CN112561269A - Advisor recommendation method and device - Google Patents
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Abstract
The application discloses a consultant recommendation method and a device, wherein the method comprises the following steps: when the electronic sign-on of a target client is detected, house-watching records and basic information of the target client are obtained; determining the intention degree of purchasing the house of the target client based on the house-watching record and the basic information; recommending a sales advisor for the target customer based on the house purchase intent. By adopting the method and the device, the room purchasing rate of the client can be improved.
Description
Technical Field
The application relates to the technical field of house property sales, in particular to an advisor recommendation method and an advisor recommendation device.
Background
After the client arrives at the case, if the client does not specify any consultant, the case is responsible for specifying the sales consultant to take the client to watch the room for the client, which may result in that the sales consultant cannot accurately obtain the client information, and further cannot accurately judge the room-buying intention of the client, and finally affects the room-buying rate of the client.
Disclosure of Invention
The embodiment of the application provides an advisor recommendation method and an advisor recommendation device.
In a first aspect, an embodiment of the present application provides an advisor recommendation method, including:
when the electronic sign-on of a target client is detected, house-watching records and basic information of the target client are obtained;
determining the intention degree of purchasing the house of the target client based on the house-watching record and the basic information;
recommending a sales advisor for the target customer based on the house purchase intent.
In one implementation, the determining the intention degree of house purchase of the target customer based on the house-watching record and the basic information includes:
and inputting the house watching record and the basic information into a house purchasing intention model, and outputting the house purchasing intention.
In one implementation, the recommending a sales advisor for the target customer based on the house purchase intention includes:
and acquiring advisor information, inputting the advisor information and the house purchasing intention into a recommendation model, and outputting the advisor information and the house purchasing intention as a recommended sales advisor of the target client.
In one implementation, the method further comprises:
when the advisor information is obtained, room source information is obtained;
and when the advisor information and the house purchasing intention are input into the recommendation model, inputting the house source information into the recommendation model and outputting the house source information as the house source recommended by the target client.
In one implementation, the recommending a sales advisor for the target customer based on the house purchase intention includes:
determining a priority of the target customer based on the house purchase intention;
recommending a sales advisor for the target customer based on the priority.
In one implementation, the method further comprises:
determining an intent to buy room feature of the target customer based on the record of seeing the room;
and acquiring house source information, and recommending house sources for the target clients based on the house source information and the intention house purchasing characteristics.
In one implementation, before determining the willingness to purchase rooms of the target customer based on the records of looking at rooms and the basic information, the method further comprises:
if the basic information comprises a specified sales consultant of the target client, recommending the specified sales consultant for the target client.
In a second aspect, an embodiment of the present application provides an advisor recommendation apparatus, including:
the system comprises an acquisition unit, a storage unit and a display unit, wherein the acquisition unit is used for acquiring the house-watching record and the basic information of a target client when the electronic sign of the target client is detected;
a determining unit, configured to determine the intention degree of purchasing the house of the target customer based on the house-watching record and the basic information;
and the recommending unit is used for recommending a sales consultant for the target client based on the house purchasing intention.
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 chip, and the program includes instructions for executing steps in any method of the first aspect of the embodiment of the present application.
In a fourth aspect, 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 makes a computer perform part or all of the steps described in any one of the methods of the first aspect of the present application.
In a fifth aspect, the present application provides a computer program product, wherein the computer program product includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to perform some or all of the steps as described in any one of the methods of the first aspect of the embodiments of the present application. The computer program product may be a software installation package.
It can be seen that, in the embodiment of the application, when the electronic check-in of the target client is detected, the room-viewing record and the basic information of the target client are obtained, then the room-purchasing intention of the target client is determined based on the room-viewing record and the basic information of the target client, and finally, a sales advisor is recommended to the target client based on the room-purchasing intention, so that a suitable sales advisor is recommended to the user based on the client information, and further, the room-purchasing rate of the client 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 application
FIG. 2 is a schematic flow chart of an advisor recommendation method provided in an embodiment of the present application;
fig. 3 is a schematic structural diagram of another electronic device provided in an embodiment of the present application;
fig. 4 is a schematic structural diagram of an advisor recommendation device according to an embodiment of the present application.
Detailed Description
In order to make the technical solutions better understood by those skilled in the art, 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 partial embodiments of the present application, but not all 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 following are detailed below.
The terms "first," "second," "third," and "fourth," etc. in the description and claims of this application and in the accompanying 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.
For example, fig. 1 shows a schematic structural diagram of an electronic device. The electronic device may include a processor 110, a memory 120, a communication interface 130, an audio module 140 (including speakers, headphones, and a microphone), a sensor module 150, a display screen 160, a camera 170, and so forth.
It is to be understood that the illustrated structure of the embodiments of the present application does not constitute a specific limitation to electronic devices. In other embodiments of the present application, an electronic device may include more or fewer components than shown, or some components may be combined, some components may be split, or a different arrangement of components may be used. The illustrated components may be implemented in hardware, software, or a combination of software and hardware.
Processor 110 may include one or more processing units, such as: the processor 110 may include an Application Processor (AP), a Graphics Processing Unit (GPU), an Image Signal Processor (ISP), a video codec, a Digital Signal Processor (DSP), a baseband processor, and the like. Wherein the different processing units may be separate components or may be integrated in one or more processors. In some embodiments, the electronic device may also include one or more processors 110. The processor 110 may generate an operation control signal according to the instruction operation code and the timing signal, and 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.
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, and/or a USB interface, etc.
It should be understood that the interface connection relationship between the modules illustrated in the embodiments of the present application is only an exemplary illustration, and does not constitute a limitation on the structure of the electronic device. In other embodiments of the present application, the electronic device may also adopt different interface connection manners or a combination of multiple interface connection manners in the above embodiments.
The electronic device implements display functions via the GPU, the display screen 160, and the application processor, etc. The GPU is a microprocessor for image processing, and is connected to the display screen 160 and an application processor. The display screen 160 is used to display images, video, and the like. The display screen 160 includes a display panel. In some embodiments, the electronic device may include 1 or more display screens 160.
The electronic device may implement a photographing function through the ISP, the camera 170, the video codec, the GPU, the display screen 160, the application processor, and the like. The ISP is used to process the data fed back by the camera 170. In some embodiments, the ISP may be provided in the camera 170. The camera 170 is used to capture still images or video. In some embodiments, the electronic device may include 1 or more cameras 170.
Memory 120 may be used to store one or more computer programs, including instructions. The processor 110 may cause the electronic device to execute the advisor recommendations provided in some embodiments of the present application, as well as various applications and data processing, etc., by executing the above-described instructions stored in the memory 120. Further, the memory 120 may include a high-speed random access memory and may also include a non-volatile memory. In some embodiments, the processor 110 may cause the electronic device to execute the advisor recommendation method provided in the embodiments of the present application, and other applications and data processing by executing instructions stored in the memory 120 and/or instructions stored in a memory disposed in the processor 110.
The electronic device may implement audio functions through an audio module 140 (e.g., speaker, microphone), and an application processor, etc. Such as audio output, audio capture, etc.
The sensor module 150 may include at least one sensor, such as a gesture sensor, a fingerprint sensor, a pressure sensor, a distance sensor, an optical proximity sensor, and the like.
Referring to fig. 2, fig. 2 is a schematic flowchart of an advisor recommendation method provided in an embodiment of the present application, applied to the electronic device, the method including:
step 201: when the electronic check-in of the target client is detected, the electronic equipment acquires the house-watching record and the basic information of the target client.
Specifically, the electronic equipment is arranged in a case, before a target customer electronically signs in, the electronic equipment displays a two-dimensional code for signing in, and after the target customer arrives at the case, the target customer scans the two-dimensional code through applications such as WeChat and the like, so that the electronic sign-in is realized. After detecting the electronic check-in of the target customer, the electronic device acquires device information of the target device for performing the electronic check-in, wherein the device information comprises the current geographic position of the target device and/or a target device identification (such as a telephone number).
Wherein, the electronic device acquires the room-viewing record and the basic information of the target client, and comprises: the electronic device extracts the room-viewing record and the basic information from a database of the electronic device based on the target device identification.
Wherein the basic information includes information of the target client and/or information of a consultant designated by the target client. The customer information is, for example, identity, age, expected price range, expected house type, etc.
Step 202: the electronic equipment determines the intention degree of purchasing the house of the target client based on the house-watching record and the basic information.
In one implementation, the electronic device determines the intention degree of house purchasing of the target customer based on the house-viewing record and the basic information, and includes: and the electronic equipment inputs the house watching record and the basic information into a house purchasing intention model and outputs the house purchasing intention.
The house purchasing intention model is obtained by training an original model based on information of the client, house watching records of the client, house purchasing information selected by the client and current house selling information. Because the house purchasing intention model is obtained by adopting a large amount of data training, the intelligent degree and the accuracy degree are higher, the complete data of each client is equivalent to a sample in actual use, and the house purchasing intention model is further continuously improved and updated.
In another implementation, the room-viewing record includes N pieces of room-viewing information, each piece of room-viewing information includes a room-viewing type, a room-viewing time, and a room-viewing selling price, the N is an integer greater than 1, the basic information includes customer information, and the customer information includes an expected price range and an expected house type; the electronic equipment determines the intention degree of purchasing the house of the target client based on the house-watching record and the basic information, and comprises the following steps:
the electronic equipment matches the house type included in each house-watching information with the expected house type to obtain N house type matching degrees; the electronic equipment matches the house-watching selling price included in each house-watching information with the expected price range to obtain N price matching degrees; the electronic equipment determines the house-looking frequency of the target client based on the house-looking time included in each piece of house-looking information;
and the electronic equipment determines the house purchasing intention of the target client based on the house watching frequency, the N house type matching degrees, the N price matching degrees and the house purchasing intention calculation formula.
Wherein, the house purchasing intention calculation formula is as follows: d ═ D (k1 xf) + (k2 xx) + (k3 xy), where D is the house purchase intention degree, k1, k2 and k3 are coefficients, f is the house viewing frequency, X is determined based on the N house type matching degrees (e.g., the maximum value and the minimum value among the N house type matching degrees are removed, and then an average value is obtained, which is X,), and Y is determined based on the N price matching degrees (e.g., the maximum value and the minimum value among the N price matching degrees are removed, and then an average value is obtained, which is Y).
It should be noted that k1+ k2+ k3 is 1, and k1, k2 and k3 may be the same or different, and are not limited herein.
Optionally, the electronic device determines the room-viewing frequency of the target client based on the room-viewing time included in each of the room-viewing information, including:
the electronic equipment determines time intervals of any two adjacent room-looking times to obtain M time intervals, wherein M is equal to N-1;
the electronic device determines a room-viewing frequency for the target customer based on the M time intervals.
Optionally, the electronic device determines the house-viewing frequency of the target customer based on the M time intervals, including:
if the M time intervals are all smaller than a preset threshold value, the electronic equipment determines that the house-watching frequency of the target client is a preset house-watching frequency;
and if K time intervals in the M time intervals are larger than the preset threshold value, the electronic equipment determines the house-watching frequency of the target client based on the preset house-watching frequency, the K and the house-watching frequency calculation formula.
The predetermined house-viewing frequency is, for example, 95%, 90%, 87%, or other values.
Wherein, the house-viewing frequency calculation formula is as follows: f ═ fg-G, said f is the frequency of looking at the room, said fgFor the preset house-viewing frequency, G is determined based on K and a first mapping, which is shown in table 1.
TABLE 1
| K | G |
| 1～2 | 10％ |
| 3～5 | 20％ |
| ...... | ...... |
For example, if k1 ═ k2 ═ k3 ═ 1/3, N ═ 5, 5 house match degrees 50%, 80%, 75%, 90%, and 95%, respectively, and 5 price match degrees 45%, 75%, 85%, 90%, and 98%, then X ═ 81.7%, Y ═ 75% + 90%/3 ═ 81.7%, and Y ═ 75% + 85% + 90%/3 ═ 83.3%. Suppose fg90%, K2, then f 90% -10%, then D (80%/3) + (81.7%/3) + (83.3%/3) — 81.6%.
Step 203: the electronic equipment recommends a sales advisor for the target customer based on the house purchase intention.
In an implementation, after step 203, the method further comprises:
the electronic equipment sends first information to a first terminal of a recommended sales advisor, wherein the first information comprises basic information of the target client and the intention degree of purchase of the target client, and the first information is used for indicating the service of the target client.
Optionally, after step 203, the method further comprises:
the electronic device displays second information including a service score, a rating, a photograph of the recommended sales advisor.
In one implementation, the electronic device recommending a sales advisor for the target customer based on the house purchase intention, comprising:
and the electronic equipment acquires advisor information, inputs the advisor information and the house purchasing intention into a recommendation model and outputs a recommended sales advisor for the target client.
The counselor information is stored in a database of the electronic equipment, and comprises information of a plurality of counselors, wherein each counselor information comprises service capability, character characteristics, service scores and the like, and the counselors are a plurality of counselors currently in store.
The recommendation model is obtained by training the original model based on the information of the consultant, the information of the house source, the intention degree of the client for buying the house and the information of the consultant selected by the client. Because the recommendation model is obtained by training a large amount of data, the degree of intellectualization and the degree of accuracy are high, the complete data of each client is equivalent to a sample in actual use, and the recommendation model is further continuously perfected and updated.
Optionally, the method further comprises:
when the advisor information is obtained, room source information is obtained;
and when the advisor information and the house purchasing intention are input into the recommendation model, inputting the house source information into the recommendation model and outputting the house source information as the house source recommended by the target client.
The house source information is stored in a database of the electronic device, the house source information comprises information of a plurality of house sources, and the information of each house source comprises a building ID, a house type, a house selling price and the like.
In another implementation, the electronic device recommends a sales advisor for the target customer based on the purchase intention, including:
the electronic equipment determines the priority of the target customer based on the house purchasing intention;
the electronic device recommends a sales advisor for the target customer based on the priority.
Optionally, the electronic device determines the priority of the target customer based on the house purchase intention degree, including: and the electronic equipment determines the priority of the target customer based on the second mapping relation between the house purchasing intention and the customer priority and the house purchasing intention.
The second mapping relationship is shown in table 2, where priority 1 is higher than priority 2, and priority 2 is higher than priority 3.
TABLE 2
Optionally, the electronic device recommends a sales advisor for the target customer based on the priority, comprising:
the electronic equipment determines a target priority of the sales advisor to be recommended based on the priority; the electronic equipment acquires a plurality of sales consultants with the target priority; the electronic equipment selects one sales advisor from the plurality of sales advisors to recommend to the target client.
The electronic device determines the target priority corresponding to the priority based on a third mapping relationship between the priority of the client and the priority of the sales advisor, where the third mapping relationship is shown in table 3, and the priority a is higher than the priority B, and the priority B is higher than the priority C.
TABLE 3
| Priority of client | Priority of sales consultants |
| Priority 1 | Priority A |
| Priority 2 | Priority class B |
| Priority 3 | Priority C |
| …… | …… |
Wherein the recommended sales advisor to the target client is the highest priority sales advisor among the plurality of sales advisors, or is a currently available sales advisor among the plurality of sales advisors, and so on.
Optionally, the method further comprises:
the electronic equipment determines the intention house-buying characteristics of the target customer based on the house-watching record;
the electronic equipment acquires the house source information and recommends the house source for the target client based on the house source information and the intention house purchasing characteristics.
The house-watching records comprise N house-watching information, each house-watching information comprises house type, house-watching time and house-watching selling price, and N is an integer greater than 1; the electronic device determines the intention house-buying characteristics of the target customer based on the house-watching record, and the method comprises the following steps: the electronic equipment analyzes the house-watching record to determine the intention house-buying characteristics of the target customer;
wherein the intended house-buying feature comprises at least one of: intention type, intention selling price.
It can be seen that, in the embodiment of the application, when the electronic check-in of the target client is detected, the room-viewing record and the basic information of the target client are obtained, then the room-purchasing intention of the target client is determined based on the room-viewing record and the basic information of the target client, and finally, a sales advisor is recommended to the target client based on the room-purchasing intention, so that a suitable sales advisor is recommended to the user based on the client information, and further, the room-purchasing rate of the client is improved.
In one implementation, before the electronic device determines the intention degree of house purchasing of the target customer based on the house-viewing record and the basic information, the method further includes:
if the basic information comprises a specified sales consultant of the target client, the electronic equipment recommends the specified sales consultant for the target client.
Optionally, after the electronic device recommends the specified sales advisor for the target customer, the method further comprises:
if the target client refuses the appointed sales consultant, the electronic equipment prompts a feedback refusing reason;
after the target client feeds back a reason for the rejection of the specified sales advisor, the electronic device prompts feedback on the characteristics of the desired sales advisor;
after the target client feeds back the characteristics of the desired sales advisor, the electronic device recommends a sales advisor for the target client based on the characteristics of the desired sales advisor fed back by the target client.
Among other features desired by the sales advisor are, for example, service ratings, business capabilities, etc.
It can be seen that, in the embodiment of the present application, if the target client refuses to designate a sales counselor, an appropriate sales counselor is recommended to the client according to the information fed back by the client, so as to recommend an appropriate sales counselor to the client, and further improve the client room purchase rate.
Referring to fig. 3, fig. 3 is a schematic structural diagram of another electronic device according to an embodiment of the present disclosure, and as shown in the drawing, the electronic device includes 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 programs include instructions for performing the following steps:
when the electronic sign-on of a target client is detected, house-watching records and basic information of the target client are obtained;
determining the intention degree of purchasing the house of the target client based on the house-watching record and the basic information;
recommending a sales advisor for the target customer based on the house purchase intent.
It can be seen that, in the embodiment of the application, when the electronic check-in of the target client is detected, the room-viewing record and the basic information of the target client are obtained, then the room-purchasing intention of the target client is determined based on the room-viewing record and the basic information of the target client, and finally, a sales advisor is recommended to the target client based on the room-purchasing intention, so that a suitable sales advisor is recommended to the user based on the client information, and further, the room-purchasing rate of the client is improved.
In one implementation, in determining the intent to purchase room of the target customer based on the record of looking at room and the basic information, the program includes instructions specifically for performing the steps of:
and inputting the house watching record and the basic information into a house purchasing intention model, and outputting the house purchasing intention.
In one implementation, in recommending a sales advisor for the target customer based on the house purchase intent, the program includes instructions specifically for performing the steps of:
and acquiring advisor information, inputting the advisor information and the house purchasing intention into a recommendation model, and outputting the advisor information and the house purchasing intention as a recommended sales advisor of the target client.
In one implementation, the program includes instructions for performing the following steps:
when the advisor information is obtained, room source information is obtained;
and when the advisor information and the house purchasing intention are input into the recommendation model, inputting the house source information into the recommendation model and outputting the house source information as the house source recommended by the target client.
In one implementation, in recommending a sales advisor for the target customer based on the house purchase intent, the program includes instructions specifically for performing the steps of:
determining a priority of the target customer based on the house purchase intention;
recommending a sales advisor for the target customer based on the priority.
In one implementation, the program includes instructions for performing the following steps:
determining an intent to buy room feature of the target customer based on the record of seeing the room;
and acquiring house source information, and recommending house sources for the target clients based on the house source information and the intention house purchasing characteristics.
In one implementation, before determining the house-buying intent of the target customer based on the house-viewing record and the basic information, the program includes instructions for further performing the steps of:
if the basic information comprises a specified sales consultant of the target client, recommending the specified sales consultant for the target client.
It should be noted that, for the specific implementation process of the present embodiment, reference may be made to the specific implementation process described in the above method embodiment, and a description thereof is omitted here.
Referring to fig. 4, fig. 4 is a schematic diagram of an advisor recommendation apparatus applied to the electronic device according to an embodiment of the present application, the advisor recommendation apparatus including:
an obtaining unit 401, configured to obtain a house-watching record and basic information of a target client when an electronic sign-on of the target client is detected;
a determining unit 402, configured to determine the intention degree of purchasing rooms of the target customer based on the record of seeing rooms and the basic information;
a recommending unit 403, configured to recommend a sales advisor for the target client based on the house purchase intention.
It can be seen that, in the embodiment of the application, when the electronic check-in of the target client is detected, the room-viewing record and the basic information of the target client are obtained, then the room-purchasing intention of the target client is determined based on the room-viewing record and the basic information of the target client, and finally, a sales advisor is recommended to the target client based on the room-purchasing intention, so that a suitable sales advisor is recommended to the user based on the client information, and further, the room-purchasing rate of the client is improved.
In an implementation manner, in determining the intention degree of house purchasing of the target customer based on the house-viewing record and the basic information, the determining unit 402 is specifically configured to:
and inputting the house watching record and the basic information into a house purchasing intention model, and outputting the house purchasing intention.
In one implementation, in recommending a sales advisor for the target client based on the house purchase intention, the recommending unit 403 is specifically configured to:
and acquiring advisor information, inputting the advisor information and the house purchasing intention into a recommendation model, and outputting the advisor information and the house purchasing intention as a recommended sales advisor of the target client.
In an implementation manner, the obtaining unit 401 is further configured to obtain the room source information when obtaining the advisor information;
the recommending unit 403 is further configured to, when the advisor information and the house purchasing intention are input into the recommendation model, input the house source information into the recommendation model, and output the house source information as a house source recommended by the target client.
In one implementation, in recommending a sales advisor for the target client based on the house purchase intention, the recommending unit 403 is specifically configured to:
determining a priority of the target customer based on the house purchase intention;
recommending a sales advisor for the target customer based on the priority.
In an implementation manner, the recommending unit 403 is further configured to determine an intended house purchasing characteristic of the target customer based on the house watching record; and acquiring house source information, and recommending house sources for the target clients based on the house source information and the intention house purchasing characteristics.
In an implementation manner, before determining the intention degree of purchasing a room of the target client based on the room watching record and the basic information, the recommending unit 403 is further configured to recommend a specified sales advisor for the target client if the basic information includes the specified sales advisor of the target client.
It should be noted that the obtaining unit 401, the determining unit 402, and the recommending unit 403 may be implemented by a processor.
The present application also provides a computer-readable storage medium, where the computer-readable storage medium stores a computer program for electronic data exchange, where the computer program makes a computer perform some or all of the steps described in the electronic device in the above method embodiments.
Embodiments of the present application also provide a computer program product, where the computer program product includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to perform some or all of the steps described in the electronic device in the above method. The computer program product may be a software installation package.
The steps of a method or algorithm described in the embodiments of the present application may be implemented in hardware, or may be implemented by a processor executing software instructions. The software instructions may be comprised of corresponding software modules that may be stored in Random Access Memory (RAM), flash Memory, Read Only Memory (ROM), Erasable Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), registers, a hard disk, a removable disk, a compact disc Read Only Memory (CD-ROM), or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor such the processor can read information from, and write information to, the storage medium. Of course, the storage medium may also be integral to the processor. The processor and the storage medium may reside in an ASIC. Additionally, the ASIC may reside in an access network device, a target network device, or a core network device. Of course, the processor and the storage medium may reside as discrete components in an access network device, a target network device, or a core network device.
Those skilled in the art will appreciate that in one or more of the examples described above, the functionality described in the embodiments of the present application may be implemented, in whole or in part, by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loaded and executed on a computer, cause the processes or functions described in accordance with the embodiments of the application to occur, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored on a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, from one website, computer, server, or data center to another website, computer, server, or data center via wire (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, such as a server, a data center, etc., that incorporates one or more of the available media. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., Digital Video Disk (DVD)), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.
The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the embodiments of the present application in further detail, and it should be understood that the above-mentioned embodiments are only specific embodiments of the present application, and are not intended to limit the scope of the embodiments of the present application, and any modifications, equivalent substitutions, improvements and the like made on the basis of the technical solutions of the embodiments of the present application should be included in the scope of the embodiments of the present application.
Claims (10)
1. A consultant recommendation method, characterized in that the method comprises:
when the electronic sign-on of a target client is detected, house-watching records and basic information of the target client are obtained;
determining the intention degree of purchasing the house of the target client based on the house-watching record and the basic information;
recommending a sales advisor for the target customer based on the house purchase intent.
2. The method of claim 1, wherein determining the intent to purchase room of the target customer based on the room-viewing record and the basic information comprises:
and inputting the house watching record and the basic information into a house purchasing intention model, and outputting the house purchasing intention.
3. The method of claim 1 or 2, wherein recommending a sales advisor for the target customer based on the house purchase intent comprises:
and acquiring advisor information, inputting the advisor information and the house purchasing intention into a recommendation model, and outputting the advisor information and the house purchasing intention as a recommended sales advisor of the target client.
4. The method of claim 3, further comprising:
when the advisor information is obtained, room source information is obtained;
and when the advisor information and the house purchasing intention are input into the recommendation model, inputting the house source information into the recommendation model and outputting the house source information as the house source recommended by the target client.
5. The method of claim 1 or 2, wherein recommending a sales advisor for the target customer based on the house purchase intent comprises:
determining a priority of the target customer based on the house purchase intention;
recommending a sales advisor for the target customer based on the priority.
6. The method of claim 5, further comprising:
determining an intent to buy room feature of the target customer based on the record of seeing the room;
and acquiring house source information, and recommending house sources for the target clients based on the house source information and the intention house purchasing characteristics.
7. The method according to any of claims 1-6, wherein prior to determining the intent to purchase room of the target customer based on the room-viewing record and the basic information, the method further comprises:
if the basic information comprises a specified sales consultant of the target client, recommending the specified sales consultant for the target client.
8. An advisor recommendation device, the device comprising:
the system comprises an acquisition unit, a storage unit and a display unit, wherein the acquisition unit is used for acquiring the house-watching record and the basic information of a target client when the electronic sign of the target client is detected;
a determining unit, configured to determine the intention degree of purchasing the house of the target customer based on the house-watching record and the basic information;
and the recommending unit is used for recommending a sales consultant for the target client based on the house purchasing intention.
9. An electronic device comprising a processor, a memory, a communication interface, and one or more programs stored in the memory and configured to be executed by the processor, the programs comprising instructions for performing the steps in the method of any of claims 1-7.
10. A computer-readable storage medium, characterized by storing a computer program for electronic data exchange; wherein the computer program causes a computer to perform the method according to any one of claims 1-7.
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| CN202011416514.7A CN112561269A (en) | 2020-12-07 | 2020-12-07 | Advisor recommendation method and device |
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113190591A (en) * | 2021-04-20 | 2021-07-30 | 北京异乡旅行网络科技有限公司 | Business opportunity distribution method, device, equipment and storage medium |
| CN113674111A (en) * | 2021-07-14 | 2021-11-19 | 深圳思为科技有限公司 | Resource management method and device |
| CN113761362A (en) * | 2021-07-30 | 2021-12-07 | 深圳市思为软件技术有限公司 | Information recommendation method, information recommendation device, electronic equipment and related products |
| CN113781098A (en) * | 2021-07-30 | 2021-12-10 | 深圳市思为软件技术有限公司 | Method and device for improving sales efficiency and computer storage medium |
| CN114387062A (en) * | 2022-01-13 | 2022-04-22 | 北京自如信息科技有限公司 | Training of housekeeper recommendation model, housekeeper recommendation method and electronic equipment |
| CN116894570A (en) * | 2023-09-11 | 2023-10-17 | 杭州及凌网络科技有限公司 | Salesman recommending method, device and equipment based on automobile sales platform |
Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106384246A (en) * | 2016-09-09 | 2017-02-08 | 珠海幸福家网络科技有限公司 | House purchase intention determination device and method |
| CN108376354A (en) * | 2018-01-10 | 2018-08-07 | 链家网（北京）科技有限公司 | A kind of recommendation method and device based on network graph structure |
| CN110163685A (en) * | 2019-05-27 | 2019-08-23 | 珠海幸福家网络科技股份有限公司 | The customer priorities analysis system and analysis method of room track are seen based on client |
| CN110689457A (en) * | 2019-10-09 | 2020-01-14 | 重庆锐云科技有限公司 | Intelligent reception method for online clients in real estate industry, server and storage medium |
| CN110764665A (en) * | 2019-09-19 | 2020-02-07 | 深圳思为科技有限公司 | Information processing method, information processing device and terminal equipment |
| CN110796515A (en) * | 2019-09-26 | 2020-02-14 | 北京瑞卓喜创科技发展有限公司 | House resource recommendation method and device, storage medium and mobile terminal |
| CN110852797A (en) * | 2019-10-29 | 2020-02-28 | 深圳市看见网络科技有限公司 | Method, mobile terminal and computer storage medium for helping broker to judge guests efficiently |
| CN110955838A (en) * | 2019-12-04 | 2020-04-03 | 青梧桐有限责任公司 | House resource recommendation processing method and device, terminal and computer readable storage medium |
| CN111210253A (en) * | 2019-11-26 | 2020-05-29 | 恒大智慧科技有限公司 | Method, device and storage medium for matching consumer with sales consultant |
| CN111414542A (en) * | 2020-03-20 | 2020-07-14 | 重庆锐云科技有限公司 | Real estate customer group identification and marketing method |
| CN111639988A (en) * | 2020-05-22 | 2020-09-08 | 贝壳技术有限公司 | Broker recommendation method, device, electronic equipment and storage medium |
-
2020
- 2020-12-07 CN CN202011416514.7A patent/CN112561269A/en active Pending
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106384246A (en) * | 2016-09-09 | 2017-02-08 | 珠海幸福家网络科技有限公司 | House purchase intention determination device and method |
| CN108376354A (en) * | 2018-01-10 | 2018-08-07 | 链家网（北京）科技有限公司 | A kind of recommendation method and device based on network graph structure |
| CN110163685A (en) * | 2019-05-27 | 2019-08-23 | 珠海幸福家网络科技股份有限公司 | The customer priorities analysis system and analysis method of room track are seen based on client |
| CN110764665A (en) * | 2019-09-19 | 2020-02-07 | 深圳思为科技有限公司 | Information processing method, information processing device and terminal equipment |
| CN110796515A (en) * | 2019-09-26 | 2020-02-14 | 北京瑞卓喜创科技发展有限公司 | House resource recommendation method and device, storage medium and mobile terminal |
| CN110689457A (en) * | 2019-10-09 | 2020-01-14 | 重庆锐云科技有限公司 | Intelligent reception method for online clients in real estate industry, server and storage medium |
| CN110852797A (en) * | 2019-10-29 | 2020-02-28 | 深圳市看见网络科技有限公司 | Method, mobile terminal and computer storage medium for helping broker to judge guests efficiently |
| CN111210253A (en) * | 2019-11-26 | 2020-05-29 | 恒大智慧科技有限公司 | Method, device and storage medium for matching consumer with sales consultant |
| CN110955838A (en) * | 2019-12-04 | 2020-04-03 | 青梧桐有限责任公司 | House resource recommendation processing method and device, terminal and computer readable storage medium |
| CN111414542A (en) * | 2020-03-20 | 2020-07-14 | 重庆锐云科技有限公司 | Real estate customer group identification and marketing method |
| CN111639988A (en) * | 2020-05-22 | 2020-09-08 | 贝壳技术有限公司 | Broker recommendation method, device, electronic equipment and storage medium |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113190591A (en) * | 2021-04-20 | 2021-07-30 | 北京异乡旅行网络科技有限公司 | Business opportunity distribution method, device, equipment and storage medium |
| CN113674111A (en) * | 2021-07-14 | 2021-11-19 | 深圳思为科技有限公司 | Resource management method and device |
| CN113761362A (en) * | 2021-07-30 | 2021-12-07 | 深圳市思为软件技术有限公司 | Information recommendation method, information recommendation device, electronic equipment and related products |
| CN113781098A (en) * | 2021-07-30 | 2021-12-10 | 深圳市思为软件技术有限公司 | Method and device for improving sales efficiency and computer storage medium |
| CN113761362B (en) * | 2021-07-30 | 2024-09-10 | 深圳市思为软件技术有限公司 | Information recommendation method, information recommendation device, electronic equipment and related products |
| CN114387062A (en) * | 2022-01-13 | 2022-04-22 | 北京自如信息科技有限公司 | Training of housekeeper recommendation model, housekeeper recommendation method and electronic equipment |
| CN116894570A (en) * | 2023-09-11 | 2023-10-17 | 杭州及凌网络科技有限公司 | Salesman recommending method, device and equipment based on automobile sales platform |
| CN116894570B (en) * | 2023-09-11 | 2023-12-05 | 杭州及凌网络科技有限公司 | Salesman recommending method, device and equipment based on automobile sales platform |
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