WO2018202170A1 - 动态语音交互系统及其菜单生成方法 - Google Patents

动态语音交互系统及其菜单生成方法 Download PDF

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Publication number
WO2018202170A1
WO2018202170A1 PCT/CN2018/085720 CN2018085720W WO2018202170A1 WO 2018202170 A1 WO2018202170 A1 WO 2018202170A1 CN 2018085720 W CN2018085720 W CN 2018085720W WO 2018202170 A1 WO2018202170 A1 WO 2018202170A1
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WIPO (PCT)
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customer
menu
broadcast
module
voice interaction
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PCT/CN2018/085720
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English (en)
French (fr)
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李德君
张鹏
张栋栋
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平安科技（深圳）有限公司
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Publication of WO2018202170A1 publication Critical patent/WO2018202170A1/zh

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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
    • G06Q30/01—Customer relationship services
    • 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
    • G06Q40/03—Credit; Loans; Processing thereof
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L15/00—Speech recognition
    • G10L15/22—Procedures used during a speech recognition process, e.g. man-machine dialogue

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  • the present application relates to an automatic voice response technology, and in particular, to a dynamic voice interaction system and a menu generation method thereof.
  • the Interactive Voice Response (IVR) and the manual service are two important channels for the operator to interact with the customer.
  • Automatic voice response can interact with customers through automatic processes to complete simple and clear functions such as query, consultation, and business processing. It is fast, clear, reasonable, simple, and low in operating cost.
  • the human service is characterized by civilization, individuality and honorable service.
  • the IVR system provided by the credit card service provider generally provides a unified and fixed IVR menu for all customers according to the service scope and service type provided by the service provider.
  • all self-service nodes of the IVR menu are tiled and cannot identify the different needs of credit card customers. This will lead to two problems. First, long-term voice broadcasts make customers feel difficult to use, and tend to transfer manual services. Second, the increase in manual labor will lead to more call losses when busy, resulting in credit card customers. Satisfaction is reduced.
  • the application provides a dynamic voice interaction system, the system comprising:
  • An analysis module for analyzing historical behavior data of a customer's credit card business
  • a determination module for determining a customer category based on the analysis result
  • a generation module for generating personalized IVR broadcast menus for different categories of customers.
  • the application also provides a menu generation method for a dynamic voice interaction system, the method comprising the following steps:
  • Historical data analysis steps analysis of historical behavior data of customers handling credit card business
  • Customer category judgment step judge the customer category based on the analysis result
  • Menu generation steps Generate personalized IVR broadcast menus for different categories of customers.
  • the dynamic voice interaction system and the menu generation method provided by the present application can classify credit card customers by analyzing historical behavior data of credit card customers for credit card business, and generate personalized IVR broadcasts for different categories of customers. menu.
  • FIG. 1 is an application environment diagram of a preferred embodiment of a dynamic voice interaction system of the present application.
  • FIG. 2 is a diagram showing an operating environment of a preferred embodiment of a dynamic voice interaction system of the present application.
  • FIG. 3 is a block diagram of a program of a preferred embodiment of a dynamic voice interaction system of the present application.
  • FIG. 4 is a flow chart of a preferred embodiment of a menu generation method for a dynamic voice interaction system of the present application.
  • FIG. 5 is a flowchart of a preferred embodiment of a menu playing method of a dynamic voice interaction system of the present application.
  • FIG. 6, FIG. 7, and FIG. 8 are schematic diagrams of generating different IVR menus by the dynamic voice interaction system of the present application.
  • FIG. 1 it is an application environment diagram of a preferred embodiment of the Interactive Voice Response (IVR) system 10 of the present application.
  • the IVR system 10 is applied to the server 1.
  • the server 1 connects a plurality of clients 3 through the network 2.
  • the network 2 can be a network of a local area network, a wide area network, a metropolitan area network, etc., and can be a wired network or a wireless network.
  • the client 3 can be a desktop computer, a notebook, a tablet, a mobile phone, or other terminal device that can communicate with the server 1 via the network 2.
  • Server 1 includes, but is not limited to, memory 11, processor 12, and display 13.
  • the memory 11 stores program code of the IVR system 10, which may include at least one type of storage medium including a flash memory, a hard disk, a multimedia card, a card type memory (eg, SD or DX memory, etc.), random Access memory (RAM), static random access memory (SRAM), read only memory (ROM), electrically erasable programmable read only memory (EEPROM), programmable read only memory (PROM), magnetic memory, magnetic disk, optical disk, etc. Wait.
  • a flash memory e.g, a flash memory, a hard disk, a multimedia card, a card type memory (eg, SD or DX memory, etc.), random Access memory (RAM), static random access memory (SRAM), read only memory (ROM), electrically erasable programmable read only memory (EEPROM), programmable read only memory (PROM), magnetic memory, magnetic disk, optical disk, etc. Wait.
  • RAM random Access memory
  • SRAM static random access memory
  • ROM read only memory
  • EEPROM electrically erasable programmable read
  • the processor 12 reads and executes the program code of the IVR system 10 from the memory 11 to provide the following functions of the IVR system 10.
  • Display 13 displays the results of processor 12 executing the program code of IVR system 10.
  • Figure 2 shows only server 1 with components 11-13, it being understood that server 1 may include more or fewer components.
  • FIG. 3 it is a program module diagram of a preferred embodiment of the IVR system 10 of the present application.
  • the memory 11 stores historical behavior data 20 for the customer to handle the credit card business.
  • the historical behavior data 20 may be historical behavior data saved by the IVR system 10, or historical behavior data provided by other network entities, or may be the sum of historical behavior data saved by the IVR system 10 and historical behavior data provided by other entities.
  • the IVR system 10 can record the customer's behavior data, and when the customer's historical behavior data needs to be collected, the previously recorded behavior data can be directly collected.
  • the IVR system 10 can provide the customer's behavior data to other entities, and when the historical behavior data of the customer needs to be collected, the behavior data can be collected from other network entities.
  • Historical behavior data can be historical behavior data of all customers of a service organization for a certain period of time (for example, the most recent month) or historical behavior data of some customers (such as a certain region).
  • the historical behavior data 20 includes customer identity related information, such as mobile phone number, ID number, etc., credit card related information under the customer name, such as quantity, credit card type, card number, credit amount, expiration date, repayment date, current status of each credit card. (such as normal, stolen, arrears, freeze) and other information, each time the customer uses the credit card related information, such as the amount of consumption, the place of consumption, etc., and the customer's self-service information using the IVR system 10 to operate the credit card each time, such as the customer used Which self-service nodes in the IVR system menu, the number of times each self-service node is used, the frequency, and so on.
  • customer identity related information such as mobile phone number, ID number, etc.
  • credit card related information under the customer name such as quantity, credit card type, card number, credit amount, expiration date, repayment date, current status of each credit card. (such as normal, stolen, arrears, freeze) and other information, each time the customer uses the credit card related information, such as the amount of
  • the IVR system 10 includes an analysis module 110, a determination module 120, a generation module 130, a receiving module 140, and an output module 150.
  • the analysis module 110 is configured to analyze the historical behavior data 20.
  • the analysis of historical behavior data 20 is to provide a basis for the upcoming IVR menu. Specifically, the customer can calculate the relevant information of each type of business of the credit card, and then use the statistical information as the basis for generating the IVR menu.
  • a customer's credit card business through the IVR system 10 generally includes: card activation, password setting, billing inquiry, billing, repayment, and quota application. If a customer has multiple credit cards, the customer identification information corresponding to the multiple credit cards is the same, for example, the credit card numbers reserved for the two credit cards are the same, and the mobile phone numbers may be the same.
  • the use of the IVR system is more than 10 operations such as billing inquiry, billing, repayment, and application quota change. Due to different customer needs, some customers may often use the IVR system 10 to conduct billing inquiries, but have never used the IVR system 10 to apply for quota changes, and some may often use the IVR system 10 to apply for quota changes and less billing queries.
  • the analysis module 110 analyzes the historical behavior data 20 to sort the historical behavior data 20 of the credit card customer.
  • Table 1 can also add other dimensions, such as the timeline (for example, the last quarter of January-March), and count the number of times customers perform each type of business in different time periods.
  • the determining module 120 is configured to determine a customer category according to the analysis result.
  • the customer categories include: new customers, old customers, and other customers.
  • the determining module 120 determines, according to the analysis result, the customer category includes: when the customer name has an activated and inactive credit card, and the inactive credit card is less than the preset time (for example, less than or equal to 30 days) from the card, or When all cards under the customer name are not activated, it is determined that the customer is a new customer.
  • a customer with ID number "36#######” has 2 credit cards under the name a, one of the credit cards is activated, but the other credit card is not currently activated.
  • the inactive credit card is away from the card.
  • the activation date has 25 days; if the customer ID of the ID number ""18#######" has only one credit card and the credit card is not activated, the judgment module 120 judges that the customer a and the customer b are new. client.
  • the determining module 120 determining the customer category according to the analysis result further includes: determining that the customer is an old customer when the customer does not satisfy the condition of the new customer, or when all the credit cards under the customer name have no control items.
  • control items include piracy, arrears, freezing, and the like. After the credit card is controlled, the customer cannot use it normally.
  • the judging module 120 judges the customer category according to the analysis result, and further includes: determining that the customer is another customer when the customer does not satisfy the condition of the new customer or the condition of the old customer.
  • the generating module 130 is configured to generate a personalized IVR broadcast menu for different categories of customers.
  • the generation module 130 sets the card activation, password management node to the priority broadcast location, and generates a first IVR broadcast menu 30.
  • Figure 6 is a schematic illustration of a first IVR broadcast menu 30 generated for a new customer. It should be noted that the figure is only an exemplary menu. In an actual application, the first IVR broadcast menu 30 may be hierarchical, and in the same level, the item containing the priority broadcast menu node is placed in front. position. The first IVR broadcast menu 30 may also not be hierarchical.
  • the generating module 130 can not only adjust (not broadcast) one or more nodes that are rarely used by new customers, except for adjusting the nodes with high new customer usage probability to the priority position of the IVR broadcast menu, for example, Repayment, billing, etc. nodes.
  • FIG. 7 is a schematic illustration of a second IVR broadcast menu 40 generated for an old customer. It should be noted that FIG. 7 is also only an exemplary menu. In an actual application, the second IVR broadcast menu 40 may be hierarchical, and in the same level, the item containing the priority broadcast menu node is placed on the same level. Front position. The second IVR broadcast menu 40 may also not be hierarchical.
  • the generating module 130 can adjust (not broadcast) one or more nodes that are rarely used by the old customer, in addition to adjusting the nodes with high usage probability of the old customers to the priority position of the IVR broadcast menu, for example, Card activation and other nodes.
  • the generation module 130 generates a default third IVR broadcast menu 50.
  • Figure 8 is a schematic illustration of a third IVR broadcast menu 50 generated for other customers. It should be noted that FIG. 8 is also only an exemplary menu. In practical applications, the third IVR broadcast menu 50 may be hierarchical or non-hierarchical.
  • the receiving module 140 is configured to receive customer information input by the client, such as identity information, card number information, etc., when the client accesses the IVR system 10 through the client 3 (for example, a mobile phone).
  • the determining module 120 is further configured to determine, according to the degree of association between the customer information input by the customer and the historical behavior data 20, which type of customer the customer is.
  • the output module 150 is configured to obtain, according to the determination result of the determining module 120, the corresponding IVR broadcast menu output from the memory 11 for the customer to self-service the credit card service.
  • the output module 150 For example, if the customer currently requesting self-service is a new customer, the output module 150 outputs a first IVR broadcast menu 30. If the customer currently requesting self-service is an old customer, the output module 150 outputs a second IVR broadcast menu 40. If the client currently requesting self-service is another client, the output module 150 outputs a third IVR broadcast menu 50.
  • FIG. 4 is a flow chart of a preferred embodiment of a menu generation method for a dynamic voice interaction system of the present application.
  • step S110 the analysis module 110 analyzes the historical behavior data 20 of the customer's credit card business.
  • the historical behavior data 20 may be historical behavior data saved by the IVR system 10, historical activity data provided by other network entities, and may be the sum of historical behavior data saved by the IVR system 10 and historical behavior data provided by other network entities.
  • the IVR system 10 can record the customer's behavior data, and when the customer's historical behavior data needs to be collected, the previously recorded behavior data can be directly collected.
  • the IVR system 10 can provide the customer's behavior data to other network entities, and can collect behavior data from other network entities when the historical behavior data of the customer needs to be collected.
  • Historical behavior data can be historical behavior data of all customers of a service organization for a certain period of time (for example, the most recent month) or historical behavior data of some customers (such as a certain region).
  • the historical behavior data 20 includes customer identity related information, such as mobile phone number, ID number, etc., credit card related information under the customer name, such as quantity, credit card type, card number, credit amount, expiration date, repayment date, current status of each credit card. (such as normal, stolen, arrears, freeze) and other information, each time the customer uses the credit card related information, such as the amount of consumption, the place of consumption, etc., and the customer's self-service information using the IVR system 10 to operate the credit card each time, such as the customer used Which self-service nodes in the IVR system menu, the number of times each self-service node is used, the frequency, and so on.
  • customer identity related information such as mobile phone number, ID number, etc.
  • credit card related information under the customer name such as quantity, credit card type, card number, credit amount, expiration date, repayment date, current status of each credit card. (such as normal, stolen, arrears, freeze) and other information, each time the customer uses the credit card related information, such as the amount of
  • the analysis of historical behavior data 20 is to provide a basis for the upcoming IVR menu. Specifically, the customer can calculate the relevant information of each type of business of the credit card, and then use the statistical information as the basis for generating the IVR menu.
  • step S120 the determining module 120 determines the customer category based on the analysis result.
  • the customer categories include: new customers, old customers, and other customers.
  • the determining module 120 determines, according to the analysis result, the customer category includes: when the customer name has an activated and inactive credit card, and the inactive credit card is less than the preset time (for example, less than or equal to 30 days) from the card, or When all cards under the customer name are not activated, it is determined that the customer is a new customer.
  • a customer with ID number "36#######” has 2 credit cards under the name a, one of the credit cards is activated, but the other credit card is not currently activated.
  • the inactive credit card is away from the card.
  • the activation date is 25 days; if the customer ID number is ""18#######", there is only one credit card under the b name, and the credit card is not activated, the judgment module 120 judges that the customer a and the customer b are new. client.
  • the determining module 120 determining the customer category according to the analysis result further includes: determining that the customer is an old customer when the customer does not satisfy the condition of the new customer, or when all the credit cards under the customer name have no control items.
  • control items include piracy, arrears, freezing, and the like. After the credit card is controlled, the customer cannot use it normally.
  • the judging module 120 judges the customer category according to the analysis result, and further includes: determining that the customer is another customer when the customer does not satisfy the condition of the new customer or the condition of the old customer.
  • step S130 the generating module 130 generates a personalized IVR broadcast menu for different categories of customers.
  • the generation module 130 sets the card activation, password management node to the priority broadcast location, and generates a first IVR broadcast menu 30.
  • FIG. 6 it is a schematic diagram of the first IVR broadcast menu 30 generated by the generating module 130 for new clients. It should be noted that the figure is only an exemplary menu. In an actual application, the first IVR broadcast menu 30 may be hierarchical, and in the same level, the item containing the priority broadcast menu node is placed in front. position. The first IVR broadcast menu 30 may also not be hierarchical.
  • the generating module 130 can not only adjust (not broadcast) one or more nodes that are rarely used by new customers, except for adjusting the nodes with high new customer usage probability to the priority position of the IVR broadcast menu, for example, Repayment, billing, etc. nodes.
  • the generating module 130 sets the billing inquiry, repayment, and quota application node to the menu priority broadcast position to generate the second IVR broadcast menu 40.
  • FIG. 7 it is a schematic diagram of the second IVR broadcast menu 40 generated by the generating module 130 for the old customer. It should be noted that FIG. 7 is also only an exemplary menu. In an actual application, the second IVR broadcast menu 40 may be hierarchical, and in the same level, the item containing the priority broadcast menu node is placed on the same level. Front position. The second IVR broadcast menu 40 may also not be hierarchical.
  • the generating module 130 can adjust (not broadcast) one or more nodes that are rarely used by the old customer, in addition to adjusting the nodes with high usage probability of the old customers to the priority position of the IVR broadcast menu, for example, Card activation and other nodes.
  • the generation module 130 For other clients, the generation module 130 generates a default third IVR broadcast menu 50. As shown in FIG. 8, it is a schematic diagram of the third IVR broadcast menu 50 generated by the generating module 130 for other clients. It should be noted that FIG. 8 is also only an exemplary menu. In practical applications, the third IVR broadcast menu 50 may be hierarchical or non-hierarchical.
  • FIG. 5 is a flowchart of a preferred embodiment of a menu playing method of a dynamic voice interaction system of the present application.
  • Step S210 when the client accesses the IVR system 10 through the client 3 (for example, a mobile phone), the receiving module 140 receives customer information input by the client, such as identity information, card number information, and the like.
  • step S220 the determining module 120 determines which type of customer the customer is based on the degree of association between the customer information input by the customer and the historical behavior data 20.
  • the judgment basis please refer to the above judgment unit 120 to judge the judgment basis of new customers, old customers and other customers.
  • the identity information and card number information input by the customer are not recorded in the historical behavior data 20, the customer is a new customer.
  • step S230 the output module 150 obtains the corresponding IVR broadcast menu output from the memory 11 according to the judgment result of the determination module 120, for the customer to self-service the credit card service.
  • the output module 150 For example, if the customer currently requesting self-service is a new customer, the output module 150 outputs a first IVR broadcast menu 30. If the customer currently requesting self-service is an old customer, the output module 150 outputs a second IVR broadcast menu 40. If the client currently requesting self-service is another client, the output module 150 outputs a third IVR broadcast menu 50.

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Abstract

本申请提供一种动态语音交互系统，应用于计算装置。该系统包括:分析模块，用于分析客户办理信用卡业务的历史行为数据；判断模块，用于根据分析结果确定客户类别；及生成模块，用于为不同类别的客户生成个性化的 IVR播报菜单。本申请还提供一种动态语音交互系统的菜单生成方法。

Description

动态语音交互系统及其菜单生成方法
本申请要求于2017年5月5日提交中国专利局，申请号为2017103119834、发明名称为“动态语音交互系统及其菜单生成方法”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。
技术领域
本申请涉及自动语音应答技术，尤其涉及一种动态语音交互系统及其菜单生成方法。
背景技术
在客服系统中，自动语音应答(InteractiveVoice Response，IVR)与人工服务是运营商与客户交互的两个重要的通道。自动语音应答可以通过自动流程与客户进行信息交互，完成简单明确的查询、咨询、业务办理等功能，具有快捷、清晰、合理、简便、运营成本低的特点。人工服务具有人性化、个性化、体现尊贵服务的特点。
目前，信用卡服务提供商提供的IVR系统，一般都是根据服务商提供的业务范围、业务类型等因素，为所有的客户提供统一的、固定的IVR菜单。在这种IVR系统中，IVR菜单的所有自助节点平铺式播报，无法识别信用卡客户的不同需求。这会导致两个问题，一是长时间的语音播报令客户感觉使用困难，倾向于转接人工服务；二是转人工量的增多会导致话路繁忙时产生更多的呼叫损失，造成信用卡客户满意度降低。
发明内容
鉴于以上内容，有必要提供一种动态语音交互系统及其菜单生成方法，可以不同需求的信用卡客户输出最符合该客户需求的、个性化的IVR播报菜单。
本申请提供一种动态语音交互系统，该系统包括:
分析模块，用于分析客户办理信用卡业务的历史行为数据；
判断模块，用于根据分析结果确定客户类别；及
生成模块，用于为不同类别的客户生成个性化的IVR播报菜单。
本申请还提供一种动态语音交互系统的菜单生成方法，该方法包括以下步骤：
历史数据分析步骤：分析客户办理信用卡业务的历史行为数据；
客户类别判断步骤：根据分析结果判断客户类别；及
菜单生成步骤：为不同类别的客户生成个性化的IVR播报菜单。
相较现有技术，本申请提供的动态语音交互系统及其菜单生成方法，可以通过分析信用卡客户办理信用卡业务的历史行为数据，对信用卡客户进行分类，为不同类别的客户生成个性化的IVR播报菜单。
附图说明
图1为本申请动态语音交互系统较佳实施例的应用环境图。
图2为本申请动态语音交互系统较佳实施例的运行环境图。
图3为本申请动态语音交互系统较佳实施例的程序模块图。
图4为本申请动态语音交互系统的菜单生成方法较佳实施例的流程图。
图5为本申请动态语音交互系统的菜单播放方法较佳实施例的流程图。
图6、图7、图8是本申请动态语音交互系统生成不同IVR菜单的示意图。
具体实施方式
如图1所示，是本申请动态语音交互(InteractiveVoice Response，IVR)系统10较佳实施例的应用环境图。该IVR系统10应用于服务器1。服务器1通过网络2连接多个客户端3。网络2可以为局域网，广域网，城域网等等类型的网络，可以为有线网络，也可以为无线网络。客户端3可以为桌上型计算机、笔记本、平板电脑、手机，或其它可以通过网络2与服务器1进行通信的终端装置。
如图2所示，是本申请IVR系统10较佳实施例的运行环境图。服务器1包括，但不仅限于，存储器11、处理器12及显示器13。
存储器11存储IVR系统10的程序代码，该存储器11可以包括至少一种类型的存储介质，所述存储介质包括闪存、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、光盘等等。
处理器12从存储器11读取并执行IVR系统10的程序代码，提供IVR系统10的下述功能。显示器13显示处理器12执行IVR系统10的程序代码的结果。图2仅示出了具有组件11-13的服务器1，应当理解的是，服务器1可以包括更多或者更少的组件。
如图3所示，是本申请IVR系统10较佳实施例的程序模块图。存储器11存储有客户办理信用卡业务的历史行为数据20。
历史行为数据20可以是IVR系统10保存的历史行为数据，也可以是其他网络实体提供的历史行为数据，还可以是IVR系统10保存的历史行为数据和其他实体提供的历史行为数据的总和。例如，信用卡客户通过IVR系统10办理信用卡业务时，IVR系统10可以记录客户的行为数据，当需要收集客户的历史行为数据时，可以直接收集这些之前记录的行为数据。再例如，客户通过IVR系统10办理信用卡业务时，IVR系统10可以将客户的行为数据提供给其他实体，当需要收集客户的历史行为数据时，可以从其他网络实体收集行为数据。历史行为数据可以为服务机构某一段时间(例如最近一个月)所有客户的历史行为数据或者部分客户(例如某地区)的历史行为数据。
所述历史行为数据20包括客户身份相关信息，例如手机号码、身份证号等，客户名下信用卡相关信息，例如数量、信用卡类型、卡号、额度、有效期、还款日、每张信用卡的当前状态(例如正常、盗刷、欠费、冻结)等信息，客户每次使用信用卡的相关信息，例如消费金额、消费场所等，以及客户每次使用IVR系统10操作信用卡的自助信息，例如客户使用过IVR系统菜单中的哪些自助节点、每个自助节点的使用次数、频率等。
该IVR系统10包括分析模块110、判断模块120、生成模块130、接收模块140及输出模块150。
分析模块110，用于分析所述历史行为数据20。
分析历史行为数据20，是为即将生成的IVR菜单提供依据。具体的，可以统计客户办理信用卡每种类型业务的相关信息，再将统计后的信息作为生成IVR菜单的依据。
例如，客户通过IVR系统10办理信用卡业务一般包括：卡片激活、密码设置、账单查询、账单分期、还款、额度申请等操作。如果一个客户有多张信用卡，那么该多张信用卡对应的客户身份信息是相同的，例如两张信用卡预留的身份证号是相同的、手机号码也可能是相同的。对于信用卡老客户，使用IVR 系统10多是进行账单查询、账单分期、还款、申请额度变更等操作。因客户需求不同，有的客户可能经常使用IVR系统10进行账单查询、但从未使用过IVR系统10申请额度变更，有的可能经常使用IVR系统10申请额度变更、较少进行账单查询。
如下表1所示，分析模块110分析所述历史行为数据20，将信用卡客户的历史行为数据20予以分类整理。表1还可以增加其它维度，例如时间轴(例如上一个季度1-3月份)，统计出客户在不同时间段执行每种类型业务的次数。
Figure PCTCN2018085720-appb-000001
表1
判断模块120，用于根据分析结果判断客户类别。
所述客户类别包括：新客户、老客户及其他客户。
判断模块120根据分析结果判断客户类别包括：当该客户名下有已激活和未激活的信用卡，且未激活的信用卡距离该卡片可激活日期小于预设时间(例如小于等于30天)，或者该客户名下所有卡片都未激活时，确定该客户为新客户。
例如，身份证号为“36#######”的客户a名下有2张信用卡，其中一张信用卡已激活、但另一张信用卡当前尚未激活，该未激活的信用卡距离该卡片可激活日期有25天；身份证号为“”18#######”的客户b名下只有1张信用卡、且该信用卡未激活，则判断模块120判断客户a、客户b为新客户。
判断模块120根据分析结果判断客户类别还包括：当该客户不满足新客户的条件，或当该客户名下的所有信用卡均未发生管制事项时，确定该客户为老客户。
所述管制事项包括盗刷、欠费、冻结等。信用卡被管制后，客户无法正常使用。
判断模块120根据分析结果判断客户类别还包括：当该客户不满足新客户的条件，也不满足老客户的条件时，确定该客户为其他客户。
生成模块130，用于为不同类别的客户生成个性化的IVR播报菜单。
例如，针对新客户，生成模块130将卡片激活、密码管理节点设置至优先播报位置，生成第一IVR播报菜单30。例如图6是为新客户生成的第一IVR播报菜单30的示意图。需要说明的是，该图仅是示意性的菜单，在实际应用中，该第一IVR播报菜单30可以是分层级的，在同一层级中，将含有优先播报菜单节点的项目放置于靠前位置。该第一IVR播报菜单30也可以不分层级。
在其他实施例中，生成模块130除了可以将新客户使用概率大的节点调整至IVR播报菜单的优先位置，还可以隐藏(不播报)一个或多个极少被新客户使用到的节点，例如还款、账单分期等节点。
针对老客户，生成模块130将账单查询、还款、额度申请节点设置至菜单优先播报位置，生成第二IVR播报菜单40。例如图7是为老客户生成的第二IVR播报菜单40的示意图。需要说明的是，图7也仅是示意性的菜单，在实际应用中，该第二IVR播报菜单40可以是分层级的，在同一层级中，将含有优先播报菜单节点的项目放置于靠前位置。该第二IVR播报菜单40也可以不分层级。
在其他实施例中，生成模块130除了可以将老客户使用概率大的节点调整至IVR播报菜单的优先位置，还可以隐藏(不播报)一个或多个极少被老客户使用到的节点，例如卡片激活等节点。
针对其他客户，生成模块130生成默认的第三IVR播报菜单50。例如图8是为其他客户生成的第三IVR播报菜单50的示意图。需要说明的是，图8也仅是示意性的菜单，在实际应用中，该第三IVR播报菜单50可以是分层级的，也可以是不分层级的。
接收模块140，用于当客户通过客户端3(例如手机)接入IVR系统10时，接收客户输入的客户信息，例如身份信息、卡号信息等。
判断模块120，还用于根据客户输入的客户信息与历史行为数据20的关联程度，判断客户是哪一种类别的客户。
输出模块150，用于根据判断模块120的判断结果，从存储器11获取对应的IVR播报菜单输出，供客户自助办理信用卡业务。
例如，若当前请求自助服务的客户为新客户，输出模块150输出第一IVR播报菜单30。若当前请求自助服务的客户为老客户，输出模块150输出第二IVR 播报菜单40。若当前请求自助服务的客户为其他客户，输出模块150输出第三IVR播报菜单50。
图4为本申请动态语音交互系统的菜单生成方法较佳实施例的流程图。
步骤S110，分析模块110分析客户办理信用卡业务的历史行为数据20。
历史行为数据20可以是IVR系统10保存的历史行为数据，也可以是其他网络实体提供的历史行为数据，还可以是IVR系统10保存的历史行为数据和其他网络实体提供的历史行为数据的总和。例如，信用卡客户通过IVR系统10办理信用卡业务时，IVR系统10可以记录客户的行为数据，当需要收集客户的历史行为数据时，可以直接收集这些之前记录的行为数据。再例如，客户通过IVR系统10办理信用卡业务时，IVR系统10可以将客户的行为数据提供给其他网络实体，当需要收集客户的历史行为数据时，可以从其他网络实体收集行为数据。历史行为数据可以为服务机构某一段时间(例如最近一个月)所有客户的历史行为数据或者部分客户(例如某地区)的历史行为数据。
所述历史行为数据20包括客户身份相关信息，例如手机号码、身份证号等，客户名下信用卡相关信息，例如数量、信用卡类型、卡号、额度、有效期、还款日、每张信用卡的当前状态(例如正常、盗刷、欠费、冻结)等信息，客户每次使用信用卡的相关信息，例如消费金额、消费场所等，以及客户每次使用IVR系统10操作信用卡的自助信息，例如客户使用过IVR系统菜单中的哪些自助节点、每个自助节点的使用次数、频率等。
分析历史行为数据20，是为即将生成的IVR菜单提供依据。具体的，可以统计客户办理信用卡每种类型业务的相关信息，再将统计后的信息作为生成IVR菜单的依据。
步骤S120，判断模块120根据分析结果判断客户类别。
所述客户类别包括：新客户、老客户及其他客户。
判断模块120根据分析结果判断客户类别包括：当该客户名下有已激活和未激活的信用卡，且未激活的信用卡距离该卡片可激活日期小于预设时间(例如小于等于30天)，或者该客户名下所有卡片都未激活时，确定该客户为新客户。
例如，身份证号为“36#######”的客户a名下有2张信用卡，其中一张信用卡已激活、但另一张信用卡当前尚未激活，该未激活的信用卡距离该卡片可激活日期有25天；身份证号为“”18#######”的客户b名下只有1张信用卡、 且该信用卡未激活，则判断模块120判断客户a、客户b为新客户。
判断模块120根据分析结果判断客户类别还包括：当该客户不满足新客户的条件，或当该客户名下的所有信用卡均未发生管制事项时，确定该客户为老客户。
所述管制事项包括盗刷、欠费、冻结等。信用卡被管制后，客户无法正常使用。
判断模块120根据分析结果判断客户类别还包括：当该客户不满足新客户的条件，也不满足老客户的条件时，确定该客户为其他客户。
步骤S130，生成模块130为不同类别的客户生成个性化的IVR播报菜单。
例如，针对新客户，生成模块130将卡片激活、密码管理节点设置至优先播报位置，生成第一IVR播报菜单30。如图6所示，是生成模块130为新客户生成的第一IVR播报菜单30的示意图。需要说明的是，该图仅是示意性的菜单，在实际应用中，该第一IVR播报菜单30可以是分层级的，在同一层级中，将含有优先播报菜单节点的项目放置于靠前位置。该第一IVR播报菜单30也可以不分层级。
在其他实施例中，生成模块130除了可以将新客户使用概率大的节点调整至IVR播报菜单的优先位置，还可以隐藏(不播报)一个或多个极少被新客户使用到的节点，例如还款、账单分期等节点。
针对老客户，生成模块130将账单查询、还款、额度申请节点设置至菜单优先播报位置，生成第二IVR播报菜单40。如图7所示，是生成模块130为老客户生成的第二IVR播报菜单40的示意图。需要说明的是，图7也仅是示意性的菜单，在实际应用中，该第二IVR播报菜单40可以是分层级的，在同一层级中，将含有优先播报菜单节点的项目放置于靠前位置。该第二IVR播报菜单40也可以不分层级。
在其他实施例中，生成模块130除了可以将老客户使用概率大的节点调整至IVR播报菜单的优先位置，还可以隐藏(不播报)一个或多个极少被老客户使用到的节点，例如卡片激活等节点。
针对其他客户，生成模块130生成默认的第三IVR播报菜单50。如图8所示，是生成模块130为其他客户生成的第三IVR播报菜单50的示意图。需要说明的是，图8也仅是示意性的菜单，在实际应用中，该第三IVR播报菜单50可以是分层级的，也可以是不分层级的。
图5为本申请动态语音交互系统的菜单播放方法较佳实施例的流程图。
步骤S210，当客户通过客户端3(例如手机)接入IVR系统10时，接收模块140接收客户输入的客户信息，例如身份信息、卡号信息等。
步骤S220，判断模块120于根据客户输入的客户信息与历史行为数据20的关联程度，判断客户是哪一种类别的客户。判断依据请参考上文中判断模块120判断新客户、老客户、其他客户的判断依据。此外，若客户输入的身份信息、卡号信息在历史行为数据20未曾记录，那么该客户为新客户。
步骤S230，输出模块150根据判断模块120的判断结果，从存储器11获取对应的IVR播报菜单输出，供客户自助办理信用卡业务。
例如，若当前请求自助服务的客户为新客户，输出模块150输出第一IVR播报菜单30。若当前请求自助服务的客户为老客户，输出模块150输出第二IVR播报菜单40。若当前请求自助服务的客户为其他客户，输出模块150输出第三IVR播报菜单50。
需要说明的是，本实施方式中提到的“一个实施例”、“另一个实施例”可以为相同的实施例，也可以为不同的实施例。
最后所应说明的是，以上实施例仅用以说明本申请的技术方案而非限制，尽管参照较佳实施例对本申请进行了详细说明，本领域的普通技术人员应当理解，可以对本申请的技术方案进行修改或等同替换，而不脱离本申请技术方案的精神和范围。

Claims (20)

  1. 一种动态语音交互系统的菜单生成方法，其特征在于，该方法包括以下步骤：
    历史数据分析步骤：分析客户办理信用卡业务的历史行为数据；
    客户类别判断步骤：根据分析结果判断客户类别；及
    菜单生成步骤：为不同类别的客户生成个性化的IVR播报菜单。
  2. 如权利要求1所述的动态语音交互系统的菜单生成方法，其特征在于，所述历史数据分析步骤包括：采集客户使用语音交互系统的菜单节点信息，对客户使用的菜单节点信息进行统计，根据统计结果确定客户类别。
  3. 如权利要求2所述的动态语音交互系统的菜单生成方法，其特征在于，所述客户类别判断步骤包括：
    当所述当该客户名下有已激活和未激活的信用卡，且未激活的信用卡距离该卡片可激活日期小于预设时间，或者该客户名下所有卡片都未激活时，判断该客户为新客户；
    当该客户不满足新客户的条件，或当该客户名下的所有信用卡均未发生管制事项时，判断该客户为老客户；及
    当该客户不满足新客户的条件，也不满足老客户的条件时，判断该客户为其他客户。
  4. 如权利要求3所述的动态语音交互系统的菜单生成方法，其特征在于，所述菜单生成步骤包括：
    针对新客户，将卡片激活、密码管理节点设置至菜单优先播报位置；
    针对老客户，将账单查询、还款、额度申请节点设置至菜单优先播报位置；及
    针对其他客户，生成默认的播报菜单。
  5. 一种动态语音交互系统的菜单播放方法，其特征在于，该方法包括以下步骤：
    接收客户通过终端接入语音交互系统的客户信息：
    根据客户信息确定客户类别；以及
    根据确定的客户类别，为该客户输出个性化的IVR播报菜单。
  6. 一种动态语音交互系统，其特征在于，该系统包括:
    分析模块，用于分析客户办理信用卡业务的历史行为数据；
    判断模块，用于根据分析结果确定客户类别；及
    生成模块，用于为不同类别的客户生成个性化的IVR播报菜单。
  7. 如权利要求6所述的动态语音交互系统，其特征在于，所述分析模块分析所述历史数据包括：采集客户使用语音交互系统的菜单节点信息，对客户使用的菜单节点信息进行统计，根据统计结果确定客户类别。
  8. 如权利要求7所述的动态语音交互系统，其特征在于，所述判断模块根据分析结果确定客户类别包括：
    当所述当该客户名下有已激活和未激活的信用卡，且未激活的信用卡距离该卡片可激活日期小于预设时间，或者该客户名下所有卡片都未激活时，判断该客户为新客户；
    当该客户不满足新客户的条件，或当该客户名下的所有信用卡均未发生管制事项时，判断该客户为老客户；及
    当该客户不满足新客户的条件，也不满足老客户的条件时，判断该客户为其他客户。
  9. 如权利要求8所述的动态语音交互系统，其特征在于，所述生成模块为不同类别的客户生成个性化的IVR播报菜单包括：
    针对新客户，将卡片激活、密码管理节点设置至菜单优先播报位置；
    针对老客户，将账单查询、还款、额度申请节点设置至菜单优先播报位置；及
    针对其他客户，生成默认的播报菜单。
  10. 如权利要求6所述的动态语音交互系统，其特征在于，该系统还包括接收模块：
    接收模块，用于接收客户通过终端输入的客户信息；及
    输出模块：用于依据客户信息确定的客户类别，为该客户输出个性化的IVR播报菜单。
  11. 如权利要求7所述的动态语音交互系统，其特征在于，该系统还包括接收模块：
    接收模块，用于接收客户通过终端输入的客户信息；及
    输出模块：用于依据客户信息确定的客户类别，为该客户输出个性化的IVR播报菜单。
  12. 如权利要求8所述的动态语音交互系统，其特征在于，该系统还包括接收模块：
    接收模块，用于接收客户通过终端输入的客户信息；及
    输出模块：用于依据客户信息确定的客户类别，为该客户输出个性化的IVR播报菜单。
  13. 如权利要求9所述的动态语音交互系统，其特征在于，该系统还包括接收模块：
    接收模块，用于接收客户通过终端输入的客户信息；及
    输出模块：用于依据客户信息确定的客户类别，为该客户输出个性化的IVR播报菜单。
  14. 一种计算机可读存储介质，所述计算机可读存储介质内存储有动态语音交互系统，其特征在于，所述动态语音交互系统包括：
    分析模块，用于分析客户办理信用卡业务的历史行为数据；
    判断模块，用于根据分析结果确定客户类别；及
    生成模块，用于为不同类别的客户生成个性化的IVR播报菜单。
  15. 如权利要求14所述的计算机可读存储介质，其特征在于，所述分析模块分析所述历史数据包括：采集客户使用语音交互系统的菜单节点信息，对客户使用的菜单节点信息进行统计，根据统计结果确定客户类别。
  16. 如权利要求15所述的计算机可读存储介质，其特征在于，所述判断模块根据分析结果确定客户类别包括：
    当所述当该客户名下有已激活和未激活的信用卡，且未激活的信用卡距离该卡片可激活日期小于预设时间，或者该客户名下所有卡片都未激活时，判断该客户为新客户；
    当该客户不满足新客户的条件，或当该客户名下的所有信用卡均未发生管制事项时，判断该客户为老客户；及
    当该客户不满足新客户的条件，也不满足老客户的条件时，判断该客户为其他客户。
  17. 如权利要求16所述的计算机可读存储介质，其特征在于，所述生成模块为不同类别的客户生成个性化的IVR播报菜单包括：
    针对新客户，将卡片激活、密码管理节点设置至菜单优先播报位置；
    针对老客户，将账单查询、还款、额度申请节点设置至菜单优先播报位置； 及
    针对其他客户，生成默认的播报菜单。
  18. 如权利要求14所述的计算机可读存储介质，其特征在于，该系统还包括接收模块：
    接收模块，用于接收客户通过终端输入的客户信息；及
    输出模块：用于依据客户信息确定的客户类别，为该客户输出个性化的IVR播报菜单。
  19. 如权利要求15所述的计算机可读存储介质，其特征在于，该系统还包括接收模块：
    接收模块，用于接收客户通过终端输入的客户信息；及
    输出模块：用于依据客户信息确定的客户类别，为该客户输出个性化的IVR播报菜单。
  20. 如权利要求16-17任一项所述的计算机可读存储介质，其特征在于，该系统还包括接收模块：
    接收模块，用于接收客户通过终端输入的客户信息；及
    输出模块：用于依据客户信息确定的客户类别，为该客户输出个性化的IVR播报菜单。
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