WO2019019714A1 - 一种微信客户行为反馈方法、设备及存储介质 - Google Patents

一种微信客户行为反馈方法、设备及存储介质 Download PDF

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Publication number
WO2019019714A1
WO2019019714A1 PCT/CN2018/083774 CN2018083774W WO2019019714A1 WO 2019019714 A1 WO2019019714 A1 WO 2019019714A1 CN 2018083774 W CN2018083774 W CN 2018083774W WO 2019019714 A1 WO2019019714 A1 WO 2019019714A1
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user
feedback method
behavior
information
wechat
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PCT/CN2018/083774
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English (en)
French (fr)
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蔡灵敏
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平安科技（深圳）有限公司
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G06Q30/0201—Market modelling; Market analysis; Collecting market data
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F16/35—Clustering; Classification
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L51/00—User-to-user messaging in packet-switching networks, transmitted according to store-and-forward or real-time protocols, e.g. e-mail
    • H04L51/21—Monitoring or handling of messages
    • H04L51/212—Monitoring or handling of messages using filtering or selective blocking
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L51/00—User-to-user messaging in packet-switching networks, transmitted according to store-and-forward or real-time protocols, e.g. e-mail
    • H04L51/52—User-to-user messaging in packet-switching networks, transmitted according to store-and-forward or real-time protocols, e.g. e-mail for supporting social networking services

Definitions

  • the present invention relates to the field of mobile internet technologies, and in particular, to a WeChat customer behavior feedback method, device, and storage medium.
  • the object of the present invention is to provide a WeChat customer behavior feedback method, device and storage medium, which solves the problem that the current WeChat public account can not know the user's operation behavior and thus affect the salesperson's active contact potential. Users, causing inefficient communication problems.
  • a WeChat customer behavior feedback method includes the following steps:
  • the basic information of each user and the behavior intention analysis result are fed back to the display interface of the corresponding follow-up agent.
  • the step of acquiring historical operation records of all users in a public number, and analyzing each user's behavior intention according to the historical operation record includes:
  • Each user's behavioral intent is analyzed based on the historical operational record.
  • the step of analyzing each user's behavior intention according to the historical operation record includes:
  • the activity level of each user is obtained according to the time information in the historical operation record;
  • Each user's behavioral intent is analyzed based on the activity, menu options, and keyword information.
  • the step of analyzing each user's behavior intention according to the activity, menu options, and keyword information includes:
  • Each user is analyzed as a potential customer according to the activity level, and each customer's demand product is analyzed according to the menu option and keyword information.
  • the step of feeding back the basic information of each user and the behavior intention analysis result to the display interface of the corresponding follow-up agent includes:
  • the basic information of the user under each category label and the behavior intention analysis result thereof are fed back to the display interface of the corresponding follow-up agent.
  • the step of performing user category division according to each user's behavior intention analysis result and setting a category label includes:
  • the user is divided into potential customers, non-potential customers, purchased customers, and customers who have cancelled the customer based on the behavioral intent analysis results of each user, and sets the corresponding category labels.
  • the basic information includes a user micro signal and reserved contact information.
  • the input information includes text information and voice information.
  • a WeChat customer behavior feedback device comprising a processor, a memory and a communication bus;
  • the communication bus is used to implement connection communication between a processor and a memory
  • the processor is configured to execute a WeChat customer behavior feedback program in the memory to implement a WeChat customer behavior feedback method as described above
  • a computer readable storage medium wherein the computer readable storage medium stores one or more programs, the one or more programs being executable by one or more processors to implement WeChat customer behavior feedback method.
  • the WeChat customer behavior feedback method obtains the basic information of the user and receives the basic information of the user after receiving the public number attention instruction input by the user. Randomly assign follow-up agents; then obtain historical operation records of all users in the public number, analyze each user's behavior intention according to the historical operation record; then feed back the basic information and behavior intention analysis results of each user to the corresponding Enter the display interface of the agent. By obtaining the historical operation record of the user in the public number, and analyzing the behavior intention, the feedback analysis result is sent to the follow-up agent, so that the follow-up agent can actively contact the user according to different user behaviors, thereby effectively improving communication efficiency. And sales performance.
  • FIG. 1 is a flowchart of a WeChat customer behavior feedback method provided by the present invention.
  • FIG. 2 is a flowchart of step S20 in the WeChat customer behavior feedback method provided by the present invention.
  • FIG. 3 is a flowchart of step S22 in the WeChat customer behavior feedback method provided by the present invention.
  • FIG. 4 is a flowchart of step S30 in the WeChat customer behavior feedback method provided by the present invention.
  • FIG. 5 is a schematic diagram of an operating environment of a preferred embodiment of a WeChat customer behavior feedback program according to the present invention.
  • FIG. 6 is a functional block diagram of a system for installing a WeChat customer behavior feedback program according to a preferred embodiment of the present invention.
  • the present invention aims to provide a WeChat customer behavior feedback method, device and storage medium, and obtain a history operation record of the user in the public number. And after analyzing the behavior intentions, the feedback analysis results are sent to the follow-up agents, so that the follow-up agents can actively contact the users according to different user behaviors, effectively improving communication efficiency and sales performance.
  • the WeChat customer behavior feedback method provided by the present invention includes the following steps:
  • the background automatically acquires the basic information of the user, for example, the user searches for the public car number of the safe car through the “sweep” function or the search function, and clicks the attention button.
  • the WeChat public account automatically obtains the user's basic information, including the user's micro-signal and reserved contact information, such as phone, email, QQ number, etc., and then randomly assigns the follow-up agent to the user.
  • Each customer is continuously followed up by a designated follow-up agent to avoid interruptions and unsmooth communication caused by frequent replacement of agents.
  • FIG. 2 is a flowchart of step S20 in the WeChat customer behavior feedback method provided by the present invention.
  • the step S20 includes:
  • the historical operation record is obtained by detecting and recording the contact information and the output information of the user in the public number, wherein the input information includes text information and voice information, for example, the user is paying attention to the public number.
  • the corresponding sub-menu obtains the corresponding information, or when there is no information required by the user in the sub-menu, the user may directly input the voice information or the text information to try to obtain the information required by the user, so in the embodiment, the contact information is detected and recorded.
  • the input information is obtained from each user's historical operation record, and then each user's behavior intention is analyzed based on the historical operation record.
  • FIG. 3 is a flowchart of step S22 in the WeChat customer behavior feedback method provided by the present invention.
  • the step S22 includes:
  • S203 Analyze the behavior intention of each user according to the activity level, menu options, and keyword information.
  • the activity level of each user may be obtained according to the time information therein, for example, the operation of the user in the public number within a preset time period (for example, one day) may be obtained according to the time information.
  • the keyword information in the analysis analyzes each user's behavior intention according to the activity, menu options, and keyword information.
  • each user is analyzed as a potential customer according to the activity level, and each customer's demand product is analyzed according to the menu option and the keyword information.
  • the activity level of the user can be judged according to the operation time of the user, and whether the user is a potential customer according to the activity level. For example, if the activity level is greater than the preset value, the user is determined to be a potential customer, indicating that the user has been paying attention to the public number, otherwise the judgment is non- Potential customers.
  • the contact information input by the user in each click of the public number corresponds to the menu option in the public number, combined with the user's text and voice information, these operation records represent the user's direction of interest in the content of the public number, For example, in the public number of Ping An Auto Insurance, there are three menus of welfare, auto insurance and customer service. Each sub-menu is divided into several sub-menus. If a user clicks on the auto-rising menu and the sub-menu under it, it indicates that the user is right. The content of auto insurance is of interest. For example, the auto insurance price option is not set in the public number. A user inputs the text information “auto insurance price and package details” through the keyboard.
  • the keywords “auto insurance” and “price” in the input information are extracted. It indicates that the user wants to know the price of auto insurance, and combines the menu options and keyword information to analyze the customer's demand information, and provides propensity suggestions for the follow-up agent and user communication, improving communication efficiency and sales success rate.
  • FIG. 4 is a flowchart of step S30 in the WeChat customer behavior feedback method provided by the present invention.
  • the step S30 includes:
  • step S31 the user may be divided into potential customers, non-potential customers, purchased customers, and customers who have canceled the attention, and set corresponding categories.
  • the label, and then the basic information of the user under each category label and the behavior intention analysis result thereof are fed back to the display interface of the corresponding follow-up agent.
  • the follow-up agent can focus on developing potential customers and maintaining the purchased customers, actively communicating with them in an interesting direction to improve communication efficiency and
  • the communication effect preferably, can be sorted according to the activity level for the potential customers and the purchased customers. For example, the higher the activity, the higher the ranking, the follow-up agent can be more easily noticed, and of course, according to the follow-up agent.
  • the sorting instruction sorts the users, which is more in line with the habits and requirements of the follow-up agents; while keeping the attention to non-potential customers, the frequency of active communication can be appropriately reduced to avoid the non-potential customers generating rebellious psychology and canceling the attention; The customer does not bother to avoid receiving user complaints and lowering the company's evaluation, thus providing a user group classification reference for follow-up agents, which improves the efficiency of follow-up agents.
  • product statistical analysis can be performed according to the collected historical operation records of all users, and a big data reference is provided in the subsequent product development process to develop consumers more interested.
  • the product further provides sales performance.
  • the present invention further provides a WeChat customer behavior feedback device.
  • the WeChat customer behavior feedback device specifically needs to directly interact with the user's mobile terminal and the agent terminal, for example, receiving an operation instruction input by the user mobile terminal, feeding it back to the agent terminal, and transmitting the contact information output by the agent terminal to the user's movement. Terminals, etc., to achieve communication between the user and the follow-up agent.
  • the WeChat customer behavior feedback device may be a computing device such as a desktop computer, a notebook, a palmtop computer, or a server.
  • the WeChat customer behavior feedback device includes, but is not limited to, processor 10, memory 20, and display 30.
  • Figure 5 shows only some of the components of the WeChat customer behavior feedback device, but it should be understood that not all illustrated components may be implemented, and more or fewer components may be implemented instead.
  • the memory 20, in some embodiments, may be an internal storage unit of the WeChat customer behavior feedback device, such as a hard disk or memory of the WeChat customer behavior feedback device.
  • the memory 20 may also be an external storage device of the WeChat customer behavior feedback device in other embodiments, such as a plug-in hard disk equipped on the WeChat customer behavior feedback device, and a smart memory card (Smart Media Card, SMC), Secure Digital (SD) card, flash card (Flash) Card) and so on.
  • the memory 20 may also include both an internal storage unit of the WeChat customer behavior feedback device and an external storage device.
  • the memory 20 is configured to store application software and various types of data installed on the WeChat customer behavior feedback device, such as the program code of the WeChat customer behavior feedback device.
  • the memory 20 can also be used to temporarily store data that has been output or is about to be output.
  • the WeChat customer behavior feedback program 40 is stored on the memory 20, and the WeChat customer behavior feedback program 40 can be executed by the processor 10 to implement the WeChat customer behavior feedback method of the embodiments of the present application.
  • the processor 10 may be a central processing unit (Central Processing Unit) in some embodiments.
  • the display 30 may be an LED display, a liquid crystal display, a touch liquid crystal display, and an OLED (Organic) in some embodiments. Light-Emitting Diode, organic light emitting diodes), etc.
  • the display 30 is for displaying information processed in the WeChat customer behavior feedback device and a user interface for displaying visualizations, such as an assignment information interface, an authentication report interface, and the like.
  • the components 10-30 of the WeChat customer behavior feedback device communicate with one another via a system bus.
  • the following steps are implemented when the processor 10 executes the WeChat customer behavior feedback program 40 in the memory 20:
  • the basic information of each user and the behavior intention analysis result are fed back to the display interface of the corresponding follow-up agent.
  • the step of acquiring historical operation records of all users in the public number, and analyzing each user's behavior intention according to the historical operation record includes:
  • Each user's behavioral intent is analyzed based on the historical operational record.
  • the step of analyzing each user's behavioral intention according to the historical operation record includes:
  • the activity level of each user is obtained according to the time information in the historical operation record;
  • Each user's behavioral intent is analyzed based on the activity, menu options, and keyword information.
  • the step of analyzing each user's behavioral intent according to the activity, menu options, and keyword information includes:
  • Each user is analyzed as a potential customer according to the activity level, and each customer's demand product is analyzed according to the menu option and keyword information.
  • the step of feeding back the basic information of each user and the behavior intention analysis result to the display interface corresponding to the follow-up agent includes:
  • the basic information of the user under each category label and the behavior intention analysis result thereof are fed back to the display interface of the corresponding follow-up agent.
  • the step of performing user category division according to each user's behavior intention analysis result and setting a category label includes:
  • the user is divided into potential customers, non-potential customers, purchased customers, and customers who have cancelled the customer based on the behavioral intent analysis results of each user, and sets the corresponding category labels.
  • the basic information includes a user micro signal and reserved contact information.
  • the input information includes text information and voice information.
  • FIG. 6 is a functional block diagram of a system for installing a WeChat customer behavior feedback program according to a preferred embodiment of the present invention.
  • the system in which the WeChat customer behavior feedback program is installed may be divided into one or more modules, the one or more modules being stored in the memory 20 and being processed by one or more processors (this Embodiments are performed by the processor 10) to complete the present invention.
  • the system in which the WeChat customer behavior feedback program is installed may be divided into a receiving module 21, an acquisition analyzing module 22, and a feedback module 23.
  • module refers to a series of computer program instruction segments capable of performing a specific function, and is more suitable than the program to describe the execution process of the WeChat customer behavior feedback program in the WeChat customer behavior feedback device. The following description will specifically describe the functions of the modules 21-24.
  • the receiving module 21 is configured to: after receiving the public number attention instruction input by the user, obtain basic information of the user and randomly assign a follow-up agent to the seat;
  • the obtaining analysis module 22 is configured to obtain historical operation records of all users in the public number, and analyze each user's behavior intention according to the historical operation record;
  • the feedback module 23 is configured to feed back the basic information of each user and the behavior intention analysis result to the display interface of the corresponding follow-up agent.
  • the WeChat customer behavior feedback method obtains basic information of the user and receives basic information of the user after receiving the public number attention instruction input by the user. Randomly assign follow-up agents; then obtain historical operation records of all users in the public number, analyze each user's behavior intention according to the historical operation record; then feed back the basic information and behavior intention analysis results of each user to the corresponding Enter the display interface of the agent.
  • the feedback analysis result is sent to the follow-up agent, so that the follow-up agent can actively contact the user according to different user behaviors, thereby effectively improving communication efficiency. And sales performance.
  • a computer program to instruct related hardware (such as a processor, a controller, etc.), and the program can be stored in one.
  • the program when executed, may include the processes of the various method embodiments as described above.
  • the storage medium described therein may be a memory, a magnetic disk, an optical disk, or the like.

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Abstract

本发明公开了一种微信客户行为反馈方法、设备及存储介质，其中，所述微信客户行为反馈方法通过接收到用户输入的公众号关注指令后，获取用户的基本信息并为其随机分配跟进坐席；之后获取所有用户在公众号内的历史操作记录，根据所述历史操作记录分析每个用户的行为意图；之后将每个用户的基本信息和行为意图分析结果反馈至对应跟进坐席的显示界面。通过获取用户在公众号内的历史操作记录，并对其进行行为意图分析后反馈分析结果给跟进坐席，使得跟进坐席可以根据不同的用户行为有针对性的主动联系用户，有效提高沟通效率及销售业绩。

Description

一种微信客户行为反馈方法、设备及存储介质
本申请要求于2017年7月24日提交中国专利局、申请号为201710606678.8、发明名称为“微信客户行为反馈方法、设备及存储介质”的中国专利申请的优先权，其全部内容通过引用结合在申请中。
技术领域
本发明涉及移动互联网技术领域，具体涉及一种微信客户行为反馈方法、设备及存储介质。
背景技术
目前，随着移动通信技术的不断发展，移动终端已成为人们生活不可或缺的工具，在众多移动终端应用中，微信则已成为最为广泛使用的社交、娱乐和生活应用之一，面对如此庞大且不断增长的用户群，很多公司均会采取建立公众号的方式以进行市场推广并吸引客流。
但是在目前微信公众号的沟通推广方式中，销售人员与用户之间的联系仅限于用户主动联系销售人员，即用户关注了公众号后，由于无法获知用户的操作，销售人员只能被动的等待用户进行联系，无法主动针对潜在用户进行主动联系，导致沟通低效，影响销售业绩的提升。
因此，现有技术还有待于改进和发展。
发明内容
鉴于上述现有技术的不足之处，本发明的目的在于提供一种微信客户行为反馈方法、设备及存储介质，解决了目前微信公众号由于无法得知用户的操作行为从而影响销售人员主动联系潜在用户，导致沟通低效的问题。
为了达到上述目的，本发明采取了以下技术方案：
一种微信客户行为反馈方法，其包括如下步骤：
接收到用户输入的公众号关注指令后，获取用户的基本信息并为其随机分配跟进坐席；
获取所有用户在公众号内的历史操作记录，根据所述历史操作记录分析每个用户的行为意图；
将每个用户的基本信息和行为意图分析结果反馈至对应跟进坐席的显示界面。
所述的微信客户行为反馈方法中，所述获取所有用户在公众号内的历史操作记录，根据所述历史操作记录分析每个用户的行为意图的步骤包括：
检测并记录每个用户在公众号内的触点信息以及输入信息，得到每个用户的历史操作记录；
根据所述历史操作记录分析每个用户的行为意图。
所述的微信客户行为反馈方法中，所述根据所述历史操作记录分析每个用户的行为意图的步骤包括：
根据历史操作记录中的时间信息得到每个用户的活跃度；
提取每个用户历史操作记录中触点信息对应的菜单选项以及输入信息对应的关键词信息；
根据所述活跃度、菜单选项和关键词信息分析每个用户的行为意图。
所述的微信客户行为反馈方法中，所述根据所述活跃度、菜单选项和关键词信息分析每个用户的行为意图的步骤包括：
根据所述活跃度分析每个用户是否为潜在客户，并根据所述菜单选项和关键词信息分析每个客户的需求产品。
所述的微信客户行为反馈方法中，所述将每个用户的基本信息和行为意图分析结果反馈至对应跟进坐席的显示界面的步骤包括：
根据每个用户的行为意图分析结果对其进行用户类别划分，并设置类别标签；
将各个类别标签下的用户的基本信息及其行为意图分析结果反馈至对应跟进坐席的显示界面。
所述的微信客户行为反馈方法中，所述根据每个用户的行为意图分析结果对其进行用户类别划分，并设置类别标签的步骤包括：
根据每个用户的行为意图分析结果将用户划分为潜在客户、非潜在客户、已购买客户和已取消关注客户，并设置相应的类别标签。
所述的微信客户行为反馈方法中，所述基本信息包括用户微信号和预留联系信息。
所述的微信客户行为反馈方法中，所述输入信息包括文字信息和语音信息。
一种微信客户行为反馈设备，其包括处理器、存储器和通信总线；
所述通信总线用于实现处理器和存储器之间的连接通信；
所述处理器用于执行所述存储器中的微信客户行为反馈程序，以实现如上所述的微信客户行为反馈方法
一种计算机可读存储介质，其特征在于，所述计算机可读存储介质存储有一个或者多个程序，所述一个或者多个程序可被一个或者多个处理器执行，以实现如上所述的微信客户行为反馈方法。
相较于现有技术，本发明提供的微信客户行为反馈方法、设备及存储介质中，所述微信客户行为反馈方法通过接收到用户输入的公众号关注指令后，获取用户的基本信息并为其随机分配跟进坐席；之后获取所有用户在公众号内的历史操作记录，根据所述历史操作记录分析每个用户的行为意图；之后将每个用户的基本信息和行为意图分析结果反馈至对应跟进坐席的显示界面。通过获取用户在公众号内的历史操作记录，并对其进行行为意图分析后反馈分析结果给跟进坐席，使得跟进坐席可以根据不同的用户行为有针对性的主动联系用户，有效提高沟通效率及销售业绩。
附图说明
图1为本发明提供的微信客户行为反馈方法的流程图。
图2为本发明提供的微信客户行为反馈方法中步骤S20的流程图。
图3为本发明提供的微信客户行为反馈方法中步骤S22的流程图。
图4为本发明提供的微信客户行为反馈方法中步骤S30的流程图。
图5为本发明微信客户行为反馈程序的较佳实施例的运行环境示意图。
图6为本发明安装微信客户行为反馈程序的系统较佳实施例的功能模块图。
具体实施方式
鉴于现有技术中微信公众号内客户沟通缺乏主动性和针对性等缺点，本发明的目的在于提供一种微信客户行为反馈方法、设备及存储介质，通过获取用户在公众号内的历史操作记录，并对其进行行为意图分析后反馈分析结果给跟进坐席，使得跟进坐席可以根据不同的用户行为有针对性的主动联系用户，有效提高沟通效率及销售业绩。
为使本发明的目的、技术方案及效果更加清楚、明确，以下参照附图并举实施例对本发明进一步详细说明。应当理解，此处所描述的具体实施例仅用以解释本发明，并不用于限定本发明。
请参阅图1，本发明提供的微信客户行为反馈方法包括以下步骤：
S10、接收到用户输入的公众号关注指令后，获取用户的基本信息并为其随机分配跟进坐席。
本实施例中，在用户输入了公众号的关注指令后，后台自动获取用户的基本信息，例如用户通过“扫一扫”功能或搜索功能搜索到平安车险公众号，并点击了关注按钮，此时微信公众号后台自动获取用户的基本信息，包括用户的微信号以及预留的联系方式，例如电话、邮箱以及QQ号等等，之后为用户随机分配跟进坐席，在后续的沟通过程中，每个客户均由指定的跟进坐席持续进行沟通跟进，以避免出现频繁更换坐席人员导致沟通中断和不顺畅的情况。
S20、获取所有用户在公众号内的历史操作记录，根据所述历史操作记录分析每个用户的行为意图。
在用户关注了微信公众号后，获取用户在公众号内的历史操作记录，具体可每隔预设时间进行获取，以更新用户的历史操作记录，并根据所述历史操作记录对用户的行为意图进行分析，从而分析得出不同用户的行为倾向，为跟进坐席更好的服务客户提供可靠的数据基础。请参阅图2，其为本发明提供的微信客户行为反馈方法中步骤S20的流程图。
如图2所示，所述步骤S20包括：
S21、检测并记录每个用户在公众号内的触点信息以及输入信息，得到每个用户的历史操作记录；
S22、根据所述历史操作记录分析每个用户的行为意图。
即在获取用户的历史操作记录时，是通过检测并记录用户在公众号内的触点信息以及输出信息得到其历史操作记录，其中输入信息包括文字信息和语音信息，例如用户在关注了公众号后，会点击公众号内各种菜单选项以获取产品信息，如平安车险公众号内，设置有福利、车险和客服三大菜单，每一菜单选项下分设多个子菜单，用户可根据自身需要点击对应的子菜单获取相应信息，或者当子菜单中没有用户所需信息时，用户可能直接输入语音信息或文字信息试图获取其所需的信息，因此本实施例中通过检测并记录触点信息和输入信息得到每个用户的历史操作记录，进而根据历史操作记录来分析每个用户的行为意图。请参阅图3，其为本发明提供的微信客户行为反馈方法中步骤S22的流程图。
如图3所示，所述步骤S22包括：
S201、根据历史操作记录中的时间信息得到每个用户的活跃度；
S202、提取每个用户历史操作记录中触点信息对应的菜单选项以及输入信息对应的关键词信息；
S203、根据所述活跃度、菜单选项和关键词信息分析每个用户的行为意图。
具体实施时，获取了用户的历史操作记录后，可根据其中的时间信息得到每个用户的活跃度，例如可根据时间信息得到用户在预设时间段内（例如一天）在公众号内的操作次数，以确定操作频率，或者根据公众号文章的推送时间以及用户点开文章的时间之差，确定用户是否在关注该公众号，之后提取历史操作记录中触点信息对应的菜单选项以及输入信息中的关键词信息，根据所述活跃度、菜单选项和关键词信息分析每个用户的行为意图。
具体来说，步骤S203中，在分析用户行为意图时，根据所述活跃度分析每个用户是否为潜在客户，并根据所述菜单选项和关键词信息分析每个客户的需求产品。如上所述，可根据用户的操作时间判断其活跃度，根据其活跃度分析用户是否为潜在客户，例如活跃度大于预设值则判断为潜在客户，表明用户一直关注公众号，否则判断为非潜在客户。
同时，用户在公众号中的每一次点击输入的触点信息均对应了公众号内的菜单选项，结合用户的文字和语音信息，这些操作记录代表了用户对公众号中内容的感兴趣方向，例如平安车险公众号内，设置有福利、车险和客服三大菜单，每一菜单选项下分设多个子菜单，若某用户操作记录中多次点击车险菜单及其下设的子菜单则表明用户对车险的内容感兴趣，再例如公众号中没有设置车险价格选项，某用户通过键盘输入文字信息“车险价格及套餐明细”，此时提取出输入信息中的关键词“车险”、“价格”，表明用户希望了解车险的价格，从而结合菜单选项和关键词信息分析得出客户的需求信息，为后续跟进坐席与用户之间的沟通提供倾向性建议，提高沟通效率和销售成功率。
S30、将每个用户的基本信息和行为意图分析结果反馈至对应跟进坐席的显示界面。
本实施例中，对用户的历史操作记录进行分析之后，将每个用户的基本信息和行为意图分析结果反馈至对应跟进坐席的显示界面，使跟进坐席可实时了解自己需跟进用户的状态、购买意愿以及意向产品等等信息，以帮助跟进坐席提高销售业绩。请参阅图4，其为本发明提供的微信客户行为反馈方法中步骤S30的流程图。
如图4所示，所述步骤S30包括：
S31、根据每个用户的行为意图分析结果对其进行用户类别划分，并设置类别标签；
S32、将各个类别标签下的用户的基本信息及其行为意图分析结果反馈至对应跟进坐席的显示界面。
在得到用户的行为意图分析结果后，根据该结果对用户进行类别划分，具体步骤S31中，可将用户划分为潜在客户、非潜在客户、已购买客户和已取消关注客户，并设置相应的类别标签，之后将各个类别标签下的用户的基本信息及其行为意图分析结果反馈至对应跟进坐席的显示界面。
即在跟进坐席的显示界面，可将所有待跟进用户按其类别标签进行分类显示，跟进坐席可重点开发潜在客户并维护已购买客户，主动与其沟通感兴趣的方向从而提高沟通效率和沟通效果，优选地，对于潜在客户和已购买客户还可按照活跃度排序显示，例如活跃度越高的排序越靠前，跟进坐席可更容易的关注到，当然也可根据跟进坐席的排序指令对用户进行排序，更加符合跟进坐席自身习惯和要求；而对于非潜在客户则保持关注，可适当降低主动沟通的频率，以避免非潜在客户产生逆反心理从而取消关注；针对已取消关注客户则不进行打扰，以免收到用户投诉降低公司评价，从而为跟进坐席提供了用户群分类参考，提高了跟进坐席的工作效率。
优选地，本发明提供的微信客户行为反馈方法中，还可根据搜集到的所有用户的历史操作记录进行产品统计分析，在后续产品开发过程中提供大数据参考，以开发出消费者更感兴趣的产品，进一步提供销售业绩。
如图5所示，基于上述微信客户行为反馈方法，本发明还相应提供了一种微信客户行为反馈设备。所述微信客户行为反馈设备具体需与用户的移动终端和坐席终端直接进行交互，例如接收用户移动终端输入的操作指令将其反馈至坐席终端，并将坐席终端输出的联系信息发送至用户的移动终端等，以实现用户与跟进坐席之间的沟通。
所述微信客户行为反馈设备可以是桌上型计算机、笔记本、掌上电脑及服务器等计算设备。该微信客户行为反馈设备包括，但不仅限于，处理器10、存储器20、及显示器30。图5仅示出了微信客户行为反馈设备的部分组件，但是应理解的是，并不要求实施所有示出的组件，可以替代的实施更多或者更少的组件。
所述存储器20在一些实施例中可以是所述微信客户行为反馈设备的内部存储单元，例如该微信客户行为反馈设备的硬盘或内存。所述存储器20在另一些实施例中也可以是所述微信客户行为反馈设备的外部存储设备，例如所述微信客户行为反馈设备上配备的插接式硬盘，智能存储卡（Smart Media Card, SMC），安全数字（Secure Digital, SD）卡，闪存卡（Flash Card）等。进一步地，所述存储器20还可以既包括所述微信客户行为反馈设备的内部存储单元也包括外部存储设备。所述存储器20用于存储安装于所述微信客户行为反馈设备的应用软件及各类数据，例如所述安装微信客户行为反馈设备的程序代码等。所述存储器20还可以用于暂时地存储已经输出或者将要输出的数据。在一实施例中，存储器20上存储有微信客户行为反馈程序40，该微信客户行为反馈程序40可被处理器10所执行，从而实现本申请各实施例的微信客户行为反馈方法。
所述处理器10在一些实施例中可以是一中央处理器（Central Processing Unit, CPU），微处理器或其他数据处理芯片，用于运行所述存储器20中存储的程序代码或处理数据，例如执行所述权限认证方法等。
所述显示器30在一些实施例中可以是LED显示器、液晶显示器、触控式液晶显示器以及OLED（Organic Light-Emitting Diode，有机发光二极管）触摸器等。所述显示器30用于显示在所述微信客户行为反馈设备中处理的信息以及用于显示可视化的用户界面，例如指派信息界面、认证报告界面等。所述微信客户行为反馈设备的部件10-30通过系统总线相互通信。
在一实施例中，当处理器10执行所述存储器20中微信客户行为反馈程序40时实现以下步骤：
接收到用户输入的公众号关注指令后，获取用户的基本信息并为其随机分配跟进坐席；
获取所有用户在公众号内的历史操作记录，根据所述历史操作记录分析每个用户的行为意图；
将每个用户的基本信息和行为意图分析结果反馈至对应跟进坐席的显示界面。
进一步的，在所述微信客户行为反馈设备中，所述获取所有用户在公众号内的历史操作记录，根据所述历史操作记录分析每个用户的行为意图的步骤包括：
检测并记录每个用户在公众号内的触点信息以及输入信息，得到每个用户的历史操作记录；
根据所述历史操作记录分析每个用户的行为意图。
所述根据所述历史操作记录分析每个用户的行为意图的步骤包括：
根据历史操作记录中的时间信息得到每个用户的活跃度；
提取每个用户历史操作记录中触点信息对应的菜单选项以及输入信息对应的关键词信息；
根据所述活跃度、菜单选项和关键词信息分析每个用户的行为意图。
所述根据所述活跃度、菜单选项和关键词信息分析每个用户的行为意图的步骤包括：
根据所述活跃度分析每个用户是否为潜在客户，并根据所述菜单选项和关键词信息分析每个客户的需求产品。
所述将每个用户的基本信息和行为意图分析结果反馈至对应跟进坐席的显示界面的步骤包括：
根据每个用户的行为意图分析结果对其进行用户类别划分，并设置类别标签；
将各个类别标签下的用户的基本信息及其行为意图分析结果反馈至对应跟进坐席的显示界面。
所述根据每个用户的行为意图分析结果对其进行用户类别划分，并设置类别标签的步骤包括：
根据每个用户的行为意图分析结果将用户划分为潜在客户、非潜在客户、已购买客户和已取消关注客户，并设置相应的类别标签。
所述基本信息包括用户微信号和预留联系信息。
所述输入信息包括文字信息和语音信息。
请参阅图6，其为本发明安装微信客户行为反馈程序的系统较佳实施例的功能模块图。在本实施例中，安装微信客户行为反馈程序的系统可以被分割成一个或多个模块，所述一个或者多个模块被存储于所述存储器20中，并由一个或多个处理器（本实施例为所述处理器10）所执行，以完成本发明。例如，在图6中，安装微信客户行为反馈程序的系统可以被分割成接收模块21、获取分析模块22和反馈模块23。本发明所称的模块是指能够完成特定功能的一系列计算机程序指令段，比程序更适合于描述所述微信客户行为反馈程序在所述微信客户行为反馈设备中的执行过程。以下描述将具体介绍所述模块21-24的功能。
接收模块21，用于接收到用户输入的公众号关注指令后，获取用户的基本信息并为其随机分配跟进坐席；
获取分析模块22，用于获取所有用户在公众号内的历史操作记录，根据所述历史操作记录分析每个用户的行为意图；
反馈模块23，用于将每个用户的基本信息和行为意图分析结果反馈至对应跟进坐席的显示界面。
综上所述，本发明提供的微信客户行为反馈方法、设备、系统及存储介质中，所述微信客户行为反馈方法通过接收到用户输入的公众号关注指令后，获取用户的基本信息并为其随机分配跟进坐席；之后获取所有用户在公众号内的历史操作记录，根据所述历史操作记录分析每个用户的行为意图；之后将每个用户的基本信息和行为意图分析结果反馈至对应跟进坐席的显示界面。通过获取用户在公众号内的历史操作记录，并对其进行行为意图分析后反馈分析结果给跟进坐席，使得跟进坐席可以根据不同的用户行为有针对性的主动联系用户，有效提高沟通效率及销售业绩。
当然，本领域普通技术人员可以理解实现上述实施例方法中的全部或部分流程，是可以通过计算机程序来指令相关硬件（如处理器，控制器等）来完成，所述的程序可存储于一计算机可读取的存储介质中，该程序在执行时可包括如上述各方法实施例的流程。其中所述的存储介质可为存储器、磁碟、光盘等。
应当理解的是，本发明的应用不限于上述的举例，对本领域普通技术人员来说，可以根据上述说明加以改进或变换，所有这些改进和变换都应属于本发明所附权利要求的保护范围。

Claims (20)

  1. 一种微信客户行为反馈方法，其特征在于，包括如下步骤：
    接收到用户输入的公众号关注指令后，获取用户的基本信息并为其随机分配跟进坐席；
    获取所有用户在公众号内的历史操作记录，根据所述历史操作记录分析每个用户的行为意图；
    将每个用户的基本信息和行为意图分析结果反馈至对应跟进坐席的显示界面。
  2. 根据权利要求1所述的微信客户行为反馈方法，其特征在于，所述获取所有用户在公众号内的历史操作记录，根据所述历史操作记录分析每个用户的行为意图的步骤包括：
    检测并记录每个用户在公众号内的触点信息以及输入信息，得到每个用户的历史操作记录；
    根据所述历史操作记录分析每个用户的行为意图。
  3. 根据权利要求2所述的微信客户行为反馈方法，其特征在于，所述将每个用户的基本信息和行为意图分析结果反馈至对应跟进坐席的显示界面的步骤包括：
    根据每个用户的行为意图分析结果对其进行用户类别划分，并设置类别标签；
    将各个类别标签下的用户的基本信息及其行为意图分析结果反馈至对应跟进坐席的显示界面。
  4. 根据权利要求3所述的微信客户行为反馈方法，其特征在于，所述根据每个用户的行为意图分析结果对其进行用户类别划分，并设置类别标签的步骤包括：
    根据每个用户的行为意图分析结果将用户划分为潜在客户、非潜在客户、已购买客户和已取消关注客户，并设置相应的类别标签。
  5. 根据权利要求2所述的微信客户行为反馈方法，其特征在于，所述基本信息包括用户微信号和预留联系信息。
  6. 根据权利要求2所述的微信客户行为反馈方法，其特征在于，所述根据所述历史操作记录分析每个用户的行为意图的步骤包括：
    根据历史操作记录中的时间信息得到每个用户的活跃度；
    提取每个用户历史操作记录中触点信息对应的菜单选项以及输入信息对应的关键词信息；
    根据所述活跃度、菜单选项和关键词信息分析每个用户的行为意图。
  7. 根据权利要求6所述的微信客户行为反馈方法，其特征在于，所述将每个用户的基本信息和行为意图分析结果反馈至对应跟进坐席的显示界面的步骤包括：
    根据每个用户的行为意图分析结果对其进行用户类别划分，并设置类别标签；
    将各个类别标签下的用户的基本信息及其行为意图分析结果反馈至对应跟进坐席的显示界面。
  8. 根据权利要求7所述的微信客户行为反馈方法，其特征在于，所述根据每个用户的行为意图分析结果对其进行用户类别划分，并设置类别标签的步骤包括：
    根据每个用户的行为意图分析结果将用户划分为潜在客户、非潜在客户、已购买客户和已取消关注客户，并设置相应的类别标签。
  9. 根据权利要求6所述的微信客户行为反馈方法，其特征在于，所述基本信息包括用户微信号和预留联系信息。
  10. 根据权利要求6所述的微信客户行为反馈方法，其特征在于，所述根据所述活跃度、菜单选项和关键词信息分析每个用户的行为意图的步骤包括：
    根据所述活跃度分析每个用户是否为潜在客户，并根据所述菜单选项和关键词信息分析每个客户的需求产品。
  11. 根据权利要求10所述的微信客户行为反馈方法，其特征在于，所述将每个用户的基本信息和行为意图分析结果反馈至对应跟进坐席的显示界面的步骤包括：
    根据每个用户的行为意图分析结果对其进行用户类别划分，并设置类别标签；
    将各个类别标签下的用户的基本信息及其行为意图分析结果反馈至对应跟进坐席的显示界面。
  12. 根据权利要求11所述的微信客户行为反馈方法，其特征在于，所述根据每个用户的行为意图分析结果对其进行用户类别划分，并设置类别标签的步骤包括：
    根据每个用户的行为意图分析结果将用户划分为潜在客户、非潜在客户、已购买客户和已取消关注客户，并设置相应的类别标签。
  13. 根据权利要求10所述的微信客户行为反馈方法，其特征在于，所述基本信息包括用户微信号和预留联系信息。
  14. 根据权利要求1所述的微信客户行为反馈方法，其特征在于，所述将每个用户的基本信息和行为意图分析结果反馈至对应跟进坐席的显示界面的步骤包括：
    根据每个用户的行为意图分析结果对其进行用户类别划分，并设置类别标签；
    将各个类别标签下的用户的基本信息及其行为意图分析结果反馈至对应跟进坐席的显示界面。
  15. 根据权利要求14所述的微信客户行为反馈方法，其特征在于，所述基本信息包括用户微信号和预留联系信息。
  16. 根据权利要求14所述的微信客户行为反馈方法，其特征在于，所述根据每个用户的行为意图分析结果对其进行用户类别划分，并设置类别标签的步骤包括：
    根据每个用户的行为意图分析结果将用户划分为潜在客户、非潜在客户、已购买客户和已取消关注客户，并设置相应的类别标签。
  17. 根据权利要求1所述的微信客户行为反馈方法，其特征在于，所述基本信息包括用户微信号和预留联系信息。
  18. 根据权利要求2所述的微信客户行为反馈方法，其特征在于，所述输入信息包括文字信息和语音信息。
  19. 一种微信客户行为反馈设备，其特征在于，所述微信客户行为反馈设备包括处理器、存储器和通信总线；
    所述通信总线用于实现处理器和存储器之间的连接通信；
    所述处理器用于执行所述存储器中的微信客户行为反馈程序，以实现如权利要求1所述的微信客户行为反馈方法。
  20. 一种计算机可读存储介质，其特征在于，所述计算机可读存储介质存储有一个或者多个程序，所述一个或者多个程序可被一个或者多个处理器执行，以实现如权利要求1所述的微信客户行为反馈方法。
PCT/CN2018/083774 2017-07-24 2018-04-19 一种微信客户行为反馈方法、设备及存储介质 WO2019019714A1 (zh)

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