A system includes a client device including a processor, a telephony radio that supports telephony communications, and a data radio that supports data communications. The client device conducts, via the telephony radio, a call with a telephony service. Further the client device identifies a context of the call, identifies a subset of stored private data associated with the context of the call; and in parallel with the call, provides the subset of the stored private data, via a data radio, to a data service.

Recently, there has been a demand for further improvement of accuracy of analysis. A system is provided that includes an acquisition unit that acquires call data which is a record of a call between a client and a contact center, a sound recognition unit that performs sound recognition on the call data by using a keyword registered in dictionary data, an analysis unit that performs analysis using a keyword included in a result of the sound recognition, and a registration unit that registers in the dictionary data, a keyword included in a product information database among a plurality of the keywords included in the result of the sound recognition, the product information database storing product information about each of a plurality of products.

Systems and methods for customizing business applications based upon user intent scores is described. A machine learning model trained to specifically predict when a user is likely to engage in a specific activity while interacting with the business application may be trained using data regarding prior interactions between a business application and a plurality of users. The machine learning model may thereafter provide a probability score for a particular user, the probability score indicating the likelihood that the user will engage in the specific activity for which the model has been trained to predict. The probability may be combined with a business value factor to produce a user intent score indicating the relative value of the user engaging in the specific activity. A business application comprising an app executing on a client device, a webpage, an automated menu at a call-in service center, or human operator interacting with the user at a call in the service center may be customized for the particular user based upon the user intent scores.

Technology for placing a user on-hold can include sending a push notification to a user device after the call has been placed on-hold. A link in the push notification can request authentication credentials from the user. When the authentication credentials have been received and verified, a chat window can be launched via an application on the user device. The intent of the call can be determined based at least in part by information received via the chat window. The authentication information and the intent of the call can be transferred to a representative answering the call.

An adaptive cloud conversation platform capable of making automated decisions regarding when and how to establish ongoing communications with consumers so as to maximize the relationship between the consumer and a given brand. The system has a connection management services layer which determines what communications should be established and how they should be established, an initiation management services layer which determines when communications should be established, and a user management services layer which stores information about consumers and brands for determination of when and how communications should be established. Certain of these services have machine learning algorithms incorporated into them trained to perform analyses of the particular type of operation handled by that service. The outputs of each service can be used as inputs to other services, such that a network of machine learnings algorithms is created which determines when and how to establish ongoing communications with consumers.

In various embodiments, a device receives profile data regarding users or devices of an on-premise telephony system. The device identifies, based on the profile data, group features associated with the users or devices of the on-premise telephony system. The device forms a candidate set of users or devices of the on-premise telephony system for migration to a cloud-hosted call agent, based on them sharing at least one of the group features. The device provides data indicative of the candidate set of users or devices to a user interface for display.

An adaptive conversational system may simultaneously monitor multiple active calls or ongoing voice or telephone conversations, may extract a different set of conversation elements from a current point in each conversation in real-time as each conversation proceeds, may determine different rules that apply to current points of different ongoing conversations based on the extracted conversation elements satisfying different rule triggers, and may control different conversations at different times according to actions of different rules that are applied at different times to different conversations. The system may selectively control the conversations when the conversations become non-compliant, deviate from best practices, or can be controlled to more effectively reach a positive disposition than when allowing a telephone agent to independently control the conversation. The system may use machine learning and/or artificial intelligence to define rules based on tracked actions that are produce a positive disposition more effectively than existing rules.

The present invention is a system and method of continuous sentiment tracking and the determination of optimized agent actions through the training of sentiment models and applying the sentiment models to new incoming interactions. The system receives conversations comprising incoming interactions and agent actions and determines customer sentiment on a micro-interaction level for each incoming interaction. Based on interaction types, the system correlates the determined sentiment with the agent action received prior to the sentiment determination to create and train sentiment models. Sentiment models include agent action recommendations for a desired sentiment outcome. Once trained, the sentiment models can be applied to new incoming interactions to provide CSRs with actions that will yield a desired sentiment outcome.

A method and system for providing a data consolidation for improved customer communication and agent performance evaluation in a multi-channel contact center are provided. The method includes receiving interaction data of an agent with customers across different communication channels within the contact center, consolidating the interaction data received across the different communication channels, aggregating the consolidated data to generate a set of metrics indicative of agent performance, inputting the set of metrics into an agent performance measurement framework, and determining a performance score for the agent based on an output of the agent performance measurement framework.

[Object] To propose an information processing apparatus, an information processing method, an information processing system, and a program that enable a user to check handover of information between an agent and an operator.

[Solving Means] An information processing apparatus according to the present technology is connected to be capable of communicating with a terminal apparatus of a user and a terminal apparatus of an operator who interacts with the user and has an agent that performs information exchange with the user about a specific topic. The information processing apparatus includes a control unit. The control unit causes the terminal apparatus of the user to display a situation where the agent is communicating a progress status of the information exchange to the operator.