Patent application number | Description | Published |
20090222313 | APPARATUS AND METHOD FOR PREDICTING CUSTOMER BEHAVIOR - 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. | 09-03-2009 |
20100138282 | MINING INTERACTIONS TO MANAGE CUSTOMER EXPERIENCE THROUGHOUT A CUSTOMER SERVICE LIFECYCLE - 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. | 06-03-2010 |
20100191658 | Predictive Engine for Interactive Voice Response System - 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. | 07-29-2010 |
20100262549 | SYSTEM AND METHOD FOR CUSTOMER REQUESTS AND CONTACT MANAGEMENT - A method and a web-based system is provided that enables a customer service center of a company to provide its customers with a choice of different modes for establishing contact with customer service representatives. The different modes of contact are displayed on a single web page. The modes of contact include, but are not limited to call, chat, e-mail and Internet talk. Further, the system provides information regarding the estimated wait time and the less busy time for the modes of contact. In addition, the system and method provide means for conducting a search in a knowledge database for automated responses to queries from customers. The system and method enables the customer to provide feedback for each interaction with the customer service center through the web page. Further, the system and method enable the storage of all interaction between each customer and the customer service center. | 10-14-2010 |
20110158398 | METHOD AND APPARATUS FOR OPTIMIZING CUSTOMER SERVICE ACROSS MULTIPLE CHANNELS - 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. | 06-30-2011 |
20120023419 | SLIDER AND HISTORY FIELD FOR SMART CHAT SESSIONS - A context sensitive slider content area provides a slide out mechanism that is automatically actuated when additional information is needed during a chat session between an agent and a visitor, e.g. where a pre-chat and/or exit form is to be completed. The context sensitive slide out content area also provides problem resolution information to the visitor to help in solving problems, e.g. the top five problems; and also provides a self-service step-by-step wizard. A history section is provided with which the visitor can track back all previous steps carried out within the smart client. A history bar provides an iconic representation of all previous activities. A technique is also disclosed for executing various actions, such as form filling or requests for additional services, in a chat session. | 01-26-2012 |
20120130771 | Chat Categorization and Agent Performance Modeling - 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. | 05-24-2012 |
20120185544 | Method and Apparatus for Analyzing and Applying Data Related to Customer Interactions with Social Media - Embodiments of the invention provide techniques that quantize community interactions with social media to understand and influence consumer experiences. | 07-19-2012 |
20120233258 | METHOD AND APPARATUS FOR ANALYZING AND APPLYING DATA RELATED TO CUSTOMER INTERACTIONS WITH SOCIAL MEDIA - Embodiments of the invention provide techniques that quantize community interactions with social media to understand and influence consumer experiences. | 09-13-2012 |
20130080362 | CUSTOMER JOURNEY PREDICTION AND RESOLUTION - Customer journey prediction and resolution is accomplished via a predictive model in which each user is mapped onto all available user journey information corresponding to a specific business. The predictive model is analyzed to understand the characteristics, preferences, and lowest effort resolution for the user related to the services that are subscribed to by the user. The predictive model is analyzed to predict the service or collection of services for each user. Embodiments interact with, provide and receive information from, and react to and/or deliver action to the customer across channels and across services. All customer and system behavior, data, and action is tracked and coordinated and leveraged for continuous feedback and performance improvement. | 03-28-2013 |
20130129076 | INTERACTION MANAGEMENT - A company/organization is enabled to optimize sessions from an agent's perspective across multiple channels. Actions may be performed, such as monitoring the journey of a user across a self service application, raising alerts to the agent based on the journey, selecting an appropriate agent to whom a session may be routed, raising alerts for a supervisor, enabling the supervisor to track sessions and intervene if required, enable the agent to run commands from an interaction window, push links to launch applications to supplement the primary interaction through appropriate mechanisms, show appropriate responses to the agent on analyzing the session, and providing shortcut keys for the agent to allow the agent to insert appropriate responses into a chat session. Analysis is provided for the sessions, data is extracted from the sessions, and appropriate forms are populated with the data from the session and with agent information. | 05-23-2013 |
20130211880 | CHAT CATEGORIZATION AND AGENT PERFORMANCE MODELING - 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. | 08-15-2013 |
20130282430 | METHOD AND APPARATUS FOR AN INTUITIVE CUSTOMER EXPERIENCE - 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. | 10-24-2013 |
20130304578 | METHOD AND APPARATUS FOR ENHANCED IN-STORE RETAIL EXPERIENCE USING LOCATION AWARENESS - Embodiments of the invention provide a nexus between a user's presence within or proximate to a brick and mortar store outside of an explicit user transaction within the store, that is based solely upon the user's presence within the store, and not on any affirmative actions taken by the user by maintaining location awareness of the user and by communicating this awareness in real time, as the user moves from location to location, to brick and mortar stores at or near to the user's location. In this way, embodiments of the invention link the user's virtual presence, for example via the Internet, and all of the user-related information that is available for data mining, for example using big data techniques, to the user's physical presence at a physical location to create an enhanced user experience within the physical location in real time. | 11-14-2013 |
20140019886 | METHOD AND APPARATUS FOR OPTIMIZING CUSTOMER SERVICE ACROSS MULTIPLE CHANNELS - 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. | 01-16-2014 |
20140067649 | METHOD AND APPARATUS FOR PROACTIVE NOTIFICATIONS BASED ON THE LOCATION OF A USER - The location of a user is obtained and, based on the location of the user and services available to, or requested by the user, a notification handler sends appropriate notifications to the user. | 03-06-2014 |
20140143017 | PROACTIVE SURVEYS BASED ON CUSTOMER INFORMATION - A context-aware computing system for delivering surveys to a customer. The choice of which survey to send to a customer may be tailored based on a click path (route), customer history, and customer interests. A customer browsing a Web page initiates the survey decision process. A control module selects a survey to send to a customer based on the criteria above and customer intent. Customer responses are then harvested from the Web-based survey. | 05-22-2014 |
20140156383 | AD-WORDS OPTIMIZATION BASED ON PERFORMANCE ACROSS MULTIPLE CHANNELS - In online advertising, ad delivery optimization is derived from ad-words searches. A user performs a keyword search for a product or service. User interactions across multiple channels, e.g. phone, text, email, and so on, and multiple browsers that are used while conducting a search are analyzed to predict user intent. Based on the intent prediction, advertisements that are determined to be the most relevant are displayed along with the search results. The user then clicks through the ads to the websites that are most relevant to his search, for example to make purchases of goods and services. | 06-05-2014 |
20140207518 | Method and Apparatus for Building a User Profile, for Personalization Using Interaction Data, and for Generating, Identifying, and Capturing User Data Across Interactions Using Unique User Identification - A user profile is creates, and personalization is provided, by compiling interaction data. The interaction data is compiled to generate a value index or score from a user model. Parameterized data is used to build tools which help decide an engagement strategy and modes of engagement with a user. Several facets relating to the user, such as user behavior, user interests, products bought, intent, chat language, and so on, are compiled to create a user profile based personalization technique. In another embodiment, a unique ID is provided that can be mapped across multiple channels for use by the user to contact various organizations across multiple channels, and thus upgrade the user's experience. | 07-24-2014 |
20140219437 | Interaction Management - A company/organization is enabled to optimize sessions from an agent's perspective across multiple channels. Actions may be performed, such as monitoring the journey of a user across a self service application, raising alerts to the agent based on the journey, selecting an appropriate agent to whom a session may be routed, raising alerts for a supervisor, enabling the supervisor to track sessions and intervene if required, enable the agent to run commands from an interaction window, push links to launch applications to supplement the primary interaction through appropriate mechanisms, show appropriate responses to the agent on analyzing the session, and providing shortcut keys for the agent to allow the agent to insert appropriate responses into a chat session. Analysis is provided for the sessions, data is extracted from the sessions, and appropriate forms are populated with the data from the session and with agent information. | 08-07-2014 |
20150081597 | Customer Journey Prediction and Resolution - Customer journey prediction and resolution is accomplished via a predictive model in which each user is mapped onto all available user journey information corresponding to a specific business. The predictive model is analyzed to understand the characteristics, preferences, and lowest effort resolution for the user related to the services that are subscribed to by the user. The predictive model is analyzed to predict the service or collection of services for each user. Embodiments interact with, provide and receive information from, and react to and/or deliver action to the customer across channels and across services. All customer and system behavior, data, and action is tracked and coordinated and leveraged for continuous feedback and performance improvement. | 03-19-2015 |