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1. 发明申请

US20100191658A1 Predictive Engine for Interactive Voice Response System 审中-公开
标题翻译：互动语音应答系统的预测引擎
公开(公告)号：US20100191658A1
公开(公告)日：2010-07-29
申请号：US12693236
申请日：2010-01-25
申请人： Pallipuram V. Kannan , Mohit Jain , Ravi Vijayaraghavan
发明人： Pallipuram V. Kannan , Mohit Jain , Ravi Vijayaraghavan
IPC分类号： G06Q10/00 , G10L13/00 , G10L15/26
CPC分类号： G06F17/279 , G06Q30/016 , G06Q30/02 , G06Q30/0202 , H04M3/5166 , H04M2203/551
摘要： A customer service issue prediction engine uses one or more models of issue probability. A method of multi-phase customer issue prediction includes a modeling phase, an application phase, and a learning phase. A telephonic interactive voice response (IVR) system predicts customer issues.
摘要翻译：客户服务问题预测引擎使用一个或多个发行概率模型。多阶段客户问题预测的方法包括建模阶段，应用阶段和学习阶段。电话互动语音响应（IVR）系统预测客户问题。

2. 发明授权

US09129290B2 Apparatus and method for predicting customer behavior 有权
标题翻译：用于预测客户行为的装置和方法
公开(公告)号：US09129290B2
公开(公告)日：2015-09-08
申请号：US12392058
申请日：2009-02-24
申请人： Pallipuram V. Kannan , Mohit Jain , Ravi Vijayaraghavan
发明人： Pallipuram V. Kannan , Mohit Jain , Ravi Vijayaraghavan
IPC分类号： G06Q10/00 , G06Q30/02
CPC分类号： G06Q30/02 , G06N7/005 , G06Q10/067 , G06Q30/016 , G06Q30/0202
摘要： A predictive model generator that enhances customer experience, reduces the cost of servicing a customer, and prevents customer attrition by predicting the appropriate interaction channel through analysis of different types of data and filtering of irrelevant data. The model includes a customer interaction data engine for transforming data into a proper format for storage, data warehouse for receiving data from a variety of sources, and a predictive engine for analyzing the data and building models.
摘要翻译：一种预测模型生成器，可增强客户体验，降低客户服务成本，并通过分析不同类型的数据和过滤不相关数据来预测适当的交互渠道，从而防止客户流失。该模型包括用于将数据转换为适当格式的客户交互数据引擎，用于从各种来源接收数据的数据仓库，以及用于分析数据和构建模型的预测引擎。

3. 发明授权

US08396741B2 Mining interactions to manage customer experience throughout a customer service lifecycle 有权
标题翻译：挖掘交互，以在整个客户服务生命周期中管理客户体验
公开(公告)号：US08396741B2
公开(公告)日：2013-03-12
申请号：US12604252
申请日：2009-10-22
申请人： Pallipuram V. Kannan , Mohit Jain , Ravi Vijayaraghavan , Ponnusamy Sam Albert , Vijayalakshmi Amudhan
发明人： Pallipuram V. Kannan , Mohit Jain , Ravi Vijayaraghavan , Ponnusamy Sam Albert , Vijayalakshmi Amudhan
IPC分类号： G06Q10/00
CPC分类号： G06Q10/06398 , G06Q30/02
摘要： A customer experience is improved through data mining and text mining technologies and that derive insights about a customer by analyzing interactions between the customer and a customer service agent. One or more numerical measurements of customer satisfaction are derived and recommended actions are provided to an agent to enhance the customer experience throughout a customer service lifecycle.
摘要翻译：通过数据挖掘和文本挖掘技术改进了客户体验，并通过分析客户和客户服务代理之间的交互来获得有关客户的洞察。导出客户满意度的一个或多个数值测量，并向代理提供推荐的操作，以增强整个客户服务生命周期中的客户体验。

4. 发明申请

US20090222313A1 APPARATUS AND METHOD FOR PREDICTING CUSTOMER BEHAVIOR 有权
标题翻译：用于预测客户行为的装置和方法
公开(公告)号：US20090222313A1
公开(公告)日：2009-09-03
申请号：US12392058
申请日：2009-02-24
申请人： Pallipuram V. Kannan , Mohit Jain , Ravi Vijayaraghavan
发明人： Pallipuram V. Kannan , Mohit Jain , Ravi Vijayaraghavan
IPC分类号： G06Q10/00 , G06N5/02 , G06F17/30 , G06F17/40 , G06Q50/00
CPC分类号： G06Q30/02 , G06N7/005 , G06Q10/067 , G06Q30/016 , G06Q30/0202
摘要： A predictive model generator that enhances customer experience, reduces the cost of servicing a customer, and prevents customer attrition by predicting the appropriate interaction channel through analysis of different types of data and filtering of irrelevant data. The model includes a customer interaction data engine for transforming data into a proper format for storage, data warehouse for receiving data from a variety of sources, and a predictive engine for analyzing the data and building models.
摘要翻译：一种预测模型生成器，可增强客户体验，降低客户服务成本，并通过分析不同类型的数据和过滤不相关数据来预测适当的交互渠道，从而防止客户流失。该模型包括用于将数据转换为适当格式的客户交互数据引擎，用于从各种来源接收数据的数据仓库，以及用于分析数据和构建模型的预测引擎。

5. 发明授权

US09519936B2 Method and apparatus for analyzing and applying data related to customer interactions with social media 有权
标题翻译：用于分析和应用与社交媒体的客户互动相关数据的方法和装置
公开(公告)号：US09519936B2
公开(公告)日：2016-12-13
申请号：US13461631
申请日：2012-05-01
申请人： Ravi Vijayaraghavan , Ravi Garikipati , Andrew Chang , Pallipuram V. Kannan
发明人： Ravi Vijayaraghavan , Ravi Garikipati , Andrew Chang , Pallipuram V. Kannan
IPC分类号： G06F11/30 , G06Q50/00 , G06Q10/06 , G06F17/30 , G06Q30/02
CPC分类号： G06Q50/01 , G06F17/30539 , G06Q10/0637 , G06Q30/02
摘要： Embodiments of the invention provide techniques that quantize community interactions with social media to understand and influence consumer experiences.
摘要翻译：本发明的实施例提供了量化与社交媒体的社区互动以了解和影响消费者体验的技术。

6. 发明申请

US20120185544A1 Method and Apparatus for Analyzing and Applying Data Related to Customer Interactions with Social Media 有权
标题翻译：用于分析和应用与社交媒体客户互动相关数据的方法和装置
公开(公告)号：US20120185544A1
公开(公告)日：2012-07-19
申请号：US13349807
申请日：2012-01-13
申请人： Andrew Chang , Pallipuram V. Kannan , Ravi Vijayaraghavan
发明人： Andrew Chang , Pallipuram V. Kannan , Ravi Vijayaraghavan
IPC分类号： G06F15/16
CPC分类号： G06Q50/01 , G06F17/30539 , G06Q10/0637 , G06Q30/02
摘要： Embodiments of the invention provide techniques that quantize community interactions with social media to understand and influence consumer experiences.
摘要翻译：本发明的实施例提供了量化与社交媒体的社区互动以了解和影响消费者体验的技术。

7. 发明授权

US09483800B2 Method and apparatus for analyzing and applying data related to customer interactions with social media 有权
公开(公告)号：US09483800B2
公开(公告)日：2016-11-01
申请号：US13461631
申请日：2012-05-01
申请人： Ravi Vijayaraghavan , Ravi Garikipati , Andrew Chang , Pallipuram V. Kannan
发明人： Ravi Vijayaraghavan , Ravi Garikipati , Andrew Chang , Pallipuram V. Kannan
IPC分类号： G06F11/30 , G06Q50/00 , G06Q10/06 , G06F17/30 , G06Q30/02
摘要： Embodiments of the invention provide techniques that quantize community interactions with social media to understand and influence consumer experiences.

8. 发明授权

US09536269B2 Method and apparatus for analyzing and applying data related to customer interactions with social media 有权
标题翻译：用于分析和应用与社交媒体的客户互动相关数据的方法和装置
公开(公告)号：US09536269B2
公开(公告)日：2017-01-03
申请号：US13349807
申请日：2012-01-13
申请人： Andrew Chang , Pallipuram V. Kannan , Ravi Vijayaraghavan
发明人： Andrew Chang , Pallipuram V. Kannan , Ravi Vijayaraghavan
IPC分类号： G06F15/177 , G06Q50/00 , G06Q10/06 , G06F17/30 , G06Q30/02
CPC分类号： G06Q50/01 , G06F17/30539 , G06Q10/0637 , G06Q30/02
摘要： Embodiments of the invention provide techniques that quantize community interactions with social media to understand and influence consumer experiences. Embodiments include a customer predictive experience platform. The platform can include an outcome engine configured for information mining and applying rules and analytics to the information, and an ops module configured for providing agent performance management, average handling time analytics, workflow management, and voice of the customer facilities. The platform can also include a chat module, a social media dialog engine, and a solution client configured for effecting predictive self-service, active auto sentiment management and rapid response to counteract negative sentiment, a customer experience ticker, a pre- and post-launch pulse, enhanced brand ambassadors, integration into corporate messaging and marketing, a social media dashboard, and a live portal configured for social media engagement and feedback.
摘要翻译：本发明的实施例提供了量化与社交媒体的社区互动以了解和影响消费者体验的技术。实施例包括客户预测体验平台。该平台可以包括配置用于信息挖掘和将信息应用规则和分析的结果引擎，以及配置为提供代理性能管理，平均处理时间分析，工作流管理和客户设施语音的操作模块。该平台还可以包括聊天模块，社交媒体对话引擎和配置用于实现预测性自助服务，主动自动情绪管理和快速响应以消除负面情绪的解决方案客户端，客户体验记录器，推出脉搏，增强品牌大使，融入企业信息和营销，社交媒体仪表板，以及配置为社交媒体参与和反馈的现场门户。

9. 发明申请

US20120130771A1 Chat Categorization and Agent Performance Modeling 审中-公开
标题翻译：聊天分类和代理性能建模
公开(公告)号：US20120130771A1
公开(公告)日：2012-05-24
申请号：US13161291
申请日：2011-06-15
申请人： Pallipuram V. Kannan , Ravi Vijayaraghavan , Rajkumar Dan , Harsh Singhal , Manish Gupta
发明人： Pallipuram V. Kannan , Ravi Vijayaraghavan , Rajkumar Dan , Harsh Singhal , Manish Gupta
IPC分类号： G06Q10/00 , G06F17/30
CPC分类号： G06Q10/06393 , G06Q10/06398 , G06Q30/016 , G06Q30/0201 , G06Q30/0202 , G06Q30/0203
摘要： Chat categorization uses semi-supervised clustering to provide Voice of the Customer (VOC) analytics over unstructured data via an historical understanding of topic categories discussed to derive an automated methodology of topic categorization for new data; application of semi-supervised clustering (SSC) for VOC analytics; generation of seed data for SSC; and a voting algorithm for use in the absence of domain knowledge/manual tagged data. Customer service interactions are mined and quality of these interactions is measured by “Customer's Vote” which, in turn, is determined by the customer's experience during the interaction and the quality of customer issue resolution. Key features of the interaction that drive a positive experience and resolution are automatically learned via machine learning driven algorithms based on historical data. This, in turn, is used to coach/teach the system/service representative on future interactions.
摘要翻译：聊天分类使用半监督聚类，通过对所讨论的主题类别的历史了解，为非结构化数据提供客户声音（VOC）分析，以获得新数据的主题分类的自动化方法; 应用半监督聚类（SSC）进行VOC分析; SSC的种子数据的生成; 以及在没有域知识/手动标记数据的情况下使用的投票算法。客户服务互动被挖掘，这些互动的质量是通过“客户的投票”衡量的，而客户的投票又由客户在交互中的经验和客户问题解决的质量决定。通过基于历史数据的机器学习驱动的算法，自动学习促进积极体验和分辨率的交互的主要特征。这反过来用于教授/教授系统/服务代表对未来的交互。

10. 发明授权

US08565411B2 Method and apparatus for optimizing customer service across multiple channels 有权
标题翻译：多渠道优化客户服务的方法和装置
公开(公告)号：US08565411B2
公开(公告)日：2013-10-22
申请号：US12973630
申请日：2010-12-20
申请人： Pallipuram V. Kannan , Ravi Vijayaraghavan
发明人： Pallipuram V. Kannan , Ravi Vijayaraghavan
IPC分类号： H04M3/00 , H04M5/00
CPC分类号： H04L65/403 , H04L12/1822 , H04L12/1827 , H04L51/04 , H04M3/5166 , H04M3/5191 , H04M7/003
摘要： A method and apparatus for a computer-implemented technique for maximizing customer satisfaction and first call resolution, including converting telephone calls into online chats, while minimizing cost is provided. Techniques for incorporating analytics as applied to customer data into particular strategies for call deflection, targeting particular individuals to increase chat acceptance rate, and computing a customer's wait time are also provided.
摘要翻译：提供了一种用于最大化客户满意度和第一呼叫解决的计算机实现技术的方法和装置，包括将电话呼叫转换成在线聊天，同时最小化成本。还提供了将分析应用于客户数据的特定技术用于特定的呼叫偏移策略，针对特定个人以增加聊天接受率以及计算客户的等待时间。

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