Abstract: A method for automatically routing a telephonic communication is provided, and includes receiving a customer identifier and communicating with a customer history database storing historic data and determining whether the received customer identifier corresponds to a stored customer identifier in the customer history database, wherein the customer profile included in the stored historic data is based on a portion of a customer's demographic identity. Historic data corresponding to the stored customer number is identified based on the comparison of the received customer identifier and the stored customer identifier. The telephonic communication is associated with a predetermined communication destination based on the identified historic data.

Abstract: An interface portal system that includes a non-transitory computer readable medium having a plurality of stored instructions adapted to generate a coaching portal based on behavioral assessment data, the plurality of instructions including instructions that, when executed, analyze one or more communications between a customer and an agent, wherein the analysis comprises instructions that, when executed, apply a linguistic-based psychological behavioral model to separated voice data for the customer, the agent, or both, from each communication by analyzing behavioral characteristics of the customer, the agent, or both, based on the one or more communications; instructions that, when executed, identify one or more customer-agent interaction events based on the analyzed behavioral characteristics; and instructions that, when executed, display a time-based graphic representation across a selected time interval based on one or more communications.

Abstract: The methods, apparatus, and systems described herein facilitate decision-making by providing predictions of student outcomes and behaviors. The methods include receiving a communication posted by a student, identifying keywords in text of the communication associated with one or more student metrics, scoring the communication for at least one student metric, and predicting a likelihood of a student outcome based on the score.

Abstract: Methods, apparatus, and systems for analyzing data trends are described herein. The present disclosure includes the identification of trending terms in data through the use of an unsupervised algorithm. Trends are identified and counted during a first and second time period. The frequency and co-occurrence of groups of terms is compared to determine a set of trending terms without reference to a library of pre-defined terms. The set of trending terms is displayed to a user.

Abstract: Methods, behavioral assessment computer program products, and systems for analyzing electronic customer communication data, generating behavioral assessment data and displaying instructions to a user that include receiving a plurality of types of electronic customer communication data by one or more servers configured to provide a user interface including a web site, web portal, or virtual portal or application, wherein at least one of the types of electronic communication data includes voice data, generating a text file from the voice data, identifying a customer associated with the electronic communication data received by the one or more servers, generating behavioral assessment data for the electronic communication data for that identified customer by analyzing the customer's electronic communication data, and displaying instructions to a user via a reporting engine, wherein the instructions are based on the generated behavioral assessment data, and wherein the user includes the identified customer or a c

Abstract: Methods, apparatus, and systems for analyzing data trends are described herein. The present disclosure includes the identification of trending terms in data through the use of an unsupervised algorithm. Trends are identified and counted during a first and second time period. The frequency and co-occurrence of groups of terms is compared to determine a set of trending terms without reference to a library of pre-defined terms. The set of trending terms is displayed to a user.

Abstract: The methods, apparatus, and systems described herein relate to routing based on customer satisfaction, and include receiving the customer communication; retrieving or predicting a first profile of a customer associated with a customer communication, wherein the retrieved or predicted profile includes a customer satisfaction score; predicting a second profile of a future customer; providing a list of currently available and expected available agents, wherein the currently available agents are selected by including only agents that exceed a predetermined work threshold based on an average customer satisfaction score determined over a selected time period; providing a routing recommendation to a communication distributor based on the retrieved or predicted first profile, the predicted second profile, and currently available agents' and expected available agents' proficiency at handling customers with the retrieved or predicted first and second profiles, wherein the communication distributor routes the communicat

Abstract: A method for automatically routing a telephonic communication is provided, and includes receiving a customer identifier and communicating with a customer history database storing historic data and determining whether the received customer identifier corresponds to a stored customer identifier in the customer history database, wherein the customer profile included in the stored historic data is based on a portion of a customer's demographic identity. Historic data corresponding to the stored customer number is identified based on the comparison of the received customer identifier and the stored customer identifier. The telephonic communication is associated with a predetermined communication destination based on the identified historic data.

Abstract: A method of generating a customer satisfaction score based on behavioral assessment data across one or more recorded communications, which includes analyzing one or more communications between a customer and an agent by applying a linguistic-based psychological behavioral model to each communication to determine a personality type of the customer, selecting at least one filter criterion which comprises a customer, an agent, a team, or a call type, calculating a customer satisfaction score using the at least one selected filter criterion across a selected time interval and based on one or more communications, and displaying a report including the calculated customer satisfaction score to a user that matches the at least one selected filter criterion for the selected time interval. Systems and non-transitory computer readable media configured to generate a customer satisfaction score based on behavioral assessment data are also included.

Abstract: A method for analyzing caller interaction events that includes receiving, by a processor, a caller interaction event between an agent and a caller, extracting, by a processor, caller event data from the caller interaction event, analyzing, by a processor, the caller event data, and generating, by a processor, a report displaying one or more selected categories of the caller event data. Systems and non-transitory, computer readable media that control an executable computer readable program code embodied therein, are also described.

Abstract: The methods, apparatus, and systems described herein facilitate dynamic occupancy routing decisions.

Abstract: Methods, customer-responsive computer program product, and system for analyzing electronic customer communication data, generating behavioral assessment data and generating a responsive communication that includes receiving, by a server, electronic customer communication data of two or more types, determining customer identification data associated with the electronic customer communication data by the server, analyzing the electronic customer communication data by applying a predetermined linguistic-based psychological behavioral model to the electronic customer communication data, generating behavioral assessment data by the contact center based on said analyzing, the behavioral assessment data providing a personality type for the analyzed electronic customer communication data, generating a responsive communication based on the generated behavioral assessment data, and providing the responsive electronic communication via a user interface.

Abstract: The methods, apparatus, non-transitory computer readable media, and systems described herein include recording a mono recording of a face-to-face communication between an agent and a customer using a microphone, wherein the mono recording is unseparated and includes agent voice data and customer voice data, separately recording the agent voice data in an agent recording using a second microphone; aligning the unseparated mono recording and the agent recording so they are time-synched; subtracting agent voice data from the unseparated mono recording using the agent recording to provide a separated recording including only customer voice data, wherein the agent voice data is subtracted from the unseparated mono recording based on the alignment, sound frequency analysis, or both; converting at least the customer voice data to text; and determining a personality type of the customer by applying one or more computer-implemented linguistic algorithms to the text of the customer voice data.

Abstract: A method for providing a responsive communication to a communicant, including receiving, by a control processor, a single electronic voice communication from a communicant; transcribing the electronic voice communication to text; analyzing, by a processor, the text of the electronic voice communication by mining the text and applying a predetermined linguistic-based psychological behavioral model to the text of the electronic voice communication; generating, by a processor, behavioral assessment data including a personality type corresponding to the analyzed text of the electronic voice communication; generating, by a processor, event data based on the analyzed text of the electronic voice communication; and generating, by a processor, a responsive communication based on the event data. Systems and non-transitory, computer readable media that control an executable computer readable program code embodied therein, are also described.

Abstract: The methods, apparatus, and systems described herein analyze mono-recorded customer-agent communications to apply distress analysis techniques to identify one or more distress events. The methods include recording a mono recording of a communication between an agent and a customer, separately recording the agent voice data in an agent recording, subtracting agent voice data from the mono recording using the agent recording to provide a separated recording including only customer voice data, convening at least the customer voice data to text, and applying distress analysis to a portion of the communication to identify one or more distress events.

Abstract: Methods and systems to predict user behavior based on analysis of a video communication by one or more processors, which methods include receiving a user video communication, extracting video analysis data optionally including facial analysis data for the user from the video communication, extracting, by the one or more processors, voice analysis data from the user video communication, generating an outcome prediction score based on the video analysis data and voice analysis data that predicts a likelihood that a user will take an action leading to an outcome, sending a responsive communication to the user based on the outcome prediction score to increase the likelihood of that outcome.

Abstract: Systems and techniques for automated quality assurance are disclosed. The systems receive and analyze communications between customers and customer service agents for quality assurance purposes, select a sub-set of communications for further quality assurance review, and display analysis results to a user.

Abstract: A method of generating a customer satisfaction score based on behavioral assessment data across one or more recorded communications, which includes analyzing one or more communications between a customer and an agent by applying a linguistic-based psychological behavioral model to each communication to determine a personality type of the customer, selecting at least one filter criterion which comprises a customer, an agent, a team, or a call type, calculating a customer satisfaction score using the at least one selected filter criterion across a selected time interval and based on one or more communications, and displaying a report including the calculated customer satisfaction score to a user that matches the at least one selected filter criterion for the selected time interval. Systems and non-transitory computer readable media configured to generate a customer satisfaction score based on behavioral assessment data are also included.

Abstract: Methods, customer-responsive computer program product, and system for analyzing electronic customer communication data, generating behavioral assessment data and generating a responsive communication that includes receiving, by a server, electronic customer communication data of two or more types, determining customer identification data associated with the electronic customer communication data by the server, analyzing the electronic customer communication data by applying a predetermined linguistic-based psychological behavioral model to the electronic customer communication data, generating behavioral assessment data by the contact center based on said analyzing, the behavioral assessment data providing a personality type for the analyzed electronic customer communication data, generating a responsive communication based on the generated behavioral assessment data, and providing the responsive electronic communication via a user interface.

Abstract: The methods, apparatus, and systems described herein facilitate dynamic occupancy routing decisions.