Abstract: A method and system for automating the analysis of performance data includes an analysis system automatically analyzing a plurality of performance data sets, a task engine, and a score engine. The task engine allows for the matching of each performance data set with an assigned task for each performance data set and the retrieval of a correct key sequence for each performance data set. The score engine compares the correct key sequence with a recorded key sequence of the performance data set to determine if the assigned task is successfully accomplished. The score engine further calculates one or more response times for each performance data set. The automated analysis of performance data allows for a cost savings, more efficient use of time, and more reliable and consistent performance data analysis results.

Abstract: A method and system for automating categorization of statements includes a categorization system having a plurality of rules to categorize the statements, a rule engine, and a category engine. The rule engine allows for the creation and storage of objective rules used to categorize the statements. The category engine automatically applies the rules to a list of statements in order to categorize the statements and automatically determines a category label for each statement. The category engine further creates an output file including each statement and the corresponding category label. The use of objective rules to categorize the statements allows for reliable and consistent categorization results and eliminates any subjectiveness in the categorization of the statements.

Abstract: A customer service call system that provides both manual (assisted by a service representative) and automated problem solving dialogs. A routing process determines which dialog is appropriate for incoming calls. The routing process determines a probability that the automated system will resolve the problem and also determines an expected hold time for the customer to reach the manual dialog. The routing process uses this information to determine how the call should be routed.

Abstract: A method and system for automating customer slamming and cramming complaints includes an automated reporting system having one or more receiving devices and a complaint module. Customers who want to report a slam or cram access the automated reporting system and report the complaint without having to speak with a customer service representative. The complaint module obtains the customer telephone number and retrieves customer account information using the customer telephone number. Using the customer account information, the complaint module extrapolates a type of complaint for the customer complaint and prompts the customer for information regarding the customer complaint and the type of the complaint. The customer provides customer responses to the prompts and the complaint module provides an indication to the customer regarding each customer response.

Abstract: A method of collecting customer intentions of customers who use automated service systems, such as web-based or interactive telephone-based service applications. Customers are surveyed when they use the application to collect their intention in visiting the system. The responses of these customers are collected and tabulated. The relative frequencies of customer intentions are analyzed and used to design an interface to the service application, so that future customers will be presented with menu-type selections that best reflect their needs.

Abstract: A method and system for automated speech-enabled responses to caller requests for information prompts caller requests for information from a menu that lists options based upon the frequency of requests for information and for automated collection and updating of content based upon the feedback provided by customers. For instance, a task analyzer classifies information requested by caller opening statements with the classifications based on the task the caller intends to accomplish. For a menu that provides information on telephone services, classifications may include instructions on how to use a service, pre-purchase information, identification of the services that the caller subscribes to, the cost of services, post-purchase information and identification of the caller's long distance carrier.

Abstract: A method of providing a caller with a directory assistance dialog. The dialog is configurable, at any level of the dialog, from an automated speech recognition (ASR) dialog to an operator-assisted (OP) dialog. The dialog is handed off to an operator if any level of the speech recognition dialog fails. Also, a configuration switch may be set to cause the dialog to be handed off to an operator even if a response at some level of the ASR dialog is successfully recognized.

Abstract: A method of designing an interface system that allows users to map the representation of their task directly to the interface. There are three major phases to the Customer-Centric Approach to Interface Design (C-CAID). End-users' tasks are categorized to determine the frequency of reasons or tasks of why users interact with a particular system. These reasons and their relative frequencies are used to design interface options that emphasize the user's task categories. Finally, the customer-centric interface designs are evaluated and compared with existing system interfaces using usability tests with actual users performing the tasks. The results from usability tests are used to pinpoint the task-option combinations that do not work well and which should be revised. Benefits of this customer-centric design are improved systems performance and increased user satisfaction.

Abstract: An interactive voice response system that allows a caller to perform a series of sequential tasks based on an instruction set. The caller is queried after each instruction to ensure that the caller has successfully completed all of the steps. Additionally, provisions are provided to automatically pause the instruction set and present reminders to the caller. Further the caller may elect to repeat instructions, back up the instruction set, receive additional details, transfer to a service representative, or receive summary information.

Abstract: The present invention relates to a customer call routing menu employing an interactive voice response system (IVR) to process a call in a customer service center. The menu messages are provided in terms of customer tasks to be performed, rather than in terms of corporate units. Further, the menu messages are arranged and played to the caller in the order of the most frequently requested tasks and include terminology commonly used by customers.

Abstract: A method and system for automating the creation of customer-centric interfaces includes a customer-centric interface system automatically creating a customer-centric interface, a collection engine, a customer language engine, a task frequency engine, a customer structure engine, and a customer performance engine. The collection engine collects a plurality of customer intention information. The customer language engine utilizes the customer intention information to create customer-centric menu prompts using the customers own terminology and action specific object words. The task frequency engine determines a frequency of occurrence for the tasks for which the customers contact the customer-centric interface and orders the tasks within the customer-centric interface. The customer structure engine determines how the customers relate the tasks together and groups the tasks according to task relationships.

Abstract: A method is provided for modeling types of customer service representatives that use a customer service representative interface. The models are used to provide data for designing the customer service representative interface. The method includes identifying behavior types of customer service representatives that use the customer service representative interface and modeling the identified behavior types of the customer service representatives to design a desired customer service representative interface.

Abstract: A method for categorizing, describing, and modeling types of system users where information from the models can be used in designing a user interface. Users may have improved performance using the user interface. A list of tentative behaviors of the users is created. This list is created by identifying the goals desired for the user interface or the user models, and listing expected and desired behaviors that are relevant to these goals. The list is revised to include only those behaviors that are important or frequent based on the goals. Categorizing the behaviors is performed by obtaining information from users regarding their characteristics and behaviors. Each user's behavioral information is then converted to a score or value. The users are then mapped or charted based on which behaviors they exhibit. The mapping or charting is analyzed to identify clusters of users. These clusters define groups of users that have similar behaviors. The groups are then analyzed to produce descriptions of each group.

Abstract: System and methods for intelligent routing of requests from customers to agents where a request is received at a service center from a customer. Identification information related to the customer is accessed. Background information on the customer is retrieved from a storage facility. Task and attitude information about the customer is gathered. A model of the customer is created. Models for at least two agents are created. A performance optimizing calculation is performed that matches the customer model and the models for the at least two agents. A best match agent from the at least two agents is determined based on the matching. The customer request is routed to the best match agent.

Abstract: A method for categorizing, describing, and modeling types of system users where information from the models can be used in designing a user interface. Users may have improved performance using the user interface. A list of tentative behaviors of the users is created. This list is created by identifying the goals desired for the user interface or the user models, and listing expected and desired behaviors that are relevant to these goals. The list is revised to include only those behaviors that are important or frequent based on the goals. Categorizing the behaviors is performed by obtaining information from users regarding their characteristics and behaviors. Each user's behavioral information is then converted to a score or value. The users are then mapped or charted based on which behaviors they exhibit. The mapping or charting is analyzed to identify clusters of users. These clusters define groups of users that have similar behaviors. The groups are then analyzed to produce descriptions of each group.