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.

Context data management in a contact center environment is provided. For example, a method comprises receiving a given contact instance for a given user of a contact center, wherein the contact center comprises a plurality of communication channels configured to enable the user to initiate a contact instance and wherein the given contact instance is received over one of the plurality of communication channels. The method further comprises one of generating and updating a context data management pattern in response to receiving the given contact instance, wherein the context data management pattern comprises a data structure of one or more records that maintain information relating to the given contact instance received over the one of the plurality of communication channels and information relating to one or more previous contact instances associated with the user received over one or more of the plurality of communication channels.

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.

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.

Methods for optimizing the routing of customer communications include receiving a customer communication; identifying a customer associated with the customer communication; accessing a profile of the identified customer to determine customer data; receiving customer metric scores for a plurality of customer metrics; identifying available agents; accessing a profile of each available agent to determine agent data; predicting interaction outcome metric values for a plurality of customer metrics based on the customer data and the agent data; calculating, in real-time, an aggregate agent-customer pairing score for each available agent; selecting a responding agent from the available agents with the highest aggregate agent-customer pairing score; and providing a routing recommendation to a communication distributor to route the customer communication to the responding agent with the highest aggregate agent-customer pairing score.

Techniques are described for generating a custom voice for a virtual agent. In one implementations, a method includes receiving information identifying a customer contacting a call center. The method includes selecting a voice for a virtual agent based on information about the customer. The method also includes assigning the voice to the virtual agent during communications with the customer.

Disclosed embodiments may include a system that 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.

Methods and systems described in this disclosure allow customers to personalize their phone experience when calling into an organization. In some embodiments, customers who may benefit from this service are identified based on the content of the customer's previous or current phone calls to the organization. The identified customers may be invited to enroll and to provide preferences for a customized Interactive Voice Response experience. In some embodiments, the customer can elect to hear the balances of one or more of his accounts without going through a phone menu or asking a representative to look up the relevant amounts. Once enrolled, when the customer dials into the organization and upon successful authentication, the organization proactively states the customer's account balances with no further customer request.

Call routing technology can route a current call from a person based on an analysis of call data related to a prior call from the same person. For example, based at least on a customer satisfaction score determined from call data related to a prior call, a call routing server can identify one or more persons to whom a current call from the same person should be routed. Next, the call routing server can route the current call to one of the identified customer service representatives.

A computerized-method for redirecting, inbound-voice-interactions to digital channels in a contact center, is provided herein. The computerized-method includes: (i) operating a digital-qualifier module to determine a digital-medium-transition-quotient, of an inbound-voice-interaction of a customer in an inbound-queue. The digital-medium-transition-quotient is an indication of a level of suitability of a digital-communication-channel to resolve a customer issue; (ii) operating an interaction-redirection module to determine a digital-communication-channel for redirection of the inbound-voice-interaction, based on customer-preference and the determined digital-medium-transition-quotient; and (iii) forwarding the inbound-voice-interaction and the determined digital-communication-channel to an Automatic Call Distribution (ACD) system to be carried-out by an agent via the determined digital-communication-channel when the determined digital-medium-transition-quotient is above a preconfigured threshold.