the executable agent acquisition module, and the occupied seat set is deleted in all the seats, and then traversed.
  • the embodiment further provides a computer device, such as a smart phone, a tablet computer, a notebook computer, a desktop computer, a rack server, a blade server, a tower server or a rack server (including a stand-alone server, or A server cluster consisting of multiple servers).
  • the computer device 20 of this embodiment includes at least but not limited to: a memory 21 and a processor 22 communicably connected to each other through a system bus, as shown in FIG. It is noted that FIG. 3 shows only computer device 20 having components 21-22, but it should be understood that not all illustrated components may be implemented and that more or fewer components may be implemented instead.
  • the memory 21 (ie, the readable storage medium) includes a flash memory, a hard disk, a multimedia card, a card type memory (for example, an SD or DX memory, etc.), a random access memory (RAM), a static random access memory (SRAM), Read only memory (ROM), electrically erasable programmable read only memory (EEPROM), programmable read only memory (PROM), magnetic memory, magnetic disk, optical disk, and the like.
  • memory 21 may be an internal storage unit of computer device 20, such as a hard disk or memory of computer device 20.
  • the memory 21 may also be an external storage device of the computer device 20, such as a plug-in hard disk equipped on the computer device 20, a smart memory card (SMC), and a secure digital (Secure Digital, SD) card, flash card, etc.
  • the memory 21 can also include both internal storage units of the computer device 20 as well as external storage devices thereof.
  • the memory 21 is generally used to store an operating system installed in the computer device 20 and various types of application software, such as the program code of the agent task management device 10 of the first embodiment. Further, the memory 21 can also be used to temporarily store various types of data that have been output or are to be output.
  • Processor 22 may be a Central Processing Unit (CPU), controller, microcontroller, microprocessor, or other data processing chip in some embodiments.
  • the processor 22 is typically used to control the overall operation of the computer device 20.
  • the processor 22 is configured to run the program code or the processing data stored in the memory 21, for example, the agent task management device 10, to implement the agent task management method of the first embodiment.
  • the embodiment further provides a computer readable storage medium such as a flash memory, a hard disk, a multimedia card, a card type memory (for example, SD or DX memory, etc.), a random access memory (RAM), a static random access memory (SRAM), and only Read memory (ROM), electrically erasable programmable read only memory (EEPROM), programmable read only memory (PROM), magnetic memory, magnetic disk, optical disk, server, App application store, etc., on which a computer program is stored.
  • the program implements the corresponding function when executed by the processor.
  • the computer readable storage medium of the embodiment is configured to store the agent task management device 10, and when executed by the processor, implement the agent task assignment method of the first embodiment.
  • the agent task management method in this embodiment is based on the first embodiment, and includes the following steps:
  • Step 01 Obtain a marketing activity task allocation request.
  • marketing activities include breakpoint tasks, IB (incoming) consulting tasks, service tasks, comprehensive sales tasks, insurance sales tasks, and after-sales tasks.
  • IB incoming
  • step 02 the marketing activity information is analyzed, and the number of tasks and the task time in the marketing activity information are extracted.
  • the analyzing the marketing activity information includes, but is not limited to, analyzing the marketing audience, extracting demographic characteristics, formulating a marketing plan, and obtaining the number of tasks and the task time according to the marketing plan.
  • the audience classification method can also classify the audience history and classify the browsing information keywords of the audience. Extract the audience profiles of the marketing audience and/or the audience characteristics in the keyword classification of the information. Develop a marketing plan based on these demographics.
  • step 03 the agent information of all agents who can perform the marketing activity task is obtained.
  • the agent information of all the agents is traversed, the agent information of the agent consistent with the audience feature is found, and the agent is retained; if the audience feature is inconsistent, the agent is deleted. Mark the traversed set of agents as the first set of seats.
  • the number of traversals is determined according to the number of demographics and the number of categories in which the agent is good at the field, and the agent is good at matching the domain with the audience classification two or three times.
  • the first traversal of the demographics is: IT people, get the first agent set.
  • the second traversal demographic feature is: 40 years old, the second traversal is performed in the first agent, and the second agent set is obtained.
  • the third matching feature has been born, and performs the third traversal in the second agent set to obtain the third seat set.
  • the feature matching degree of the third agent set is greater than the feature matching degree of the second agent set, and the feature matching degree of the second seat set is greater than the feature matching degree of the first seat set.
  • step 04 it is determined whether the agents have a binding relationship with the client corresponding to the marketing activity task, if yes, step 05 is performed, and if not, step 06 is performed.
  • the agent having the binding relationship with the customer (marketing audience) corresponding to the marketing task belongs to the seat set obtained by the last traversal, proceeding to step S05; if there is a binding relationship, and corresponding to the marketing task
  • the client (marketing audience) has a binding relationship, and the agent belongs to the agent set obtained according to the demographic traversal agent, but does not belong to the agent set obtained in the last traversal; before proceeding to step S05, the method further includes feedback to the marketing audience. Give the marketing audience an opportunity to accept the agent's choice, and if not, proceed to step S06.
  • the specific method for determining the binding relationship is: obtaining the marketing activity information from the database of the marketing activity task, using SQL to obtain the historical binding relationship column in the database, and querying the binding relationship between a marketing audience and a specific agent in the database.
  • SQL a program that specifies the binding relationship between a marketing audience and a specific agent in the database.
  • the records need to be arranged according to the time sequence of the timed record of the query binding relationship, and the most The agent corresponding to the binding time record in which the timestamp is located serves as the agent in the binding relationship with the client, and records the next step.
  • step 05 the marketing activity task of the customer with the binding relationship is assigned to the corresponding agent.
  • the system automatically selects a customer category for the agent according to the degree of feature matching, and preferentially assigns the remaining binding client to the agent with a high degree of feature matching under the same idleness condition.
  • the system records the agent whose rated task amount is full, and marks it as occupying the seat set. Before feeding back to the traversing step of step S03, the occupied seat set is deleted in all the seat sets, and then traversed.
  • step 06 the marketing activity task of the unbounded customer is evenly distributed to all available agents.
  • the date is the planned completion period of the task, and the system selects the idle time period of the agent from the start date to the end date range. Select the time period to mark as the occupation time.
  • the system acquires and evenly distributes the tasks of MYC push.
  • the distribution rules are as follows:
  • task A has 300 total tasks completed in 6 days, involving 3 seats.
  • seat 1 should be divided into 100
  • seat 2 should be divided into 80
  • seat 3 should be divided into 120.
  • assign the tasks of different agents 1 point for 100 seats, 2 points for 90 seats, and 3 points for 110 seats.
  • step 07 the amount of tasks per agent per day is established according to the number of tasks assigned to each agent and the task time.
  • the task scheduled to be completed for a certain date of the agent whose deadline is earlier than the planned completion date of the daily task amount the task is advanced to some time before the scheduled date The workday is completed. If the task amount of the workday scheduled for this task has exceeded the daily task amount, the workload of the work day is still increased to meet the system requirement, but the event of adding a certain day workload to the agent is fed back to step S06 via the system. The allocation rule in step S06 is adjusted.
  • the agent task assigning device 30 of the present embodiment is based on the first embodiment, and is used to implement the agent task management method of the second embodiment, which includes the functions of each program module:
  • the request obtaining module 11 is configured to obtain a marketing activity task allocation request
  • the analyzing module 12 is configured to analyze the marketing activity information, and extract the number of tasks and the task time in the marketing activity information;
  • An executable agent obtaining module 13 is configured to obtain agent information of all agents who can perform a marketing campaign task
  • the determining module 14 is configured to determine whether the obtained executable agent has a binding relationship with a client corresponding to the marketing activity task;
  • the execution module 15 is configured to allocate a marketing activity task of the customer with the binding relationship to the corresponding agent, and distribute the marketing activity task of the unbounded customer to all available agents equally;
  • the task quantity management module 16 is configured to establish the amount of tasks per agent per day according to the number of tasks assigned to each agent and the task time.
  • the executable agent acquisition module further includes an agent screening module 19, wherein the agent screening module determines the number of traversal times according to the number of demographics and the number of categories of the domain of the agent-professional domain, and the agent-accustomed domain matches the audience classification at least once.
  • the feedback module 20 is further included, and the agent having the binding relationship and having the binding relationship with the client corresponding to the marketing task belongs to the agent set obtained according to the demographic traversal agent, but is not the seat set obtained by the last traversal.
  • the feedback module gives the marketing audience an opportunity to select whether to accept the agent set; when there is a binding relationship and the client having the binding relationship corresponding to the marketing task does not belong to the traversed agent set, the feedback module feedback Bind the agent to the event.

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Abstract

本申请提供一种坐席任务分配方法、装置、计算机设备及存储介质，系统根据各种营销活动推荐来获取不同类型的客户，借此来实现精准营销。智能分配坐席的任务量，并智能拣选绑定客户分配给绑定的坐席。根据分类器给客户做受众特征分类、根据分类器给坐席领域分类，并把与受众特征与坐席匹配之后，在进行分配，这样分配任务的精准度高，结合绑定任务调整，更人性化；反馈模块根据需求动态调整，使分配任务更科学。

Description

坐席任务分配方法、装置、计算机设备及存储介质
本申请申明享有2018年4月18日递交的申请号为CN 2018103495324、名称为“坐席任务分配方法、装置、计算机设备及存储介质”的中国专利申请的优先权，该中国专利申请的整体内容以参考的方式结合在本申请中。
技术领域
本申请涉及任务管理技术领域，尤其涉及一种呼叫中心坐席的坐席任务分配方法、装置、计算机设备及存储介质。
背景技术
呼叫中心系统作为企业和用户终端保持紧密联系的无形服务窗口，在产品宣传、产品销售、技术支持、售后服务、咨询和投诉等方面起着越来越重要的作用，在企业的经营活动中扮演着越来越重要的角色。
坐席服务是呼叫中心系统为客户提供服务的一种重要方式，坐席服务是指坐席人员通过呼叫中心的支撑系统为客户提供相应的服务的过程。
坐席系统会根据各种营销活动推荐来获取不同类型的客户，借此来实现精准营销。但是下发的任务过分人工参与，将任务绑定客户，然后人工将客户绑定坐席。应尽可能采用智能化的分配模式，根据坐席实际客户量、任务量，和坐席实际日均的处理量来分配客户。
发明内容
本申请的目的是提供一种坐席任务分配方法，用于解决现有技术存在的问题。
为实现上述目的，本申请提供一种坐席任务分配方法，适用于针对保险 等领域营销活动中分配给坐席任务的方法，包括以下步骤：
步骤01，获取营销活动任务分配请求；
步骤02，分析所述营销活动信息，提取营销活动信息中的任务数量及任务时间；
步骤03，获取可执行营销活动任务的所有坐席的坐席信息；
步骤04，判断这些坐席是否与营销活动任务对应的客户有绑定关系，若有则执行步骤05，若无则执行步骤06；
步骤05，将具有绑定关系的客户的营销活动任务分配给对应坐席；
步骤06，将无绑定关系的客户的营销活动任务平均分配给所有可用坐席；
步骤07，根据每个坐席分配到的任务数量及任务时间，建立每个坐席每天的任务量。
为实现上述目的，本申请还提供一种任务分配装置，其包括：
请求获取模块，用于获取营销活动任务分配请求；
分析模块，用于分析营销活动信息，提取营销活动信息中的任务数量及任务时间；
可执行坐席获取模块，用于获取可执行营销活动任务的所有坐席的坐席信息；
判断模块，用于判断获取的可执行坐席是否与营销活动任务对应的客户有绑定关系；
执行模块，用于将具有绑定关系的客户的营销活动任务分配给对应坐席，将无绑定关系的客户的营销活动任务平均分配给所有可用坐席；
任务量管理模块，用于根据每个坐席分配到的任务数量及任务时间建立每个坐席每天的任务量。
为实现上述目的，本申请还提供一种计算机设备，包括存储器、处理器以及存储在存储器上并可在处理器上运行的计算机程序，所述处理器执行所述计算机程序时实现坐席任务分配方法的以下步骤：
步骤01，获取营销活动任务分配请求；
步骤02，分析所述营销活动信息，提取营销活动信息中的任务数量及任务时间；
步骤03，获取可执行营销活动任务的所有坐席的坐席信息；
步骤04，判断这些坐席是否与营销活动任务对应的客户有绑定关系，若有则执行步骤05，若无则执行步骤06；
步骤05，将具有绑定关系的客户的营销活动任务分配给对应坐席；
步骤06，将无绑定关系的客户的营销活动任务平均分配给所有可用坐席；
步骤07，根据每个坐席分配到的任务数量及任务时间，建立每个坐席每天的任务量。
为实现上述目的，本申请还提供计算机可读存储介质，其上存储有计算机程序，所述计算机程序被处理器执行时实现坐席任务分配方法的以下步骤：
步骤01，获取营销活动任务分配请求；
步骤02，分析所述营销活动信息，提取营销活动信息中的任务数量及任务时间；
步骤03，获取可执行营销活动任务的所有坐席的坐席信息；
步骤04，判断这些坐席是否与营销活动任务对应的客户有绑定关系，若有则执行步骤05，若无则执行步骤06；
步骤05，将具有绑定关系的客户的营销活动任务分配给对应坐席；
步骤06，将无绑定关系的客户的营销活动任务平均分配给所有可用坐席；
步骤07，根据每个坐席分配到的任务数量及任务时间，建立每个坐席每天的任务量。
本申请提供的任务分配装置、装置、计算机设备及存储介质，为坐席提供一种基于智能管理、分配、调整坐席工作量的任务管理方法。系统根据各种营销活动推荐来获取不同类型的客户，借此来实现精准营销。智能分配坐席的任务量，并智能拣选绑定客户分配给绑定的坐席。根据分类器给客户做 受众特征分类、根据分类器给坐席领域分类，并把与受众特征与坐席匹配之后，在进行分配，这样分配任务的精准度高，结合绑定任务调整，更人性化。反馈模块根据需求动态调整，使分配任务更科学。
附图说明
图1为本申请坐席任务管理方法实施例一的流程图；
图2为本申请坐席任务管理装置实施例一的程序模块示意图；
图3为本申请坐席任务管理装置实施例一的硬件结构示意图；
图4为本申请坐席任务管理方法实施例二的流程图；
图5为本申请坐席任务管理装置实施例二的程序模块示意图。
具体实施方式
为了使本申请的目的、技术方案及优点更加清楚明白，以下结合附图及实施例，对本申请进行进一步详细说明。应当理解，此处所描述的具体实施例仅用以解释本申请，并不用于限定本申请。基于本申请中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本申请保护的范围。
本申请提供的坐席任务分配方法、装置、计算机设备及存储介质，适用于保险业务领域，为坐席提供一种基于智能管理、分配、调整坐席工作量的任务管理方法。系统根据各种营销活动推荐来获取不同类型的客户，借此来实现精准营销。智能分配坐席的任务量，并智能拣选绑定客户分配给绑定的坐席。根据分类器给客户做受众特征分类、根据分类器给坐席领域分类，并把与受众特征与坐席匹配之后，在进行分配，这样分配任务的精准度高，结合绑定任务调整，更人性化。反馈模块根据需求动态调整，使分配任务更科学。
实施例一
请参阅图1，本实施例的一种坐席任务分配方法，适用于针对保险等领域营销活动中分配给坐席任务的方法。
包括以下步骤：
步骤01，获取营销活动任务分配请求。
其中，营销活动任务包括断点任务、IB(呼入)咨询任务、服务类任务、综金销售类任务、保险销售类任务和售后类任务等等。营销任务分配包括但不限于营销任务类别按照优先级顺序来排列处理顺序、经过统计的营销任务中某一类别任务的总数量、任务分配请求中对某一类别任务堆栈集中的任务数量限制、任务分配请求中处理某一类别任务的频率限制。
步骤02，分析所述营销活动信息，提取营销活动信息中的任务数量及任务时间。
其中，分析所述营销活动信息包括但不限于分析营销受众、提取受众特征、制定营销方案，并按照营销方案规划获取任务数量和任务时间。分析营销受众时，根据受众的获取信息给营销受众分类，分类可按照受众的履历分类，即按照受众的年龄、性别、职业、职位、家庭情况、学历、地区进行分类，也可以按照受众的浏览信息关键词分类。
步骤03，获取可执行营销活动任务的所有坐席的坐席信息。
其中，获取坐席信息时，遍历所有坐席的坐席信息，找出与该受众特征一致的坐席，保留该坐席；与受众特征不一致的，删除该坐席。将遍历得到的坐席集，标记为第一坐席集。优选地，根据受众特征数量和坐席擅长领域分类类别数量确定遍历次数，坐席擅长领域与受众分类匹配进行两次或三次。优选地，当其他条件系统允许时，以最后一次遍历获得的坐席集作为可执行营销活动任务的所有坐席。
步骤04，判断这些坐席是否与营销活动任务对应的客户有绑定关系，若有则执行步骤05，若无则执行步骤06。
其中，若有绑定关系，但是与营销任务对应的客户(营销受众)具有绑定关系的坐席不属于遍历得到的坐席集时，还包括反馈绑定坐席该事件，由该绑定坐席选择继续绑定或解除绑定。若继续绑定，则进入步骤S05，若解除绑定，则进入步骤S06。
其中，判断绑定关系的具体方法是：获取营销活动信息出自营销活动任务的数据库，使用SQL获取数据库中的历史绑定关系栏，查询数据库中某一营销受众与特定坐席的绑定关系。在现实操作中，使用SQL查询数据库中的绑定关系时，若有多于一条绑定关系记录，则需要根据查询到的绑定关系记录的时间戳的时间顺序排列这些记录，并以最靠后的时间戳所在的绑定关系记录对应的坐席作为与该客户绑定关系的坐席，记录下来进入下一步骤。
步骤05，将具有绑定关系的客户的营销活动任务分配给对应坐席。
其中，当某一坐席的绑定关系的客户数量多于该坐席的额定任务量时，将该坐席所有绑定关系的客户分类，并给予坐席选择客户类别的机会，没有选择的客户，由系统统一重新回到步骤S03。
步骤06，将无绑定关系的客户的营销活动任务平均分配给所有可用坐席。
其中，平均分配的具体步骤为：
S061：设置任务分配频率：按天分配。设置任务待办事项待办时间：早上9：15。设置任务优先级：中。
S062：根据MYC推送的任务中包含的起始日期和结束日期，这段日期为此任务的计划完成周期，系统选择起始日期到结束日期范围内该坐席的空闲时间段，选择完成之后将该选择时间段标记为占用时间。
例如，系统获取并平均分配MYC推送的任务，分配规则如下：
如任务A有300条总任务6天完成，涉及坐席有3人，依据坐席客户绑定关系，坐席1应分100条，坐席2应分80条，坐席3应分120条。先将不 同坐席的任务整理分配好：坐席1分100条，坐席2分90条，坐席3分110条。
步骤07，根据每个坐席分配到的任务数量及任务时间，建立每个坐席每天的任务量。
其中，根据每个坐席分配到的任务数量及任务时间，建立每个坐席每天的任务量。如第一坐席的每日任务＝第一坐席的总任务/任务计划完成周期(100/6)。第一坐席的日均任务量100/6＝16.6667不是整数，则取整数17，每天分配17条任务，最后一天分配15条。第二坐席的日均任务量90/6＝15，每天分配15条任务。其中，建立每个坐席的总任务量时，将总任务量制成总任务清单，根据所在任务的截止时间顺序给总任务清单排序，在分配坐席日均任务时，按照上述计算出的坐席日均任务量，优先截止日期安排截止日期靠前的任务。
通过本实施例的坐席任务管理方法，可以在不影响任务进度的条件下，最科学、合理的均匀分配任务给每个坐席，提高坐席任务管理的科学性、便捷性和人性化。
请继续参阅图2，示出了一种坐席任务分配装置10，在本实施例中，坐席任务分配装置10可以包括或被分割成一个或多个程序模块，一个或者多个程序模块被存储于存储介质中，并由一个或多个处理器所执行，以完成本申请，并可实现上述坐席任务管理方法。本申请所称的程序模块是指能够完成特定功能的一系列计算机程序指令段，比程序本身更适合于描述坐席任务分配装置10在存储介质中的执行过程。以下描述将具体介绍本实施例各程序模块的功能：
请求获取模块11，用于获取营销活动任务分配请求；
分析模块12，用于分析营销活动信息，提取营销活动信息中的任务数量及任务时间；
可执行坐席获取模块13，用于获取可执行营销活动任务的所有坐席的坐席信息；
判断模块14，用于判断获取的可执行坐席是否与营销活动任务对应的客户有绑定关系；
执行模块15，用于将具有绑定关系的客户的营销活动任务分配给对应坐席，将无绑定关系的客户的营销活动任务平均分配给所有可用坐席；
任务量管理模块16，用于根据每个坐席分配到的任务数量及任务时间建立每个坐席每天的任务量。
优选地，还包括请求匹配模块17，所述请求匹配模块用于与系统自身处理能力相匹配，若营销活动任务分配请求的处理需求大于系统自身处理能力时，拒绝该营销活动任务分配请求并接收下一条营销活动任务分配请求，再进行匹配，直至接收到营销活动分配请求的处理需求与系统处理能力匹配为止。
优选地，所述分析模块包括受众分析模块、特征提取模块、方案生成模块。
优选地，所述受众分析模块包括按照受众的年龄、性别、职业、职位、家庭情况、学历、地区中一种或几种类别分类的分类器以及按照受众的浏览信息关键词分类的分类器。
优选地，还包括任务调整模块18，所述任务调整模块根据特征匹配程度自动给坐席选择客户类别，并将剩余绑定客户优先分配给空闲程度相同条件下特征匹配程度高的坐席，若额定任务量已满则标记为占用坐席集，反馈至可执行坐席获取模块，在所有坐席集中删除占用坐席集，再进行遍历。
本实施例还提供一种计算机设备，如可以执行程序的智能手机、平板电脑、笔记本电脑、台式计算机、机架式服务器、刀片式服务器、塔式服务器或机柜式服务器(包括独立的服务器，或者多个服务器所组成的服务器集群)等。本实施例的计算机设备20至少包括但不限于：可通过系统总线相互通信 连接的存储器21、处理器22，如图3所示。需要指出的是，图3仅示出了具有组件21-22的计算机设备20，但是应理解的是，并不要求实施所有示出的组件，可以替代的实施更多或者更少的组件。
本实施例中，存储器21(即可读存储介质)包括闪存、硬盘、多媒体卡、卡型存储器(例如，SD或DX存储器等)、随机访问存储器(RAM)、静态随机访问存储器(SRAM)、只读存储器(ROM)、电可擦除可编程只读存储器(EEPROM)、可编程只读存储器(PROM)、磁性存储器、磁盘、光盘等。在一些实施例中，存储器21可以是计算机设备20的内部存储单元，例如该计算机设备20的硬盘或内存。在另一些实施例中，存储器21也可以是计算机设备20的外部存储设备，例如该计算机设备20上配备的插接式硬盘，智能存储卡(Smart Media Card,SMC)，安全数字(Secure Digital,SD)卡，闪存卡(Flash Card)等。当然，存储器21还可以既包括计算机设备20的内部存储单元也包括其外部存储设备。本实施例中，存储器21通常用于存储安装于计算机设备20的操作系统和各类应用软件，例如实施例一的坐席任务管理装置10的程序代码等。此外，存储器21还可以用于暂时地存储已经输出或者将要输出的各类数据。
处理器22在一些实施例中可以是中央处理器(Central Processing Unit，CPU)、控制器、微控制器、微处理器、或其他数据处理芯片。该处理器22通常用于控制计算机设备20的总体操作。本实施例中，处理器22用于运行存储器21中存储的程序代码或者处理数据，例如运行坐席任务管理装置10，以实现实施例一的坐席任务管理方法。
本实施例还提供一种计算机可读存储介质，如闪存、硬盘、多媒体卡、卡型存储器(例如，SD或DX存储器等)、随机访问存储器(RAM)、静态随机访问存储器(SRAM)、只读存储器(ROM)、电可擦除可编程只读存储器(EEPROM)、可编程只读存储器(PROM)、磁性存储器、磁盘、光盘、服务 器、App应用商城等等，其上存储有计算机程序，程序被处理器执行时实现相应功能。本实施例的计算机可读存储介质用于存储坐席任务管理装置10，被处理器执行时实现实施例一的坐席任务分配方法。
实施例二
请参阅图4，本实施例的坐席任务管理方法以实施例一为基础，包括以下步骤：
步骤01，获取营销活动任务分配请求。
其中，营销活动任务包括断点任务、IB(呼入)咨询任务、服务类任务、综金销售类任务、保险销售类任务和售后类任务等等。系统获取到营销活动任务分配请求之后，与系统自身处理能力相匹配，若营销活动任务分配请求的处理需求大于系统自身处理能力时，系统拒绝该营销活动任务分配请求，并接收下一条营销活动任务分配请求，再进行匹配，直至接收到营销活动分配请求的处理需求与系统处理能力匹配为止，进入下一步骤。
步骤02，分析所述营销活动信息，提取营销活动信息中的任务数量及任务时间。
其中，分析所述营销活动信息包括但不限于分析营销受众、提取受众特征、制定营销方案，并按照营销方案规划获取任务数量和任务时间。优选地，受众分类方式还可以同时对受众履历分类且对受众的浏览信息关键词分类。分别提取营销受众履历分类和/或浏览信息关键词分类中的受众特征。根据这些受众特征制定营销方案。
步骤03，获取可执行营销活动任务的所有坐席的坐席信息。
其中，获取坐席信息时，遍历所有坐席的坐席信息，找出与该受众特征一致的坐席的坐席信息，保留该坐席；与受众特征不一致的，删除该坐席。将遍历得到的坐席集，标记为第一坐席集。优选地，根据受众特征数量和坐席擅长领域分类类别数量确定遍历次数，坐席擅长领域与受众分类匹配进行 两次或三次。例如，第一次遍历受众特征为：IT人士，获得第一坐席集。第二次遍历受众特征为：40岁，在第一坐席集中进行第二次遍历，获得第二坐席集。第三匹配特征：已生育，在第二坐席集中进行第三次遍历，获得第三坐席集。第三坐席集的特征匹配度大于第二坐席集的特征匹配度，第二坐席集的特征匹配度大于第一坐席集的特征匹配度。
步骤04，判断这些坐席是否与营销活动任务对应的客户有绑定关系，若有则执行步骤05，若无则执行步骤06。
其中，若有绑定关系，且与营销任务对应的客户(营销受众)具有绑定关系的坐席属于最后一次遍历获得的坐席集，则进入步骤S05；若有绑定关系，且与营销任务对应的客户(营销受众)具有绑定关系的坐席属于根据受众特征遍历坐席擅长领域获得的坐席集，但是不属于最后一次遍历获得的坐席集；则在进入步骤S05前，还包括反馈该营销受众并给予该营销受众是否接受该坐席的选择机会，若拒绝则进入步骤S06。
其中，判断绑定关系的具体方法是：获取营销活动信息出自营销活动任务的数据库，使用SQL获取数据库中的历史绑定关系栏，查询数据库中某一营销受众与特定坐席的绑定关系。在现实操作中，使用SQL查询数据库中的绑定关系时，若有多于一条绑定关系记录，则需要根据查询到的绑定关系记录的时间戳的时间顺序排列这些记录，并以最靠后的时间戳所在的绑定关系记录对应的坐席作为与该客户绑定关系的坐席，记录下来进入下一步骤。
步骤05，将具有绑定关系的客户的营销活动任务分配给对应坐席。
其中，优选地，系统根据特征匹配程度自动给坐席选择客户类别，并将剩余绑定客户优先分配给空闲程度相同条件下特征匹配程度高的坐席。系统记录额定任务量已满的坐席，标记为占用坐席集，反馈至步骤S03的遍历步骤之前，在所有坐席集中删除占用坐席集，再进行遍历。
步骤06，将无绑定关系的客户的营销活动任务平均分配给所有可用坐席。
其中，平均分配的具体步骤为：
S061：设置任务分配频率：按天分配。设置任务待办事项待办时间：早上9：15。设置任务优先级：中。
S062：根据MYC推送的任务中包含的起始日期和结束日期，这段日期为此任务的计划完成周期，系统选择起始日期到结束日期范围内该坐席的空闲时间段，选择完成之后将该选择时间段标记为占用时间。
例如，系统获取并平均分配MYC推送的任务，分配规则如下：
如任务A有300条总任务6天完成，涉及坐席有3人，依据坐席客户绑定关系，坐席1应分100条，坐席2应分80条，坐席3应分120条。先将不同坐席的任务整理分配好：坐席1分100条，坐席2分90条，坐席3分110条。
步骤07，根据每个坐席分配到的任务数量及任务时间，建立每个坐席每天的任务量。
其中，优选地，当总任务清单中，安排给某坐席的某一日期完成的任务，其截止日期早于该每日任务量的计划完成日期，则将该任务提早至安排日期之前的某一工作日完成。若此任务后续安排的工作日的任务量已经超过日均任务量，则仍然增加该工作日的工作量以满足系统需求，但是给该坐席增加某日工作量的事件经过系统反馈至步骤S06。调整步骤S06中的分配规则。
请继续参阅图5，本实施例的坐席任务分配装置30以实施例一为基础，用以实现实施例二的坐席任务管理方法，其包括的各程序模块的功能：
请求获取模块11，用于获取营销活动任务分配请求；
分析模块12，用于分析营销活动信息，提取营销活动信息中的任务数量及任务时间；
可执行坐席获取模块13，用于获取可执行营销活动任务的所有坐席的坐席信息；
判断模块14，用于判断获取的可执行坐席是否与营销活动任务对应的客 户有绑定关系；
执行模块15，用于将具有绑定关系的客户的营销活动任务分配给对应坐席，将无绑定关系的客户的营销活动任务平均分配给所有可用坐席；
任务量管理模块16，用于根据每个坐席分配到的任务数量及任务时间建立每个坐席每天的任务量。
优选地，所述可执行坐席获取模块还包括坐席筛选模块19，所述坐席筛选模块根据受众特征数量和坐席擅长领域分类类别数量确定遍历次数，坐席擅长领域与受众分类匹配进行至少一次。
优选地，还包括反馈模块20，当有绑定关系且与营销任务对应的客户具有绑定关系的坐席属于根据受众特征遍历坐席擅长领域获得的坐席集，但是不属于最后一次遍历获得的坐席集时，所述反馈模块给予营销受众选择是否接受该坐席集的机会；当有绑定关系且与营销任务对应的客户具有绑定关系的坐席不属于遍历得到的坐席集时，所述反馈模块反馈绑定坐席该事件。
上述本申请实施例序号仅仅为了描述，不代表实施例的优劣。
通过以上的实施方式的描述，本领域的技术人员可以清楚地了解到上述实施例方法可借助软件加必需的通用硬件平台的方式来实现，当然也可以通过硬件，但很多情况下前者是更佳的实施方式。
以上仅为本申请的优选实施例，并非因此限制本申请的专利范围，凡是利用本申请说明书及附图内容所作的等效结构或等效流程变换，或直接或间接运用在其他相关的技术领域，均同理包括在本申请的专利保护范围内。

Claims (20)

  1. 一种坐席任务分配方法，其特征在于，包括以下步骤：
    步骤01，获取营销活动任务分配请求；
    步骤02，分析所述营销活动信息，提取营销活动信息中的任务数量及任务时间；
    步骤03，获取可执行营销活动任务的所有坐席的坐席信息；
    步骤04，判断这些坐席是否与营销活动任务对应的客户有绑定关系，若有则执行步骤05，若无则执行步骤06；
    步骤05，将具有绑定关系的客户的营销活动任务分配给对应坐席；
    步骤06，将无绑定关系的客户的营销活动任务平均分配给所有可用坐席；
    步骤07，根据每个坐席分配到的任务数量及任务时间，建立每个坐席每天的任务量。
  2. 根据权利要求1所述的坐席任务分配方法，其特征在于：步骤S01中，系统获取到营销活动任务分配请求之后，与系统自身处理能力相匹配，若营销活动任务分配请求的处理需求大于系统自身处理能力时，系统拒绝该营销活动任务分配请求，并接收下一条营销活动任务分配请求，再进行匹配，直至接收到营销活动分配请求的处理需求与系统处理能力匹配为止，进入下一步骤。
  3. 根据权利要求1所述的坐席任务分配方法，其特征在于：步骤S02中，分析所述营销活动信息包括但不限于分析营销受众、提取受众特征、制定营销方案，并按照营销方案规划获取任务数量和任务时间。
  4. 根据权利要求3所述的坐席任务分配方法，其特征在于：步骤S02中，分析营销受众时，根据受众的获取信息给营销受众分类，分类可按照受众的履历分类或按照受众的浏览信息关键词分类。
  5. 根据权利要求1所述的坐席任务分配方法，其特征在于：步骤S03中， 获取坐席的坐席信息时，还包括以下步骤：遍历所有坐席的坐席信息，找出与该受众特征一致的坐席，保留该坐席；根据受众特征数量和坐席擅长领域分类类别数量确定遍历次数，坐席擅长领域与受众分类匹配进行两次或三次；当其他条件系统允许时，以最后一次遍历获得的坐席集作为可执行营销活动任务的所有坐席。
  6. 根据权利要求5所述的坐席任务分配方法，其特征在于：步骤S05中，当某一坐席的绑定关系的客户数量多于该坐席的额定任务量时，将该坐席所有绑定关系的客户分类，并给予坐席选择客户类别的机会，没有选择的客户，由系统统一重新回到步骤S03。
  7. 根据权利要求5所述的坐席任务分配方法，其特征在于：步骤S05中，系统根据特征匹配程度自动给坐席选择客户类别，并将剩余绑定客户优先分配给空闲程度相同条件下特征匹配程度高的坐席，系统记录额定任务量已满的坐席，标记为占用坐席集，反馈至步骤S03的遍历步骤之前，在所有坐席集中删除占用坐席集，再进行遍历。
  8. 一种坐席任务分配装置，其特征在于，其包括：
    请求获取模块，用于获取营销活动任务分配请求；
    分析模块，用于分析营销活动信息，提取营销活动信息中的任务数量及任务时间；
    可执行坐席获取模块，用于获取可执行营销活动任务的所有坐席的坐席信息；
    判断模块，用于判断获取的可执行坐席是否与营销活动任务对应的客户有绑定关系；
    执行模块，用于将具有绑定关系的客户的营销活动任务分配给对应坐席，将无绑定关系的客户的营销活动任务平均分配给所有可用坐席；
    任务量管理模块，用于根据每个坐席分配到的任务数量及任务时间建立每个坐席每天的任务量。
  9. 根据权利要求8所述的坐席任务分配装置，其特征在于：还包括请求匹配模块，所述请求匹配模块用于与系统自身处理能力相匹配。
  10. 根据权利要求8所述的坐席任务分配装置，其特征在于：所述分析模块包括受众分析模块、特征提取模块、方案生成模块，所述受众分析模块包括按照受众的年龄、性别、职业、职位、家庭情况、学历、地区中一种或几种类别分类的分类器以及按照受众的浏览信息关键词分类的分类器。
  11. 根据权利要求8所述的坐席任务分配装置，其特征在于：所述可执行坐席获取模块还包括坐席筛选模块，所述坐席筛选模块根据受众特征数量和坐席擅长领域分类类别数量确定遍历次数，坐席擅长领域与受众分类匹配进行至少一次。
  12. 根据权利要求11所述的坐席任务分配装置，其特征在于：还包括反馈模块，当有绑定关系且与营销任务对应的客户具有绑定关系的坐席属于根据受众特征遍历坐席擅长领域获得的坐席集，但是不属于最后一次遍历获得的坐席集时，所述反馈模块给予营销受众选择是否接受该坐席集的机会。
  13. 根据权利要求11所述的坐席任务分配装置，其特征在于：还包括任务调整模块，所述任务调整模块根据特征匹配程度自动给坐席选择客户类别，并将剩余绑定客户优先分配给空闲程度相同条件下特征匹配程度高的坐席。
  14. 一种计算机设备，包括存储器、处理器以及存储在存储器上并可在处理器上运行的计算机程序，所述处理器执行所述计算机程序时实现坐席任务分配方法的以下步骤：
    步骤01，获取营销活动任务分配请求；
    步骤02，分析所述营销活动信息，提取营销活动信息中的任务数量及任务时间；
    步骤03，获取可执行营销活动任务的所有坐席的坐席信息；
    步骤04，判断这些坐席是否与营销活动任务对应的客户有绑定关系，若有则执行步骤05，若无则执行步骤06；
    步骤05，将具有绑定关系的客户的营销活动任务分配给对应坐席；
    步骤06，将无绑定关系的客户的营销活动任务平均分配给所有可用坐席；
    步骤07，根据每个坐席分配到的任务数量及任务时间，建立每个坐席每天的任务量。
  15. 根据权利要求14所述的计算机设备，其特征在于：步骤S01中，系统获取到营销活动任务分配请求之后，与系统自身处理能力相匹配，若营销活动任务分配请求的处理需求大于系统自身处理能力时，系统拒绝该营销活动任务分配请求，并接收下一条营销活动任务分配请求，再进行匹配，直至接收到营销活动分配请求的处理需求与系统处理能力匹配为止，进入下一步骤；步骤S02中，分析所述营销活动信息包括但不限于分析营销受众、提取受众特征、制定营销方案，并按照营销方案规划获取任务数量和任务时间，分析营销受众时，根据受众的获取信息给营销受众分类，分类可按照受众的履历分类或按照受众的浏览信息关键词分类。
  16. 根据权利要求14所述的计算机设备，其特征在于：步骤S03中，获取坐席的坐席信息时，还包括以下步骤：遍历所有坐席的坐席信息，找出与该受众特征一致的坐席，保留该坐席；根据受众特征数量和坐席擅长领域分类类别数量确定遍历次数，坐席擅长领域与受众分类匹配进行两次或三次；当其他条件系统允许时，以最后一次遍历获得的坐席集作为可执行营销活动任务的所有坐席；步骤S05中，当某一坐席的绑定关系的客户数量多于该坐席的额定任务量时，将该坐席所有绑定关系的客户分类，并给予坐席选择客户类别的机会，没有选择的客户，由系统统一重新回到步骤S03，或步骤S05中，系统根据特征匹配程度自动给坐席选择客户类别，并将剩余绑定客户优先分配给空闲程度相同条件下特征匹配程度高的坐席，系统记录额定任务量已满的坐席，标记为占用坐席集，反馈至步骤S03的遍历步骤之前，在所有 坐席集中删除占用坐席集，再进行遍历。
  17. 一种计算机可读存储介质，其上存储有计算机程序，其特征在于：所述计算机程序被处理器执行时实现坐席任务分配方法的以下步骤：
    步骤01，获取营销活动任务分配请求；
    步骤02，分析所述营销活动信息，提取营销活动信息中的任务数量及任务时间；
    步骤03，获取可执行营销活动任务的所有坐席的坐席信息；
    步骤04，判断这些坐席是否与营销活动任务对应的客户有绑定关系，若有则执行步骤05，若无则执行步骤06；
    步骤05，将具有绑定关系的客户的营销活动任务分配给对应坐席；
    步骤06，将无绑定关系的客户的营销活动任务平均分配给所有可用坐席；
    步骤07，根据每个坐席分配到的任务数量及任务时间，建立每个坐席每天的任务量。
  18. 根据权利要求17所述的计算机可读存储介质，其特征在于：步骤S01中，系统获取到营销活动任务分配请求之后，与系统自身处理能力相匹配，若营销活动任务分配请求的处理需求大于系统自身处理能力时，系统拒绝该营销活动任务分配请求，并接收下一条营销活动任务分配请求，再进行匹配，直至接收到营销活动分配请求的处理需求与系统处理能力匹配为止，进入下一步骤；步骤S02中，分析所述营销活动信息包括但不限于分析营销受众、提取受众特征、制定营销方案，并按照营销方案规划获取任务数量和任务时间，分析营销受众时，根据受众的获取信息给营销受众分类，分类可按照受众的履历分类或按照受众的浏览信息关键词分类。
  19. 根据权利要求17所述的计算机可读存储介质，其特征在于：步骤S03中，获取坐席的坐席信息时，还包括以下步骤：遍历所有坐席的坐席信息，找出与该受众特征一致的坐席，保留该坐席；根据受众特征数量和坐席擅长领域分类类别数量确定遍历次数，坐席擅长领域与受众分类匹配进行两次或 三次；当其他条件系统允许时，以最后一次遍历获得的坐席集作为可执行营销活动任务的所有坐席；步骤S05中，当某一坐席的绑定关系的客户数量多于该坐席的额定任务量时，将该坐席所有绑定关系的客户分类，并给予坐席选择客户类别的机会，没有选择的客户，由系统统一重新回到步骤S03。
  20. 根据权利要求17所述的计算机可读存储介质，其特征在于：步骤S03中，获取坐席的坐席信息时，还包括以下步骤：遍历所有坐席的坐席信息，找出与该受众特征一致的坐席，保留该坐席；根据受众特征数量和坐席擅长领域分类类别数量确定遍历次数，坐席擅长领域与受众分类匹配进行两次或三次；当其他条件系统允许时，以最后一次遍历获得的坐席集作为可执行营销活动任务的所有坐席；步骤S05中，系统根据特征匹配程度自动给坐席选择客户类别，并将剩余绑定客户优先分配给空闲程度相同条件下特征匹配程度高的坐席，系统记录额定任务量已满的坐席，标记为占用坐席集，反馈至步骤S03的遍历步骤之前，在所有坐席集中删除占用坐席集，再进行遍历。
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