Implementations are directed to using an assistant to initiate automated telephone calls with entities. Some implementations identify an item of interest, identify a group of entities associated with the item, and initiate the calls with the entities. During a given call with a given entity, the assistant can request a status update regarding the item, and determine a temporal delay before initiating another call with the given entity to request a further status update regarding the item based on information received responsive to the request. Other implementations receive a request to perform an action on behalf of a user, identify a group of entities that can perform the action, and initiate a given call with a given entity. During the given call, the assistant can initiate an additional call with an additional entity, and generate notification(s), for the user, based on result(s) of the given call and/or the additional call.

A method and system for automatically executing an action within a call center environment. Data is aggregated from multiple data sources into a combined data stream. One of the data sources is a source of data corresponding to at least one communication processed by the call center one of the data sources can be a source of external data representing activity that is external to the call center. The combined data stream is processed into successive batches of data corresponding to one or more communications between a call center agent and a communicating party received by the call center. A sensor data structure specifying at least one rule is applied to the batches of data. The at least one rule can include a machine learning model and a configuration data structure based on historical data from the multiple data sources. When it is determined that at least one of the batches satisfies the at least one rule, a notification message relating to the one or more communications is generated. The call center executes an action specified by the sensor data structure based on the notification message. The action can address a situation corresponding the at least one communication. The actions can be various actions such as notifying a specified party, generating an API call, or the like.

Call propensity source data may be received that include a first percentage of call propensity source data that correspond to presence of post-visit phone calls to a customer service of an entity after some customer visits to a web site of an entity and a second percentage of call propensity source data that correspond to absence of post-visit phone calls to the customer service after other customer visits to the website. A machine-learning model is trained based on a plurality of features in at least a portion of the call propensity source data to generate a trained machine-learning model. The trained machine-learning model is applied to multiple features included in at least one of corresponding website activity data and corresponding activity error data of a customer to generate a probability score that measures a likelihood of the customer calling the customer service regarding an issue that is unresolved via the website.

An agent queuing system implemented without relying on a private branch exchange. The queuing system can be cloud-based and routes calls to agents, for example, through a first-in/first-out (FIFO) queue. Clients are assigned a unique number that identify one or more queues. When a call is received, a database maintains the unique number that was called and the associated company information is retrieved, along with any queues allocated for their company. A call is placed to the next available agent from the selected queue. A recording is played to the agent identifying the queue the call is arriving from and the agent is prompted to accept the call. If the call is accepted, the agent is taken out of the available agent pool for the duration of the call. The call can be routed without exposing the phone numbers of the caller or agent involved in the call.

A call processing system and method for processing calls from high volume callers. A frequency of call activity is monitored for callers to determine reception of a call from a high frequency caller. When a call is received from such a caller, provided is information predicted to be requested from the caller prior to the caller being voice connected to a company representative. The retrieved information is then provided to a company representative prior to the caller being voice connected with a company representative as to expedite the call. Additionally, a customized message for the high frequency caller may be generated prior to the caller being voice connected with a company representative whereby the customized message contains information predicted to be responsive to a predicted inquiry from the determined high frequency caller to mitigate the need to connect the caller to a company representative.

An agent queuing system implemented without relying on a private branch exchange. The queuing system can be cloud-based and routes calls to agents, for example, through a first-in/first-out (FIFO) queue. Clients are assigned a unique number that identify one or more queues. When a call is received, a database maintains the unique number that was called and the associated company information is retrieved, along with any queues allocated for their company. A call is placed to the next available agent from the selected queue. A recording is played to the agent identifying the queue the call is arriving from and the agent is prompted to accept the call. If the call is accepted, the agent is taken out of the available agent pool for the duration of the call. The call can be routed without exposing the phone numbers of the caller or agent involved in the call.

The present disclosure relates generally to facilitating routing of communications. One example includes a communication server determining capacities associated with a terminal devices based on workloads for agents associated with the terminal devices. Historical acceptance data is accessed for past interaction invitations to user devices associated with one or more criteria. Current data is then used to determine available interactions and to facilitate interactions using interaction invitations based on the historical data and the current number of available interactions.

Sharing data by defining a data encoding table, maintaining a data record database, defining a data encryption code, providing the data encryption code with an outgoing call, receiving an audio response including encrypted data, decrypting the encrypted data, and updating the data record database according to the data.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for announcing and detecting automated conversation are disclosed. One of the methods includes initiating, over a natural language communication channel, a conversation with a communication participant using a natural language communication method that includes a dialogue of natural language communications. The communication participant is determined to be automated using a pre-defined adaptive interactive protocol that specifies natural language linguistic transformations defined in a sequence. The conversation can be transitioned to a communication method that is different form the natural language communication method in response to determining that the communication participant is automated.

Disclosed herein are systems and methods for determining whether an automated telephone call has been answered by a particular user, a different person, or a voicemail service. In response to determining that the call has been answered by the user, a different person, or a voicemail service, the systems and methods can output different respective messages, initiate messaging to the user via alternate communication paths, or perform other actions.