One or more embodiments of techniques or systems for intelligent data presentation are provided herein. Data can be presented on similar devices having different characteristics in different manners. For example, data may be rendered in a first manner on a first device having one monitor, the same data may be rendered in a second manner on a second device having two displays or a different display size. Financial information, sales data, banking information, etc. may be presented in a variety of ways based on capabilities or properties of a device accessing the information or data. Similarly, renderings may be selected based on interaction capabilities or interaction options a user may have with different renderings or presentations. In other embodiments, user interaction with an automated teller machine (ATM), call center, vehicle, or other interface can be based on device properties or device capabilities.

Methods for routing customers to an agent include receiving a customer communication; representing the customer communication as an array of one or more agent skills desired to handle the customer communication in one hot coding format or as a vector with an induced metric using an embedding algorithm; routing the represented customer communication to an agent having the one or more agent skills; measuring performance of the agent in relation to the one or more agent skills during or after the customer communication; updating, in real-time, one or more performance scores of the agent in a skill profile, wherein the one or more performance scores are related to the one or more agent skills; and routing subsequent customer communications based on the updated one or more performance scores.

Systems and methods are disclosed for intelligent scheduling of calls to sales leads, leveraging machine learning (ML) to optimize expected results. One exemplary method includes determining, using a connectivity prediction model, call connectivity rate predictions; determining timeslot resources; allocating, based at least on the call connectivity rate predictions and timeslot resources, leads to timeslots in a first time period; determining, within a timeslot and using a lead scoring model, lead prioritization among leads within the timeslot; configuring, based at least on the lead prioritization, the telephone unit with lead information for placing a phone call; and applying a contextual bandit (ML) process to update the connectivity prediction model, the lead scoring model, or both. During subsequent time periods, the updated connectivity prediction and lead scoring models are used, thereby improving expected results over time.

Disclosed herein are a system, method, and computer-readable medium with instructions for recommending a service provider based on a user's approximate current location. The service provider may be recommended for a service that is verified under a user's insurance policy and is also within proximity to the user's approximate current location. The user's approximate current location may be determined by location-based technology. The entity that receives and/or recommends the service provider may initiate a request for the service from the service provider. Further embodiments are related to routing a call to provide information to the user that is responsive to the user's location-relevant request. For example, systems, such as an automotive telematics system, may request information and be routed to the appropriate division of a user's insurance provider such that the automotive telematics system can provide services to the user that are user-specific (e.g., covered by the user's insurance policy).

A platform can receive information regarding a user interaction, wherein the user interaction is associated with one or more channels that correspond to respective interfaces or media for the user interaction; retrieve supplemental information associated with the user interaction, wherein the supplemental information relates to at least one of: a state of a managed device associated with the user interaction, or a previous user interaction; identify, based on the information regarding the user interaction or the one or more channels, one or more models to process the information regarding the user interaction and the supplemental information, wherein the one or more models are identified from a plurality of models; determine, using the one or more models, an action to be performed with regard to the user interaction; and provide information identifying the action.

Techniques for behavioral pairing in a task assignment system are disclosed. In one particular embodiment, the techniques may be realized as a method for behavioral pairing in a task assignment system comprising: determining, by at least one computer processor communicatively coupled to and configured to operate in the task assignment system, a priority for each of a plurality of tasks; determining, by the at least one computer processor, an agent available for assignment to any of the plurality of tasks; and assigning, by the at least one computer processor, a first task of the plurality of tasks to the agent using a task assignment strategy, wherein the first task has a lower-priority than a second task of the plurality of tasks.

Systems and methods of placing a telephone call for a user include monitoring the telephone number that the user has requested to reach. Depending upon the telephone number requested by the user, the system might take an alternate action, rather than simply placing a call to the requested telephone number. In some instances, the system might take an action in addition to placing a call to the requested telephone number.

Technologies for monitoring interactions between customers and agents include an interaction management computing device communicatively coupling a customer computing device and an agent computing device to facilitate a support call interaction. The interaction management computing device is configured to receive a video call from a customer and perform a facial recognition analysis of the customer based on images of the customer received with the video call. Additionally, the interaction management computing device is configured to determine a probable emotional state of the customer as a function of the facial recognition analysis of the customer and insert the video call into a service queue as a function of the probable emotional state of the customer. Additional embodiments are described herein.

A system for scheduling resources and rules for routing includes a server connected to a network, a scheduling application executable from the server, and at least one programmable software agent for scheduling routing rules. The scheduling application receives statistics about forecast arrival rates for incoming interactions and current resource availability data and schedules resources and routing rules according to the forecast requirements the software agent propagating the portion of scheduling relative to the routing rules.

A system and method for asynchronous conversation routing and tracing that allows a client and agent to connect and reconnect to one another over a discontinuous engagement. The system and method facilitate this by allowing multiple methods of communication between the client and agent, including live communications and out-of-band communications. All communications between a client and agent are tied to a client case accessible by the agent, and the client case can include context and environmental data to further assist the agent or to route a customer service call to an appropriate agent. At any time, the client or agent can send out-of-band messages to one another to advance the customer service process, or the client or agent can seek to re-establish live communication with each other. This provides the client with a consistent point of contact not easily supportable with phone based call centers where support is single-threaded.