A system and method for optimizing callback times to increase the success rate of callbacks while managing overflow of calls to alternate sites when callbacks are unsuccessful. The system and method use a context-aware pacing algorithm to determine when callbacks are likely to be successful from a preferred contact site, routing to alternate callback sites when callbacks are unsuccessful, and preferences for re-routing back to the preferred site when a callback is successful and the agent with whom the caller has interacted previously is available.

A system for providing integrated contact information with search results, comprising a plurality of contact centers, each comprising at least a plurality of contact agents; a callback cloud, comprising at least a plurality of contact agents; a queue manager, comprising at least a software components operating and stored on a computing device; wherein the contact agents receive and respond to customer interactions; further wherein the queue manager monitors contact agent availability; further wherein the queue manager receives interaction requests; and further wherein the queue manager provides queue information to interaction requestors.

A system and method for managing virtual queues. A cloud-based queue service manages a plurality of queues hosted by one or more entities. The queue service is in constant communication with the entities providing queue management, queue analysis, and queue recommendations. The queue service is likewise in direct communication with queued persons. Sending periodic updates while also motivating and incentivizing punctuality and minimizing wait times based on predictive analysis. The predictive analysis uses “Big Data” and other available data resources, for which the predictions assist in the balancing of persons across multiple queues for the same event or multiple persons across a sequence of queues for sequential events.

A system for providing active callback management using callback objects and contact information integration, utilizing a cloud callback system comprising at least a profile manager, callback manager, interaction manager, media server, and environment analyzer, allowing users to call businesses, agents in contact centers, or other users who are connected to a cloud callback system, and, failing to connect to the individual they called, allow for an automatic callback object to be created, whereby the two users may be automatically called and bridged together at a time when both users are available.

A system and method for managing virtual queues. A cloud-based queue service manages a plurality of queues hosted by one or more entities. The queue service is in constant communication with the entities providing queue management, queue analysis, and queue recommendations. The queue service is likewise in direct communication with queued persons. Sending periodic updates while also motivating and incentivizing punctuality and minimizing wait times based on predictive analysis. The predictive analysis uses “Big Data” and other available data resources, for which the predictions assist in the balancing of persons across multiple queues for the same event or multiple persons across a sequence of queues for sequential events. Furthermore, the system utilizes a virtual agent engine and various predictive models to schedule and execute callbacks between a person in a virtual queue and a virtual agent based on predictive model results.

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.

A call management system of a call center retrieves from a customer database enterprise customer data associated with an identified customer in a customer call, which may include customer event data, attributions data, and activity event data. The customer database tracks prospects, leads, new business, and purchasers of an enterprise. The system retrieves customer demographic data associated with the identified customer. A predictive model is selected from a plurality of predictive models based on retrieved enterprise customer data. The selected predictive model, including a logistic regression model, and tree-based model, determines a value prediction signal for the identified customer, then classifies the identified customer into a first value group or a second value group. The system routes a customer call classified in the first value group to a first call queue assignment, and routes a customer call classified in the second value group to a second call queue assignment.

An enhanced abandoned call recovery (“E-ACR”) process allows certain abandoned calls to be eligible for a callback call. An E-ACR assignment point defines which abandoned calls in an inbound campaign or interactive voice response (“IVR”) menu are eligible to be processed to determine whether the E-ACR callback should occur. The determination of whether a callback occurs involves various compliance tests, such as ensuring calling window, call attempts, and other regulatory concerns are addressed. Once a callback is determined to occur, it is associated with a specific campaign to ensure the called party is provided with agents having the skill set as defined for that assignment point. In this manner, only eligible callers receive an E-ACR callback, and further receive the callback in a compliant manner and handled by the same skill set of agents as would have been allocated to the caller had they not abandoned their call.

Aspects described herein may allow for deploying third-party callback to be performed on a mobile device. For example, the mobile device may configure a third-party callback to be performed after a triggering event is detected by a remote device. The triggering event may relate to a remote device associated with the mobile device. A determination may be made as to whether the mobile device is within a pre-determined proximity of the remote device. If the two devices are in proximity and if the mobile device receives a message that indicates the triggering event has been detected, the mobile device may perform the third-party callback. In this way, a user's need to request services conveniently and accurately is facilitated.

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.