CN110245287B - 分析驱动参与 - Google Patents
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Abstract
本发明公开了分析驱动参与。各种实施方式涉及基于形成和修改的参与规则发起代理设备和用户设备之间的联系的参与服务器和相关方法。在一个实施方式中,参与服务器可接收一个或多个第三方分析报告并使用它们,以形成确定参与服务器何时发起代理设备和用户设备之间的联系的参与规则。在一些实施方式中,参与服务器还可从用户设备接收用户交互数据来修改参与规则以适应特定用户。在一些实施方式中,参与服务器可使用第三方分析报告和/或来自多个用户的用户交互数据以形成统计模型。然后,参与服务器可使用统计模型来形成和/或修改参与规则。
Description
本申请是申请日为2013年2月7日、申请号为201380019406.8、发明名称为“分析驱动参与”的中国专利申请的分案申请。
技术领域
本文公开的各种示例性实施方式总体涉及用于分析驱动参与的在计算机上执行的方法和基于计算机的装置,包括计算机程序产品。
背景技术
公司可以以各种方式使用其网站来向其消费者传达信息。例如,在消费者做出购买决定之前,公司可以配置其网站为消费者提供信息。在其它情况下,公司可以通过其网站直接为其消费者提供其产品和/或服务,通过支持网提供消费者服务,和/或收集有关其潜在消费者的具体信息。
为了实现这样广泛的服务(该服务是这个时代的消费者会期望从因特网公司获得的),许多公司必须采用大且稳健的网站并保持大网站的存在。创建如此大且复杂的网站的结果之一是许多消费者不容易找到他们期望的信息或服务。例如,消费者可以在公司的网站上导航到期望的位置(例如网页),但是许多消费者在到达期望的位置后并不知道采取适当的下一步(例如,如何完成购买交易,如何将显示的产品与其它产品进行比较,等等)。确定何时联系网站的用户(例如,提供在线聊天帮助、发送优惠券和发送广告等)常常是困难的。
发明内容
本文公开的方法和装置可以在用户需要帮助(例如,通过消费者服务代理提供在线聊天、提供优惠券等)时允许网站联系网站用户(或使用户参与)。可以使用与用户和网站的交互相关联的动作或其它特性来决定网站何时应联系消费者(例如,提供帮忙)。
提出了各种示例性实施方式的简要概述。在以下概述中做了一些简化和省略,其目的是突出介绍各种示例性实施方式的一些方面,而不限制本发明的范围。足以使本领域的普通技术人员制造和使用本发明构思的优选示例性实施方式的详细说明会跟在后面的章节。
在一个实施方式中,表征了一种基于用户与网站的交互自动调整参与规则的计算机化的方法。该方法包括服务器计算机存储用于网站的一组参与规则,其中每个参与规则定义了这样的准则:如果满足该准则,则该准则使网站联系网站的用户。该方法包括服务器计算机接收指示一组用户与网站的交互的数据,其中该数据由第三方数据提供者生成。该方法还包括服务器计算机基于接收到的数据自动调整该组参与规则中的一个或多个生成的规则。
在另一个实施方式中,表征了一种有形地包含在永久性计算机可读介质中的计算机程序产品。该计算机程序产品包括被配置为使数据处理装置存储用于网站的一组参与规则的指令,其中每个参与规则定义了这样的准则:如果满足该准则,则该准则使网站联系网站的用户。该计算机程序产品包括被配置为使数据处理装置接收指示用户与网站的一组交互的数据的指令,其中该数据由第三方数据提供者生成。该计算机程序产品包括被配置为使数据处理装置基于接收到的数据自动调整该组参与规则中的一个或多个生成的规则的指令。
在另一个实施方式中,表征了一种用于基于用户与网站的交互自动调整参与规则的装置。该装置包括处理器和存储器。该装置被配置为存储用于网站的一组参与规则,其中每个参与规则定义了这样的准则:如果满足该准则,则该准则使网站联系网站的用户。该装置被配置为接收指示用户与网站的一组交互的数据,其中该数据由第三方数据提供者生成。该装置被配置为基于接收到的数据自动调整该组参与规则中的一个或多个生成的规则。
在其它示例中,以上任一方面包括一个或多个下列特征。在一些示例中,服务器计算机接收指示用户与网站的第二组交互的第二数据,其中该第二数据由不同于第三方数据提供者的第二个第三方数据提供者生成。在一些示例中,服务器计算机基于接收到的数据和接收到的第二数据生成统计模型。接收到的数据和接收到的第二数据均可包含一个或多个参数。生成统计模型可包括使用主分量分析(PCA)将来自接收到的数据的第一参数和来自接收到的第二数据的第二参数相关联。
在一些示例中,统计模型可指示用户与网站的交互。接收到的数据可包含网站分析报告。联系用户可包括传送弹出窗口给用户。自动调整可包括在该组参与规则中创建新的参与规则。自动调整可包括改变在该组参与规则中现有的参与规则。
应当明显的是,以这种方式,各种示例性实施方式实现在网站上的代理和用户之间的动态联系(或其它用户联系,例如提供有针对性的广告、提供优惠券等)。特别地,通过使用分析报告和建模,代理可以在预定义的条件下联系用户,这将导致代理和用户之间更有意义的联系。
本文中描述的包含方法和装置的技术可提供一个或多个下列优点。一个或多个第三方分析工具与分析报告的合并允许该系统确定何时联系用户(例如,基于稳健统计),以更可能引起代理和用户之间的成功的联系(例如,对用户来说有用的联系、促进产品或服务销售的联系等)。自动整合这样的分析工具和其余的参与系统消除手动创建和保持定义了系统何时联系用户的准则的参与规则的需求。从以下结合附图仅以示例的方式说明本发明的原理的详细说明中,实施方式的其它方面和优点将变得明显。
附图说明
为了更好地理解各种示例性实施方式,参照了附图,其中:
图1示出了示例性的分析驱动参与系统;
图2示出了发起联系的示例性方法的流程图;以及
图3示出了发起联系的另一示例性方法的流程图。
具体实施方式
现在,参考附图(附图中相同的附图标记指的是相同的部件或步骤),公开了各种示例性的实施方式的主要方面。
总的来说,为分析驱动参与系统提供了计算机化的系统和方法,该分析驱动参与系统至少基于分析报告和/或分析工具发起与用户的联系(例如,消费者服务代理和用户之间的联系)。分析报告和工具均可在内部生成且可从第三方接收。例如,联系可包括代理和用户之间的直接通信(例如,在线文本聊天、语音聊天、视频聊天等)。联系还可包括基于用户与网站的交互的其它形式的动作。例如,可为用户呈现指导性的文本或视频(例如,基于用户在网站采取的操作而自动生成的)、优惠券(例如用于在网站上提供的产品和/或用于与网站内容相关的产品)、文章、社区创建内容、社交媒体内容(例如,Facebook、Twitter)等。参与服务器可在用户连接到网站或网页时监控用户的行为。参与服务器使用由至少分析工具动态形成的参与规则,等待直到在联系用户之前该参与规则能够满足。在一些实施方式中,参与服务器可以从其它用户的活动数据形成该参与规则。在一些实施方式中,参与服务器可通过在用户设备和代理设备上的聊天会话的创建来发起代理和用户之间的联系,聊天会话的创建使得用户和代理之间可以进行直接通信。在一些实施方式中,参与服务器可发起另一形式的启动,例如提供如广告的具体内容。
图1示出了示例性分析驱动参与系统100,包括用户设备101、网络服务器103、网络107、参与服务器111、参与数据库(DB)113、代理设备115、第三方服务器121A-121B和第三方数据库123A-123B。用户设备101包括连接至网络服务器103的网络浏览器102。网络浏览器102还可包括标签104。在示例性实施方式中,用户设备101与网络服务器103通信,而参与服务器111与参与DB 113和代理设备115通信。在一些实施方式中,参与服务器111可通过网络浏览器102中的标签104使用户设备101和代理设备115之间进行通信(例如,标签104确定满足参与规则,并通过参与服务器111建立用户设备101的用户和代理设备115之间的聊天会话)。在一些实施方式中,参与服务器111可通过网络服务器103和网络107接收来自标签104的信息,其中网络服务器103和网络107在参与服务器111和标签104之间传递信息(例如,如通过连接117示出)。
例如,网络107可以是分组交换网络,其基于包含在数据包中的信息将数据包转发给其它设备。例如,网络107可为诸如与网络107通信的用户设备101和代理设备115的各种设备提供电话和/或互联网服务。
例如,参与服务器111可以是具有处理器和存储器的单个网络服务器。在一些实施方式中,参与服务器111可包括多个直接连接或通过网络107连接的网络服务器。例如,代理或代理公司可在其认为合适的时间(例如,由参与规则定义)通过连接其代理和其消费者(或用户)来提高品牌管理和/或消费者服务。有利地,参与服务器111可从特定的用户设备101(例如从标签104)接收用户交互数据并使用各种参与规则来决定何时联系用户设备101(例如,通过代理设备115和用户设备101发起代理和用户之间的联系)。在一些实施方式中,参与服务器111可检索其它数据(例如存储在参与数据库(DB)113中的用户分析)来形成和/或修改其参与规则。参与服务器111还可在参与数据库113中存储参与规则。在一些实施方式中,参与服务器111可在形成和/或修改存储的参与规则时通过第三方服务器121A-121B从第三方数据库123A-123B中检索一个或多个第三方分析,例如第三方分析报告。参与服务器111还可为用户设备101和代理设备115提供其它软件。例如,参与服务器111可为用户设备101和代理设备115提供聊天软件以方便用户设备101和代理设备115之间的聊天会话。
参与数据库(DB)113可以是与参与服务器111通信的数据库,其为参与服务器111提供用户分析。在一些实施方式中,参与DB 113可通过直接连接与参与服务器111通信。在其它实施方式中,参与DB 113可通过网络107与参与服务器111通信。在一些实施方式中,参与数据库113可存储参与规则。在一些实施方式中,参与DB 113可存储由参与服务器111接收的网络分析。在一些实施方式中,参与DB 113可随着时间的推移积累和存储由参与服务器111从多个用户设备101接收的用户交互数据。在一些实施方式中,参与DB 113可存储由参与服务器111形成的统计模型。参与服务器111可在形成和更新参与规则、统计模型和积累的用户交互数据时访问参与DB 113。参与服务器111可在形成或修改参与规则和/或统计模型时使用存储在参与DB 113中的信息和其它信息,例如从其它源检索到的第三方网络分析。
第三方数据库(DB)123A-123B可以是通过网络107和第三方服务器121A-121B与参与服务器111通信的一个或多个数据库。例如,每个第三方服务器121A-121B可以是具有处理器和存储器的单台网络服务器,其受除用户或代理之外的一方控制。第三方DB 123A-123B可累积和存储网络分析,参与服务器111在形成和修改其参与规则和/或统计模型时可访问该网络分析。在一些实施方式中,存储在第三方DB 123A-123B中的网络分析可以是静态的网络分析报告。在其它实施方式中,第三方DB可包括由第三方连续更新的网络分析报告。在一些实施方式中,参与服务器111可在形成和修改其参与规则时或在形成和修改其统计模型时,访问存储在一个或多个第三方DB中的静态的和/或更新的网络分析报告。例如,参与服务器111可连接至第一个第三方DB 123A来检索静态的第三方报告,连接至第二个第三方DB 123B来检索更新的第三方报告,和/或连接至参与DB 113来检索累积的用户交互数据以形成用于用户的统计模型。
在一些实施方式中,使用偏最小二乘法预测潜在的结构(PLS)、主分量分析(PCA)、或PLS和PCA的结合来生成统计模型。PCA和PLS分析的进一步的细节可以在“Multi-andMegavariate Data Analysis,Part I,Basic Principles and Applications”(Eriksson等,Umetrics Academy,2006年1月)和“Multi-and Megavariate Data Analysis,Part II,Advanced Applications and Method Extensions”(Eriksson等,Umetrics Academy,2006年3月)中找到,其全部内容通过引用并入本文。
PLS是多变量分析工具,通常用来分析数据。PLS是通过线性多变量模型将两个数据矩阵X和Y相互关联的方法。在其最简单的形式中,线性模型指定因变量或响应变量y、或一组响应变量Y与一组预测变量X之间的关系。例如,响应变量y是用户指定的不规则物体的质量,预测变量X是测量的不规则物体的数据。
PLS分量包括X分数t、Y分数u,权重w和c,以及载荷p的向量。PLS模型的PLS分量传统上使用非线性迭代偏最小二乘(NIPALS)算法来计算。在NIPALS算法上有很多变化,其包括矩阵向量乘法(例如X’y)来生成权重向量w。矩阵向量乘法通过一组向量-向量乘法Xk’×y来计算,得到标量结果wk。
PLS可以以图形的形式呈现。例如,考虑利用N个观察结果、3个X变量(因子/预测)和1个y变量(响应)的回归应用。此处,X矩阵的大小通过N个观察结果是3列,以及Y矩阵的大小通过N个观察结果是1列。由于有两个矩阵,每行(或N个观察结果中的每一个观察结果)对应于两个点,一个点在X矩阵的X空间以及一个点在Y矩阵的Y空间。当针对所有N个观察结果绘制数据表时,在X空间有一簇N个点以及在Y空间有一簇N个点。第一PLS分量是在X空间的线或向量,其接近该簇点并提供与y向量的良好相关性。在计算第一PLS分量时,通过将样本投射到线上来得到观察结果i的分数ti1,可以获得沿着第一分量向量的观察结果i的坐标。所有观察结果的分数形成第一X分数向量t1。通过将t1乘以y向量量的权重c1,可以确定y的模型估计。
其中:
c1是y向量的权重;以及
t1是第一X分数向量。
通常,一个PLS分量不足以充分模拟y数据中的变化。使用第二PLS分量以在PLS模型上扩展。第二PLS分量也是X空间中的线,其通过原点并与第一PLS分量正交。在计算第二PLS分量后,得到第二分数向量t2以及权重c2和w2:
其中:
c1是第一y向量的权重;
t1是第一X分数向量;
c2是第二y向量的权重;以及
t2是第二X分数向量。
重复该PLS分量生成过程直到达到期望数量的PLS模型的分量。额外地,其可以通过单个响应y或多个响应Y来实现。
NIPALS算法的向量-向量乘法生成的结果与通过原点b=(x’y)/(x’x)的线的斜度的最小二乘估计类似,其中x’x是常量。此外,分为三个部分的分类数据集的部分平均给出了b=(yy3-yy1)/(xx3-xx1)的良好的估计,其中y的最高三分之一的平均为yy3,y的最低三分之一的平均为yy1,x的最高三分之一的平均为xx3,x的最低三分之一的平均为xx1。虽然部分平均可以是b的良好的估计,但是部分平均会受到外部的分布尾部的影响。此外,PLS分量的计算基于在处理系统中可获得的存储器的数量而被限制。随着大量的数据存储可以以更低的价格获得,数据集的大小与在处理系统中可获得的计算机存储器相比变得越来越大。因此,对大数据集的PLS处理变得耗时。此外,标准的PLS使X和Y矩阵均缩小以通过常向量减法来加速计算。
PCA是多变量投影方法,其被设计成提取和显示数据矩阵X中的系统变化来展现多组观察结果、趋势和离群值。数据矩阵X是具有N行(观察结果)和K列(变量)的数据矩阵。例如,观察结果可以是分析样本、化合物或化学反应、连续处理的处理时间点、批处理中的批次、生物个体、DOE协议的踪迹和其它测量值。为了表征观察结果的属性,测量了变量。例如,该变量可以具有光谱的原点、色谱的原点或在一个过程中的来自传感器的测量结果(例如,温度、流、压力、曲线等)。
在一些实施方式中,数据被预处理(例如,通过缩放和均值中心化,下文更详细地描述)。一旦进行预处理(如果有的话),则计算第一主分量(PC1),即在最接近最小二乘意义上的数据的K维空间中的线。该线通过平均点,以及每个观察结果被投射至该线来计算该观察结果的分数。使用额外的主分量可以扩展该模型。通常,一个主分量不足以模拟数据集的系统变化。例如,也通过在K维空间中的线表示第二主分量,其与第一PC正交。该线也通过平均点,并尽可能提高X数据的近似。
为了确定哪个变量对在观察结果中看到的样式负责,分析了主分量载荷,即向量p1和p2。在几何学上,主分量载荷表示在K维变量空间中的模型平面的方向。通过用于每个变量的角的余弦给出了与原始变量相关的PC1的方向。例如,对于三个变量,其方向为α1、α2和α3。这些值表明了原始变量(例如,三个变量矩阵的x1、x2和x3)如何加载或作用在PC1上。第二组载荷系数表示与原始变量相关的PC2的方向。
通过使用PCA,数据表X被建模为:
其中:
T*P'模拟该结构;以及
E包含噪声。
主分量分数是分数矩阵T的列(例如,第一、第二和第三分量的分数为t1、t2和t3)。这些分数是模型中的观察结果的坐标。分数可以以重要性下降的方式分类(例如,t1比t2说明更多的变化)。如上所述,载荷给出了分数的含义,其建立了载荷矩阵P(第一、第二和第三分量的载荷为p1、p2和p3)。载荷证明了测量的变量对分数的作用的大小(例如,大或小的相关性)和方式(例如,正的或负的相关性)。
在一些实施方式中,在执行PCA和/或PLS之前预处理数据矩阵。例如,在使用PLS时,通过预处理方法变换、居中和/或缩放一个或多个矩阵(例如,矩阵X和/或矩阵Y)。类似地,在PCA之前,数据可以被预处理成适合分析的形式(例如,重塑数据以更好地完成重要的假设)。PLS建模在数据通常对称分布并具有恒定误差方差时工作得最好。变化多于十倍的变量可以在分析之前被对数变换以除去不想要的行为。变换变量可以提高多变量模型的预测力和可解释性。例如,包括作为离群值的测量值的数据集可过度影响模型建立。在数据分析之前以一些方式操纵这样的测量值可避免该测量值在模型上施加大的影响,导致该测量值支配其它测量值。例如,可以除去离群值来最小化测量值在模型上的影响。
为了在随后的分析中给出权重相对或近似相等的矩阵的变量(即列),可以对数据进行列式变换、缩放和/或居中。通常使用变量的变换以使其分布更对称。例如,可以使用对数变换、负对数缩放、分对数缩放、平方根缩放、四次方根缩放、逆缩放或幂变换缩放。
对于许多类型的数据,居中和缩放是缠结在一起的。居中对应于参考向量的减法,其中缩放变量涉及将变量乘以缩放向量。缩放向量的选择是关键的。在遇到变量的原点和数值范围不同的情况下,通常选择缩放向量作为变量的逆传播。在其它情况下,例如在具有处理数据的情况下,可相对变量中可容忍的传播定义缩放向量。
缩放向量表示在线上的许多观察结果,从而点的定位在一些数学意义上与一个或多个与观察结果相关的准则有关。缩放过程涉及根据预定义的准则(例如,将每个坐标轴的长度设置成相同的方差)调节变量空间中的坐标轴的长度。缩放数据的常用技术为“单位方差”“UV”缩放或“自动缩放”。单位方差缩放涉及计算数据集中的特定变量的标准偏差。缩放权重被计算为标准偏差的倒数。将变量的每个值乘以缩放权重来确定缩放变量。在数据矩阵中的所有变量被缩放后,每个变量(即坐标轴)具有单位方差。
在图1中,例如,网络服务器103可以是具有处理器和存储器的单台网络服务器。在其它实施方式中,网络服务器103可以是被配置为提供网络服务给用户设备101的多个网络服务器。网站可提供标签104和网站代码(例如,HTML代码),包括代码(例如JavaScript代码),当该代码由用户设备101上的网络浏览器102执行时,会监控与显示在网络浏览器102上的网站相关的用户活动。在一些实施方式中,代替标签104或除标签104以外,由网络服务器103提供的网站可提供应用程序接口(API),其方便监控用户活动,例如监控信息中的关键字,或在网站内使用的其它数据(例如,可由用户设备101观看的数据)。API可以是由网站实现的接口,使得其它软件程序可以与网站交互。在一些实施方式中,网络服务器103可提供相同的网站,该网站通过网络浏览器102在用户设备101上观看和在代理设备115(例如,通过代理设备115上的网络浏览器,未示出)上观看。在这样的情况下,在代理设备115和用户设备101上观看的网站可能是不同的。
用户设备101可以是具有处理器和存储器的计算设备,可通过其网络浏览器102与网站交互。例如,用户设备101可包括连接至网络107的台式电脑、笔记本电脑、平板电脑和/或移动电话。用户设备101的用户可使用用户设备101来连接至由网络服务器103提供的网站并可以通过参与服务器111参与代理设备(例如,代理设备115)。
网络浏览器102可以是由用户设备使用以通过网络107连接至其它设备的软件。在一些实施方式中,在连接至网络107之前,用户设备可连接至网络服务器103。在其它实施方式中,网络服务器103可通过网络107连接至用户设备101。
标签104可以是编码标签,例如HTML标签,其可以包含在网络服务器103通过网络浏览器102提供给用户设备101的网页中。在一些实施方式中,标签104可以是存储在用户设备101的存储器中的标签模块,该用户设备101与网络服务器103通信和/或通过连接117与参与服务器111通信。例如,当用户使网络浏览器102加载网页时,网络浏览器102处理标签104,其导致网络浏览器102从网络服务器103下载默认标签代码(例如,JavaScript代码文件)。在一些实施方式中,参与服务器111可提供默认标签代码给网络浏览器102。网络浏览器102可接收、处理和执行默认标签代码来生成标签。默认标签代码可包括监控和传输指示用户与网页的交互的信息(例如,用户交互数据)给网络服务器103和/或参与服务器111的代码/指令。例如,用户交互数据可包括鼠标点击、表单条目和统一资源定位符(URL)历史。一个或多个用户交互的结合可触发参与服务器111的动作,以下参考图2和图3进行描述。
代理设备115可以是具有处理器和存储器的计算设备,可连接至参与服务器111并可与用户设备101通信。例如,代理设备115可包括连接至网络107的台式电脑、笔记本电脑、平板电脑和/或移动电话。使用代理设备115的代理可使用代理设备115以通过由参与服务器111发起的联系(例如,聊天、视频聊天、电话聊天等)连接至用户设备。一旦发起联系,则代理设备115和用户设备101可通过网络107相互通信。例如,这可允许代理和用户之间的通过诸如即时聊天会话的交互的联系。
图2示出了用于发起联系用户(例如,浏览网站的用户)的示例性方法200的流程图。例如,参与服务器111可运行方法200来确定是否将代理设备115连接至用户设备101。方法200开始于步骤201并进行到步骤203,其中参与服务器111接收和存储参与规则(例如,将参与规则接收并存储在参与DB 113中)。这些参与规则可以是用于确定何时(例如,基于某些用户与网站的交互、基于预配置的时间量的流逝等)将代理设备115连接至用户设备101以用于直接联系(或介导联系)、或用于网络服务器103或参与服务器111提供具体内容给用户设备101(例如,优惠券、有针对性的广告等)的规则。例如,参与规则可被配置成这样,参与服务器111在用户设备101已经在网站内的相同网页上停留了特定时间段时发起代理设备115和用户设备101之间的聊天会话。在一些实施方式中,参与规则可以基于先前的第三方分析生成。例如,参与服务器111可从第三方数据库123A-123B检索一个或多个第三方分析报告,该第三方分析报告可以指示用户一旦到达特定网页(例如,“FAQ”或“帮助”网页)则具有更高的跳出率。之后,参与服务器111可创建和存储参与规则,该参与规则在用户设备101正在访问这些特定的“高跳出”网页之一时包括缩短的定时器。
接着,参与服务器111可进行到步骤205,其中参与服务器111从用户设备101接收用户交互数据。例如,包含在用户设备101中的标签104(例如,从网络服务器103下载)可跟踪和记录网络浏览器102内的用户交互数据。在一些实施方式中,标签104发送用户交互数据给网络服务器103,网络服务器103之后可以通过网络107发送该用户交互数据给参与服务器111。在一些实施方式中,标签104通过连接117直接发送用户交互数据给参与服务器。在一些实施方式中,标签104可以以标准时间间隔将用户交互数据以数据包发送给参与服务器111,其中参与服务器111可累积数据包。在其它实施方式中,标签104可以等待触发来发送用户交互数据给参与服务器111。例如,这可减小发送给参与服务器111的用户交互数据的量。
在接收到用户交互数据后,参与服务器111随后可以进行到步骤207,其中参与服务器111可调整参与规则。在一些实施方式中,例如,参与服务器111可将先前存储的参与规则调整为基于不同条件触发。例如,参与服务器111在步骤205可能接收到指示用户在转到网站内的其它网页之前在每个网页上花了比平均时间更长的时间的用户交互数据。则参与服务器111可将参与规则调整为具有更长的触发时间,使得参与服务器111在更长的时间段后发起代理设备115和用户设备101之间的联系(例如,以防止在用户可能需要帮助之前发起联系)。
在步骤209中,参与服务器111确定其是否接收到指示满足参与规则的数据。在一些实施方式中,参与服务器111可监控在步骤205接收到的用户交互数据并将该用户交互数据与多个参与规则进行比较,从而在多个参与规则中的任何一个的条件满足时发起代理设备115和用户设备101之间的联系。例如,参与服务器111可以正在使用这样的参与规则:该参与规则等待直到用户已经在特定网页(例如FAQ网页)上停留了至少特定的持续时间。当参与服务器111检查接收到的用户交互数据以确定用户已经在特定网页上停留超过特定的持续时间时,则参与服务器可以进行到步骤211并发起与用户设备101之间的联系(例如,向用户设备101呈现弹出消息、在用户设备101和代理设备115之间建立服务会话(例如,聊天会话、视频会话等)等)。否则,参与服务器111可以返回步骤209(例如,分析新接收的用户交互数据)以确定其任何参与规则是否已经满足。
在步骤211中,参与服务器111可发起与用户的联系。例如,参与服务器111可通过代理设备115和用户设备101发起代理和用户之间的聊天会话。在一些实施方式中,参与服务器111可通过其它方法来发起与用户的联系,例如基于满足的参与规则提供额外的文本或视频指令。例如,参与服务器111可监控关于用户比较两个或更多同类产品的参与规则。一旦参与服务器111确定已经满足比较参与规则,则参与服务器111可提供存储的两个或更多同类产品的视频比较。在一些实施方式中,参与服务器可通过JavaScript和HTML使用其它方法来联系用户设备101。例如,这可以包括为网络浏览器102提供横幅、工具提示、悬停文本和类似的方法为用户提供更多的信息。一旦已经发起联系,则参与服务器111可在步骤213停止方法200。
图3示出了发起联系的另一示例性方法的流程图。与方法200类似(例如,由参与服务器111执行),参与服务器111可执行方法300来将来自各种源的网络分析和接收到的用户交互数据合并以确定是否发起与用户设备101的联系。方法300开始于步骤301并进行到步骤303,其中参与服务器111接收和存储一个或多个参与规则。与步骤203类似,参与服务器111可接收可以指示何时发起用户设备101和代理设备115之间的联系的一个或多个参与规则。在一些实施方式中,参与服务器111可通过第三方服务器121A-121B将来自一个或多个第三方数据库123A-123B的一个或多个第三方分析(例如多个第三方分析报告)合并。
在步骤305中,参与服务器111可从多个类似于图1中的用户设备101的用户设备接收用户交互数据。与方法200中的步骤205类似,参与服务器111可接收指示特定用户如何与网站交互的数据。在步骤305,参与服务器111可从多个用户设备101接收用户交互数据,例如同时从多个用户设备101并行接收数据。在一些实施方式中,参与服务器111可累积来自多个用户的用户交互数据并存储该数据供以后使用。参与服务器111可跟踪用于不同的个体用户的不同数据;该数据还可由参与服务器111在以后的使用中一起使用。
接着,参与服务器111可从步骤305进行到步骤306,其中参与服务器111基于累积的用户交互数据生成统计模型。在一些实施方式中,参与服务器除了使用存储的用户交互数据和在步骤305接收到的用户交互数据,还可以使用从多个第三方数据库123A-123B接收到的各种第三方分析。参与服务器111可形成统计模型来创建“模型”用户配置文件(例如,可表示典型的默认用户的预期的动作)。在这样的情况下,参与服务器111基于默认统计配置文件来决定参与,该配置文件可在参与服务器111接收到新的用户交互数据时不断更新。在一些实施方式中,参与服务器111可使用统计模型来形成多个用户配置文件,它可使用用户配置文件来模仿多个用户设备中的每一个,其接收用户设备的用户交互数据。
在创建统计模型后,则参与服务器111可进行到步骤307,其中参与服务器11可基于接收到的用户交互数据调整参与规则。在一些实施方式中,参与服务器111可使用用户交互数据来调整参与规则。在其它实施方式中,参与服务器111可先使用统计模型来调整参与规则并随后使用用户交互数据来进一步调整参与规则。参与服务器111可以以与步骤207类似的方式动作,如参与服务器111可使用用户交互数据和统计模型来修改先前接收到并存储的参与规则以使参与服务器111在更适当的时间发起代理设备115和用户设备101之间的联系。
为了确定是否是发起用户设备101和代理设备115之间的联系的适当的时间,参与服务器111可进行到步骤309,其中参与服务器111确定其是否已经接收到来自用户设备101的指示满足任何参与规则的用户交互数据。在一些实施方式中,参与服务器111可不断监控多个用户设备101并确定多个用户设备101之一是否满足其参与条件。如果不满足,则参与服务器111可返回步骤309并等待直到条件满足。
在条件满足时,参与服务器111可进行到步骤311,其中参与服务器111发起与用户设备101的联系。与步骤211类似,参与服务器111可通过代理设备115和用户设备101发起代理和用户之间的直接通信,例如,文本或视频聊天会话。一旦参与服务器111成功发起与用户设备101的联系,则其可进行到步骤313并结束方法300。
以上描述的计算机化的方法和装置可由数字和/或模拟电子电路、或计算机硬件、固件、软件、或它们的结合来实现。该实现方式可以是计算机程序产品,即有形地包含在机器可读存储设备中的计算机程序,其由数据处理装置(例如,可编程处理器、计算机、和/或多个计算机)执行或控制数据处理装置的操作。计算机程序可以以任何形式的计算机或编程语言(包括源代码、编译代码、解释代码和/或机器代码)来编写,以及计算机程序可以以任何形式(包括作为独立的程序或作为子程序、元素、或适合在计算环境中使用的其它单元)部署。计算机程序可被部署成在一个计算机上执行或在一个或多个地点的多个计算机上执行。
计算机化的方法步骤可由一个或多个执行计算机程序的处理器执行,以通过操作输入数据和/或生成输出数据来实现本发明的功能。方法步骤还可通过专用逻辑电路来执行且装置可实现为专用逻辑电路,该专用逻辑电路例如为FPGA(现场可编程门阵列)、FPAA(现场可编程模拟阵列)、CPLD(复杂可编程逻辑器件)、PSoC(片上可编程系统)、ASIP(专用指令集处理器)、或ASIC(专用集成电路)。子程序可以指计算机程序和/或处理器/专用电路的实现一个或多个功能的部分。
举例来说,适合执行计算机程序的处理器包括通用和专用微处理器和任何类型的数字或模拟计算机的一个或多个处理器。通常,处理器从只读存储器和/或随机访问存储器接收指令和数据。计算机的必不可少的元件为用于执行指令的处理器和用于存储指令和/或数据的一个或多个存储设备。存储设备,例如高速缓冲存储器,可用来暂时存储数据。存储设备还可用来长期存储数据。通常,计算机还包括用于存储数据的一个或多个大容量存储设备(例如磁盘、磁光盘、或光盘),或计算机被操作地联接成从该大容量存储设备接收数据和/或将数据发送给大容量存储设备。计算机还可操作地联接至通信网络以从该网络接收指令和/或数据和/或将指令和/或数据发送给该网络。适于包含计算机程序指令和数据的计算机可读存储设备包括所有形式的易失性和非易失性存储器,举例来说,包括半导体存储设备,例如DRAM、SRAM、EPROM、EEPROM和闪存设备;磁盘,例如内部硬盘或可移动盘;磁光盘;和光盘,例如CD、DVD、HD-DVD和蓝光光盘。处理器和存储器可以由专用逻辑电路补充和/或合并在专用逻辑电路中。
为了提供与用户的交互,以上描述的技术可在与显示设备、键盘、和指向设备(例如鼠标、跟踪球、触摸板或运动传感器)通信的计算机上实现,显示设备例如为CRT(阴极射线管)、等离子体、或LCD(液晶显示器),用于显示信息给用户,通过该键盘和指向设备用户可提供输入给计算机(例如,与用户界面元素交互)。也可使用其它类型的设备来提供与用户的交互;例如,提供给用户的反馈可以是任何形式的感觉反馈,例如视觉反馈、听觉反馈或触觉反馈;可以以任何形式接收来自用户的输入,包括声音输入、语音输入和/或触觉输入。
以上描述的技术可在包含后端组件的分布式计算机系统中实现。例如,后端组件可以是数据服务器、中间件组件、和/或应用服务器。以上描述的技术可在包含前端组件的分布式计算机系统中实现。例如,前端组件可以是具有图形用户界面的客户端计算机、网络浏览器(例如,用户通过网络浏览器可以与示例实现方式交互)、和/或用于传输设备的其它图形用户界面。以上描述的技术可在包含这样的后端组件、中间件组件或前端组件的任意组合的分布式计算机系统中实现。
计算系统可包括客户端和服务器。通常,客户端和服务器彼此远离并通过通信网络进行交互。客户端和服务器的关系通过运行在各计算机上且具有客户端-服务器相互关系的计算机程序而产生。
计算系统的组件可通过任何形式互连,或通过数字或模拟数据通信的媒介(例如,通信网络)互连。通信网络的示例包括基于电路的网络和基于分组的网络。例如,基于分组的网络可包括因特网、运营商互联网协议(IP)网络(例如,局域网(LAN)、广域网(WAN)、校园网(CAN)、城域网(MAN)、家域网(HAN))、专用IP网、IP专用小交换机(IPBX)、无线网(例如,无线接入网(RAN)、802.11网、802.16网、通用分组无线业务(GPRS)网、高性能无线局域网)、和/或其它基于分组的网络。例如,基于电路的网络可以包括公共交换电话网(PSTN)、专用小交换机(PBX)、无线网(例如,RAN、蓝牙、码分多址(CDMA)网、时分多址(TDMA)网、全球移动通信系统(GSM)网)、和/或其它基于电路的网络。
例如,计算系统的设备和/或计算设备可包括计算机、具有浏览器设备的计算机、电话、IP电话、移动设备(例如,蜂窝电话、个人数字助理(PDA)设备、便携式电脑、电子邮件设备)、服务器、具有一个或多个处理卡的架、专用电路、和/或其它通信设备。例如,浏览器设备包括具有万维网浏览器(例如,可从Microsoft Corporation获得的Internet可从Mozilla Corporation获得的Firefox)的计算机(例如,台式电脑、便携式电脑)。例如,移动计算设备包括例如,IP电话包括可从Cisco System公司获得的Unified IP Phone 7985G、和/或可从Cisco System公司获得的Unified Wireless Phone 7920。
本领域技术人员将认识到可以以其它具体的形式来体现本发明而不脱离本发明的精神或本质特征。因此,应当考虑前面的实施方式在所有方面是说明性的而非限制此处描述的发明。因此,本发明的范围由所附权利要求书而非前面的描述表示,以及在权利要求的等效的含义和范围内的所有变化也包含在内。
Claims (18)
1.一种系统,包括:
一个或多个数据处理器,以及
非暂时性计算机可读存储介质,所述非暂时性计算机可读存储介质包括指令,所述指令在所述一个或多个数据处理器上被执行时,使所述一个或多个数据处理器执行包括以下的操作:
访问第三方数据库以检索关于网站的第三方分析数据,其中,所述第三方分析数据包括与和所述网站的交互有关的统计信息,所述统计信息指示用于联系的适当时间;
使用所述第三方分析数据确定用于参与规则的初始参数,其中,所述初始参数促进在所述适当时间的联系;
使用所述初始参数自动地生成参与规则,其中,所述参与规则包括优化条件,并且所述优化条件在被满足时促进成功的联系;
接收表示设备与所述网站的交互的交互数据;
将所述交互数据应用于所述参与规则;
确定是否满足所述参与规则的所述优化条件;以及
当满足所述参与规则时,促进与所述设备的联系。
2.根据权利要求1所述的系统,其中,所述操作还包括:
使用所述交互数据确定更新的参数,其中,确定所述更新的参数包括从所述交互数据确定用于联系的更适当时间;以及
使用所述更新的参数更新所述参与规则,其中,更新所述参与规则包括使用所述更适当时间来更新所述优化条件以在所述优化条件被满足时进一步促进成功的联系。
3.根据权利要求1所述的系统,其中,所述操作还包括:
检索附加的第三方分析数据;
使用所述附加的第三方分析数据动态地确定更新的参数,其中,确定所述更新的参数包括从所述附加的第三方分析数据确定用于联系的更适当时间;以及
使用所述更新的参数动态地更新所述参与规则,其中,更新所述参与规则包括使用所述更适当时间更新所述优化条件以在所述优化条件被满足时进一步促进成功的联系。
4.根据权利要求1所述的系统,其中,所述操作还包括基于所述第三方分析数据生成统计模型,并且确定所述初始参数包括使用所述统计模型优化所述初始参数。
5.根据权利要求4所述的系统,其中,所述操作还包括:
通过将所述交互数据应用于所述统计模型来生成设备配置文件;
存储所述设备配置文件;
接收表示所述设备与所述网站的附加交互的附加交互数据;
使用所述附加交互数据以及存储的所述设备配置文件动态地确定更新的参数,其中,动态地确定所述更新的参数包括将所述附加交互数据应用于存储的所述设备配置文件以确定特定于设备的用于联系的适当时间;
使用所述更新的参数动态地更新所述参与规则,其中,动态地更新所述参与规则包括使用所述特定于设备的用于联系的适当时间来更新所述优化条件以促进与所述设备的成功的联系;
将所述附加交互数据应用于更新的参与规则;以及
确定是否满足所述更新的参与规则的更新的优化条件。
6.根据权利要求4所述的系统,其中,所述操作还包括:
检索附加的第三方分析数据;
使用所述交互数据和所述附加的第三方分析数据动态地更新所述统计模型;
使用更新的统计模型动态地确定更新的参数,其中,动态地确定所述更新的参数包括使用所述更新的统计模型来确定用于联系的更适当时间;以及
使用所述更新的参数动态地更新所述参与规则,其中,更新所述参与规则包括使用所述更适当时间来更新所述优化条件以进一步促进成功的联系。
7.一种计算机实现的方法,包括:
访问第三方数据库以检索关于网站的第三方分析数据,其中,所述第三方分析数据包括与和所述网站的交互有关的统计信息,所述统计信息指示用于联系的适当时间;
使用所述第三方分析数据确定用于参与规则的初始参数,其中,所述初始参数促进在所述适当时间的联系;
使用所述初始参数自动地生成参与规则,其中,所述参与规则包括优化条件,并且所述优化条件在被满足时促进成功的联系;
接收表示设备与所述网站的交互的交互数据;
将所述交互数据应用于所述参与规则;
确定是否满足所述参与规则的所述优化条件;以及
当满足所述参与规则时,促进与所述设备的联系。
8.根据权利要求7所述的方法,还包括:
使用所述交互数据确定更新的参数,其中,确定所述更新的参数包括从所述交互数据确定用于联系的更适当时间;以及
使用所述更新的参数更新所述参与规则,其中,更新所述参与规则包括使用所述更适当时间来更新所述优化条件以在所述优化条件被满足时进一步促进成功的联系。
9.根据权利要求7所述的方法,还包括:
检索附加的第三方分析数据;
使用所述附加的第三方分析数据动态地确定更新的参数,其中,确定所述更新的参数包括从所述附加的第三方分析数据确定用于联系的更适当时间;以及
使用所述更新的参数动态地更新所述参与规则,其中,更新所述参与规则包括使用所述更适当时间更新所述优化条件以在所述优化条件被满足时进一步促进成功的联系。
10.根据权利要求7所述的方法,还包括基于所述第三方分析数据生成统计模型,以及
其中,确定所述初始参数包括使用所述统计模型优化所述初始参数。
11.根据权利要求10所述的方法,还包括:
通过将所述交互数据应用于所述统计模型来生成设备配置文件;
存储所述设备配置文件;
接收表示所述设备与所述网站的附加交互的附加交互数据;
使用所述附加交互数据以及存储的所述设备配置文件动态地确定更新的参数,其中,动态地确定所述更新的参数包括将所述附加交互数据应用于存储的所述设备配置文件以确定特定于设备的用于联系的适当时间;
使用所述更新的参数动态地更新所述参与规则,其中,动态地更新所述参与规则包括使用所述特定于设备的用于联系的适当时间来更新所述优化条件以促进与所述设备的成功的联系;
将所述附加交互数据应用于更新的参与规则;以及
确定是否满足所述更新的参与规则的更新的优化条件。
12.根据权利要求10所述的方法,还包括:
检索附加的第三方分析数据;
使用所述交互数据和所述附加的第三方分析数据动态地更新所述统计模型;
使用更新的统计模型动态地确定更新的参数,其中,动态地确定所述更新的参数包括使用所述更新的统计模型来确定用于联系的更适当时间;以及
使用所述更新的参数动态地更新所述参与规则,其中,更新所述参与规则包括使用所述更适当时间来更新所述优化条件以进一步促进成功的联系。
13.一种非暂时性机器可读存储介质,所述非暂时性机器可读存储介质包括指令,所述指令被配置成使数据处理设备执行包括以下的操作:
访问第三方数据库以检索关于网站的第三方分析数据,其中,所述第三方分析数据包括与和所述网站的交互有关的统计信息,所述统计信息指示用于联系的适当时间;
使用所述第三方分析数据确定用于参与规则的初始参数,其中,所述初始参数促进在所述适当时间的联系;
使用所述初始参数自动地生成参与规则,其中,所述参与规则包括优化条件,并且所述优化条件在被满足时促进成功的联系;
接收表示设备与所述网站的交互的交互数据;
将所述交互数据应用于所述参与规则;
确定是否满足所述参与规则的所述优化条件;以及
当满足所述参与规则时,促进与所述设备的联系。
14.根据权利要求13所述的非暂时性机器可读存储介质,其中,所述操作还包括:
使用所述交互数据确定更新的参数,其中,确定所述更新的参数包括从所述交互数据确定用于联系的更适当时间;以及
使用所述更新的参数更新所述参与规则,其中,更新所述参与规则包括使用所述更适当时间来更新所述优化条件以在所述优化条件被满足时进一步促进成功的联系。
15.根据权利要求13所述的非暂时性机器可读存储介质,其中,所述操作还包括:
检索附加的第三方分析数据;
使用所述附加的第三方分析数据动态地确定更新的参数,其中,确定所述更新的参数包括从所述附加的第三方分析数据确定用于联系的更适当时间;以及
使用所述更新的参数动态地更新所述参与规则,其中,更新所述参与规则包括使用所述更适当时间更新所述优化条件以在所述优化条件被满足时进一步促进成功的联系。
16.根据权利要求13所述的非暂时性机器可读存储介质,其中,所述操作还包括基于所述第三方分析数据生成统计模型,并且确定所述初始参数包括使用所述统计模型优化所述初始参数。
17.根据权利要求16所述的非暂时性机器可读存储介质,其中,所述操作还包括:
通过将所述交互数据应用于所述统计模型来生成设备配置文件;
存储所述设备配置文件;
接收表示所述设备与所述网站的附加交互的附加交互数据;
使用所述附加交互数据以及存储的所述设备配置文件动态地确定更新的参数,其中,动态地确定所述更新的参数包括将所述附加交互数据应用于存储的所述设备配置文件以确定特定于设备的用于联系的适当时间;
使用所述更新的参数动态地更新所述参与规则,其中,动态地更新所述参与规则包括使用所述特定于设备的用于联系的适当时间来更新所述优化条件以促进与所述设备的成功的联系;
将所述附加交互数据应用于更新的参与规则;以及
确定是否满足所述更新的参与规则的更新的优化条件。
18.根据权利要求16所述的非暂时性机器可读存储介质,其中,所述操作还包括:
检索附加的第三方分析数据;
使用所述交互数据和所述附加的第三方分析数据动态地更新所述统计模型;
使用更新的统计模型动态地确定更新的参数,其中,动态地确定所述更新的参数包括使用所述更新的统计模型来确定用于联系的更适当时间;以及
使用所述更新的参数动态地更新所述参与规则,其中,更新所述参与规则包括使用所述更适当时间来更新所述优化条件以进一步促进成功的联系。
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AU2013217027A1 (en) | 2014-09-25 |
CN104246768B (zh) | 2019-06-11 |
AU2018214099A1 (en) | 2018-08-30 |
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