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 method of facilitating predictive intent-based routing of service requests. Accordingly, the method may include receiving a service request data from a user device, initiating a chatbot, retrieving a service portfolio based on the receiving of the service request data, processing the service portfolio and the service request data, determining a service level, analyzing the service request data using a first machine learning model, determining an intent based on the analyzing, generating an adjusted service level based on the intent using a second machine learning model, assigning an agent to a user of the at least one user based on the adjusted service level, generating a service notification for the agent based on the assigning, transmitting the service notification to the user device and an agent device associated with the agent, and storing the service request data, the service notification, and the adjusted service level.

Apparatus and methods concerning call routing are disclosed. In an example embodiment, a call alert message, indicative of the call answer options, is communicated from a data-communications server to the communication device, determined in response to receiving an incoming call for a communication device at the server. A selected option is received from the communication device. In response to the selected option indicating the first call answer option, the call is routed to the communication device as a call via a data network or in response to the selected option indicating the second call answer option, the call is routed to the communication device via a PSTN.

Disclosed is a precision queuing (PQ) system that automatically and dynamically revises the values of precision queue step rules (PQSRs) with customizable thresholds based on current contact center conditions such as varying hours of operation and number of agents available.

Unsolicited electronic communications such as robocalls and person-initiated solicitation calls are reduced by imposing tolls for completion of the connections to the called parties, and refunding the tolls to the entities indicated by the electronic communications as the calling parties. In this way, a dishonest originator of a spoofed call bears the cost of the toll, and the toll is not refunded to the dishonest originator. On the other hand, the toll collected from an honest originator of a non-spoofed call is refunded to the honest originator, making the toll transparent to the honest originator and avoiding annoyance of the honest caller caused by the toll. Unsolicited calls may be subjected to filtering, particularly filtering based on the indications of the origins of the calls.

A system and method for secure storage and management of transitory data, comprising at least a profile manager, a callback manager, a context analysis engine, and a vault manager, which allows a user to create a data container to store data preferences, which encrypts the data stored within a data container, which creates a password for accessing the data container, which temporarily stores the data container, which manages data container interactions between the system user and a second user, such as a business enterprise, and which establishes default preferences and creates a default container based upon context content data.

Embodiments described herein provide for passive caller verification and/or passive fraud risk assessments for calls to customer call centers. Systems and methods may be used in real time as a call is coming into a call center. An analytics server of an analytics service looks at the purported Caller ID of the call, as well as the unaltered carrier metadata, which the analytics server then uses to generate or retrieve one or more probability scores using one or more lookup tables and/or a machine-learning model. A probability score indicates the likelihood that information derived using the Caller ID information has occurred or should occur given the carrier metadata received with the inbound call. The one or more probability scores be used to generate a risk score for the current call that indicates the probability of the call being valid (e.g., originated from a verified caller or calling device, non-fraudulent).

A resource managing computer system for managing at least one resource in an enterprise is disclosed. The resource managing computer system includes a communication interface for establishing at least one web based chat communication session with at least one customer. The system further includes a monitoring module for monitoring one or more parameters associated with the at least one web based chat communication session. The system further includes a computing module for computing at least one confidence score based on the one or more monitored parameters of the at least one web based chat communication session. The system further includes an allocation module for allocating the at least one resource to the at least one web based chat communication session, wherein the allocation is performed based on the at least one computed confidence score.

A method of facilitating predictive intent-based routing of service requests. Accordingly, the method may include receiving a service request data from a user device, initiating a chatbot, retrieving a service portfolio based on the receiving of the service request data, processing the service portfolio and the service request data, determining a service level, analyzing the service request data using a first machine learning model, determining an intent based on the analyzing, generating an adjusted service level based on the intent using a second machine learning model, assigning an agent to a user of the at least one user based on the adjusted service level, generating a service notification for the agent based on the assigning, transmitting the service notification to the user device and an agent device associated with the agent, and storing the service request data, the service notification, and the adjusted service level.

Customers can become bored with an interaction with an agent. By providing speech and/or images, of a celebrity disguising the speech, and/or image, of the agent, customers can appear to interact with a particular celebrity. As a result, customers are more likely to stay engaged and have a positive experience. The celebrity, or a particular persona of a celebrity, may be selected from customer preferences and/or a purpose of the call. For example, a movie star's role may have a persona, such as a “heavy,” suitable for collection calls (audio or audio-video), whereas a scientific or technical innovator may be selected for technical support calls.