Abstract: Improvement of customer experiences during online commerce is accomplished by providing unique experiences to customers as a result of anticipating customer needs, simplifying customer engagement based on predicted customer intent, and updating system knowledge about customers with information gathered from new customer interactions. In this way, the customer experience is improved.

Abstract: An embodiment of the invention takes advantage of the fact that the intuitive power of a self-serve app lies in constant learning. The app must quickly evolve to predict customer needs and provide the right content to the right customer. In an embodiment, Web and mobile self-serve apps are optimized by leveraging the chat data of drop-off customers from each screen of the app. In an embodiment, self-serve drop-off data is combined with chat data, the customer's identity data and Web log data to provide a powerful source for driving the targeting and content optimization of the app.

Abstract: 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.

Abstract: A method and apparatus enables identification of customer characteristics and behavior, and predicts the customer's intent. Such prediction can be used to adopt various business strategies to increase the chances of conversion of customer interaction to a sale, and thereby can increase revenue, and/or enhance the customer's experience.

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: 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: A technique is taught that improves how an organization engages with customers. In an embodiment, keywords are discovered to optimize for, and to integrate with, advertising systems to advertise a company website. A set of advertisements is created that improve the click-through rate from users. A optimized landing page experience is created to provide a best user experience to drive issue resolution and sales.

Abstract: Embodiments of the invention provide techniques that quantize community interactions with social media to understand and influence consumer experiences.

Abstract: Embodiments of the invention provide techniques that quantize community interactions with social media to understand and influence consumer experiences.

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 mechanism for facilitating customer interactions within a customer service environment provides prompt and accurate answers to customer questions. A smart chat facility for use in a customer service environment to predict a customer problem examines a customer chat transcript to identify customer statements that set forth a customer issue and, responsive to this, can route the customer to an agent, an appropriate FAQ, or can implement a problem specific widget in the customer UI. Customer queries are matched with most correct responses and accumulated knowledge is used to predict a best response to future customer queries. The iterative system thus learns from each customer interaction and can adapt to customer responses over time to improve the accuracy of problem prediction.

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: 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.

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 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: 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.

Abstract: A method for quantitatively predicting and consequently minimizing the amount of critical phases such as eutectic Al2Cu formed during solidification of Al—Si—Cu alloys used in a vehicle engine component comprises developing a micromodel to simulate microstructure evolution in cast Al—Si or Al—Cu alloys. The micromodel is calibrated using experimental thermal analysis cooling curves and an optimization process. Microstructure evolution and cooling curves are simulated for a casting using the calibrated micromodel. Precipitation of critical phases such as Al2Cu in the casting is predicted as a function of solidification conditions. The model allows casting process variables to be varied with predictable results so that the casting process can be controlled via the micromodel.