Systems and methods for intelligently routing a member of an organization to a single point-of-contact within an optimized, secure network to address all the member's healthcare needs are described. The disclosed intelligent routing configurations transform and process, in real-time, vast amounts of member data to generate aggregated diagnoses and a member score specific to each member's household. The scores, among other things, are used to determine an identification of special needs and an appropriate advocate within the organization to route the member, and its account file containing real-time member and household level data.

A system and method for intelligently routing calls between customers and agents. The system and method use knowledge graphs to generate route recommendations for a route selection system. The system uses dynamically selected objective functions to generate the route recommendations. The objective functions may be selected according to the intent of the call. The system and method can also be used to reroute ongoing calls when the intent of the call changes.

In one aspect, an example methodology implementing the disclosed techniques includes, in response to receipt at a call center of a call by a caller, generating a compatibility score for the caller, the compatibility score for the caller optimizes for caller satisfaction and potential upsell opportunities. The method also includes generating a compatibility score for individual agents available to handle the call, the compatibility score for the individual agents optimize for caller satisfaction and potential upsell opportunities. The method also includes matching the compatibility score for the caller to the compatibility scores for the individual agents and assigning an agent to the call based on the matching of the compatibility scores for the caller and the individual agents.

Aspects of systems and methods for maintaining and operating agent nodes are provided. In some embodiments, calls, contacts, and other work units may be routed to individual customer service agents via a centralized queue based on a variety of factors. Some embodiments may provide market-based call pricing and customer service agent compensation.

A system and method for managing a customer's experience with a contact center that takes available data about the customer, the agents of the contact center, and the organization represented by the contact center, for identifying opportunities for additional conversations/interactions with the customer and engaging in those additional conversations/interactions at a time and with a resource predicted to maximize outcomes for the organization. A processor is configured to identify express and/or implied intents for an interaction between the customer and the contact center. A business goal related to the express and/or implied intents is also identified for determining a current performance of the contact center and for identifying any performance gaps. Contact center targets are identified based on their performance in handling the express and/or implied intents, and the identified performance gaps. An available one of the identified targets is then selected for routing the interaction to the target.

A system may receive an indication that a user is accessing an ATM, receive, from the ATM, average session duration data over a predetermined period, generate, using a machine learning model, a busyness score for the ATM based on the average session duration data over the predetermined period, and determine whether the busyness score for the ATM exceeds a busyness score threshold. When the busyness score for the ATM does not exceed the busyness score threshold, the system may cause the ATM to present, via a first graphical user interface, a default ATM experience. When the busyness score for the ATM exceeds the busyness score threshold, the system may cause the ATM to present via, a second graphical user interface, a busy ATM experience.

Embodiments of the present invention provide systems and methods for determining an engagement level for a customer-agent interaction (e.g., a phone call, text chat, etc.), and the engagement level can be used to evaluate the performance of the agent. For example, the engagement level can be used to determine or adjust a skill level of the agent, a performance of the communication channel that facilitates the interaction, and/or an optimal workload of the agent. According to some embodiments, the engagement level is used to determine that the agent may be experiencing difficulty satisfying a customer inquiry such that the agent should be assigned resources or assistance.

Provided are a call deflection and response system and method, wherein a voice call from a caller device is received, a skill group is determined to resolve an issue associated with the call, and a text response to the issue is sent to the caller device, providing a context-based personalized response. A caller leaves a detailed voicemail explaining an issue needing resolution, which is electronically transcribed and then run through a classifier to determine concepts and intents associated with the call. Based on the concepts and intents, responsibility for the call and associated files are transferred to a particular skill group on a chat platform for resolution. A chat entity from the appropriate skill group determines and provides an issue response via text message to the caller device, e.g., to the caller's mobile phone.

Methods to reduce agent effort and improve customer experience quality through artificial intelligence. The Agent Assist tool provides contact centers with an innovative tool designed to reduce agent effort, improve quality and reduce costs by minimizing search and data entry tasks The Agent Assist tool is natively built and fully unified within the agent interface while keeping all data internally protected from third-party sharing.

Apparatuses and methods concerning providing a data-communications contact center virtual agent are disclosed. As an example, user-data-communications between client and participant stations are facilitated as follows, which may be implemented using a data communications server and associated communications circuitry. Service request data is received from users at a participant stations, and context information is identified for user-data-communications between a client station and the participant stations based on the service request data at least one communications-specific characteristic associated with the user-data-communications. The identified context information is aggregated for the client station and used for choosing a data routing option routing data with each user at the participant stations, based on the service request data and the aggregated context information.