Abstract:
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.
Abstract:
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.
Abstract:
With regard to searches and, more particularly, to searches performed on information repositories belonging to an enterprise, a centralized management system is used by the enterprise to manage the predictive search experience for users. A system offers a rich resolution experience to the end users based on user intent as determined from a variety of mechanisms, such as keywords, end user journey, clustered journey, etc. Also disclosed herein is a system that derives and offers various suggestions to end users to help them accomplish their objectives.
Abstract:
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.
Abstract:
A DC-DC converter receives input power from a power source and generates a regulated DC voltage as an output. The DC-DC converter contains multiple blocks, each of which is powered by a power supply received on a supply terminal. The DC-DC converter also contains a voltage regulator to generate a lower voltage from the power source. The lower voltage generated by the regulator is provided as the power supply on the supply terminal when the regulated DC voltage is less than a reference value, and the regulated DC voltage itself is provided as the power supply on the supply terminal otherwise. The regulator is switched off when the blocks are powered by the regulated DC voltage, thereby leading to increased efficiency of the DC-DC converter.
Abstract:
Embodiments of the invention provide techniques that quantize community interactions with social media to understand and influence consumer experiences.
Abstract:
With regard to searches and, more particularly, to searches performed on information repositories belonging to an enterprise, a centralized management system is used by the enterprise to manage the predictive search experience for users. A system offers a rich resolution experience to the end users based on user intent as determined from a variety of mechanisms, such as keywords, end user journey, clustered journey, etc. Also disclosed herein is a system that derives and offers various suggestions to end users to help them accomplish their objectives.
Abstract:
Embodiments of the invention provide techniques that quantize community interactions with social media to understand and influence consumer experiences.
Abstract:
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.
Abstract:
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.