CN112396326A

CN112396326A - Method, device and storage medium for distributing agent for obtaining new client by internet

Info

Publication number: CN112396326A
Application number: CN202011308253.7A
Authority: CN
Inventors: 石海洋; 陈依云
Original assignee: Ping An Life Insurance Company of China Ltd
Current assignee: Ping An Life Insurance Company of China Ltd
Priority date: 2020-11-20
Filing date: 2020-11-20
Publication date: 2021-02-23
Anticipated expiration: 2040-11-20
Also published as: CN112396326B

Abstract

The application relates to an agent distribution method for acquiring new customers by the Internet, which is applied to electronic equipment and comprises the following steps: the electronic equipment acquires the characteristic information of the agent and determines the range of the service agent according to the characteristic information; and acquiring the address resolution precision of the client identifier, matching the agents in the region corresponding to the precision from the service agent range, and distributing the client identifier to the agents in the corresponding region. The technical scheme provided by the application can automatically distribute the Internet clients, quickly responds to the distribution of the clients, and has the advantage of reducing the distribution cost of the clients.

Description

Method, device and storage medium for distributing agent for obtaining new client by internet

Technical Field

The application relates to the technical field of internet, in particular to a method, a device and a storage medium for distributing agents for acquiring new clients by the internet.

Background

With the change of the operation environment, the client intention clue is obtained by cooperating with an external Internet platform, which becomes an important channel for obtaining new clients in the life insurance operation, and how to distribute offline agents (insurance agents or insurance businessmen) is a core link of the life insurance operation.

An H5 page of safe life insurance is embedded in an external Internet platform, and client consulting information is obtained after the intent client is filled in, and comprises basic information such as client mobile phone numbers, intent products, contact names, contact sexes, consulting time, IP addresses, delivery channels and the like. And manually informing the client of the intention according to the client information to remind the agent to contact the client.

The existing allocation method of the new client depends on manual allocation, the new client cannot be allocated in time by manual participation, and the manual allocation cost is high.

Disclosure of Invention

The embodiment of the application provides a method, a device and a storage medium for allocating agents for acquiring new clients by the Internet, which can automatically allocate the clients to the Internet, quickly respond to the allocation of the clients and reduce the allocation cost of the clients.

In a first aspect, a method for assigning an agent for obtaining a new client from the internet is provided, and the method is applied to an electronic device and includes:

the electronic equipment acquires the characteristic information of the agent and determines the range of the service agent according to the characteristic information;

acquiring the address resolution precision of the client identification, matching the agents in the area corresponding to the precision from the range of the service agents, and distributing the client identification to the agents in the corresponding area;

the level of the corresponding regional agent is higher than the level of the characteristic information, and the level of the characteristic information is determined by a product result obtained by calculating input data of the characteristic information and a preset weight vector.

In a second aspect, an electronic device is provided, the electronic device comprising:

the acquisition unit is used for acquiring the characteristic information of the agent and determining the range of the service agent according to the characteristic information;

the processing unit is used for acquiring the address resolution precision of the client identifier; matching the agents in the region corresponding to the precision from the service agent range, and distributing the client identification to the agents in the corresponding region;

In a third aspect, an embodiment of the present application provides an electronic device, including a processor, a memory, a communication interface, and one or more programs, where the one or more programs are stored in the memory and configured to be executed by the processor, and the program includes instructions for executing the steps in the first aspect of the embodiment of the present application.

In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, where the computer-readable storage medium stores a computer program for electronic data exchange, where the computer program enables a computer to perform some or all of the steps described in the first aspect of the embodiment of the present application.

In a fifth aspect, embodiments of the present application provide a computer program product, where the computer program product includes a non-transitory computer-readable storage medium storing a computer program, where the computer program is operable to cause a computer to perform some or all of the steps as described in the first aspect of the embodiments of the present application. The computer program product may be a software installation package.

The embodiment of the application has the following beneficial effects:

it can be seen that the technical scheme of the application is automatically distributed by the electronic equipment, so that the client resource retention thread circulation speed is increased, the time interval of the agent touching the client is effectively reduced, and the thread conversion rate is increased. The original agent allocation is implemented by a business department manager, and the allocation accuracy depends on the personal experience of the business department manager and the familiarity degree of the agent; the new scheme collects and integrates the operation experience of the business department manager, and the operation experience is packaged into a unified algorithm, so that the distribution stability is ensured; through a closed loop of agent passenger-touching operation feedback, according to the intention and passenger-touching behavior of an agent, dynamically serving an agent list to eliminate agents with insufficient service intentions; by tracking and analyzing the thread management effect, relevant parameters are continuously optimized and adjusted, and the distribution accuracy of the agent is improved.

Drawings

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.

Fig. 1 is a schematic structural diagram of an electronic device according to an embodiment of the present disclosure;

fig. 2 is a schematic flowchart of an agent allocation method for acquiring a new client by the internet according to an embodiment of the present disclosure;

fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present application.

Detailed Description

In order to make the technical solutions of the present application better understood, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.

The terms "first," "second," and the like in the description and claims of the present application and in the above-described drawings are used for distinguishing between different objects and not for describing a particular order. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus.

Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.

The technical scheme provided by the embodiment of the application is executed based on a hardware structure of the electronic device, and the electronic device can be a portable electronic device which also comprises other functions such as functions of a personal digital assistant and/or a music player, such as a mobile phone, a tablet computer, a wearable electronic device (such as a smart watch) with a wireless communication function, and the like. Of course, stationary electronic devices such as traffic cameras, surveillance cameras, and the like may also be included. Exemplary embodiments of portable electronic devices as well as stationary electronic devices include, but are not limited to, portable electronic devices or stationary electronic devices that carry an IOS system, an Android system, a Microsoft system, or other operating systems (e.g., embedded operating systems). The portable electronic device may also be other portable electronic devices such as a Laptop computer (Laptop) or the like. It should also be understood that in other embodiments, the electronic device may not be a portable electronic device, but may be a desktop computer or a stationary camera.

An electronic device is a device deployed in an indoor environment or an outdoor environment to transceive signals. For example, the signal Transceiver device may be an evolved Node B (eNB), a Radio Network Controller (RNC), a Node B (NB), a Base Station Controller (BSC), a Base Transceiver Station (BTS), a Home Base Station (e.g., Home evolved Node B or Home Node B, HNB), an Access Controller (AC), a WIFI Access Point (AP), or the like.

The software and hardware operating environment of the technical scheme disclosed by the application is introduced as follows.

Fig. 1 shows a schematic structural diagram of an electronic device 100. This electronic equipment specifically can be intelligent camera, and above-mentioned electronic equipment of course still can be wearable equipment, specifically can be, wearable portable equipment such as intelligent wrist-watch, intelligent bracelet. The electronic device 100 may include a processor 110, an external memory interface 120, an internal memory 121, a Universal Serial Bus (USB) interface 130, a charge management module 140, a power management module 141, a battery 142, an antenna 1, an antenna 2, a mobile communication module 150, a wireless communication module 160, an audio module 170, a speaker 170A, a receiver 170B, a microphone 170C, an earphone interface 170D, a sensor module 180, a compass 190, a motor 191, a pointer 192, a camera 193, a display screen 194, a Subscriber Identification Module (SIM) card interface 195, and the like.

Processor 110 may include one or more processing units, such as: the processor 110 may include an Application Processor (AP), a modem processor, a Graphics Processing Unit (GPU), an Image Signal Processor (ISP), a controller, a video codec, a Digital Signal Processor (DSP), a baseband processor, and/or a neural-Network Processing Unit (NPU), etc. Wherein the different processing units may be separate components or may be integrated in one or more processors. In some embodiments, the electronic device 100 may also include one or more processors 110. The controller can generate an operation control signal according to the instruction operation code and the time sequence signal to complete the control of instruction fetching and instruction execution. In other embodiments, a memory may also be provided in processor 110 for storing instructions and data. Illustratively, the memory in the processor 110 may be a cache memory. The memory may hold instructions or data that have just been used or recycled by the processor 110. If the processor 110 needs to reuse the instruction or data, it can be called directly from the memory. This avoids repeated accesses and reduces the latency of the processor 110, thereby increasing the efficiency with which the electronic device 100 processes data or executes instructions.

In some embodiments, processor 110 may include one or more interfaces. The interface may include an inter-integrated circuit (I2C) interface, an inter-integrated circuit audio (I2S) interface, a Pulse Code Modulation (PCM) interface, a universal asynchronous receiver/transmitter (UART) interface, a Mobile Industry Processor Interface (MIPI), a general-purpose input/output (GPIO) interface, a SIM card interface, a USB interface, and/or the like. The USB interface 130 is an interface conforming to the USB standard specification, and may specifically be a Mini USB interface, a Micro USB interface, a USB Type C interface, or the like. The USB interface 130 may be used to connect a charger to charge the electronic device 101, and may also be used to transmit data between the electronic device 101 and peripheral devices. The USB interface 130 may also be used to connect to a headset to play audio through the headset.

It should be understood that the interface connection relationship between the modules illustrated in the embodiments of the present application is only an illustration, and does not limit the structure of the electronic device 100. In other embodiments of the present application, the electronic device 100 may also adopt different interface connection manners or a combination of multiple interface connection manners in the above embodiments.

The application provides an agent distribution method for obtaining a new client by the internet, which can be executed by an electronic device shown in fig. 1, and specifically includes the following steps, as shown in fig. 2:

step S201, acquiring characteristic information of an agent, and determining a service agent range according to the characteristic information;

the characteristic information includes but is not limited to: the service period (service period or practical period), the quality deduction in the last half year, customer complaints, achievement of diamond manpower standard, and participation rate before entry, etc., and the agents are screened out and combined with the service start will of the agents.

The feature information may also be adjusted according to different service ranges, and the present application does not limit the specific representation form of the feature information, for example, in an alternative, the feature information may be a registration address of an agent, and for example, in another alternative, the feature information may be a graduation school, a specialty, and the like of the agent.

Step S202, obtaining the address resolution precision of the client ID (identification), adapting the agent of the corresponding area from the service agent range, and distributing the client identification to the agent of the corresponding area.

For example, the feature information is formed into an input vector, the input vector and a predetermined weight vector are subjected to vector multiplication to obtain a multiplication result, and the feature information level is determined according to the range of the multiplication result.

The accuracy of the address resolution may be province, city, district (county), street, road, etc. The information of the business department to which the agent belongs can be standardized and also can be divided according to the precision of the address analysis, and the agent in the corresponding area is adapted according to the precision of the address analysis of the client ID.

The technical scheme of this application has promoted the customer and has kept the speed of resource thread circulation by electronic equipment automatic allocation, effectively reduces agent person and touches the passenger time interval, promotes the thread conversion rate. The original agent allocation is implemented by a business department manager, and the allocation accuracy depends on the personal experience of the business department manager and the familiarity degree of the agent; the new scheme collects and integrates the operation experience of the business department manager, and the operation experience is packaged into a unified algorithm, so that the distribution stability is ensured; through a closed loop of agent passenger-touching operation feedback, according to the intention and passenger-touching behavior of an agent, dynamically serving an agent list to eliminate agents with insufficient service intentions; by tracking and analyzing the thread management effect, relevant parameters are continuously optimized and adjusted, and the distribution accuracy of the agent is improved.

The above-mentioned precision of address resolution for obtaining the client ID (identification) may specifically include:

the method comprises the steps of obtaining a plurality of historical addresses corresponding to a client ID, counting y addresses with the number of the same address information being larger than a number threshold value in the plurality of historical addresses, determining the minimum area range from the y addresses as the resolution precision of the addresses, wherein y is an integer larger than or equal to 1.

For example, when the number threshold is 20 times, the precision of the address resolution is determined as the yuanhui (50 times), the nan shan (40 times), and the yuehai street (35 times), and this way can dynamically adjust the precision of the address resolution of the client ID to better match the active region of the client ID, and is better a proxy of the client ID matching region.

The specific implementation method can be that if the address resolution precision of the client ID is that the Shenzhen city south mountain area Yuehai street, the agent of the Yuehai street is adapted from the service agent range.

The matching may be performed by LBS (Location Based Services), but in practical applications, the matching may be performed in other manners.

Optionally, the determining the range of the service broker according to the feature information may specifically include:

and forming the characteristic information into an input vector, performing vector multiplication operation on the input vector and a preset weight vector to obtain a multiplication result, determining the grade of the characteristic information according to a range corresponding to the multiplication result, and determining an agent with the grade higher than the grade of the characteristic information as a service agent range.

The method for forming the input vector may specifically include:

if the feature information includes: and when the department age (namely the service age or the practice age), the quality deduction in the last half year, the customer complaint, the achievement of the diamond manpower standard and the pre-entry participation rate, sequentially forming the values of the department age (namely the service age or the practice age), the quality deduction in the last half year, the customer complaint, the achievement of the diamond manpower standard and the pre-entry participation rate into an input vector.

Optionally, the level of the feature information may be adjusted by:

the service data of the agent is obtained, the service ability score is calculated according to the service data, and the grade of the characteristic information of the agent is adjusted according to the service ability score.

The above-mentioned manner of adjusting the characteristic information of the agent according to the service data may specifically include: calculating service data score, if the service data score is higher than a set threshold, adjusting the grade of the feature information up (for example, up one grade or two grades), if the service data score is lower than the set threshold, adjusting the grade of the feature information down (for example, blind one grade or two grades)

Agent service ability score, as shown in Table 1, is calculated monthly agent service ability score according to Table 1

Table 1:

wherein X is an actual index value, Y is an index reference value, Z is an index reference score, i is an index label, and alpha is a service capability score.

In an optional aspect, the method may further include:

and adjusting the grade of the characteristic information according to the service capability score and the service satisfaction score. The manner in which it adjusts the level of characteristic information may be adjusted up or down.

The service satisfaction degree scoring can be implemented by inviting the client to evaluate the agent after the contact client finishes the service, and comprises the dimensions of description conformity, response speed, service attitude, professional degree, advantage/deficiency and the like, and is calculated based on the client evaluation.

Wherein, B is the initial satisfaction score; p_iThe star mapping scores of various indexes are evaluated for single customer service, i is a label, N is the number of times of customer evaluation agent service in the latest set time (for example, 1 month or 3 months), and beta can be the service satisfaction score.

In an optional aspect, the method may further include:

and when the set conditions are met, the agent is quitted from the database.

The setting conditions may include: the agent automatically exits the candidate list without intention; the agent does not touch the guest in time for 3 times continuously, and the service is suspended for 3 months; the customer service evaluation was continued for 2 times under 60 points, and the service was suspended for 1 month.

In an optional aspect, the method may further include:

the method comprises the steps of obtaining a first identity of a first agent in a corresponding area, obtaining an agent feature vector of the first identity, obtaining a customer feature vector of a customer ID, carrying out vector subtraction on the two feature vectors to obtain a difference value, if the difference value is smaller than a difference threshold value, determining that the first agent is matched with the customer ID, if the difference value is larger than the difference threshold value, determining that the first agent is not matched with the customer ID, and shielding the customer ID for the first agent.

The first identity of the first agent may be obtained in various ways, such as obtaining a license of the first agent and extracting the first identity of the license. Of course, the method may also be implemented in other ways, and the present application is not limited to the specific implementation scheme for obtaining the first identity of the first agent.

The implementation method for obtaining the customer feature vector of the customer ID may specifically include:

acquiring a picture corresponding to a client ID, establishing input data according to the picture, inputting the input data into a face recognition model, executing n layers of convolution operation to obtain an nth layer of convolution operation result, inputting the nth layer of convolution operation result into a full connection layer, executing full connection operation to obtain a full connection calculation result, calculating a difference value between the full connection calculation result and a preset face template result, if the difference value is smaller than a difference value threshold value, determining the identity of the client ID as the identity of the preset face template by UE, and extracting a client feature vector corresponding to the identity.

In the technical scheme of the application, the electronic device is preconfigured with the mapping relationship between the identity and the customer feature vector, that is, after the identity is determined, the customer feature vector can be determined through the mapping relationship.

In an optional scheme, the inputting the input data into the face recognition model to perform n-th layer of convolution operation to obtain an nth layer of convolution operation result specifically may include:

the electronic device may be provided with a separate AI chip, the AI chip being configured to perform the verification of the identity of the target object, the AI chip including: the AI chip acquires a matrix size CI CH of input data, if the convolution kernel size in n layers of convolution operation is 3X 3 convolution kernels, the distribution calculation processing circuit divides the CI CH into CI/x data blocks (assuming that CI is an integer of x) according to the CI direction, distributes the CI/x data blocks to the x calculation processing circuits in sequence, the x calculation processing circuits respectively execute the ith layer of convolution operation on the 1 data block received and distributed and the ith layer of convolution kernel to obtain the ith convolution result (namely, the ith convolution result is obtained by sequentially combining x result matrixes (CI/x-2) (CH-2) of the x calculation processing circuits), and sends the result of 2 columns at the edge of the ith convolution result (the result of the adjacent columns is 2 columns obtained by calculation of different calculation processing circuits) to the distribution processing circuit, the x calculation processing circuits execute convolution operation on the ith layer of convolution result and the (i +1) th layer of convolution kernel to obtain an (i +1) th layer of convolution result, the (i +1) th layer of convolution result is sent to the distribution calculation circuit, the distribution calculation processing circuit executes the ith layer of convolution operation on the (CI/x-1) th combined data block and the ith layer of convolution kernel to obtain an ith combined result, the ith combined result and the edge 2 column result of the ith convolution result are spliced (the ith combined result is inserted into the middle of the edge 2 column according to the mathematical rule of the convolution operation) to obtain an (i +1) th combined data block, the (i +1) th combined data block and the (i +1) th convolution kernel execute convolution operation to obtain an (i +1) th combined result, the (i +1) th combined result is inserted into the (i +1) th layer of convolution result between the edge column (the results of the adjacent columns are calculated by different calculation processing circuits) to obtain an (i +1) th layer of convolution result, and the AI chip executes the operation of the residual convolution layer (convolution kernel after the layer i +1) according to the convolution result of the layer (i +1) to obtain the convolution operation result of the layer n. The combined data block may be a 4 × CI matrix composed of 4 columns of data between 2 adjacent data blocks, for example, a 4 × CH matrix composed of the last 2 columns of the 1 st data block (the data block allocated to the 1 st calculation processing circuit) and the first 2 columns of data of the 2 nd data block (the data block allocated to the 2 nd calculation processing circuit).

The calculation of the above-mentioned remaining convolutional layers can also be referred to the calculation of the i-th layer and the (i +1) -th layer, where i is an integer not less than 1 and not more than n, where n is the total number of convolutional layers of the AI model, i is the layer number of the convolutional layer, CI is the column value of the matrix, and CH is the row value of the matrix.

It will be appreciated that the electronic device, in order to implement the above-described functions, comprises corresponding hardware and/or software modules for performing the respective functions. The present application is capable of being implemented in hardware or a combination of hardware and computer software in conjunction with the exemplary algorithm steps described in connection with the embodiments disclosed herein. Whether a function is performed as hardware or computer software drives hardware depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, with the embodiment described in connection with the particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

In this embodiment, the electronic device may be divided into functional modules according to the above method example, for example, each functional module may be divided corresponding to each function, or two or more functions may be integrated into one processing module. The integrated module may be implemented in the form of hardware. It should be noted that the division of the modules in this embodiment is schematic, and is only a logic function division, and there may be another division manner in actual implementation.

In the case of dividing each functional module with corresponding functions, fig. 3 shows an electronic device, the apparatus including:

an obtaining unit 301, configured to obtain feature information of an agent, and determine a service agent range according to the feature information;

a processing unit 302, configured to obtain the accuracy of address resolution of the client identifier; and matching the agents in the region corresponding to the precision from the range of the service agents, and allocating the client identification to the agents in the corresponding region.

Wherein, the obtaining unit 301 may be configured to support the electronic device to perform the above step 201 and/or other processes for the techniques described herein, and the processing unit 302 is configured to support the electronic device to perform the above step 202 and/or other processes for the techniques described herein.

It should be noted that all relevant contents of each step related to the above method embodiment may be referred to the functional description of the corresponding functional module, and are not described herein again.

The electronic device provided by the embodiment is used for executing the position determining method, so that the same effect as the implementation method can be achieved.

In case an integrated unit is employed, the electronic device may comprise a processing module, a storage module and a communication module. The processing module may be configured to control and manage an action of the electronic device, for example, may be configured to support the electronic device to execute the steps executed by the acquiring unit 301 and the processing unit 302. The memory module may be used to support the electronic device in executing stored program codes and data, etc. The communication module can be used for supporting the communication between the electronic equipment and other equipment.

The processing module may be a processor or a controller. Which may implement or perform the various illustrative logical blocks, modules, and circuits described in connection with the disclosure. A processor may also be a combination of computing functions, e.g., a combination of one or more microprocessors, a Digital Signal Processing (DSP) and a microprocessor, or the like. The storage module may be a memory. The communication module may specifically be a radio frequency circuit, a bluetooth chip, a Wi-Fi chip, or other devices that interact with other electronic devices.

In an embodiment, when the processing module is a processor and the storage module is a memory, the electronic device according to this embodiment may be a device having the structure shown in fig. 1.

An embodiment of the present application further provides an electronic device, including a processor and a memory, where the memory is configured to store one or more programs and is configured to be executed by the processor, and the program includes instructions for performing the following steps, where the following steps may specifically include:

acquiring characteristic information of an agent, and determining a service agent range according to the characteristic information;

and acquiring the address resolution precision of the client identifier, matching the agents in the region corresponding to the precision from the service agent range, and distributing the client identifier to the agents in the corresponding region.

The instructions executed by the program can also include the refinement scheme of step S201 and step S202 shown in fig. 2, and of course, the instructions of the program can also include the alternatives shown in the embodiment shown in fig. 2. And will not be described in detail herein.

Embodiments of the present application also provide a computer storage medium, wherein the computer storage medium stores a computer program for electronic data exchange, and the computer program enables a computer to execute part or all of the steps of any one of the methods as described in the above method embodiments.

Embodiments of the present application also provide a computer program product comprising a non-transitory computer readable storage medium storing a computer program operable to cause a computer to perform some or all of the steps of any of the methods as described in the above method embodiments. The computer program product may be a software installation package.

It should be noted that, for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present application is not limited by the order of acts described, as some steps may occur in other orders or concurrently depending on the application. Further, those skilled in the art should also appreciate that the embodiments described in the specification are preferred embodiments and that the acts and modules referred to are not necessarily required in this application.

In the foregoing embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.

In the embodiments provided in the present application, it should be understood that the disclosed apparatus may be implemented in other manners. For example, the above-described embodiments of the apparatus are merely illustrative, and for example, the above-described division of the units is only one type of division of logical functions, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of some interfaces, devices or units, and may be an electric or other form.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.

The integrated unit may be stored in a computer readable memory if it is implemented in the form of a software functional unit and sold or used as a stand-alone product. Based on such understanding, the technical solution of the present application may be substantially implemented or a part of or all or part of the technical solution contributing to the prior art may be embodied in the form of a software product stored in a memory, and including several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the above-mentioned method of the embodiments of the present application. And the aforementioned memory comprises: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.

Those skilled in the art will appreciate that all or part of the steps in the methods of the above embodiments may be implemented by associated hardware instructed by a program, which may be stored in a computer-readable memory, which may include: flash Memory disks, Read-Only memories (ROMs), Random Access Memories (RAMs), magnetic or optical disks, and the like.

The foregoing detailed description of the embodiments of the present application has been presented to illustrate the principles and implementations of the present application, and the above description of the embodiments is only provided to help understand the method and the core concept of the present application; meanwhile, for a person skilled in the art, according to the idea of the present application, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present application.

Claims

1. An agent distribution method for acquiring new clients through the Internet is applied to electronic equipment, and the method comprises the following steps:

2. The method of claim 1, wherein obtaining the resolution accuracy of the address of the client identifier specifically comprises:

3. The method of claim 1, wherein said determining a service agent scope based on the characteristic information specifically comprises:

and forming the characteristic information into an input vector, performing vector multiplication operation on the input vector and a preset weight vector to obtain a multiplication result, determining the grade of the characteristic information according to a range corresponding to the multiplication result, and determining an agent with the grade higher than a preset grade as a service agent range.

4. The method of any of claim 3, further comprising: adjusting the grade of the feature information specifically includes:

and calculating a service data score according to the service data of the agent, if the service data score is higher than a set threshold value, adjusting the grade of the characteristic information upwards, and if the service data score is lower than the set threshold value, adjusting the grade of the characteristic information downwards.

5. The method of claim 3,

6. The method of claim 3, further comprising: adjusting the grade of the feature information specifically includes: :

adjusting the grade of the characteristic information according to the service ability score and the service satisfaction score;

wherein, B is the initial satisfaction score; p_iAnd evaluating each index star-level mapping score for single customer service, wherein i is a label, N is the number of times of service of a customer evaluation agent at the latest set time, and beta is the service satisfaction score.

7. The method of claim 1, further comprising:

if the service agent meets the set conditions, the service agent is deleted from the service agent scope.

8. An electronic device, characterized in that the electronic device comprises:

9. An electronic device comprising a processor, a memory for storing one or more programs and configured for execution by the processor, the programs comprising instructions for performing the steps of the method of any of claims 1-7.

10. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program comprising program instructions that, when executed by a processor, cause the processor to carry out the method according to any one of claims 1-7.