CN107491983B - WeChat client behavior feedback method, equipment and storage medium - Google Patents
WeChat client behavior feedback method, equipment and storage medium Download PDFInfo
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Abstract
The invention discloses a method, equipment and a storage medium for feedback of a WeChat client behavior, wherein the method for feedback of the WeChat client behavior obtains basic information of a user and randomly allocates follow-up seats for the basic information after receiving a public number attention instruction input by the user; then, acquiring historical operation records of all users in the public number, and analyzing the behavior intention of each user according to the historical operation records; and then feeding back the basic information and the behavior intention analysis result of each user to a display interface of the corresponding follow-up seat. Through acquiring the historical operation records of the users in the public number and feeding back the analysis results to the follow-up seat after analyzing the behavior intentions of the users, the follow-up seat can actively contact the users with pertinence according to different user behaviors, and the communication efficiency and the sales performance are effectively improved.
Description
Technical Field
The invention relates to the technical field of mobile internet, in particular to a WeChat client behavior feedback method, equipment and a storage medium.
Background
At present, with the continuous development of mobile communication technology, mobile terminals have become indispensable tools for people's lives, among numerous mobile terminal applications, WeChat has become one of the most widely used social, entertainment and life applications, and in the face of such a huge and growing user group, many companies will adopt a public number establishment mode to market and attract passenger flow.
However, in the communication popularization mode of the existing WeChat public number, the contact between the sales staff and the user is limited to the active contact of the user with the sales staff, that is, after the user pays attention to the public number, the sales staff can only passively wait for the contact of the user due to the fact that the user cannot know the operation of the user, and the active contact cannot be actively carried out on the potential user, so that the communication inefficiency is caused, and the promotion of the sales performance is influenced.
Accordingly, the prior art is yet to be improved and developed.
Disclosure of Invention
In view of the defects of the prior art, the invention aims to provide a method, equipment and a storage medium for feedback of the behavior of a wechat client, and solves the problem of low communication efficiency caused by the fact that the current wechat public number influences a salesperson to actively contact a potential user because the operation behavior of the user cannot be known.
In order to achieve the purpose, the invention adopts the following technical scheme:
a WeChat client behavior feedback method comprises the following steps:
after receiving a public number attention instruction input by a user, acquiring basic information of the user and randomly distributing follow-up seats for the user;
acquiring historical operation records of all users in a public number, and analyzing the behavior intention of each user according to the historical operation records;
and feeding back the basic information and the behavior intention analysis result of each user to a display interface of the corresponding follow-up seat.
In the WeChat client behavior feedback method, the step of obtaining the historical operation records of all users in the public number and analyzing the behavior intention of each user according to the historical operation records comprises the following steps:
detecting and recording contact information and input information of each user in a public number to obtain a historical operation record of each user;
and analyzing the behavior intention of each user according to the historical operation records.
In the WeChat client behavior feedback method, the step of analyzing the behavior intention of each user according to the historical operation records comprises the following steps:
obtaining the activity of each user according to the time information in the historical operation records;
extracting menu options corresponding to the contact information in each user historical operation record and keyword information corresponding to the input information;
and analyzing the behavior intention of each user according to the liveness, the menu options and the keyword information.
In the WeChat client behavior feedback method, the step of analyzing the behavior intention of each user according to the liveness, the menu options and the keyword information comprises the following steps:
and analyzing whether each user is a potential customer according to the liveness, and analyzing the required product of each customer according to the menu option and the keyword information.
In the WeChat client behavior feedback method, the step of feeding back the basic information and behavior intention analysis result of each user to the display interface of the corresponding follow-up seat comprises the following steps:
according to the behavior intention analysis result of each user, carrying out user category division on the user and setting a category label;
and feeding back the basic information of the user under each category label and the behavior intention analysis result thereof to a display interface of the corresponding follow-up seat.
In the WeChat client behavior feedback method, the steps of classifying the user types according to the behavior intention analysis result of each user and setting the type labels include:
and classifying the users into potential customers, non-potential customers, purchased customers and paid customers according to the behavior intention analysis result of each user, and setting corresponding category labels.
In the WeChat client behavior feedback method, the basic information comprises user micro signals and reserved contact information.
In the WeChat client behavior feedback method, the input information comprises text information and voice information.
A wechat client behavior feedback device comprising a processor, a memory, and a communication bus;
the communication bus is used for realizing connection communication between the processor and the memory;
the processor is used for executing the wechat client behavior feedback program in the memory to realize the wechat client behavior feedback method
A computer readable storage medium, wherein the computer readable storage medium stores one or more programs, which are executable by one or more processors, to implement a wechat client behavior feedback method as described above.
Compared with the prior art, in the method, the device and the storage medium for the feedback of the WeChat client behavior, the basic information of the user is acquired and the follow-up seat is randomly allocated to the basic information after the WeChat client behavior feedback method receives the public number attention instruction input by the user; then, acquiring historical operation records of all users in the public number, and analyzing the behavior intention of each user according to the historical operation records; and then feeding back the basic information and the behavior intention analysis result of each user to a display interface of the corresponding follow-up seat. Through acquiring the historical operation records of the users in the public number and feeding back the analysis results to the follow-up seat after analyzing the behavior intentions of the users, the follow-up seat can actively contact the users with pertinence according to different user behaviors, and the communication efficiency and the sales performance are effectively improved.
Drawings
Fig. 1 is a flowchart of a WeChat client behavior feedback method provided by the present invention.
Fig. 2 is a flowchart of step S20 in the method for feedback of wechat client behavior provided by the present invention.
Fig. 3 is a flowchart of step S22 in the method for feedback of wechat client behavior provided by the present invention.
Fig. 4 is a flowchart of step S30 in the method for feedback of wechat client behavior provided by the present invention.
FIG. 5 is a diagram illustrating an operating environment of a WeChat client behavior feedback process according to a preferred embodiment of the present invention.
FIG. 6 is a functional block diagram of a preferred embodiment of the system for installing a WeChat client behavior feedback program according to the present invention.
Detailed Description
In view of the defects that the communication of clients in the WeChat public number in the prior art is lack of initiative and pertinence and the like, the invention aims to provide a method, equipment and a storage medium for feedback of the behavior of WeChat clients.
In order to make the objects, technical solutions and effects of the present invention clearer and clearer, the present invention is further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Referring to fig. 1, the method for feedback of WeChat client behavior provided by the present invention includes the following steps:
and S10, after receiving the public number attention instruction input by the user, acquiring the basic information of the user and randomly distributing a follow-up seat for the user.
In this embodiment, after the user inputs the attention instruction of the public number, the background automatically acquires the basic information of the user, for example, the user searches for the public number of the safe automobile insurance through a "scanning" function or a search function, and clicks the attention button, at this time, the background of the WeChat public number automatically acquires the basic information of the user, including the user's micro-signal and the reserved contact ways, such as a telephone, a mailbox, a QQ number, and the like, and then randomly allocates follow-up seats to the user, in the subsequent communication process, each client continuously communicates with the designated follow-up seats to avoid the occurrence of communication interruption and unsmooth conditions caused by frequent replacement of seat personnel.
And S20, acquiring historical operation records of all users in the public number, and analyzing the behavior intention of each user according to the historical operation records.
After the user pays attention to the WeChat public number, the historical operation records of the user in the public number are obtained, specifically, the historical operation records of the user can be obtained at preset time intervals to update the historical operation records of the user, and the behavior intention of the user is analyzed according to the historical operation records, so that behavior trends of different users are obtained through analysis, and a reliable data basis is provided for better following service customers. Please refer to fig. 2, which is a flowchart of step S20 in the method for feedback of WeChat client behavior according to the present invention.
As shown in fig. 2, the step S20 includes:
s21, detecting and recording contact information and input information of each user in the public number to obtain historical operation records of each user;
and S22, analyzing the behavior intention of each user according to the historical operation records.
Namely, when the historical operation record of the user is obtained, the historical operation record is obtained by detecting and recording the contact information of the user in the public number and outputting the information, wherein the input information comprises text information and voice information, for example, after the user pays attention to the public number, the user can click various menu options in the public number to obtain product information, for example, in the public number of safe vehicle insurance, three menus of welfare, vehicle insurance and customer service are arranged, a plurality of submenus are respectively arranged under each menu option, a user can click the corresponding submenu to obtain corresponding information according to the self requirement, or, when there is no information desired by the user in the sub-menu, the user may directly input voice information or text information in an attempt to acquire information desired by the user, therefore, in the embodiment, the historical operation record of each user is obtained by detecting and recording the contact information and the input information, and the behavior intention of each user is analyzed according to the historical operation record. Please refer to fig. 3, which is a flowchart of step S22 in the method for feedback of WeChat client behavior according to the present invention.
As shown in fig. 3, the step S22 includes:
s201, obtaining the activity of each user according to the time information in the historical operation records;
s202, extracting menu options corresponding to contact information in each user historical operation record and keyword information corresponding to input information;
and S203, analyzing the behavior intention of each user according to the liveness, the menu options and the keyword information.
In specific implementation, after the historical operation records of the users are obtained, the activity of each user can be obtained according to the time information, for example, the operation times of the users in the public numbers within a preset time period (for example, one day) can be obtained according to the time information to determine the operation frequency, or whether the users pay attention to the public numbers is determined according to the push time of articles in the public numbers and the difference between the time when the users click the articles, then, menu options corresponding to the contact information in the historical operation records and keyword information in the input information are extracted, and the behavior intention of each user is analyzed according to the activity, the menu options and the keyword information.
Specifically, in step S203, when analyzing the user behavior intention, it is analyzed whether each user is a potential customer according to the liveness, and the required product of each customer is analyzed according to the menu option and the keyword information. As described above, the activity of the user can be judged according to the operation time of the user, and whether the user is a potential customer is analyzed according to the activity, for example, if the activity is greater than a preset value, the user is judged to be a potential customer, which indicates that the user always pays attention to the public account, otherwise, the user is judged to be a non-potential customer.
Meanwhile, the contact information input by the user in the public number by clicking each time corresponds to menu options in the public number, and by combining with the text and voice information of the user, the operation records represent the interested direction of the user to the content in the public number, for example, three menus of welfare, car insurance and customer service are arranged in the safe car insurance public number, a plurality of submenus are respectively arranged under each menu option, if the car insurance menu and submenus arranged under the car insurance menu are clicked for a plurality of times in the operation records of the user, the content of the car insurance is shown to be interested by the user, for example, no car insurance price option is arranged in the public number, the text information of the user, namely the car insurance price and package detail, is input by the user through a keyboard, at the moment, the keywords, namely the car insurance and the price, in the input information are extracted, the user wants to know the price of the car insurance, so that the demand information of the user is obtained by combining with, and a tendency suggestion is provided for the follow-up communication between the seat and the user, and the communication efficiency and the sales success rate are improved.
And S30, feeding back the basic information and the behavior intention analysis result of each user to a display interface of the corresponding follow-up seat.
In the embodiment, after the historical operation records of the users are analyzed, the basic information and the behavior intention analysis result of each user are fed back to the display interface of the corresponding follow-up seat, so that the follow-up seat can know the information such as the state, the purchase intention and the intention product of the user in real time, and the follow-up seat is helped to improve the sales performance. Please refer to fig. 4, which is a flowchart of step S30 in the method for feedback of WeChat client behavior according to the present invention.
As shown in fig. 4, the step S30 includes:
s31, performing user category division according to the behavior intention analysis result of each user, and setting category labels;
and S32, feeding back the basic information of the user under each category label and the behavior intention analysis result thereof to the display interface of the corresponding follow-up seat.
After the behavior intention analysis result of the user is obtained, the user is classified according to the result, and in step S31, the user may be classified into a potential customer, a non-potential customer, a purchased customer, and a customer with cancelled attention, and corresponding category labels are set, and then the basic information of the user and the behavior intention analysis result thereof under each category label are fed back to the display interface of the corresponding follow-up seat.
The method comprises the steps that firstly, a user to be followed can be classified and displayed according to category labels on a display interface of a follow-up seat, the follow-up seat can intensively develop potential customers and maintain purchased customers, and actively communicate with the purchased customers in interested directions so as to improve communication efficiency and communication effect, preferably, the potential customers and the purchased customers can be sorted and displayed according to liveness, for example, the higher the liveness, the closer the ranking, the easier the follow-up seat can pay attention to, and certainly, the user can be sorted according to the sorting instruction of the follow-up seat, so that the habit and the requirement of the follow-up seat are better met; the attention of the non-potential customers is kept, and the frequency of active communication can be properly reduced, so that the non-potential customers are prevented from generating adverse psychology and canceling the attention; and the disturbance is not carried out aiming at the cancelled concerned customers so as to avoid receiving the complaints of the users and reduce the company evaluation, thereby providing the classification reference of the user groups for the follow-up seat and improving the working efficiency of the follow-up seat.
Preferably, in the WeChat client behavior feedback method provided by the invention, product statistical analysis can be performed according to the collected historical operation records of all users, and big data reference is provided in the subsequent product development process, so that products which are more interested by consumers can be developed, and further sales performance can be provided.
As shown in fig. 5, based on the above-mentioned WeChat client behavior feedback method, the present invention also provides a WeChat client behavior feedback device accordingly. The WeChat client behavior feedback device specifically needs to interact with a mobile terminal and an agent terminal of a user, for example, receives an operation instruction input by the mobile terminal of the user, feeds the operation instruction back to the agent terminal, and sends contact information output by the agent terminal to the mobile terminal of the user, so as to realize communication between the user and a follow-up agent.
The WeChat client behavior feedback device can be a desktop computer, a notebook, a palm computer, a server and other computing devices. The wechat client behavior feedback devices include, but are not limited to, a processor 10, a memory 20, and a display 30. Fig. 5 shows only some of the components of the WeChat client behavior feedback device, but it should be understood that not all of the shown components are required and that more or fewer components may be implemented instead.
The storage 20 may in some embodiments be an internal storage unit of the wechat client behavior feedback device, for example, a hard disk or a memory of the wechat client behavior feedback device. The memory 20 may also be an external storage device of the wechat client behavior feedback device in other embodiments, 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 provided on the wechat client behavior feedback device. Further, the memory 20 may also include both an internal storage unit and an external storage device of the wechat client behavior feedback device. The memory 20 is used for storing application software installed in the wechat client behavior feedback device and various types of data, such as program codes of the installed wechat client behavior feedback device. The memory 20 may also be used to temporarily store data that has been output or is to be output. In one embodiment, the memory 20 stores a wechat client behavior feedback program 40, and the wechat client behavior feedback program 40 can be executed by the processor 10, so as to implement the wechat client behavior feedback method according to the embodiments of the present application.
The processor 10 may be, in some embodiments, a Central Processing Unit (CPU), a microprocessor or other data Processing chip, and is configured to run program codes stored in the memory 20 or process data, such as executing the WeChat client behavior feedback method.
The display 30 may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch panel, or the like in some embodiments. The display 30 is used to display information processed in the wechat client behavior feedback device and to display a visual user interface. The components 10-30 of the wechat client behavior feedback device communicate with each other via a system bus.
In one embodiment, the following steps are implemented when the processor 10 executes the untrusted client behavior feedback program 40 in the memory 20:
after receiving a public number attention instruction input by a user, acquiring basic information of the user and randomly distributing follow-up seats for the user;
acquiring historical operation records of all users in a public number, and analyzing the behavior intention of each user according to the historical operation records;
and feeding back the basic information and the behavior intention analysis result of each user to a display interface of the corresponding follow-up seat.
Further, in the wechat client behavior feedback device, the step of obtaining historical operation records of all users in public numbers and analyzing the behavior intention of each user according to the historical operation records includes:
detecting and recording contact information and input information of each user in a public number to obtain a historical operation record of each user;
and analyzing the behavior intention of each user according to the historical operation records.
The step of analyzing the behavioral intention of each user according to the historical operation records comprises the following steps:
obtaining the activity of each user according to the time information in the historical operation records;
extracting menu options corresponding to the contact information in each user historical operation record and keyword information corresponding to the input information;
and analyzing the behavior intention of each user according to the liveness, the menu options and the keyword information.
The step of analyzing the behavioral intention of each user according to the liveness, menu options and keyword information includes:
and analyzing whether each user is a potential customer according to the liveness, and analyzing the required product of each customer according to the menu option and the keyword information.
The step of feeding back the basic information and the behavior intention analysis result of each user to the display interface of the corresponding follow-up seat comprises the following steps:
according to the behavior intention analysis result of each user, carrying out user category division on the user and setting a category label;
and feeding back the basic information of the user under each category label and the behavior intention analysis result thereof to a display interface of the corresponding follow-up seat.
The step of classifying the user category according to the behavior intention analysis result of each user and setting a category label comprises the following steps:
and classifying the users into potential customers, non-potential customers, purchased customers and paid customers according to the behavior intention analysis result of each user, and setting corresponding category labels.
The basic information comprises user micro-signals and reserved contact information.
The input information includes text information and voice information.
Please refer to fig. 6, which is a functional block diagram of a system for installing a WeChat client behavior feedback program according to a preferred embodiment of the present invention. In this embodiment, the system for installing the WeChat client behavior feedback program may be divided into one or more modules, and the one or more modules are stored in the memory 20 and executed by one or more processors (in this embodiment, the processor 10) to complete the present invention. For example, in fig. 6, the system for installing the wechat client behavior feedback program may be divided into a receiving module 21, an acquisition analysis module 22, and a feedback module 23. The module referred to in the invention refers to a series of computer program instruction segments capable of completing specific functions, and is more suitable for describing the execution process of the wechat client behavior feedback program in the wechat client behavior feedback device than a program. The following description will specifically describe the functionality of the modules 21-24.
The receiving module 21 is configured to obtain basic information of a user and randomly allocate a follow-up seat to the basic information after receiving a public number attention instruction input by the user;
the acquisition and analysis module 22 is used for acquiring historical operation records of all users in the public number and analyzing the behavior intention of each user according to the historical operation records;
and the feedback module 23 is configured to feed back the basic information and the behavior intention analysis result of each user to a display interface of the corresponding follow-up agent.
In summary, in the method, the device, the system and the storage medium for feedback of the wechat client behavior provided by the present invention, after receiving the public number attention instruction input by the user, the method for feedback of the wechat client behavior obtains the basic information of the user and randomly allocates a follow-up seat to the basic information; then, acquiring historical operation records of all users in the public number, and analyzing the behavior intention of each user according to the historical operation records; and then feeding back the basic information and the behavior intention analysis result of each user to a display interface of the corresponding follow-up seat. Through acquiring the historical operation records of the users in the public number and feeding back the analysis results to the follow-up seat after analyzing the behavior intentions of the users, the follow-up seat can actively contact the users with pertinence according to different user behaviors, and the communication efficiency and the sales performance are effectively improved.
Of course, it will be understood by those skilled in the art that all or part of the processes of the methods of the above embodiments may be implemented by a computer program instructing relevant hardware (such as a processor, a controller, etc.), and the program may be stored in a computer readable storage medium, and when executed, the program may include the processes of the above method embodiments. The storage medium may be a memory, a magnetic disk, an optical disk, etc.
It is to be understood that the invention is not limited to the examples described above, but that modifications and variations may be effected thereto by those of ordinary skill in the art in light of the foregoing description, and that all such modifications and variations are intended to be within the scope of the invention as defined by the appended claims.
Claims (8)
1. A WeChat client behavior feedback method is characterized by comprising the following steps:
after receiving a public number attention instruction input by a user, acquiring basic information of the user and randomly distributing follow-up seats for the user;
then randomly distributing follow-up seats for the users, and in the subsequent communication process, each client continuously communicates and follows up by the appointed follow-up seat;
acquiring historical operation records of all users in the public number at preset intervals, and analyzing the behavior intention of each user according to the historical operation records;
the step of analyzing the behavioral intention of each user according to the historical operation records comprises the following steps:
obtaining the activity of each user according to the time information in the historical operation records;
extracting menu options corresponding to the contact information in each user historical operation record and keyword information corresponding to the input information;
analyzing the behavior intention of each user according to the liveness, the menu options and the keyword information;
feeding back the basic information and the behavior intention analysis result of each user to a display interface of the corresponding follow-up seat;
the step of feeding back the basic information and the behavior intention analysis result of each user to the display interface of the corresponding follow-up seat comprises the following steps:
according to the behavior intention analysis result of each user, carrying out user category division on the user and setting a category label;
feeding back the basic information of the user under each category label and the behavior intention analysis result thereof to a display interface of the corresponding follow-up seat;
classifying and displaying all users to be followed according to the category labels, and sequencing and displaying potential customers and purchased customers according to the activity;
and performing product statistical analysis according to the collected historical operation records of all users, and providing big data reference in the subsequent product development process.
2. The WeChat client behavior feedback method according to claim 1, wherein the step of obtaining historical operation records of all users in public numbers, and analyzing the behavior intention of each user according to the historical operation records comprises:
detecting and recording contact information and input information of each user in a public number to obtain a historical operation record of each user;
and analyzing the behavior intention of each user according to the historical operation records.
3. The WeChat client behavior feedback method according to claim 1, wherein the step of analyzing the behavior intention of each user according to the liveness, menu option and keyword information comprises:
and analyzing whether each user is a potential customer according to the liveness, and analyzing the required product of each customer according to the menu option and the keyword information.
4. The WeChat client behavior feedback method according to claim 1, wherein the step of performing user category division on each user according to the behavior intention analysis result of the user and setting a category label comprises: and classifying the users into potential customers, non-potential customers, purchased customers and paid customers according to the behavior intention analysis result of each user, and setting corresponding category labels.
5. The WeChat client behavior feedback method of claim 1, wherein the basic information includes user micro-signals and reserved contact information.
6. A wechat client behavior feedback method in accordance with claim 2, wherein the input information includes text information and voice information.
7. A wechat client behavior feedback device, characterized in that the wechat client behavior feedback device comprises a processor, a memory and a communication bus;
the communication bus is used for realizing connection communication between the processor and the memory;
the processor is used for executing the wechat client behavior feedback program in the memory to realize the wechat client behavior feedback method according to any one of claims 1 to 6.
8. A computer-readable storage medium, storing one or more programs, which are executable by one or more processors, to implement the method of wechat client behavior feedback of any of claims 1-6.
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| CN201710606678.8A CN107491983B (en) | 2017-07-24 | 2017-07-24 | WeChat client behavior feedback method, equipment and storage medium |
| PCT/CN2018/083774 WO2019019714A1 (en) | 2017-07-24 | 2018-04-19 | Wechat client behavior feedback method, apparatus and storage medium |
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| CN107491983B (en) * | 2017-07-24 | 2020-08-14 | 平安科技（深圳）有限公司 | WeChat client behavior feedback method, equipment and storage medium |
| CN108551532A (en) * | 2018-02-28 | 2018-09-18 | 平安科技（深圳）有限公司 | It attends a banquet and recommends method, apparatus, equipment and storage medium |
| CN109033299A (en) * | 2018-07-16 | 2018-12-18 | 深圳市谷熊网络科技有限公司 | It is a kind of by terminal applies to the method, device and equipment of user's recommendation information |
| CN109063134A (en) * | 2018-08-03 | 2018-12-21 | 湖南财经工业职业技术学院 | A kind of method and system of wechat public platform big data analysis |
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| CN109461034A (en) * | 2018-11-15 | 2019-03-12 | 嘉兴意匠堂营销策划有限公司 | Customer Tracking method and device |
| CN109933782B (en) * | 2018-12-03 | 2023-11-28 | 创新先进技术有限公司 | User emotion prediction method and device |
| CN110209316B (en) * | 2019-06-11 | 2021-03-16 | 北京达佳互联信息技术有限公司 | Category label display method, device, terminal and storage medium |
| CN110648046A (en) * | 2019-08-16 | 2020-01-03 | 中国平安财产保险股份有限公司 | Service processing scheduling method and device, computer equipment and storage medium |
| CN112328905A (en) * | 2020-10-30 | 2021-02-05 | 中国平安人寿保险股份有限公司 | Online marketing content pushing method and device, computer equipment and storage medium |
| CN112866089B (en) * | 2021-01-19 | 2023-06-09 | 北京明略软件系统有限公司 | Follow-up recording method and system in instant messaging application |
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| CN114757186B (en) * | 2022-04-25 | 2023-11-14 | 中国电信股份有限公司 | User intention analysis method and device, computer storage medium and electronic equipment |
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