CN113689074B - Client distribution method, device, equipment and medium - Google Patents
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Abstract
The application discloses a client distribution method, a device, equipment and a medium, wherein the client distribution method comprises the following steps: the method comprises the steps of obtaining business behavior information, converting the business behavior information into weight coefficients according to preset business behavior rules, constructing a sharing relation link diagram corresponding to a client to be distributed, and distributing the client to be distributed in the sharing relation link diagram to a target salesman based on the sharing relation link diagram and the weight coefficients. The method and the device solve the technical problem of low efficiency of customer distribution.
Description
Technical Field
The present application relates to the field of computer technologies, and in particular, to a method, an apparatus, a device, and a medium for client allocation.
Background
With the development of computer technology, in order to increase the number of services applied by clients, many companies are provided with service staff, and the service staff can communicate with the clients to follow up the services.
Disclosure of Invention
The present application mainly aims to provide a method, an apparatus, a device and a medium for allocating customers, and aims to solve the technical problem of low efficiency of customer allocation in the prior art.
In order to achieve the above object, the present application provides a customer allocation method, including:
acquiring service behavior information;
converting the service behavior information into a weight coefficient according to a preset service behavior rule;
constructing a sharing relationship link diagram corresponding to a client to be distributed;
and allocating the clients to be allocated in the sharing relation link diagram to a target salesman based on the sharing relation link diagram and the weight coefficient.
Optionally, the step of constructing a sharing relationship link map corresponding to the client to be distributed includes:
acquiring sharing attribute information between a client and a salesman;
generating each sharing transmission link based on the role sharing level in the sharing attribute information;
and combining the sharing propagation links to form the sharing relationship link diagram.
Optionally, the step of allocating the to-be-allocated customer in the shared relationship link map to a target salesman based on the shared relationship link map and the weight coefficient includes:
traversing each node path in the sharing relationship link graph through a graph algorithm;
calculating a weight coefficient corresponding to each node path in the sharing relationship link diagram;
selecting a distribution path according with a preset selection rule according to the weight coefficient corresponding to each node path;
and distributing the clients to be distributed to the target salesman according to the distribution path.
Optionally, the step of selecting, according to the weight coefficient corresponding to each node path, a distribution path that meets a preset selection rule includes:
comparing the weight coefficients corresponding to the node paths;
and selecting the node path with the minimum weight coefficient as the distribution path.
Optionally, the step of allocating the customer to be allocated to the target salesman according to the allocation path includes:
judging whether the distribution path is a customer distribution path;
if yes, the customer to be distributed is distributed to a target salesman of the customer distribution path according to a preset distribution rule;
if not, determining that the distribution path is a project distribution path, and distributing the customer to be distributed to a target operator associated with a service project in the project distribution path.
Optionally, the step of allocating the customer to be allocated to the target salesman of the customer allocation path according to a preset allocation rule includes:
determining a recursion depth coefficient corresponding to the customer distribution path based on a preset service depth calculation rule;
selecting a target node corresponding to a preset recursion depth coefficient from the customer distribution path;
and distributing the to-be-distributed clients to target operators corresponding to the target nodes based on the target nodes.
The present application further provides a client distribution device, where the client distribution device is a virtual device, and the client distribution device includes:
the acquisition module is used for acquiring the service behavior information;
the weight coefficient conversion module is used for converting the business behavior information into a weight coefficient according to a preset business behavior rule;
the building module is used for building a sharing relationship link diagram corresponding to the client to be distributed;
and the distribution module is used for distributing the clients to be distributed in the sharing relation link diagram to the target salesman based on the sharing relation link diagram and the weight coefficient.
Optionally, the building module is further configured to:
acquiring sharing attribute information between a client and a salesman;
generating each sharing transmission link based on the role sharing level in the sharing attribute information;
and combining the sharing propagation links to form the sharing relationship link diagram.
Optionally, the allocation module is further configured to:
traversing each node path in the sharing relationship link graph through a graph algorithm;
calculating a weight coefficient corresponding to each node path in the sharing relationship link diagram;
selecting a distribution path according with a preset selection rule according to the weight coefficient corresponding to each node path;
and distributing the clients to be distributed to the target salesman according to the distribution path.
Optionally, the allocation module is further configured to:
comparing the weight coefficients corresponding to the node paths;
and selecting the node path with the minimum weight coefficient as the distribution path.
Optionally, the allocation module is further configured to:
judging whether the distribution path is a customer distribution path;
if yes, the customer to be distributed is distributed to a target salesman of the customer distribution path according to a preset distribution rule;
if not, determining that the distribution path is a project distribution path, and distributing the customer to be distributed to a target operator associated with a service project in the project distribution path.
Optionally, the allocation module is further configured to:
determining a recursion depth coefficient corresponding to the customer distribution path based on a preset service depth calculation rule;
selecting a target node corresponding to a preset recursion depth coefficient from the customer distribution path;
and distributing the to-be-distributed clients to target operators corresponding to the target nodes based on the target nodes.
The present application further provides a customer distribution device, where the customer distribution device is an entity device, and the customer distribution device includes: a memory, a processor and a customer distribution program stored on the memory, the customer distribution program being executed by the processor to implement the steps of the customer distribution method as described above.
The present application also provides a medium which is a readable storage medium on which a customer distribution program is stored, the customer distribution program being executed by a processor to implement the steps of the customer distribution method as described above.
The application provides a client allocation method, a device, equipment and a medium, compared with the technical means of manually allocating clients in the prior art, the method comprises the steps of firstly acquiring business behavior information, then converting the business behavior information into weight coefficients according to preset business behavior rules, further constructing a sharing relation link diagram corresponding to the clients to be allocated, further allocating the clients to be allocated in the sharing relation link diagram to target service staff based on the sharing relation link diagram and the weight coefficients, realizing the calculation of the weight coefficients according to different business behavior information, further automatically calculating finally allocatable service staff in the sharing relation link diagram, namely, the allocation of the clients is not required to be manually performed, and overcoming the defect that when the number of the clients is large in the prior art, the workload of the traditional manual allocation is large, the technical defects that the cost is long and the client distribution efficiency is low are caused, and the client distribution efficiency is improved.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and together with the description, serve to explain the principles of the application.
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly described below, and it is obvious to those skilled in the art that other drawings can be obtained according to the drawings without inventive exercise.
FIG. 1 is a schematic flow chart of a first embodiment of a customer allocation method according to the present application;
FIG. 2 is a schematic flow chart illustrating a second embodiment of a client allocation method according to the present application;
fig. 3 is a schematic structural diagram of a client allocation apparatus of a hardware operating environment related to a client allocation method in an embodiment of the present application.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
In a first embodiment of the customer allocation method of the present application, referring to fig. 1, the customer allocation method includes:
step S10, acquiring service behavior information;
in this embodiment, it should be noted that the service behavior information includes behavior information such as checking a building, checking a house type, and the like
The method includes the steps of obtaining business behavior information, specifically, according to the fact that corresponding behavior operations are carried out in an applet or a related application program by a client and a waiter, and when the behavior operations are carried out, obtaining the business behavior information corresponding to the behavior operations by a background.
Step S20, according to the preset business behavior rule, the business behavior information is converted into a weight coefficient;
in this embodiment, it should be noted that the preset service behavior rule is a rule that different service behavior information is set with different weight coefficients.
And converting the service behavior information into weight coefficients according to a preset service behavior rule, specifically, setting different service behavior information into different weight coefficients respectively, and performing graph algorithm calculation according to the weight coefficients.
Step S30, constructing a sharing relationship link diagram corresponding to the client to be distributed;
in this embodiment, it should be noted that the sharing relationship link map is a link map formed by sharing between the clients or the staff.
Establishing a sharing relationship link diagram corresponding to a client to be distributed, specifically, obtaining sharing attribute information between the client and a salesman, wherein the sharing attribute information includes information such as a client ID, a client mobile phone number, a salesman ID and a project resource ID, and further generating each sharing propagation link based on a role sharing level in the sharing attribute information, wherein the role sharing level includes information levels such as a starting user, a second-level sharing user, a third-level sharing user and a fourth-level sharing user, the starting user corresponds to a root node of the sharing propagation link, further, each sharing propagation link is combined to form the sharing relationship link diagram, for example, the salesman a shares floor information to the client B, the client C shares the house type information to the client B, and by obtaining the ID of the salesman a, the ID of the client B, the project resource ID corresponding to the floor information and the project resource ID corresponding to the house type information, and further forming a relation link diagram of the A service person corresponding to the B client and the C client corresponding to the B client.
The step of constructing a sharing relationship link diagram corresponding to the client to be distributed comprises the following steps:
step S31, acquiring shared attribute information between the client and the salesman;
in this embodiment, it should be noted that when the client and the staff share the shared information, the background acquires corresponding sharing attribute information, for example, information such as a sharer identity ID, a shared project resource ID, a shared client ID, a role sharing level, and the like, and additionally, the sharer identity ID, the shared project resource ID, and the shared client ID are unique identifiers, and a unique identifier can be generated by using a uuid striping utilities and a database.
The method comprises the steps of obtaining sharing attribute information between a client and a salesman, specifically obtaining corresponding information of the client and the salesman in a sharing process, so that a corresponding relationship link is created according to the shared information.
Step S32, based on the role sharing level in the sharing attribute information, generating each sharing propagation link;
in this embodiment, it should be noted that the role sharing levels include an originating user, a secondary sharing user, a tertiary sharing user, a quaternary sharing user, and the like, where the originating user corresponds to a root node of the sharing propagation link, and then a node corresponding to the sharing propagation link may be determined according to other role sharing levels.
The method comprises the steps of generating sharing propagation links based on role sharing levels in sharing attribute information, specifically, after the sharing attribute information between a client and a salesperson is obtained, corresponding to different weight coefficients according to different shared business behavior information between the client and the salesperson, and determining the sharing propagation links according to the role sharing levels in the sharing attribute information, for example, the salesperson shares floor information to a client A, the client A shares the floor information to a client B, the client B shares the floor information to a client C, namely the salesperson is an initial user, the client A is a secondary sharing user, the client B is a tertiary sharing user, and the client C is a quaternary sharing user, so that a sharing propagation link is formed.
Step S33, combining the sharing propagation links to form the sharing relationship link map.
In this embodiment, the sharing relationship link map is generated based on the sharing attribute information, and specifically, the sharing propagation links are combined to form the sharing relationship link map, so as to select a corresponding path according to the sharing relationship link map for client distribution.
And step S40, based on the sharing relationship link diagram and the weight coefficient, allocating the clients to be allocated in the sharing relationship link diagram to the target salesman.
In this embodiment, based on the sharing relationship link graph and the weight coefficient, the to-be-allocated client in the sharing relationship link graph is allocated to the target salesman, specifically, each node path in the sharing relationship link graph is traversed through a graph algorithm, wherein the graph algorithm comprises Dijkstra algorithm (Dixtra algorithm) and Floyd algorithm (Floyed algorithm), further, calculating a weight coefficient corresponding to each node path in the sharing relationship link graph, and further, selecting a distribution path according with a preset selection rule according to the weight coefficient corresponding to each node path, wherein the preset selection rule is a rule with the minimum selection weight coefficient, the finally allocatable salesman is calculated, and then the client to be distributed is distributed to the target salesman, so that the effect of automatic distribution of the client is achieved.
Compared with the technical means of manual customer allocation adopted in the prior art, the customer allocation method comprises the steps of firstly obtaining business behavior information, then converting the business behavior information into weight coefficients according to preset business behavior rules, further constructing a sharing relation link diagram corresponding to customers to be allocated, further allocating the customers to be allocated in the sharing relation link diagram to target salesmen based on the sharing relation link diagram and the weight coefficients, calculating the weight coefficients according to different business behavior information, further calculating finally allocable salesmen in the sharing relation link diagram, namely, manually allocating the customers, and overcoming the defects that when the number of customers is large in the prior art, the workload of traditional manual customer allocation is large, and the time cost is long, and further causes the technical defect of low efficiency of customer allocation, thereby improving the efficiency of customer allocation.
Further, referring to fig. 2, based on the first embodiment of the present application, in another embodiment of the present application, the step of allocating the to-be-allocated customer in the shared relationship link map to the target salesperson based on the shared relationship link map and the weight coefficient includes:
step A10, traversing each node path in the sharing relationship link graph through a graph algorithm;
in the embodiments, it should be noted that the graph algorithm includes Dijkstra algorithm (dixtre algorithm) and Floyd algorithm (freoude algorithm).
And traversing each node path in the sharing relationship link graph through a graph algorithm, specifically, traversing each node path in the sharing relationship link graph to obtain the weight corresponding to each node path.
Step A20, calculating a weight coefficient corresponding to each node path in the sharing relationship link diagram;
in this embodiment, it should be noted that, in the sharing relationship link graph, nodes all have corresponding weight coefficients.
Calculating a weight coefficient corresponding to each node path in the sharing relationship link graph, specifically, respectively counting the sum of the weight coefficients of each node path by traversing each node path in the sharing relationship link graph.
Step A30, selecting a distribution path according with a preset selection rule according to the weight coefficient corresponding to each node path;
in this embodiment, it should be noted that the preset selection rule is a rule for selecting a path with the smallest weight coefficient.
And selecting a distribution path according with a preset selection rule according to the weight coefficient corresponding to each node path, specifically, calculating the weight coefficient corresponding to each node path, and selecting the path with the minimum weight coefficient as the distribution path.
The step of selecting a distribution path according to a preset selection rule according to the weight coefficient corresponding to each node path comprises:
step A31, comparing the weight coefficients corresponding to the node paths;
step a32, selecting the node path with the smallest weight coefficient as the distribution path.
In this embodiment, the node path with the smallest weight coefficient is selected as the distribution path, specifically, the path with the smallest weight coefficient is selected as the distribution path in each node path by comparing the weight coefficients corresponding to the node paths, for example, the sharing relationship link map has two sharing propagation links, i.e., a-B-C and E-B-C, where the weight coefficient of a-B is 1, the weight coefficient of E-B is 2, the weight coefficient of B-C is 3, the weight coefficient of a-B-C is 4, the weight coefficient of E-B-C is 5, and further, the sharing propagation link is selected as a-B-C.
Step A40, according to the distribution path, distributing the customer to be distributed to the target salesman.
In this embodiment, the to-be-allocated customer is allocated to the target salesman according to the allocation path, specifically, if the allocation path is a customer allocation path, a target node corresponding to a preset recursion depth coefficient is selected from the customer allocation path, where the recursion depth coefficient is preset, and then the to-be-allocated customer is allocated to the target salesman corresponding to the target node based on the target node.
Wherein the step of allocating the customer to be allocated to the target salesman according to the allocation path comprises:
step A41, judging whether the distribution path is a customer distribution path;
in this embodiment, it should be noted that the customer distribution path is a path that distributes the customer to be distributed to a serviceman corresponding to the distribution path.
Step A42, if yes, the customer to be distributed is distributed to the target salesman of the customer distribution path according to a preset distribution rule;
in this embodiment, if yes, the to-be-allocated customer is allocated to the target salesman of the customer allocation path according to a preset allocation rule, specifically, if the allocation path is a customer allocation path, a target node corresponding to a preset recursion depth coefficient is selected from the customer allocation path, and then the to-be-allocated customer is allocated to the target salesman corresponding to the target node based on the target node.
Wherein, the step of allocating the customer to be allocated to the target salesman of the customer allocation path according to a preset allocation rule comprises:
step A421, determining a recursion depth coefficient corresponding to the customer distribution path based on a preset service depth calculation rule;
in this embodiment, it should be noted that the preset service depth calculation rule is a rule for performing deep recursion on the sharing relationship link map, and the recursion depth coefficient is a preset coefficient.
Step A422, selecting a target node corresponding to a preset recursion depth coefficient from the customer distribution path;
in this embodiment, a target node corresponding to a preset recursion depth coefficient is selected from the customer distribution path, specifically, depth recursion is performed on the customer distribution path, and then, based on the preset recursion depth coefficient, recursion is performed on the customer distribution path to a node corresponding to the preset recursion depth coefficient, and further, the target node is obtained. For example, the nodes that the customer distribution path sequentially passes through are a, B, C, D, and E, the E customer is distributed, and then recursion starts from the E node, the preset recursion depth coefficient is 3, and the B node is a target node of the recursion.
Step a423, based on the target node, allocating the customer to be allocated to a target salesman corresponding to the target node.
In this embodiment, based on the target node, the customer to be allocated is allocated to the target salesman corresponding to the target node, specifically, the customer to be allocated is allocated to the target salesman corresponding to the target node, for example, nodes of the customer allocation path in sequence are a, B, C, D, and E, the E customer is allocated, and then recursion starts from the E node, the preset recursion depth coefficient is 3, the B node is a recursive target node, and it is assumed that the B node is a B customer, and then the E customer is allocated to the salesman corresponding to the B customer.
Step A43, if not, determining that the distribution path is a project distribution path, and distributing the customer to be distributed to a target salesman associated with the business project in the project distribution path.
In this embodiment, it should be noted that the item allocation path is a path that allocates the to-be-allocated customer to a service item corresponding to the item allocation path.
If not, determining that the distribution path is a project distribution path, and distributing the to-be-distributed client to a target salesman associated with a service project in the project distribution path, specifically, if the distribution path is the project distribution path, distributing the to-be-distributed client to a service project corresponding to the project distribution path, and further determining the target salesman corresponding to the service project according to the service project, so as to distribute the to-be-distributed client to the target salesman.
The embodiment of the application provides a customer allocation method, namely, traversing each node path in the sharing relationship link graph through a graph algorithm, calculating a weight coefficient corresponding to each node path in the sharing relationship link graph, further selecting an allocation path according with a preset selection rule according to the weight coefficient corresponding to each node path, selecting a shortest path through the graph algorithm based on the weight coefficient, calculating a final assignable salesman, and allocating the customer to be allocated to the target salesman according to the allocation path.
Referring to fig. 3, fig. 3 is a schematic structural diagram of a client distribution device of a hardware operating environment according to an embodiment of the present application.
As shown in fig. 3, the customer distribution facility may include: a processor 1001, such as a CPU, a memory 1005, and a communication bus 1002. The communication bus 1002 is used for realizing connection communication between the processor 1001 and the memory 1005. The memory 1005 may be a high-speed RAM memory or a non-volatile memory (e.g., a magnetic disk memory). The memory 1005 may alternatively be a memory device separate from the processor 1001 described above.
Optionally, the customer distribution device may further comprise a rectangular user interface, a network interface, a camera, RF (Radio Frequency) circuitry, sensors, audio circuitry, a WiFi module, and the like. The rectangular user interface may comprise a Display screen (Display), an input sub-module such as a Keyboard (Keyboard), and the optional rectangular user interface may also comprise a standard wired interface, a wireless interface. The network interface may optionally include a standard wired interface, a wireless interface (e.g., WIFI interface).
Those skilled in the art will appreciate that the customer distribution facility configuration shown in fig. 3 does not constitute a limitation of the customer distribution facility and may include more or fewer components than shown, or some components may be combined, or a different arrangement of components.
As shown in fig. 3, a memory 1005, which is a kind of computer storage medium, may include an operating system, a network communication module, and a client distribution program therein. The operating system is a program that manages and controls the hardware and software resources of the customer distribution facility, supporting the execution of the customer distribution facility as well as other software and/or programs. The network communications module is used to enable communication between the various components within the memory 1005, as well as with other hardware and software in the customer distribution system.
In the customer distribution facility shown in fig. 3, the processor 1001 is configured to execute a customer distribution program stored in the memory 1005 to implement the steps of any of the customer distribution methods described above.
The specific implementation of the client allocation device of the present application is substantially the same as that of each embodiment of the client allocation method, and is not described herein again.
The present application further provides a customer distribution device, comprising:
the acquisition module is used for acquiring the service behavior information;
the weight coefficient conversion module is used for converting the business behavior information into a weight coefficient according to a preset business behavior rule;
the building module is used for building a sharing relationship link diagram corresponding to the client to be distributed;
and the distribution module is used for distributing the clients to be distributed in the sharing relation link diagram to the target salesman based on the sharing relation link diagram and the weight coefficient.
Optionally, the building module is further configured to:
acquiring sharing attribute information between a client and a salesman;
generating each sharing propagation link based on the weight coefficient and the role sharing level in the sharing attribute information;
and combining the sharing propagation links to form the sharing relationship link diagram.
Optionally, the allocation module is further configured to:
traversing each node path in the sharing relationship link graph through a graph algorithm;
calculating a weight coefficient corresponding to each node path in the sharing relationship link diagram;
selecting a distribution path according with a preset selection rule according to the weight coefficient corresponding to each node path;
and distributing the clients to be distributed to the target salesman according to the distribution path.
Optionally, the allocation module is further configured to:
comparing the weight coefficients corresponding to the node paths;
and selecting the node path with the minimum weight coefficient as the distribution path.
Optionally, the allocation module is further configured to:
judging whether the distribution path is a customer distribution path;
if yes, the customer to be distributed is distributed to a target salesman of the customer distribution path according to a preset distribution rule;
if not, determining that the distribution path is a project distribution path, and distributing the customer to be distributed to a target operator associated with a service project in the project distribution path.
Optionally, the allocation module is further configured to:
determining a recursion depth coefficient corresponding to the customer distribution path based on a preset service depth calculation rule;
selecting a target node corresponding to a preset recursion depth coefficient from the customer distribution path;
and distributing the to-be-distributed clients to target operators corresponding to the target nodes based on the target nodes.
The specific implementation of the client allocation apparatus of the present application is substantially the same as that of the above embodiments of the client allocation method, and is not described herein again.
The present application provides a medium, which is a readable storage medium, and the readable storage medium stores one or more programs, and the one or more programs can be further executed by one or more processors to implement the steps of the customer allocation method described in any one of the above.
The specific implementation of the readable storage medium of the present application is substantially the same as that of the foregoing embodiments of the client allocation method, and is not described herein again.
The above description is only a preferred embodiment of the present application, and not intended to limit the scope of the present application, and all modifications of equivalent structures and equivalent processes, which are made by the contents of the specification and the drawings, or which are directly or indirectly applied to other related technical fields, are included in the scope of the present application.
Claims (8)
1. A customer distribution method, characterized in that the customer distribution method comprises:
acquiring service behavior information;
converting the service behavior information into a weight coefficient according to a preset service behavior rule;
constructing a sharing relationship link diagram corresponding to a client to be distributed;
based on the sharing relation link diagram and the weight coefficient, allocating the clients to be allocated in the sharing relation link diagram to a target salesman;
the step of allocating the to-be-allocated client in the sharing relationship link map to a target salesman based on the sharing relationship link map and the weight coefficient includes:
traversing each node path in the sharing relationship link graph through a graph algorithm;
calculating a weight coefficient corresponding to each node path in the sharing relationship link diagram;
selecting a distribution path according with a preset selection rule according to the weight coefficient corresponding to each node path;
and distributing the clients to be distributed to the target salesman according to the distribution path.
2. The customer distribution method according to claim 1, wherein the step of constructing the sharing relationship link map corresponding to the customer to be distributed comprises:
acquiring sharing attribute information between a client and a salesman;
generating each sharing transmission link based on the role sharing level in the sharing attribute information;
and combining the sharing propagation links to form the sharing relationship link diagram.
3. The customer distribution method according to claim 1, wherein the step of selecting a distribution route according to a preset selection rule according to the weighting factor corresponding to each node route comprises:
comparing the weight coefficients corresponding to the node paths;
and selecting the node path with the minimum weight coefficient as the distribution path.
4. The customer distribution method according to claim 1, wherein the step of distributing the customer to be distributed to the target salesman according to the distribution path comprises:
judging whether the distribution path is a customer distribution path;
if yes, the customer to be distributed is distributed to a target salesman of the customer distribution path according to a preset distribution rule;
if not, determining that the distribution path is a project distribution path, and distributing the customer to be distributed to a target operator associated with a service project in the project distribution path.
5. The customer distribution method according to claim 4, wherein the step of distributing the customer to be distributed to the target servicer of the customer distribution path according to a preset distribution rule comprises:
determining a recursion depth coefficient corresponding to the customer distribution path based on a preset service depth calculation rule;
selecting a target node corresponding to a preset recursion depth coefficient from the customer distribution path;
and distributing the to-be-distributed clients to target operators corresponding to the target nodes based on the target nodes.
6. A customer distribution apparatus, the customer distribution apparatus comprising:
the acquisition module is used for acquiring the service behavior information;
the weight coefficient conversion module is used for converting the business behavior information into a weight coefficient according to a preset business behavior rule;
the building module is used for building a sharing relationship link diagram corresponding to the client to be distributed;
the distribution module is used for distributing the clients to be distributed in the sharing relation link diagram to a target salesman based on the sharing relation link diagram and the weight coefficient;
wherein the allocation module is further configured to:
traversing each node path in the sharing relationship link graph through a graph algorithm;
calculating a weight coefficient corresponding to each node path in the sharing relationship link diagram;
selecting a distribution path according with a preset selection rule according to the weight coefficient corresponding to each node path;
and distributing the clients to be distributed to the target salesman according to the distribution path.
7. A customer distribution facility, the customer distribution facility comprising: a memory, a processor, and a guest allocator stored on the memory,
the customer distribution program being executed by the processor for carrying out the steps of the customer distribution method according to any one of claims 1 to 5.
8. A medium, readable by a storage medium, having a customer distribution program stored thereon, the customer distribution program being executable by a processor to perform steps for implementing a customer distribution method as claimed in any one of claims 1 to 5.
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| CN202110830612.3A CN113689074B (en) | 2021-07-22 | 2021-07-22 | Client distribution method, device, equipment and medium |
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| CN202110830612.3A CN113689074B (en) | 2021-07-22 | 2021-07-22 | Client distribution method, device, equipment and medium |
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| CN108132998A (en) * | 2017-12-21 | 2018-06-08 | 浪潮软件集团有限公司 | Personnel relationship analysis method and system |
| CN110443494A (en) * | 2019-08-02 | 2019-11-12 | 泰康保险集团股份有限公司 | Data distributing method and device |
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| US8311874B2 (en) * | 2005-03-31 | 2012-11-13 | Oracle Financial Services Software Limited | Systems and methods for customer relationship evaluation and resource allocation |
| CN111476469B (en) * | 2020-03-30 | 2023-11-03 | 深圳思为科技有限公司 | Guest-rubbing method, terminal equipment and storage medium |
| CN112200437A (en) * | 2020-09-28 | 2021-01-08 | 绿瘦健康产业集团有限公司 | Customer distribution method and device |
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| CN105225027A (en) * | 2015-08-26 | 2016-01-06 | 上海银天下科技有限公司 | Customer allocation method and system |
| CN108132998A (en) * | 2017-12-21 | 2018-06-08 | 浪潮软件集团有限公司 | Personnel relationship analysis method and system |
| CN110443494A (en) * | 2019-08-02 | 2019-11-12 | 泰康保险集团股份有限公司 | Data distributing method and device |
| CN112528166A (en) * | 2020-12-16 | 2021-03-19 | 平安养老保险股份有限公司 | User relationship analysis method and device, computer equipment and storage medium |
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