Abstract: A system and method for testing of automated contact center customer response systems using a customer response testing system and a real time conversation engine, wherein the customer response testing system generates simulated human queries using persona profiles, sends test cases containing those queries to a contact center under test, and receives and analyzes the responses to determine whether the contact center's automated response systems understand the queries and respond appropriately.

Abstract: A system and method for testing of automated contact center customer response systems using a customer response testing system and a real time conversation engine, wherein the customer response testing system generates simulated human queries using persona profiles, sends test cases containing those queries to a contact center under test, and receives and analyzes the responses to determine whether the contact center's automated response systems understand the queries and respond appropriately.

Abstract: A system and method for testing of automated contact center customer response systems using a customer response testing system and a real time conversation engine, wherein the customer response testing system generates simulated human queries using persona profiles, sends test cases containing those queries to a contact center under test, and receives and analyzes the responses to determine whether the contact center's automated response systems understand the queries and respond appropriately.

Abstract: A system and method for testing of automated contact center customer response systems using a customer response testing system and a real time conversation engine, wherein the customer response testing system generates simulated human queries using persona profiles, sends test cases containing those queries to a contact center under test, and receives and analyzes the responses to determine whether the contact center's automated response systems understand the queries and respond appropriately.

Abstract: A system and method for testing of automated contact center customer response systems using a customer response testing system and a real time conversation engine, wherein the customer response testing system generates simulated human queries using persona profiles, sends test cases containing those queries to a contact center under test, and receives and analyzes the responses to determine whether the contact center's automated response systems understand the queries and respond appropriately.

Abstract: A computer-implemented method and an apparatus facilitate management of customer interactions on multiple interaction channels. A communication quality metric and a contextual environment are tracked for an ongoing customer interaction executed on a first interaction channel. A closure of the first interaction channel is effected based on at least one of: a detected change in a current value associated with the communication quality metric to be below a preset threshold value, a detected or an anticipated change in the contextual environment, and a receipt of a customer request for closing the first interaction channel. The effecting of the closure of the first interaction channel includes a transitioning of the ongoing customer interaction from the first interaction channel to a second interaction channel.

Abstract: An intelligent IVR system identifies a customer based on previous customer interactions. Customer intent is predicted for an ongoing interaction and personalized services are proactively offered to the customer. A self-optimizing algorithm improves intent prediction, customer identity, and customer willingness to engage and use IVR.

Abstract: A computer-implemented method and an apparatus facilitate management of customer interactions on multiple interaction channels. A communication quality metric and a contextual environment are tracked for an ongoing customer interaction executed on a first interaction channel. A closure of the first interaction channel is effected based on at least one of: a detected change in a current value associated with the communication quality metric to be below a preset threshold value, a detected or an anticipated change in the contextual environment, and a receipt of a customer request for closing the first interaction channel. The effecting of the closure of the first interaction channel includes a transitioning of the ongoing customer interaction from the first interaction channel to a second interaction channel.

Abstract: A computer-implemented method and an apparatus for automatic execution of at least one next action during a customer interaction receives current information related to a customer from at least one device associated with the customer. At least one next action is determined for the customer in response to the received current information. The at least one next action is determined based on the current information and stored past information corresponding to the customer. Further, an automatic execution of the at least one next action is effected on behalf of the customer if the at least one next action satisfies one or more predefined criteria. The at least one next action is executed on a device from among the at least one device associated with the customer.

Abstract: A device application is linked to a customer service interface. Information related to a user and to one or more user interactions is stored with an application associated with a user device. The information related to the user and the one or more user interactions configures an interaction context. A request to communicate with a customer service interface is received from the user during an on-going user interaction with the application. An authentication of the user is performed upon receiving the user request. The interaction context is provided to the customer service interface upon authenticating the user. The authentication of the user and the providing of the interaction context facilitate a seamless continuation of the on-going user interaction from the application associated with the user device to the customer service interface.

Abstract: An intelligent IVR system identifies a customer based on previous customer interactions. Customer intent is predicted for an ongoing interaction and personalized services are proactively offered to the customer. A self-optimizing algorithm improves intent prediction, customer identity, and customer willingness to engage and use IVR.

Abstract: An intelligent IVR system identifies a customer based on previous customer interactions. Customer intent is predicted for an ongoing interaction and personalized services are proactively offered to the customer. A self-optimizing algorithm improves intent prediction, customer identity, and customer willingness to engage and use IVR.

Abstract: An intelligent IVR system identifies a customer based on previous customer interactions. Customer intent is predicted for an ongoing interaction and personalized services are proactively offered to the customer. A self-optimizing algorithm improves intent prediction, customer identity, and customer willingness to engage and use IVR.