WO2019041522A1 - 电子装置、保险推荐方法、及计算机可读存储介质 - Google Patents
电子装置、保险推荐方法、及计算机可读存储介质 Download PDFInfo
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- WO2019041522A1 WO2019041522A1 PCT/CN2017/108800 CN2017108800W WO2019041522A1 WO 2019041522 A1 WO2019041522 A1 WO 2019041522A1 CN 2017108800 W CN2017108800 W CN 2017108800W WO 2019041522 A1 WO2019041522 A1 WO 2019041522A1
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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
- G06Q30/06—Buying, selling or leasing transactions
- G06Q30/0601—Electronic shopping [e-shopping]
- G06Q30/0631—Item recommendations
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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
- G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
- G06Q40/08—Insurance
Definitions
- the present application relates to the field of sales of security products, and in particular, to an electronic device, an insurance recommendation method, and a computer readable storage medium.
- the present application provides an electronic device, an insurance recommendation method, and a computer readable storage medium, which can contact a customer according to a contact pattern of a customer's preference, improve the customer experience, excavate a potential intention customer, and improve the business personnel. Business efficiency.
- a first aspect of the present application provides an electronic device, where the electronic device includes a memory, a processor, the memory is communicably connected to the processor, and an insurance recommendation program is stored on the memory.
- the insurance recommendation program is executed by the processor to implement the following steps:
- the predetermined first The data source includes customer identification information and customer feedback data on the marketing model
- the customer's access to the marketing call is calculated according to the customer's feedback information on the telemarketing and the call duration exceeds the preset.
- a first probability value of the first time threshold a first probability value of the first time threshold, and calculating, according to the feedback information of the customer on the network marketing, the second probability value that the customer clicks on the network marketing link and browses the network marketing link for more than a preset second time threshold, and compares The first probability value and the second a size of the probability value, if the first probability value is greater than the second probability value, determining that the marketing mode preferred by the customer is telemarketing, and if the first probability value is less than the second probability value, determining the The preferred marketing model for customers is online marketing;
- a second aspect of the present application provides an insurance recommendation method, the method comprising the following steps:
- the customer identification information includes the identity a license number, a mobile phone number, and a passport number
- the predetermined first data source includes customer identification information and feedback data of the customer on the marketing mode
- the customer's access to the marketing call is calculated according to the customer's feedback information on the telemarketing and the call duration exceeds the preset.
- a first probability value of the first time threshold a first probability value of the first time threshold, and calculating, according to the feedback information of the customer on the network marketing, the second probability value that the customer clicks on the network marketing link and browses the network marketing link for more than a preset second time threshold, and compares Determining, by the first probability value and the second probability value, if the first probability value is greater than the second probability value, determining that the customer preferred marketing mode is telemarketing, if the first probability value If the value is less than the second probability value, determining that the marketing mode preferred by the customer is network marketing;
- a third aspect of the present application provides a computer readable storage medium storing an insurance recommendation program, the insurance recommendation program being executable by at least one processor to enable The at least one processor performs the following steps:
- the predetermined first The data source includes customer identification information and customer feedback data on the marketing model
- the customer's access to the marketing call is calculated according to the customer's feedback information on the telemarketing and the call duration exceeds the preset.
- a first probability value of the first time threshold a first probability value of the first time threshold, and calculating, according to the feedback information of the customer on the network marketing, the second probability value that the customer clicks on the network marketing link and browses the network marketing link for more than a preset second time threshold, and compares Determining, by the first probability value and the second probability value, if the first probability value is greater than the second probability value, determining that the customer preferred marketing mode is telemarketing, if the first probability value If the value is less than the second probability value, determining that the marketing mode preferred by the customer is network marketing;
- the electronic device, the insurance recommendation method, and the computer readable storage medium proposed by the present application firstly, after receiving the insurance recommendation request with the customer identification information sent by the front end, And searching, by the predetermined first data source, the feedback data of the customer to the marketing mode corresponding to the customer identification information; and then, if the customer’s feedback data of the marketing mode corresponding to the customer identification information is found, analyzing the customer pair
- the feedback data of the marketing model is used to determine the marketing mode preferred by the customer; and then, the insurance recommendation instruction for the marketing mode of the customer is issued to the front end according to the marketing mode preferred by the customer.
- the customer can be recommended for insurance according to the customer's preferred marketing model, improve the customer's experience, and help to further explore potential intent customers and improve the business efficiency of the business personnel.
- FIG. 1 is a schematic diagram of a hardware architecture of a preferred embodiment of an electronic device of the present application
- FIG. 2 is a schematic diagram of a program module of an insurance recommendation program in an embodiment of the electronic device of the present application
- FIG. 3 is a schematic flow chart showing an implementation of a preferred embodiment of the insurance recommendation method of the present application.
- first, second and the like in the present application are for the purpose of description only, and are not to be construed as indicating or implying their relative importance or implicitly indicating the number of technical features indicated. .
- features defining “first” and “second” may include at least one of the features, either explicitly or implicitly.
- the technical solutions between the various embodiments may be combined with each other, but must be based on the realization of those skilled in the art, and when the combination of the technical solutions is contradictory or impossible to implement, it should be considered that the combination of the technical solutions does not exist. Nor is it within the scope of protection required by this application.
- FIG. 1 it is a schematic diagram of a hardware architecture of a preferred embodiment of the electronic device 2 of the present application.
- the electronic device 2 may include, but is not limited to, the memory 11, the processor 12, and the network interface 13 being communicably connected to each other through a system bus.
- FIG. 2 only shows the electronic device 2 having the components 11-13, but it should be understood that not all illustrated components may be implemented, and more or fewer components may be implemented instead.
- the memory 11 includes at least one type of readable storage medium including a flash memory, a hard disk, a multimedia card, a card type memory (for example, SD or DX memory, etc.), a random access memory (RAM), and a static random access.
- Memory SRAM
- ROM read only memory
- EEPROM electrically erasable programmable read only memory
- PROM programmable read only memory
- magnetic memory magnetic disk, optical disk, and the like.
- the memory 11 may be an internal storage unit of the electronic device 2, such as a hard disk or a memory of the electronic device 2.
- the memory 11 is also It may be an external storage device of the electronic device 2, such as a plug-in hard disk equipped on the electronic device 2, a smart memory card (SMC), a Secure Digital (SD) card, a flash card, or the like.
- the memory 11 can also include both an internal storage unit of the electronic device 2 and an external storage device thereof.
- the memory 11 is generally used to store an operating system installed in the electronic device 2 and various types of application software, such as program codes of the insurance recommendation system 200. Further, the memory 11 can also be used to temporarily store various types of data that have been output or are to be output.
- Processor 12 may be a Central Processing Unit (CPU), controller, microcontroller, microprocessor, or other data processing chip in some embodiments.
- the processor 12 is typically used to control the overall operation of the electronic device 2, such as performing control and processing related to data interaction or communication with the front end 1.
- the processor 12 is configured to run program code or processing data stored in the memory 11, such as the running insurance recommendation system 200 and the like.
- the network interface 13 may include a wireless network interface or a wired network interface, and the network interface 13 is typically used to establish a communication connection between the electronic device 2 and other electronic devices.
- the electronic device 2 may further include a user interface, and the user interface may include a display, an input unit such as a keyboard, and the optional user interface may further include a standard wired interface and a wireless interface.
- the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch sensor, or the like.
- the display may also be appropriately referred to as a display screen or display unit for displaying information processed in the electronic device 2 and a user interface for displaying visualization.
- the insurance recommendation program is stored in the memory 11; when the processor 12 executes the insurance recommendation program stored in the memory 11, the following steps are implemented:
- the predetermined first data source After receiving the insurance recommendation request with the customer identification information sent by the front end, searching for the feedback data of the customer to the marketing mode corresponding to the customer identification information from the predetermined first data source, the predetermined first data source Including customer identification information and customer feedback data on marketing models;
- the customer's access to the marketing call is calculated according to the customer's feedback information on the telemarketing and the call duration exceeds the preset.
- a first probability value of the first time threshold a first probability value of the first time threshold, and calculating, according to the feedback information of the customer on the network marketing, the second probability value that the customer clicks on the network marketing link and browses the network marketing link for more than a preset second time threshold, and compares Determining a size of the first probability value and the second probability value, if the first probability value is greater than the second probability value, determining that the marketing mode preferred by the customer is telemarketing, and determining the customer if the first probability value is less than the second probability value
- the preferred marketing model is online marketing;
- the feedback data of the customer to the telemarketing mode is used as an example to explain the solution of the network marketing mode.
- the predetermined first data source includes customer identification information (eg, ID number, mobile phone number, passport number, etc.) and the customer does not Feedback data with the same marketing model (eg, online marketing model, and/or telemarketing model) (eg, the probability of being willing to connect to the marketing call is greater than 70%, and the probability of each communication being greater than 10 minutes is 50%, and / Or, the probability of clicking the connection when receiving the SMS message or the pushed APP message notification is 60%, and the probability of clicking at night is greater than 50%).
- customer identification information eg, ID number, mobile phone number, passport number, etc.
- the customer does not Feedback data with the same marketing model (eg, online marketing model, and/or telemarketing model) (eg, the probability of being willing to connect to the marketing call is greater than 70%, and the probability of each communication being greater than 10 minutes is 50%, and / Or, the probability of clicking the connection when receiving
- step B if the customer's feedback information on the telemarketing corresponding to the customer identification information is found, and the customer's feedback information on the network marketing corresponding to the customer identification information is not found, according to the The customer's feedback information on the telemarketing calculates a first probability value (eg, 40%) that the customer connects to the marketing call and the call duration exceeds a preset first time threshold (eg, 10 minutes), if the first probability value is greater than the preset a probability threshold (for example, 35%), determining that the customer's preferred marketing mode is telemarketing; or, if the customer's feedback to the network marketing corresponding to the customer identification information is found, and the customer identification is not found.
- the feedback information of the customer corresponding to the telephone marketing according to the information is calculated according to the feedback information of the customer on the network marketing, and the duration of the browsing of the network marketing link by the customer exceeds the preset second time threshold (for example, 8 minutes).
- a second probability value eg, 50 percent
- the insurance recommendation system of the present application can protect customers' products according to the customer's preferred marketing mode, thereby improving the customer experience, excavating potential customers, and improving the business efficiency of the business personnel.
- a predetermined second data source for example, an insurance service database, a banking database, and a public network platform
- Obtaining the first all-round data information of the customer corresponding to the customer identification information eg, ID number, phone number, registered account number, etc.
- customer identity attribute information e.g.
- customer asset status information e.g.
- insurance wealth management information e.g.
- Family information e.g., customer identity attribute information, customer asset status information, insurance wealth management information, Hobbies, and family information
- predetermined matching rules for example, the second omnidirectional data information is the same as the first omnidirectional data information, or the second omnidirectional data information is the same as the first omnidirectional data information
- Probability is greater than 80%
- will be the first comprehensive data information with a predetermined customer base for example, life support needs customer group, health demand customer group, children's education needs customer group, personal pension needs customer group, wealth
- the second comprehensive data information of each customer in the value-added demand customer group is matched to confirm The
- the preset first time threshold, the preset second time threshold, the preset probability threshold, and the like which are involved in the foregoing embodiments, need to be preset, and can be set by the user according to actual conditions.
- the insurance recommendation program may also be divided into one or more modules, one or more modules being stored in the memory 11 and being processed by one or more processors (this embodiment is The processor 12) is executed to complete the application, and a module referred to herein refers to a series of computer program instructions that are capable of performing a particular function.
- FIG. 2 it is a schematic diagram of a program module of an insurance recommendation program in an embodiment of the electronic device of the present application.
- the insurance recommendation program may be divided into a search module 201, an analysis module 202, and a recommendation module 203, wherein
- the functions or operational steps implemented by modules 201-203 are similar to the above, and are not described in detail herein, by way of example, for example:
- the searching module 201 is configured to: after receiving the insurance recommendation request with the customer identification information sent by the front end, search for the feedback data of the customer to the marketing mode corresponding to the customer identification information from the predetermined first data source, where the predetermined The first data source includes customer identification information and customer feedback data on the marketing model;
- the analyzing module 202 is configured to: if the customer's feedback information on the telemarketing corresponding to the customer identification information and the feedback information to the network marketing are found, calculate the customer's access marketing call and the duration of the call according to the customer's feedback information on the telemarketing And exceeding a first probability value of the preset first time threshold, and calculating, according to the feedback information of the customer on the network marketing, the second probability that the customer clicks on the network marketing link and the duration of browsing the network marketing link exceeds a preset second time threshold a value, comparing the size of the first probability value and the second probability value, if the first probability value is greater than the second probability value, determining that the customer preferred marketing mode is telemarketing, if the If the probability value is less than the second probability value, determining that the customer's preferred marketing mode is network marketing;
- the recommendation module 203 is configured to issue an insurance recommendation instruction to the front end for the marketing mode of the customer according to the marketing mode of the customer preference.
- the present application also proposes an insurance recommendation method.
- the insurance recommendation method includes steps S301 to S303.
- Step S301 after receiving the insurance recommendation request with the customer identification information sent by the front end, searching for the feedback data of the customer's marketing mode corresponding to the customer identification information from the predetermined first data source, the predetermined first data.
- the source includes customer identification information and customer feedback data on the marketing model;
- Step S302 if the customer's feedback information about the telephone marketing corresponding to the customer identification information and the feedback information to the network marketing are found, the customer conducts the marketing call according to the customer's feedback information on the telephone marketing, and the call duration exceeds the pre-payment. Setting a first probability value of the first time threshold, and calculating, according to the feedback information of the customer on the network marketing, the second probability value that the customer clicks on the network marketing link and browses the network marketing link for more than a preset second time threshold.
- Step S303 issuing an insurance recommendation instruction for the marketing mode of the customer to the front end according to the marketing mode preferred by the customer.
- the feedback data of the customer to the telemarketing mode is used as an example to explain the solution of the network marketing mode.
- the predetermined first data source includes customer identification information (eg, ID number, mobile phone number, passport number, etc.) and feedback data of the customer on different marketing modes (eg, online marketing mode, and/or telemarketing mode).
- customer identification information eg, ID number, mobile phone number, passport number, etc.
- feedback data of the customer on different marketing modes eg, online marketing mode, and/or telemarketing mode.
- the probability that a willingness to connect to a marketing call is greater than 70%, and the probability of each communication being longer than 10 minutes is 50%, and/or the probability of clicking a connection when receiving a marketing message or a pushed APP message notification is 60. %, and the probability of clicking at night is greater than 50%).
- step B if the customer's feedback information on the telemarketing corresponding to the customer identification information is found, and the customer's feedback information on the network marketing corresponding to the customer identification information is not found, according to the The customer's feedback information on the telemarketing calculates a first probability value (eg, 40%) that the customer connects to the marketing call and the call duration exceeds a preset first time threshold (eg, 10 minutes), if the first probability value is greater than the preset a probability threshold (for example, 35%), determining that the customer's preferred marketing mode is telemarketing; or, if the customer's feedback to the network marketing corresponding to the customer identification information is found, and the customer identification is not found.
- the feedback information of the customer corresponding to the telephone marketing according to the information is calculated according to the feedback information of the customer on the network marketing, and the duration of the browsing of the network marketing link by the customer exceeds the preset second time threshold (for example, 8 minutes).
- a second probability value eg, 50 percent
- the insurance recommendation system of the present application can protect customers' products according to the customer's preferred marketing mode, thereby improving the customer experience, excavating potential customers, and improving the business efficiency of the business personnel.
- a predetermined second data source for example, an insurance service database, a banking database, and a public network platform
- Obtaining the first all-round data information of the customer corresponding to the customer identification information eg, ID number, phone number, registered account number, etc.
- customer identity attribute information e.g.
- customer asset status information e.g.
- insurance wealth management information e.g.
- Family information e.g., customer identity attribute information, customer asset status information, insurance wealth management information, Hobbies, and family information
- predetermined matching rules for example, the second omnidirectional data information is the same as the first omnidirectional data information, or the second omnidirectional data information is the same as the first omnidirectional data information
- Probability is greater than 80%
- will be the first comprehensive data information with a predetermined customer base for example, life support needs customer group, health demand customer group, children's education needs customer group, personal pension needs customer group, wealth
- the second comprehensive data information of each customer in the value-added demand customer group is matched to confirm The
- the insurance recommendation method after receiving the insurance recommendation request with the customer identification information sent by the front end, searching for the feedback data of the customer to the marketing mode corresponding to the customer identification information from the predetermined first data source; If the customer's feedback data corresponding to the customer identification information is found, analyzing the customer's feedback data on the marketing model to determine the marketing mode preferred by the customer; and then, according to the customer's preferred marketing mode to the front end Issue an insurance recommendation instruction for the customer's marketing model.
- the customer can be recommended for insurance according to the customer's preferred marketing model, improve the customer's experience, and help to further explore potential intent customers and improve the business efficiency of the business personnel.
- the embodiment of the present application further provides a computer readable storage medium, where the insurance recommendation program is stored, and the insurance recommendation program is executed by the processor to:
- the predetermined first data source After receiving the insurance recommendation request with the customer identification information sent by the front end, searching for the feedback data of the customer to the marketing mode corresponding to the customer identification information from the predetermined first data source, the predetermined first data source includes the customer Identification information and customer feedback data on marketing models;
- the customer's access to the marketing call is calculated according to the customer's feedback information on the telemarketing and the duration of the call exceeds the preset number.
- a first probability value of a time threshold and calculating a second probability value that the customer clicks on the network marketing link and browses the network marketing link for more than a preset second time threshold according to the customer's feedback information on the network marketing, and compares the first a probability value and a second probability value. If the first probability value is greater than the second probability value, determining that the customer preferred marketing mode is telemarketing, and if the first probability value is less than the second probability value, determining the customer preference Marketing model is network marketing;
- an insurance recommendation instruction for the customer's marketing model is issued to the front end.
- the predetermined first data source After receiving the insurance recommendation request with the customer identification information sent by the front end, searching for the feedback data of the customer to the marketing mode corresponding to the customer identification information from the predetermined first data source, the predetermined first data source includes the customer Identification information and customer feedback data on marketing models;
- the customer is calculated according to the customer's feedback information on the telemarketing a first probability value of the marketing call and the duration of the call exceeding a preset first time threshold. If the first probability value is greater than the preset probability threshold, determining that the preferred marketing mode of the customer is telemarketing; or, if The customer's feedback information on the network marketing corresponding to the customer identification information, and the customer's feedback information on the telephone marketing corresponding to the customer identification information is not found, and the customer clicks on the network marketing according to the customer's feedback information on the network marketing.
- the second probability value of connecting and browsing the network marketing connection exceeds a preset second time threshold, and if the second probability value is greater than the preset probability threshold, determining that the customer preferred marketing mode is network marketing;
- the front end issues insurance push for the customer's marketing model. Recommended instruction.
- the predetermined first data source After receiving the insurance recommendation request with the customer identification information sent by the front end, searching for the feedback data of the customer to the marketing mode corresponding to the customer identification information from the predetermined first data source, the predetermined first data source includes the customer Identification information and customer feedback data on marketing models;
- the customer's access to the marketing call is calculated according to the customer's feedback information on the telemarketing and the duration of the call exceeds the preset number.
- a first probability value of a time threshold and calculating a second probability value that the customer clicks on the network marketing link and browses the network marketing link for more than a preset second time threshold according to the customer's feedback information on the network marketing, and compares the first a probability value and a second probability value. If the first probability value is greater than the second probability value, determining that the customer preferred marketing mode is telemarketing, and if the first probability value is less than the second probability value, determining the customer preference Marketing model is network marketing;
- first Comprehensive data information includes customer identity attribute information, customer asset status information, insurance wealth management information, interest preferences, and family information;
- the front end issues a recommendation instruction for the insurance category and marketing mode of the customer.
- the predetermined first data source After receiving the insurance recommendation request with the customer identification information sent by the front end, searching for the feedback data of the customer to the marketing mode corresponding to the customer identification information from the predetermined first data source, the predetermined first data source includes the customer Identification information and customer feedback data on marketing models;
- the customer is calculated according to the customer's feedback information on the telemarketing a first probability value of the marketing call and the duration of the call exceeding a preset first time threshold. If the first probability value is greater than the preset probability threshold, determining that the preferred marketing mode of the customer is telemarketing; or, if The customer's feedback information on the network marketing corresponding to the customer identification information, and the customer's feedback information on the telephone marketing corresponding to the customer identification information is not found, and the customer clicks on the network marketing according to the customer's feedback information on the network marketing. And a second probability value of linking and browsing the network marketing link exceeds a preset second time threshold, and if the second probability value is greater than the preset probability threshold, determining that the customer preferred marketing mode is network marketing;
- first Comprehensive data information includes customer identity attribute information, customer asset status information, insurance wealth management information, interest preferences, and family information;
- the front end issues a recommendation instruction for the insurance category and marketing mode of the customer.
- the electronic device, the insurance recommendation method, and the computer readable storage medium of the present application firstly receive a first recommendation from the first data source after receiving the insurance recommendation request with the customer identification information sent by the front end.
- Finding feedback data of the customer's marketing mode corresponding to the customer identification information secondly, if the customer's feedback data corresponding to the customer identification information is found, analyzing the customer pair according to the preset marketing mode preference judgment rule
- the feedback model of the marketing model determines the marketing model preferred by the customer; again, the insurance recommendation instruction for the marketing model of the customer is issued to the front end according to the marketing model preferred by the customer. In this way, the customer can be contacted according to the customer's preferred contact method, thereby improving the customer's experience, facilitating further digging out potential intent customers, and improving the business efficiency of the business personnel.
- the foregoing embodiment method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be through hardware, but in many cases, the former is better.
- Implementation Based on such understanding, the technical solution of the present application, which is essential or contributes to the prior art, may be embodied in the form of a software product stored in a storage medium (such as ROM/RAM, disk,
- the optical disc includes a number of instructions for causing a terminal device (which may be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to perform the methods described in various embodiments of the present application.
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Abstract
一种保险推荐方法,所述方法包括:在收到前端发送的带有客户标识信息的保险推荐请求后,从预先确定的第一数据源查找与该客户标识信息对应的客户对营销模式的反馈数据(S301);若查找到与该客户标识信息对应的客户对营销模式的反馈数据,则分析该客户对营销模式的反馈数据,以确定该客户偏好的营销模式(S302);根据该客户偏好的营销模式向前端发出针对该客户的营销模式的保险推荐指令(S303)。该方法能够根据客户偏好的营销模式对客户进行保险推荐,提高客户的体验效果、挖掘出潜在的意向客户、提高业务人员的业务效率。
Description
本申请要求于2017年8月31日提交中国专利局、申请号为201710776130.8,发明名称为“电子装置、保险推荐方法、及计算机可读存储介质”的中国专利申请的优先权,其全部内容通过引用结合在本申请中。
本申请涉及保障类产品销售领域,尤其涉及一种电子装置、保险推荐方法及计算机可读存储介质。
目前,随着人们生活水平的提高,越来越多的人开始重视保障类服务产品,而购买保险是首选的保障类服务之一。随着保险业务市场的活跃,现有的保险行业无论是线下业务人员或是线上电销坐席,在进行产品销售时为了提高销售成功率,均开始考虑根据用户个人喜好和生活习性向不同的用户有针对性地推荐相关的产品信息。
但是,不管是线下业务人员或是线上电销坐席通常很难根据客户提供的信息对客户的需求进行精准的分类(例如,客户喜欢的沟通方式,客户最需求的产品类型等),只有在与客户的接触沟通中,才能进一步精准地了解客户的真实需求。因此,若能根据客户偏好的营销模式对客户进行保险推荐,则可以提高客户的体验效果、挖掘出潜在的意向客户、提高业务人员的业务效率。
发明内容
有鉴于此,本申请提出一种电子装置、保险推荐方法及计算机可读存储介质,能够根据客户偏好的接触方式与客户进行接触,提高客户的体验效果、挖掘出潜在的意向客户、提高业务人员的业务效率。
首先,为实现上述目的,本申请第一方面提出一种电子装置,所述电子装置包括存储器、处理器,所述存储器与所述处理器通信连接,且所述存储器上存储有保险推荐程序,所述保险推荐程序被所述处理器执行,以实现如下步骤:
A、在收到前端发送的带有客户标识信息的保险推荐请求后,从预先确定的第一数据源查找与该客户标识信息对应的客户对营销模式的反馈数据;所述预先确定的第一数据源包括客户标识信息及客户对营销模式的反馈数据;
B、若查找到与该客户标识信息对应的客户对电话营销的反馈信息及对网络营销的反馈信息,则根据该客户对电话营销的反馈信息计算该客户接通营销电话且通话时长超过预设的第一时间阈值的第一概率值,并根据该客户对网络营销的反馈信息计算该客户点击网络营销链接且浏览网络营销链接的时长超过预设的第二时间阈值的第二概率值,比较所述第一概率值与所述第二
概率值的大小,若所述第一概率值大于所述第二概率值,则确定该客户偏好的营销模式为电话营销,若所述第一概率值小于所述第二概率值,则确定该客户偏好的营销模式为网络营销;
C、根据该客户偏好的营销模式向前端发出针对该客户的营销模式的保险推荐指令。
此外,为实现上述目的,本申请第二方面提供一种保险推荐方法,该方法包括如下步骤:
A、在收到前端发送的带有客户标识信息的保险推荐请求后,从预先确定的第一数据源查找与该客户标识信息对应的客户对营销模式的反馈数据;所述客户标识信息包括身份证号、手机号、及护照号;所述预先确定的第一数据源包括客户标识信息及客户对营销模式的反馈数据;
B、若查找到与该客户标识信息对应的客户对电话营销的反馈信息及对网络营销的反馈信息,则根据该客户对电话营销的反馈信息计算该客户接通营销电话且通话时长超过预设的第一时间阈值的第一概率值,并根据该客户对网络营销的反馈信息计算该客户点击网络营销链接且浏览网络营销链接的时长超过预设的第二时间阈值的第二概率值,比较所述第一概率值与所述第二概率值的大小,若所述第一概率值大于所述第二概率值,则确定该客户偏好的营销模式为电话营销,若所述第一概率值小于所述第二概率值,则确定该客户偏好的营销模式为网络营销;
C、根据该客户偏好的营销模式向前端发出针对该客户的营销模式的保险推荐指令。
进一步地,为实现上述目的,本申请第三方面提供一种计算机可读存储介质,所述计算机可读存储介质存储有保险推荐程序,所述保险推荐程序可被至少一个处理器执行,以使所述至少一个处理器执行如下步骤:
A、在收到前端发送的带有客户标识信息的保险推荐请求后,从预先确定的第一数据源查找与该客户标识信息对应的客户对营销模式的反馈数据,所述预先确定的第一数据源包括客户标识信息及客户对营销模式的反馈数据;
B、若查找到与该客户标识信息对应的客户对电话营销的反馈信息及对网络营销的反馈信息,则根据该客户对电话营销的反馈信息计算该客户接通营销电话且通话时长超过预设的第一时间阈值的第一概率值,并根据该客户对网络营销的反馈信息计算该客户点击网络营销链接且浏览网络营销链接的时长超过预设的第二时间阈值的第二概率值,比较所述第一概率值与所述第二概率值的大小,若所述第一概率值大于所述第二概率值,则确定该客户偏好的营销模式为电话营销,若所述第一概率值小于所述第二概率值,则确定该客户偏好的营销模式为网络营销;
C、根据该客户偏好的营销模式向前端发出针对该客户的营销模式的保险推荐指令。
相较于现有技术,本申请所提出的电子装置、保险推荐方法及计算机可读存储介质,首先,在收到前端发送的带有客户标识信息的保险推荐请求后,
从预先确定的第一数据源查找与该客户标识信息对应的客户对营销模式的反馈数据;然后,若查找到与该客户标识信息对应的该客户对营销模式的反馈数据,则分析该客户对营销模式的反馈数据,以确定该客户偏好的营销模式;接着,根据该客户偏好的营销模式向前端发出针对该客户的营销模式的保险推荐指令。这样,可以根据客户偏好的营销模式对客户进行保险推荐,提高客户的体验效果、有利于进一步挖掘出潜在的意向客户、提高业务人员的业务效率。
图1是本申请电子装置较佳实施例选的硬件架构的示意图;
图2是本申请电子装置一施例中保险推荐程序的程序模块示意图;
图3是本申请保险推荐方法较佳实施例的实施流程示意图。
本申请目的的实现、功能特点及优点将结合实施例,参照附图做进一步说明。
为了使本申请的目的、技术方案及优点更加清楚明白,以下结合附图及实施例,对本申请进行进一步详细说明。应当理解,此处所描述的具体实施例仅用以解释本申请,并不用于限定本申请。基于本申请中的实施例,本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例,都属于本申请保护的范围。
需要说明的是,在本申请中涉及“第一”、“第二”等的描述仅用于描述目的,而不能理解为指示或暗示其相对重要性或者隐含指明所指示的技术特征的数量。由此,限定有“第一”、“第二”的特征可以明示或者隐含地包括至少一个该特征。另外,各个实施例之间的技术方案可以相互结合,但是必须是以本领域普通技术人员能够实现为基础,当技术方案的结合出现相互矛盾或无法实现时应当认为这种技术方案的结合不存在,也不在本申请要求的保护范围之内。
参阅图1所示,是本申请电子装置2较佳实施例的硬件架构的示意图。本实施例中,电子装置2可包括,但不仅限于,可通过***总线相互通信连接存储器11、处理器12、及网络接口13。需要指出的是,图2仅示出了具有组件11-13的电子装置2,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。
其中,存储器11至少包括一种类型的可读存储介质,可读存储介质包括闪存、硬盘、多媒体卡、卡型存储器(例如,SD或DX存储器等)、随机访问存储器(RAM)、静态随机访问存储器(SRAM)、只读存储器(ROM)、电可擦除可编程只读存储器(EEPROM)、可编程只读存储器(PROM)、磁性存储器、磁盘、光盘等。在一些实施例中,存储器11可以是电子装置2的内部存储单元,例如电子装置2的硬盘或内存。在另一些实施例中,存储器11也
可以是电子装置2的外部存储设备,例如电子装置2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。当然,存储器11还可以既包括电子装置2的内部存储单元也包括其外部存储设备。本实施例中,存储器11通常用于存储安装于电子装置2的操作***和各类应用软件,例如保险推荐***200的程序代码等。此外,存储器11还可以用于暂时地存储已经输出或者将要输出的各类数据。
处理器12在一些实施例中可以是中央处理器(Central Processing Unit,CPU)、控制器、微控制器、微处理器、或其他数据处理芯片。处理器12通常用于控制电子装置2的总体操作,例如执行与前端1进行数据交互或者通信相关的控制和处理等。本实施例中,处理器12用于运行存储器11中存储的程序代码或者处理数据,例如运行的保险推荐***200等。
网络接口13可包括无线网络接口或有线网络接口,网络接口13通常用于在电子装置2与其他电子设备之间建立通信连接。
可选地,电子装置2还可以包括用户接口,用户接口可以包括显示器(Display)、输入单元比如键盘(Keyboard),可选的用户接口还可以包括标准的有线接口、无线接口。可选地,在一些实施例中,显示器可以是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。其中,显示器也可以适当的称为显示屏或显示单元,用于显示在电子装置2中处理的信息以及用于显示可视化的用户界面。
在图1所示的电子装置2的实施例中,存储器11中存储有保险推荐程序;处理器12执行存储器11中存储的保险推荐程序时实现如下步骤:
A、在收到前端发送的带有客户标识信息的保险推荐请求后,从预先确定的第一数据源查找与该客户标识信息对应的客户对营销模式的反馈数据,预先确定的第一数据源包括客户标识信息及客户对营销模式的反馈数据;
B、若查找到与该客户标识信息对应的客户对电话营销的反馈信息及对网络营销的反馈信息,则根据该客户对电话营销的反馈信息计算该客户接通营销电话且通话时长超过预设的第一时间阈值的第一概率值,并根据该客户对网络营销的反馈信息计算该客户点击网络营销链接且浏览网络营销链接的时长超过预设的第二时间阈值的第二概率值,比较第一概率值与第二概率值的大小,若第一概率值大于第二概率值,则确定该客户偏好的营销模式为电话营销,若第一概率值小于第二概率值,则确定该客户偏好的营销模式为网络营销;
C、根据该客户偏好的营销模式向前端发出针对该客户的营销模式的保险推荐指令。
在本实施例中,以客户对电话营销模式的反馈数据集客户对网络营销模式的反馈数据为例,来对本申请的方案进行解释。其中,预先确定的第一数据源包括客户标识信息(例如,身份证号、手机号、护照号等)及客户对不
同营销模式(例如,网络营销模式、和/或电话营销模式)的反馈数据(例如,愿意接通营销电话的概率大于70%,并且每次沟通时长大于10分钟的概率为50%、和/或,在接到营销短信或者推送的APP消息通知时点击连接的概率为60%,且在晚上点击的概率大于50%)。
需要说明的是,在步骤B中,若查找到与该客户标识信息对应的客户对电话营销的反馈信息、且没有查找到与该客户标识信息对应的客户对网络营销的反馈信息,则根据该客户对电话营销的反馈信息计算该客户接通营销电话且通话时长超过预设的第一时间阈值(例如,10分钟)的第一概率值(例如40%),若第一概率值大于预设的概率阈值(例如,35%),则确定该客户偏好的营销模式为电话营销;或者,若查找到与该客户标识信息对应的客户对网络营销的反馈信息、且没有查找到与该客户标识信息对应的客户对电话营销的反馈信息,则根据该客户对网络营销的反馈信息计算该客户点击网络营销链接且浏览网络营销链接的时长超过预设的第二时间阈值(例如,8分钟)的第二概率值(例如,50百分之),若所述第二概率值大于预设的概率阈值(例如,百分之40),则确定该客户偏好的营销模式为网络营销。
从上述实施例可知,本申请的保险推荐***,可以根据客户偏好的营销模式对客户进行保险的产品,从而提高客户的体验效果,挖掘出潜在的客户,提高业务人员的业务效率。
进一步为了提高保险推荐的准确性,作为一种实施方式,在确定了该客户偏好的营销模式之后,从预先确定的第二数据源(例如,保险业务数据库、银行业务数据库、及公共网络平台)中获取与该客户标识信息(例如,身份证号、电话号码、注册账号等)对应的该客户的第一全方位数据信息(例如,客户的身份属性信息、客户资产状况信息、保险理财信息、兴趣爱好、及家庭信息);利用预先确定的匹配规则(例如,有第二全方位数据信息均与第一全方位数据信息相同,或者有第二全方位数据信息与第一全方位数据信息相同的概率大于80%)将第一全方位数据信息与预先确定的客户群体(例如,生命保障需求类客户群、健康需求类客户群、子女教育需求类客户群、个人养老需求类客户群、财富增值需求类客户群)中各个客户的第二全方位数据信息进行匹配,以确定出该客户所属的第一客户群体;根据预存的客户群体与保险需求类别之间的映射关系,确定第一客户群体对应需求的保险类别(例如,生命保障需求类、健康需求类、子女教育需求类、个人养老需求类、财富增值需求类);根据第一客户群体对应需求的保险类别及该客户偏好的营销模式向前端发出针对该客户的保险类别及营销模式的推荐指令。这样,可以根据客户偏好的营销模式以及客户所属的客户群体需求的保险类别对客户进行保险推荐,提高客户的体验效果、有利于进一步挖掘出潜在的意向客户、提高业务人员的业务效率。
可以理解的是,上述各实施例中涉及到的预设的第一时间阈值、预设的第二时间阈值、预设的概率阈值等需要预先设置的参数,可以用户根据实际情况进行设置。
可选地,在其他的实施例中,保险推荐程序还可以被分割为一个或者多个模块,一个或者多个模块被存储于存储器11中,并由一个或多个处理器(本实施例为处理器12)所执行,以完成本申请,本申请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。
例如,参照图2所示,为本申请电子装置一实施例中保险推荐程序的程序模块示意图,该实施例中,保险推荐程序可以被分割为查找模块201、分析模块202、推荐模块203,其中模块201-203所实现的功能或操作步骤均与上文类似,此处不再详述,示例性地,例如其中:
查找模块201用于在收到前端发送的带有客户标识信息的保险推荐请求后,从预先确定的第一数据源查找与该客户标识信息对应的客户对营销模式的反馈数据,所述预先确定的第一数据源包括客户标识信息及客户对营销模式的反馈数据;
分析模块202用于若查找到与该客户标识信息对应的客户对电话营销的反馈信息及对网络营销的反馈信息,则根据该客户对电话营销的反馈信息计算该客户接通营销电话且通话时长超过预设的第一时间阈值的第一概率值,并根据该客户对网络营销的反馈信息计算该客户点击网络营销链接且浏览网络营销链接的时长超过预设的第二时间阈值的第二概率值,比较所述第一概率值与所述第二概率值的大小,若所述第一概率值大于所述第二概率值,则确定该客户偏好的营销模式为电话营销,若所述第一概率值小于所述第二概率值,则确定该客户偏好的营销模式为网络营销;
推荐模块203用于根据该客户偏好的营销模式向前端发出针对该客户的营销模式的保险推荐指令。
此外,本申请还提出一种保险推荐方法。
参阅图3所示,是本申请保险推荐方法第一实施例的实施流程示意图。由图3可知,在本实施例中,保险推荐方法包括步骤S301至步骤S303。
步骤S301,在收到前端发送的带有客户标识信息的保险推荐请求后,从预先确定的第一数据源查找与该客户标识信息对应的客户对营销模式的反馈数据,预先确定的第一数据源包括客户标识信息及客户对营销模式的反馈数据;
步骤S302,若查找到与该客户标识信息对应的客户对电话营销的反馈信息及对网络营销的反馈信息,则根据该客户对电话营销的反馈信息计算该客户接通营销电话且通话时长超过预设的第一时间阈值的第一概率值,并根据该客户对网络营销的反馈信息计算该客户点击网络营销链接且浏览网络营销链接的时长超过预设的第二时间阈值的第二概率值,比较第一概率值与第二概率值的大小,若第一概率值大于第二概率值,则确定该客户偏好的营销模式为电话营销,若第一概率值小于第二概率值,则确定该客户偏好的营销模式为网络营销;
步骤S303,根据该客户偏好的营销模式向前端发出针对该客户的营销模式的保险推荐指令。
在本实施例中,以客户对电话营销模式的反馈数据集客户对网络营销模式的反馈数据为例,来对本申请的方案进行解释。其中,预先确定的第一数据源包括客户标识信息(例如,身份证号、手机号、护照号等)及客户对不同营销模式(例如,网络营销模式、和/或电话营销模式)的反馈数据(例如,愿意接通营销电话的概率大于70%,并且每次沟通时长大于10分钟的概率为50%、和/或,在接到营销短信或者推送的APP消息通知时点击连接的概率为60%,且在晚上点击的概率大于50%)。
需要说明的是,在步骤B中,若查找到与该客户标识信息对应的客户对电话营销的反馈信息、且没有查找到与该客户标识信息对应的客户对网络营销的反馈信息,则根据该客户对电话营销的反馈信息计算该客户接通营销电话且通话时长超过预设的第一时间阈值(例如,10分钟)的第一概率值(例如40%),若第一概率值大于预设的概率阈值(例如,35%),则确定该客户偏好的营销模式为电话营销;或者,若查找到与该客户标识信息对应的客户对网络营销的反馈信息、且没有查找到与该客户标识信息对应的客户对电话营销的反馈信息,则根据该客户对网络营销的反馈信息计算该客户点击网络营销链接且浏览网络营销链接的时长超过预设的第二时间阈值(例如,8分钟)的第二概率值(例如,50百分之),若所述第二概率值大于预设的概率阈值(例如,百分之40),则确定该客户偏好的营销模式为网络营销。
从上述实施例可知,本申请的保险推荐***,可以根据客户偏好的营销模式对客户进行保险的产品,从而提高客户的体验效果,挖掘出潜在的客户,提高业务人员的业务效率。
进一步为了提高保险推荐的准确性,作为一种实施方式,在确定了该客户偏好的营销模式之后,从预先确定的第二数据源(例如,保险业务数据库、银行业务数据库、及公共网络平台)中获取与该客户标识信息(例如,身份证号、电话号码、注册账号等)对应的该客户的第一全方位数据信息(例如,客户的身份属性信息、客户资产状况信息、保险理财信息、兴趣爱好、及家庭信息);利用预先确定的匹配规则(例如,有第二全方位数据信息均与第一全方位数据信息相同,或者有第二全方位数据信息与第一全方位数据信息相同的概率大于80%)将第一全方位数据信息与预先确定的客户群体(例如,生命保障需求类客户群、健康需求类客户群、子女教育需求类客户群、个人养老需求类客户群、财富增值需求类客户群)中各个客户的第二全方位数据信息进行匹配,以确定出该客户所属的第一客户群体;根据预存的客户群体与保险需求类别之间的映射关系,确定第一客户群体对应需求的保险类别(例如,生命保障需求类、健康需求类、子女教育需求类、个人养老需求类、财富增值需求类);根据第一客户群体对应需求的保险类别及该客户偏好的营销模式向前端发出针对该客户的保险类别及营销模式的推荐指令。这样,可以根据客户偏好的营销模式以及客户所属的客户群体需求的保险类别对客户进行保险推荐,提高客户的体验效果、有利于进一步挖掘出潜在的意向客户、提高业务人员的业务效率。
上述实施例提出的保险推荐方法,在收到前端发送的带有客户标识信息的保险推荐请求后,从预先确定的第一数据源查找与该客户标识信息对应的客户对营销模式的反馈数据;若查找到与该客户标识信息对应的该客户对营销模式的反馈数据,则分析该客户对营销模式的反馈数据,以确定该客户偏好的营销模式;接着,根据该客户偏好的营销模式向前端发出针对该客户的营销模式的保险推荐指令。这样,可以根据客户偏好的营销模式对客户进行保险推荐,提高客户的体验效果、有利于进一步挖掘出潜在的意向客户、提高业务人员的业务效率。
此外,本申请实施例还提出一种计算机可读存储介质,该计算机可读存储介质上存储有保险推荐程序,该保险推荐程序被处理器执行时实现如下操作:
在收到前端发送的带有客户标识信息的保险推荐请求后,从预先确定的第一数据源查找与该客户标识信息对应的客户对营销模式的反馈数据,预先确定的第一数据源包括客户标识信息及客户对营销模式的反馈数据;
若查找到与该客户标识信息对应的客户对电话营销的反馈信息及对网络营销的反馈信息,则根据该客户对电话营销的反馈信息计算该客户接通营销电话且通话时长超过预设的第一时间阈值的第一概率值,并根据该客户对网络营销的反馈信息计算该客户点击网络营销链接且浏览网络营销链接的时长超过预设的第二时间阈值的第二概率值,比较第一概率值与第二概率值的大小,若第一概率值大于第二概率值,则确定该客户偏好的营销模式为电话营销,若第一概率值小于第二概率值,则确定该客户偏好的营销模式为网络营销;
根据该客户偏好的营销模式向前端发出针对该客户的营销模式的保险推荐指令。
进一步地,该保险推荐程序被处理器执行时,还实现如下操作:
在收到前端发送的带有客户标识信息的保险推荐请求后,从预先确定的第一数据源查找与该客户标识信息对应的客户对营销模式的反馈数据,预先确定的第一数据源包括客户标识信息及客户对营销模式的反馈数据;
若查找到与该客户标识信息对应的客户对电话营销的反馈信息、且没有查找到与该客户标识信息对应的客户对网络营销的反馈信息,则根据该客户对电话营销的反馈信息计算该客户接通营销电话且通话时长超过预设的第一时间阈值的第一概率值,若第一概率值大于预设的概率阈值,则确定该客户偏好的营销模式为电话营销;或者,若查找到与该客户标识信息对应的客户对网络营销的反馈信息、且没有查找到与该客户标识信息对应的客户对电话营销的反馈信息,则根据该客户对网络营销的反馈信息计算该客户点击网络营销连接且浏览网络营销连接的时长超过预设的第二时间阈值的第二概率值,若第二概率值大于预设的概率阈值,则确定该客户偏好的营销模式为网络营销;
根据该客户偏好的营销模式向前端发出针对该客户的营销模式的保险推
荐指令。
进一步地,该保险推荐程序被处理器执行时,还实现如下操作:
在收到前端发送的带有客户标识信息的保险推荐请求后,从预先确定的第一数据源查找与该客户标识信息对应的客户对营销模式的反馈数据,预先确定的第一数据源包括客户标识信息及客户对营销模式的反馈数据;
若查找到与该客户标识信息对应的客户对电话营销的反馈信息及对网络营销的反馈信息,则根据该客户对电话营销的反馈信息计算该客户接通营销电话且通话时长超过预设的第一时间阈值的第一概率值,并根据该客户对网络营销的反馈信息计算该客户点击网络营销链接且浏览网络营销链接的时长超过预设的第二时间阈值的第二概率值,比较第一概率值与第二概率值的大小,若第一概率值大于第二概率值,则确定该客户偏好的营销模式为电话营销,若第一概率值小于第二概率值,则确定该客户偏好的营销模式为网络营销;
从预先确定的第二数据源中获取与该客户标识信息对应的该客户的第一全方位数据信息,预先确定的第二数据源包括保险业务数据库、银行业务数据库、及公共网络平台,第一全方位数据信息包括客户的身份属性信息、客户资产状况信息、保险理财信息、兴趣偏好、及家庭信息;
利用预先确定的匹配规则将第一全方位数据信息与预先确定的客户群体中各个客户的第二全方位数据信息进行匹配,以确定出该客户所属的第一客户群体;
根据预存的客户群体与保险需求类别之间的映射关系,确定第一客户群体对应需求的保险类别;
根据第一客户群体对应需求的保险类别及该客户偏好的营销模式向前端发出针对该客户的保险类别及营销模式的推荐指令。
进一步地,该保险推荐程序被处理器执行时,还实现如下操作:
在收到前端发送的带有客户标识信息的保险推荐请求后,从预先确定的第一数据源查找与该客户标识信息对应的客户对营销模式的反馈数据,预先确定的第一数据源包括客户标识信息及客户对营销模式的反馈数据;
若查找到与该客户标识信息对应的客户对电话营销的反馈信息、且没有查找到与该客户标识信息对应的客户对网络营销的反馈信息,则根据该客户对电话营销的反馈信息计算该客户接通营销电话且通话时长超过预设的第一时间阈值的第一概率值,若第一概率值大于预设的概率阈值,则确定该客户偏好的营销模式为电话营销;或者,若查找到与该客户标识信息对应的客户对网络营销的反馈信息、且没有查找到与该客户标识信息对应的客户对电话营销的反馈信息,则根据该客户对网络营销的反馈信息计算该客户点击网络营销链接且浏览网络营销链接的时长超过预设的第二时间阈值的第二概率值,若第二概率值大于预设的概率阈值,则确定该客户偏好的营销模式为网络营销;
从预先确定的第二数据源中获取与该客户标识信息对应的该客户的第一全方位数据信息,预先确定的第二数据源包括保险业务数据库、银行业务数据库、及公共网络平台,第一全方位数据信息包括客户的身份属性信息、客户资产状况信息、保险理财信息、兴趣偏好、及家庭信息;
利用预先确定的匹配规则将所述第一全方位数据信息与预先确定的客户群体中各个客户的第二全方位数据信息进行匹配,以确定出该客户所属的第一客户群体;
根据预存的客户群体与保险需求类别之间的映射关系,确定第一客户群体对应需求的保险类别;
根据第一客户群体对应需求的保险类别及该客户偏好的营销模式向前端发出针对该客户的保险类别及营销模式的推荐指令。
本申请计算机可读存储介质具体实施方式与上述电子装置和保险推荐方法各实施例基本相同,在此不作累述。
通过上述各实施例可知,本申请的电子装置,保险推荐方法及计算机可读存储介质,首先,在收到前端发送的带有客户标识信息的保险推荐请求后,从预先确定的第一数据源查找与该客户标识信息对应的客户对营销模式的反馈数据;其次,若查找到与该客户标识信息对应的客户对营销模式的反馈数据,则根据预设的营销模式偏好判断规则分析该客户对营销模式的反馈数据,以确定该客户偏好的营销模式;再次,根据该客户偏好的营销模式向前端发出针对该客户的营销模式的保险推荐指令。这样,可以根据客户偏好的接触方式与客户进行接触,提高客户的体验效果、有利于进一步挖掘出潜在的意向客户、提高业务人员的业务效率。
上述本申请实施例序号仅仅为了描述,不代表实施例的优劣。
通过以上的实施方式的描述,本领域的技术人员可以清楚地了解到上述实施例方法可借助软件加必需的通用硬件平台的方式来实现,当然也可以通过硬件,但很多情况下前者是更佳的实施方式。基于这样的理解,本申请的技术方案本质上或者说对现有技术做出贡献的部分可以以软件产品的形式体现出来,该计算机软件产品存储在一个存储介质(如ROM/RAM、磁碟、光盘)中,包括若干指令用以使得一台终端设备(可以是手机,计算机,服务器,空调器,或者网络设备等)执行本申请各个实施例所述的方法。
以上仅为本申请的优选实施例,并非因此限制本申请的专利范围,凡是利用本申请说明书及附图内容所作的等效结构或等效流程变换,或直接或间接运用在其他相关的技术领域,均同理包括在本申请的专利保护范围内。
Claims (20)
- 一种电子装置,其特征在于,所述电子装置包括存储器、处理器,所述存储器与所述处理器通信连接,且所述存储器上存储有保险推荐程序,所述保险推荐程序可被所述处理器执行,以实现如下步骤:A、在收到前端发送的带有客户标识信息的保险推荐请求后,从预先确定的第一数据源查找与该客户标识信息对应的客户对营销模式的反馈数据,所述预先确定的第一数据源包括客户标识信息及客户对营销模式的反馈数据;B、若查找到与该客户标识信息对应的客户对电话营销的反馈信息及对网络营销的反馈信息,则根据该客户对电话营销的反馈信息计算该客户接通营销电话且通话时长超过预设的第一时间阈值的第一概率值,并根据该客户对网络营销的反馈信息计算该客户点击网络营销链接且浏览网络营销链接的时长超过预设的第二时间阈值的第二概率值,比较所述第一概率值与所述第二概率值的大小,若所述第一概率值大于所述第二概率值,则确定该客户偏好的营销模式为电话营销,若所述第一概率值小于所述第二概率值,则确定该客户偏好的营销模式为网络营销;C、根据该客户偏好的营销模式向前端发出针对该客户的营销模式的保险推荐指令。
- 如权利要求1所述的电子装置,其特征在于,所述步骤B可替换为如下步骤:若查找到与该客户标识信息对应的客户对电话营销的反馈信息、且没有查找到与该客户标识信息对应的客户对网络营销的反馈信息,则根据该客户对电话营销的反馈信息计算该客户接通营销电话且通话时长超过预设的第一时间阈值的第一概率值,若所述第一概率值大于预设的概率阈值,则确定该客户偏好的营销模式为电话营销;或者,若查找到与该客户标识信息对应的客户对网络营销的反馈信息、且没有查找到与该客户标识信息对应的客户对电话营销的反馈信息,则根据该客户对网络营销的反馈信息计算该客户点击网络营销链接且浏览网络营销链接的时长超过预设的第二时间阈值的第二概率值,若所述第二概率值大于预设的概率阈值,则确定该客户偏好的营销模式为网络营销。
- 如权利要求1所述的电子装置,其特征在于,所述步骤C可替换为如下步骤:E、从预先确定的第二数据源中获取与该客户标识信息对应的该客户的第一全方位数据信息,其中,所述预先确定的第二数据源包括保险业务数据库、银行业务数据库、及公共网络平台,所述第一全方位数据信息包括客户的身份属性信息、客户资产状况信息、保险理财信息、兴趣偏好、及家庭信息;F、利用预先确定的匹配规则将所述第一全方位数据信息与预先确定的客户群体中各个客户的第二全方位数据信息进行匹配,以确定出该客户所属的第一客户群体;G、根据预存的客户群体与保险需求类别之间的映射关系,确定所述第一客户群体对应需求的保险类别;H、根据所述第一客户群体对应需求的保险类别及该客户偏好的营销模式向前端发出针对该客户的保险类别及营销模式的推荐指令。
- 如权利要求2所述的电子装置,其特征在于,所述步骤C可替换为如下步骤:E、从预先确定的第二数据源中获取与该客户标识信息对应的该客户的第一全方位数据信息,其中,所述预先确定的第二数据源包括保险业务数据库、银行业务数据库、及公共网络平台,所述第一全方位数据信息包括客户的身份属性信息、客户资产状况信息、保险理财信息、兴趣偏好、及家庭信息;F、利用预先确定的匹配规则将所述第一全方位数据信息与预先确定的客户群体中各个客户的第二全方位数据信息进行匹配,以确定出该客户所属的第一客户群体;G、根据预存的客户群体与保险需求类别之间的映射关系,确定所述第一客户群体对应需求的保险类别;H、根据所述第一客户群体对应需求的保险类别及该客户偏好的营销模式向前端发出针对该客户的保险类别及营销模式的推荐指令。
- 如权利要求3所述的电子装置,其特征在于,所述预先确定的客户群体包括生命保障需求类客户群、健康需求类客户群、子女教育需求类客户群、个人养老需求类客户群、财富增值需求类客户群。
- 如权利要求3所述的电子装置,其特征在于,所述保险推荐程序被所述处理器执行时还实现如下步骤:从业务数据库获取每个业务人员的业务数据,并根据所获取的业务数据评估出每个业务人员擅长接触的客户群体,若有业务人员擅长接触的客户群体与该客户所属的客户群体对应一致,则向前端发出针对该客户的业务人员推荐保险指令。
- 如权利要求4所述的电子装置,其特征在于,所述预先确定的客户群体包括生命保障需求类客户群、健康需求类客户群、子女教育需求类客户群、个人养老需求类客户群、财富增值需求类客户群。
- 一种保险推荐方法,其特征在于,所述方法包括如下步骤:A、在收到前端发送的带有客户标识信息的保险推荐请求后,从预先确定的第一数据源查找与该客户标识信息对应的客户对营销模式的反馈数据,所述预先确定的第一数据源包括客户标识信息及客户对营销模式的反馈数据;B、若查找到与该客户标识信息对应的客户对电话营销的反馈信息及对网络营销的反馈信息,则根据该客户对电话营销的反馈信息计算该客户接通营销电话且通话时长超过预设的第一时间阈值的第一概率值,并根据该客户对网络营销的反馈信息计算该客户点击网络营销链接且浏览网络营销链接的时长超过预设的第二时间阈值的第二概率值,比较所述第一概率值与所述第二概率值的大小,若所述第一概率值大于所述第二概率值,则确定该客户偏好 的营销模式为电话营销,若所述第一概率值小于所述第二概率值,则确定该客户偏好的营销模式为网络营销;C、根据该客户偏好的营销模式向前端发出针对该客户的营销模式的保险推荐指令。
- 如权利要求8所述的保险推荐方法,其特征在于,所述步骤B可替换为如下步骤:若查找到与该客户标识信息对应的客户对电话营销的反馈信息、且没有查找到与该客户标识信息对应的客户对网络营销的反馈信息,则根据该客户对电话营销的反馈信息计算该客户接通营销电话且通话时长超过预设的第一时间阈值的第一概率值,若所述第一概率值大于预设的概率阈值,则确定该客户偏好的营销模式为电话营销;或者,若查找到与该客户标识信息对应的客户对网络营销的反馈信息、且没有查找到与该客户标识信息对应的客户对电话营销的反馈信息,则根据该客户对网络营销的反馈信息计算该客户点击网络营销链接且浏览网络营销链接的时长超过预设的第二时间阈值的第二概率值,若所述第二概率值大于预设的概率阈值,则确定该客户偏好的营销模式为网络营销。
- 如权利要求8所述的保险推荐方法,其特征在于,所述步骤C可替换为如下步骤:E、从预先确定的第二数据源中获取与该客户标识信息对应的该客户的第一全方位数据信息,其中,所述预先确定的第二数据源包括保险业务数据库、银行业务数据库、及公共网络平台,所述第一全方位数据信息包括客户的身份属性信息、客户资产状况信息、保险理财信息、兴趣偏好、及家庭信息;F、利用预先确定的匹配规则将所述第一全方位数据信息与预先确定的客户群体中各个客户的第二全方位数据信息进行匹配,以确定出该客户所属的第一客户群体;G、根据预存的客户群体与保险需求类别之间的映射关系,确定所述第一客户群体对应需求的保险类别;H、根据所述第一客户群体对应需求的保险类别及该客户偏好的营销模式向前端发出针对该客户的保险类别及营销模式的推荐指令。
- 如权利要求9所述的保险推荐方法,其特征在于,所述步骤C可替换为如下步骤:E、从预先确定的第二数据源中获取与该客户标识信息对应的该客户的第一全方位数据信息,其中,所述预先确定的第二数据源包括保险业务数据库、银行业务数据库、及公共网络平台,所述第一全方位数据信息包括客户的身份属性信息、客户资产状况信息、保险理财信息、兴趣偏好、及家庭信息;F、利用预先确定的匹配规则将所述第一全方位数据信息与预先确定的客户群体中各个客户的第二全方位数据信息进行匹配,以确定出该客户所属的第一客户群体;G、根据预存的客户群体与保险需求类别之间的映射关系,确定所述第一客户群体对应需求的保险类别;H、根据所述第一客户群体对应需求的保险类别及该客户偏好的营销模式向前端发出针对该客户的保险类别及营销模式的推荐指令。
- 如权利要求10所述的保险推荐方法,其特征在于,所述预先确定的客户群体包括生命保障需求类客户群、健康需求类客户群、子女教育需求类客户群、个人养老需求类客户群、财富增值需求类客户群。
- 如权利要求10所述的保险推荐方法,其特征在于,所述保险推荐程序被所述处理器执行时还实现如下步骤:从业务数据库获取每个业务人员的业务数据,并根据所获取的业务数据评估出每个业务人员擅长接触的客户群体,若有业务人员擅长接触的客户群体与该客户所属的客户群体对应一致,则向前端发出针对该客户的业务人员推荐保险指令。
- 如权利要求11所述的保险推荐方法,其特征在于,所述预先确定的客户群体包括生命保障需求类客户群、健康需求类客户群、子女教育需求类客户群、个人养老需求类客户群、财富增值需求类客户群。
- [根据细则26改正11.01.2018]
一种计算机可读存储介质,所述计算机可读存储介质存储有保险推荐程序,所述保险推荐程序可被至少一个处理器执行,以使所述至少一个处理器执行如下步骤:A、在收到前端发送的带有客户标识信息的保险推荐请求后,从预先确定的第一数据源查找与该客户标识信息对应的客户对营销模式的反馈数据,所述预先确定的第一数据源包括客户标识信息及客户对营销模式的反馈数据;B、若查找到与该客户标识信息对应的客户对电话营销的反馈信息及对网络营销的反馈信息,则根据该客户对电话营销的反馈信息计算该客户接通营销电话且通话时长超过预设的第一时间阈值的第一概率值,并根据该客户对网络营销的反馈信息计算该客户点击网络营销链接且浏览网络营销链接的时长超过预设的第二时间阈值的第二概率值,比较所述第一概率值与所述第二概率值的大小,若所述第一概率值大于所述第二概率值,则确定该客户偏好的营销模式为电话营销,若所述第一概率值小于所述第二概率值,则确定该客户偏好的营销模式为网络营销;C、根据该客户偏好的营销模式向前端发出针对该客户的营销模式的保险推荐指令。 - 如权利要求15所述的计算机可读存储介质,其特征在于,所述步骤B可替换为如下步骤:若查找到与该客户标识信息对应的客户对电话营销的反馈信息、且没有查找到与该客户标识信息对应的客户对网络营销的反馈信息,则根据该客户对电话营销的反馈信息计算该客户接通营销电话且通话时长超过预设的第一时间阈值的第一概率值,若所述第一概率值大于预设的概率阈值,则确定该客户偏好的营销模式为电话营销;或者,若查找到与该客户标识信息对应的客户对网络营销的反馈信息、且没有查找到与该客户标识信息对应的客户对 电话营销的反馈信息,则根据该客户对网络营销的反馈信息计算该客户点击网络营销链接且浏览网络营销链接的时长超过预设的第二时间阈值的第二概率值,若所述第二概率值大于预设的概率阈值,则确定该客户偏好的营销模式为网络营销。
- 如权利要求15所述的计算机可读存储介质,其特征在于,所述步骤C可替换为如下步骤:E、从预先确定的第二数据源中获取与该客户标识信息对应的该客户的第一全方位数据信息,其中,所述预先确定的第二数据源包括保险业务数据库、银行业务数据库、及公共网络平台,所述第一全方位数据信息包括客户的身份属性信息、客户资产状况信息、保险理财信息、兴趣偏好、及家庭信息;F、利用预先确定的匹配规则将所述第一全方位数据信息与预先确定的客户群体中各个客户的第二全方位数据信息进行匹配,以确定出该客户所属的第一客户群体;G、根据预存的客户群体与保险需求类别之间的映射关系,确定所述第一客户群体对应需求的保险类别;H、根据所述第一客户群体对应需求的保险类别及该客户偏好的营销模式向前端发出针对该客户的保险类别及营销模式的推荐指令。
- 如权利要求16所述的计算机可读存储介质,其特征在于,所述步骤C可替换为如下步骤:E、从预先确定的第二数据源中获取与该客户标识信息对应的该客户的第一全方位数据信息,其中,所述预先确定的第二数据源包括保险业务数据库、银行业务数据库、及公共网络平台,所述第一全方位数据信息包括客户的身份属性信息、客户资产状况信息、保险理财信息、兴趣偏好、及家庭信息;F、利用预先确定的匹配规则将所述第一全方位数据信息与预先确定的客户群体中各个客户的第二全方位数据信息进行匹配,以确定出该客户所属的第一客户群体;G、根据预存的客户群体与保险需求类别之间的映射关系,确定所述第一客户群体对应需求的保险类别;H、根据所述第一客户群体对应需求的保险类别及该客户偏好的营销模式向前端发出针对该客户的保险类别及营销模式的推荐指令。
- 如权利要求17所述的计算机可读存储介质,其特征在于,所述预先确定的客户群体包括生命保障需求类客户群、健康需求类客户群、子女教育需求类客户群、个人养老需求类客户群、财富增值需求类客户群。
- 如权利要求17所述的计算机可读存储介质,其特征在于,所述保险推荐程序被所述处理器执行时还实现如下步骤:从业务数据库获取每个业务人员的业务数据,并根据所获取的业务数据评估出每个业务人员擅长接触的客户群体,若有业务人员擅长接触的客户群体与该客户所属的客户群体对应一致,则向前端发出针对该客户的业务人员推荐保险指令。
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