CN112948416A - Method, device and equipment for publishing house property sales task - Google Patents
Method, device and equipment for publishing house property sales task Download PDFInfo
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Abstract
A method for issuing a house property sales task comprises the following steps: acquiring position information for releasing the house property sales task and the house property sales task to be released; searching the matching degree of the house sales task to be issued and the acquired position information according to the preset matching relation between the position information and the house sales task; and selecting position information for the house property sales task to be issued according to the matching degree. The release of the house property sales task is not limited by the experience of the publisher, so that the accuracy of the release of the house property sales task is improved, and the release efficiency of the house property sales task is improved.
Description
Technical Field
The application belongs to the field of real estate, and particularly relates to a method, a device and equipment for releasing a real estate sales task.
Background
After a real estate developer completes building a real estate, the built real estate needs to be sold to a house buyer. A real estate developer typically completes a corresponding real estate sales task by a sales team through its own project team by dispatching the real estate sales task to the project team.
In assigning a property sales task to a sales team, the distribution of the sales task is typically performed for each sales team based on industry experience. The method is limited by the experience of the distributor, is not beneficial to improving the precision of the release of the house property sales task and is not beneficial to improving the task completion efficiency.
Disclosure of Invention
In view of this, embodiments of the present application provide a method, an apparatus, and a device for issuing a house property sales task, so as to solve the problem in the prior art that issuing a house property sales task is limited by experience of an assignor, which is not beneficial to improving accuracy of issuing the house property sales task and is not beneficial to improving task completion efficiency.
A first aspect of an embodiment of the present application provides a method for issuing a property sales task, where the method for issuing a property sales task includes:
acquiring position information for releasing the house property sales task and the house property sales task to be released;
searching the matching degree of the house sales task to be issued and the acquired position information according to the preset matching relation between the position information and the house sales task;
and selecting position information for the house property sales task to be issued according to the matching degree.
With reference to the first aspect, in a first possible implementation manner of the first aspect, searching for a matching degree between the house sales task to be issued and the acquired location information according to a preset matching relationship between the location information and the house sales task includes:
acquiring first attribute information of the position information;
acquiring second attribute information corresponding to the house property sales task to be issued;
and determining the matching degree of the house sales task to be issued and the acquired position information according to the first attribute information and the second attribute information.
With reference to the first possible implementation manner of the first aspect, in a second possible implementation manner of the first aspect, determining a matching degree between the property sales task to be issued and the acquired location information according to the first attribute information and the second attribute information includes:
acquiring a pre-trained matching degree network model;
and inputting the first attribute information and the second attribute information into the matching degree network model to obtain the matching degree of the house sales task to be issued and the acquired position information.
With reference to the second possible implementation manner of the first aspect, in a third possible implementation manner of the first aspect, before the obtaining of the pre-trained match degree network model, the method further includes:
acquiring sales sample data, wherein the sales sample data comprises first attribute information corresponding to position information in a sales record, second attribute information corresponding to a house property sales task and sales achievement information in the sales record;
inputting the first attribute information and the second attribute information in the sales sample data into a matching degree network model, and calculating to obtain a first matching degree of the position information and the house property sales task;
and converting the performance information in the sample data into a second matching degree, and adjusting the matching degree network model according to the difference between the first matching degree and the second matching degree until the difference meets the preset precision requirement.
With reference to the third possible implementation manner of the first aspect, in a fourth possible implementation manner of the first aspect, the converting performance information in the sample data into a second matching degree includes:
acquiring the house source transaction proportion and the house source transaction speed included in the performance information in the sample data;
and determining a second matching degree corresponding to the performance information according to the house source transaction proportion and the house source transaction speed.
With reference to the fourth possible implementation manner of the first aspect, in a fifth possible implementation manner of the first aspect, the determining a second matching degree corresponding to the performance information according to the house source transaction proportion and the house source transaction speed includes:
acquiring a first weight coefficient corresponding to the house source transaction proportion, and acquiring a second weight coefficient corresponding to the house source transaction speed;
and calculating a second matching degree corresponding to the performance information according to the house source transaction proportion, the first weight coefficient, the house source transaction speed and the second weight coefficient.
With reference to the first possible implementation manner of the first aspect, the second possible implementation manner of the first aspect, the third possible implementation manner of the first aspect, the fourth possible implementation manner of the first aspect, or the fifth possible implementation manner of the first aspect, in a sixth possible implementation manner of the first aspect, the first attribute information includes one or more of population quantity information, income level information, improved housing demand information, rental proportion information, and intention customer registration quantity information, and the second attribute information includes one or more of house source price hierarchy information, house source area information, house source type information, and house source marketing stage information.
A second aspect of the embodiments of the present application provides a device for issuing a house property sales task, where the device for issuing a house property sales task includes:
the system comprises an information acquisition unit, a processing unit and a processing unit, wherein the information acquisition unit is used for acquiring position information for releasing a house property sales task and the house property sales task to be released;
the matching unit is used for searching the matching degree of the house sales task to be issued and the acquired position information according to the preset matching relation between the position information and the house sales task;
and the position selection unit is used for selecting position information for the house property sales task to be issued according to the matching degree.
A third aspect of the embodiments of the present application provides a property sales task issuing apparatus, including a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor implements the steps of the property sales task issuing method according to any one of the first aspect when executing the computer program.
A fourth aspect of the embodiments of the present application provides a computer-readable storage medium storing a computer program, which when executed by a processor, implements the steps of the method for issuing a house property sales task according to any one of the first aspects.
Compared with the prior art, the embodiment of the application has the advantages that: the matching degree corresponding to different position information can be determined according to the matching relation by setting the matching relation between the position information and the house property sales task, and the house property sales task is issued according to the searched matching degree, so that the issuing of the house property sales task is not limited by the experience of an issuer, the accuracy of issuing the house property sales task is improved, and the issuing efficiency of the house property sales task is improved.
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In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.
Fig. 1 is a schematic flow chart illustrating an implementation process of a method for issuing a property sales task according to an embodiment of the present application;
FIG. 2 is a schematic diagram of a device for issuing a house property selling task according to an embodiment of the present application;
fig. 3 is a schematic diagram of a publishing device for a property selling task provided by an embodiment of the present application.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system structures, techniques, etc. in order to provide a thorough understanding of the embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.
In order to explain the technical solution described in the present application, the following description will be given by way of specific examples.
Fig. 1 is a schematic diagram of a release flow of a house property sales task provided in an embodiment of the present application, which is detailed as follows:
in step S101, position information for release of a house property sales task and a house property sales task to be released are acquired;
the location information published by the real estate sales task can be divided according to the sales objects planned by the real estate developer. For example, a sales target corresponding to a certain property is a resident of a certain city, and location information of a plurality of different areas can be obtained according to the division manner of administrative areas. Without being limited to this, in some task allocation manners that may be more accurate, the location information for the property sales task release may be obtained according to a division manner of areas such as communities.
The location information may include purchasing characteristics of residents at the location, the location information corresponding to the first attribute information. The first attribute information may include one or more of population quantity information, income level information, improved housing demand information, rental housing proportion information, intention customer registration quantity information, and the like, of the location. The position information can be obtained by blackboard writing statistical data or sampling survey data.
The population number information may include information such as the number of families corresponding to the location, the total population number, and the population distribution ratio of each age group. For example, the population distribution ratio of each age group can be obtained according to the division of the age group, including the division modes of the age groups such as 18-23, 23-25, 25-30, 30-35, 35-40, and the like, and the number of residents included in different age groups can be obtained.
The income level information may include information of working units of residents, public accumulation money information, deposit information, payroll information, and the like. By means of the income level information, the purchasing power of the residents of the location can be influenced. In a possible implementation manner, the first attribute information may further acquire consumption habit information of a resident at the location.
The information of improving the housing demand degree can be determined according to the living area per capita of the user corresponding to the position. For example, the living area of the home purchased in the location may be obtained, and the living area of the home per capita may be obtained by combining the family population. Alternatively, the total living area may be calculated from the total population of the home living in the location and the total living area of the location.
The renting proportion information can determine the number of residents who do not own the house at the position. In a possible implementation manner, the tenant proportion information may further include data such as age segment information to which the tenant group belongs.
The information on the number of the intended customers to be registered may be the number of the intended customers registered through an online or offline channel before the house property sales task is released, or the number of the intended customers. In some implementations, the intent customers may also be divided according to intent levels, with different intent levels corresponding to different purchasing possibilities.
The house property sales tasks to be released can be divided according to the sales experience or record of the project team. For example, when a salesperson who includes a plurality of project teams issues a house sales task, the expertise of each project team can be acquired first, the house sales task to be issued is divided, and if the project team a is specialized in the sale of a small house type house source, the small house type house source can be allocated to the project team a; the project team B is specialized in the sale of the large house type house resources, and the large house type house resources can be distributed to the project team B. Or, in the distribution process, a large proportion of small house type house resources can be distributed to the project team A, and a large proportion of large house type house resources can be distributed to the project team B. The greater proportion is relative data obtained by comparison with other teams.
The second attribute information corresponding to the property sales task to be released may include one or more items of property price hierarchy information, property area information, property type information, or property marketing phase information.
The house source price level information can refer to the local house source price to determine the price level corresponding to the house source in the house selling task to be released. For example, if the price of the local house source is X, the ratio of the price of the house source of the house sales task to be released to X may be used to determine the price level corresponding to the house sales task to be released. For example, the value intervals corresponding to the price levels may be divided in advance, and the corresponding value intervals are searched according to the ratio, so that the corresponding price levels can be determined.
The house source area information may include total building area information, indoor area information, hall size information, balcony type information, balcony area information, and the like. The balcony type may include a hall-out balcony, a bedroom-out balcony, and the like.
The house source type may include an apartment type, a general commercial house type, an improved house type, a newly required house type, and the like. The same source may have two or more types of features due to different types of division criteria. For example, a house source may be of the improved housing type and also of the general commodity word type.
The house source selling stage can be a stage divided by planning the selling stage by a house and region manufacturer, and the attribute information can be determined according to the stage where the house selling task to be issued is currently located.
In step S102, according to the preset matching relationship between the position information and the house sales task, the matching degree between the house sales task to be issued and the acquired position information is searched;
the preset matching relationship between the position information and the house property sales tasks can determine the matching relationship between different position information and different house property sales tasks according to sales records in the history records.
Wherein the matching relationship can be described by a matching degree. When the matching degree in a certain sales record is determined, the performance information of the sales can be obtained, and the ratio of house-source transaction and the house-source transaction speed in the performance information of the sales are combined to determine. Alternatively, the performance information may also include factors such as the size of the discount rate of the house source trade.
In calculating the matching degree, a first weight coefficient may be set for the deal proportion, a second weight coefficient may be set for the deal speed, and different scores may be divided for different deal speeds. And obtaining a comprehensive score through the comprehensive deal proportion and the deal speed, and taking the comprehensive score as the matching degree corresponding to the performance information.
In an implementation manner, the matching relationship between the location information and the property sales task may be a matching degree corresponding to the first attribute information of the location information in the historical sales record and the second attribute information of the property sales task. Through statistics of historical record data, the matching degree of the same house property sales task and different position information or the matching degree of the same position information and different house property sales tasks can be obtained.
According to the matching degree of the position information and the house property sales task which are obtained in advance through statistics, when the house property sales task to be issued is received, the house property sales task to be issued can be analyzed, second attribute information corresponding to the house property sales task is obtained, and according to the second attribute information, a historical sales task corresponding to the house property sales task to be issued is searched. And according to the matching degree of the searched historical sales tasks and different position information.
In one implementation, the data in the history record can be used as sample data, and the sample data for training the matching degree network model is used according to the first attribute information corresponding to the position information in the history record, the second attribute information corresponding to the property sales task in the history record, and the matching degree corresponding to the performance information of the recorded first attribute information and the second attribute information. The first attribute information and the second attribute information in any one history record are input into the matching degree network model, the matching degree calculated by the matching degree network model is output, the calculated matching degree is compared with the matching degree in sample data, the matching degree difference is determined, the parameters of the matching degree network model are adjusted according to the matching degree difference, and the training of the matching degree network model is completed until the difference between the calculated matching degree and the matching degree in the sample data meets the preset requirement.
And inputting second attribute information corresponding to the house sales task to be issued and first attribute information corresponding to different position information into the matching degree network model according to the trained matching degree network model, and calculating to obtain the matching degree of the house sales task to be issued and the different position information.
In step S103, according to the matching degree, location information is selected for the house property sales task to be released.
According to the matching degree of the to-be-released house sales task and different position information obtained by calculation or obtained in the searched historical record, the position information with higher matching degree can be selected as the position information corresponding to the to-be-released house sales task.
In an implementation manner of the application, the method can also be used for distributing the house property sales task to be released to different project teams by combining with the attribute information of the project teams. For example, the matching degree between the house sales task to be released and the different project teams can be determined according to the matching degree between the different project teams and the house sales task in the history record, and the project team with the higher matching degree can be searched and used as the project team corresponding to the house sales task to be released. Or the attribute information corresponding to the project team in the historical record and the second attribute information corresponding to the house property sales task are input into the neural network model by constructing the neural network model, and the neural network model obtained by training can be used for calculating the matching degree of the project team and the house property sales task to be issued.
In one implementation mode, the matching degrees of different project teams, different position information and the house property sales task can be obtained according to the statistical data, the matching degrees of the house property sales task to be issued, the different project teams and the different position information are determined according to the statistical matching degrees, and the project team with the higher matching degree and the corresponding position information are selected so as to issue the house property sales task more accurately.
Or, a neural network model can be constructed, the attribute information of the project team, the first attribute information of the position information and the attribute information of the house property sales task in the history record are used as the input of the neural network model, the neural network model is trained according to the matching degree in the history record and the matching degree calculated by the neural network model, the trained neural network model is obtained, and the matching degree of the house property sales task to be issued and different project teams and position information is calculated. And selecting the project team with better matching degree and the position information to release the house property sales task.
It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.
Fig. 2 is a schematic structural diagram of an apparatus for issuing a property sales task according to an embodiment of the present application, and as shown in fig. 2, the apparatus for issuing a property sales task includes:
an information obtaining unit 201, configured to obtain location information for issuing a house property sales task and a house property sales task to be issued;
the matching unit 202 is used for searching the matching degree between the house sales task to be issued and the acquired position information according to the preset matching relationship between the position information and the house sales task;
and the position selecting unit 203 is used for selecting position information for the house property selling task to be issued according to the matching degree.
The apparatus for issuing a house sales task shown in fig. 2 corresponds to the method for issuing a house sales task shown in fig. 1.
Fig. 3 is a schematic diagram of a distribution device for a house property sales task according to an embodiment of the present application. As shown in fig. 3, the distribution apparatus 3 of the house property selling task of this embodiment includes: a processor 30, a memory 31 and a computer program 32 stored in said memory 31 and operable on said processor 30, such as a distribution program for a property sales task. The processor 30, when executing the computer program 32, implements the steps in the various real estate sales task publishing method embodiments described above. Alternatively, the processor 30 implements the functions of the modules/units in the above-described device embodiments when executing the computer program 32.
Illustratively, the computer program 32 may be partitioned into one or more modules/units that are stored in the memory 31 and executed by the processor 30 to accomplish the present application. The one or more modules/units may be a series of computer program instruction segments capable of performing specific functions for describing the execution process of the computer program 32 in the distribution apparatus 3 of the property sales task.
The release device 3 of the house property sales task can be a desktop computer, a notebook, a palm computer, a cloud server and other computing devices. The issuing device of the property sales task may include, but is not limited to, a processor 30, a memory 31. It will be understood by those skilled in the art that fig. 3 is only an example of the distribution device 3 of the property sales task and does not constitute a limitation to the distribution device 3 of the property sales task, and may include more or less components than those shown, or combine some components, or different components, for example, the distribution device of the property sales task may further include an input-output device, a network access device, a bus, etc.
The Processor 30 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The storage 31 may be an internal storage unit of the property sales task issuing device 3, such as a hard disk or a memory of the property sales task issuing device 3. The memory 31 may also be an external storage device of the property sales task issuing device 3, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, which are provided on the property sales task issuing device 3. Further, the memory 31 may also include both an internal storage unit and an external storage device of the distribution device 3 of the house sales task. The memory 31 is used for storing the computer program and other programs and data required by the distribution device of the house sales task. The memory 31 may also be used to temporarily store data that has been output or is to be output.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-mentioned functions. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working processes of the units and modules in the system may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus/terminal device and method may be implemented in other ways. For example, the above-described embodiments of the apparatus/terminal device are merely illustrative, and for example, the division of the modules or units is only one logical division, and there may be other divisions when actually implemented, 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 through some interfaces, devices or units, and may be in an electrical, mechanical 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 modules/units, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. Based on such understanding, all or part of the flow in the method of the embodiments described above can be realized by a computer program, which can be stored in a computer-readable storage medium and can realize the steps of the embodiments of the methods described above when the computer program is executed by a processor. . Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like. It should be noted that the computer readable medium may contain other components which may be suitably increased or decreased as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media which may not include electrical carrier signals and telecommunications signals in accordance with legislation and patent practice.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present application and are intended to be included within the scope of the present application.
Claims (10)
1. A method for releasing a house property sales task is characterized by comprising the following steps:
acquiring position information for releasing the house property sales task and the house property sales task to be released;
searching the matching degree of the house sales task to be issued and the acquired position information according to the preset matching relation between the position information and the house sales task;
and selecting position information for the house property sales task to be issued according to the matching degree.
2. The method for issuing a house property sales task according to claim 1, wherein the step of searching for the matching degree between the house property sales task to be issued and the acquired location information according to the matching relationship between the preset location information and the house property sales task comprises:
acquiring first attribute information of the position information;
acquiring second attribute information corresponding to the house property sales task to be issued;
and determining the matching degree of the house sales task to be issued and the acquired position information according to the first attribute information and the second attribute information.
3. The method for issuing a house property sales task according to claim 2, wherein determining the matching degree between the house property sales task to be issued and the acquired location information according to the first attribute information and the second attribute information comprises:
acquiring a pre-trained matching degree network model;
and inputting the first attribute information and the second attribute information into the matching degree network model to obtain the matching degree of the house sales task to be issued and the acquired position information.
4. The method for issuing a house property sales task according to claim 3, wherein before the obtaining of the pre-trained matching degree network model, the method further comprises:
acquiring sales sample data, wherein the sales sample data comprises first attribute information corresponding to position information in a sales record, second attribute information corresponding to a house property sales task and sales achievement information in the sales record;
inputting the first attribute information and the second attribute information in the sales sample data into a matching degree network model, and calculating to obtain a first matching degree of the position information and the house property sales task;
and converting the performance information in the sample data into a second matching degree, and adjusting the matching degree network model according to the difference between the first matching degree and the second matching degree until the difference meets the preset precision requirement.
5. The method for issuing a house property sales task according to claim 4, wherein converting the performance information in the sample data into a second matching degree comprises:
acquiring the house source transaction proportion and the house source transaction speed included in the performance information in the sample data;
and determining a second matching degree corresponding to the performance information according to the house source transaction proportion and the house source transaction speed.
6. The method for issuing a house property sales task according to claim 5, wherein determining a second matching degree corresponding to the performance information according to the house source transaction proportion and the house source transaction speed comprises:
acquiring a first weight coefficient corresponding to the house source transaction proportion, and acquiring a second weight coefficient corresponding to the house source transaction speed;
and calculating a second matching degree corresponding to the performance information according to the house source transaction proportion, the first weight coefficient, the house source transaction speed and the second weight coefficient.
7. The method for issuing a house property sales task according to any one of claims 2 to 6, wherein the first attribute information includes one or more of population quantity information, income level information, improved housing demand information, rent ratio information, and intention customer registration quantity information, and the second attribute information includes one or more of house source price hierarchy information, house source area information, house source type information, and house source marketing phase information.
8. A property sales task issuing apparatus, characterized by comprising:
the system comprises an information acquisition unit, a processing unit and a processing unit, wherein the information acquisition unit is used for acquiring position information for releasing a house property sales task and the house property sales task to be released;
the matching unit is used for searching the matching degree of the house sales task to be issued and the acquired position information according to the preset matching relation between the position information and the house sales task;
and the position selection unit is used for selecting position information for the house property sales task to be issued according to the matching degree.
9. A property sales task issuing apparatus comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the property sales task issuing method according to any one of claims 1 to 7 when executing the computer program.
10. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the method for issuing a house sales task according to any one of claims 1 to 7.
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Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN113255846A (en) * | 2021-07-06 | 2021-08-13 | 贝壳找房(北京)科技有限公司 | Room resource task allocation method and medium |
Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20140136255A1 (en) * | 2012-11-14 | 2014-05-15 | Wal-Mart Stores, Inc. | Dynamic Task Management |
CN107909304A (en) * | 2017-12-20 | 2018-04-13 | 李旭光 | A kind of management role order sends method and device with charge free |
CN109598404A (en) * | 2018-10-23 | 2019-04-09 | 平安科技(深圳)有限公司 | Automatically to the method and apparatus for issuing the progress data processing of sales task list |
CN109919417A (en) * | 2019-01-18 | 2019-06-21 | 深圳壹账通智能科技有限公司 | Method for allocating tasks and device, electronic equipment, the storage medium of financial system |
CN110458410A (en) * | 2019-07-15 | 2019-11-15 | 联动优势科技有限公司 | A kind of method and apparatus of task distribution |
-
2020
- 2020-05-21 CN CN202010437263.4A patent/CN112948416A/en active Pending
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20140136255A1 (en) * | 2012-11-14 | 2014-05-15 | Wal-Mart Stores, Inc. | Dynamic Task Management |
CN107909304A (en) * | 2017-12-20 | 2018-04-13 | 李旭光 | A kind of management role order sends method and device with charge free |
CN109598404A (en) * | 2018-10-23 | 2019-04-09 | 平安科技(深圳)有限公司 | Automatically to the method and apparatus for issuing the progress data processing of sales task list |
CN109919417A (en) * | 2019-01-18 | 2019-06-21 | 深圳壹账通智能科技有限公司 | Method for allocating tasks and device, electronic equipment, the storage medium of financial system |
CN110458410A (en) * | 2019-07-15 | 2019-11-15 | 联动优势科技有限公司 | A kind of method and apparatus of task distribution |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN113255846A (en) * | 2021-07-06 | 2021-08-13 | 贝壳找房(北京)科技有限公司 | Room resource task allocation method and medium |
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