Abstract: A method for automatically routing a telephonic communication to at least one of a plurality of communication destination addresses is provided. The method is implemented by a computer readable medium having a plurality of code segments. The method comprises the step of receiving customer identifier and communicating with a customer history database configured to store historic data. The method also includes determining whether the received customer identifier corresponds to a stored customer identifier in the customer history database. 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. The associated communication data is transmitted to a switching signal.

Abstract: A method for automatically routing a telephonic communication to at least one of a plurality of communication destination addresses is provided. The method is implemented by a computer readable medium having a plurality of code segments. The method comprises the step of receiving customer identifier and communicating with a customer history database configured to store historic data. The method also includes determining whether the received customer identifier corresponds to a stored customer identifier in the customer history database. 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. The associated communication data is transmitted to a switching signal.

Abstract: The methods, apparatus, and systems described herein are designed to route customer communications to the best available agent. The methods include predicting a personality type of the customer, determining the occupancy level of agents to provide a list of available agents, providing a routing recommendation based on the predicted personality type of the customer and agent data such as proficiency in handling customers with the predicted personality type, and/or analyzing real-time customer-agent interactions.

Abstract: A method and system for analyzing electronic communication data is provided. In one embodiment, a method includes receiving electronic customer communication data by a contact center, analyzing the electronic customer communication data by applying a predetermined linguistic-based psychological behavioral model to the electronic customer communication data, and 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. In one or more embodiments, electronic customer communication data may be one or more of electronic-mail data, web content data, text message data, voice over IP data, online forum data, social media data, update status, media feed, social media review, social media data stream. In other embodiments, electronic customer communication data may include data received during a customer communication with a graphical user interface for the contact center.

Abstract: A method and system for analyzing electronic communication data is provided. In one embodiment, a method includes receiving electronic customer communication data by a contact center, analyzing the electronic customer communication data by applying a predetermined linguistic-based psychological behavioral model to the electronic customer communication data, and 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. In one or more embodiments, electronic customer communication data may be one or more of electronic-mail data, web content data, text message data, voice over IP data, online forum data, social media data, update status, media feed, social media review, social media data stream. In other embodiments, electronic customer communication data may include data received during a customer communication with a graphical user interface for the contact center.

Abstract: A method for customer-based outcome prediction that includes receiving recordings of interactions with customers in a customer group, analyzing the recordings of the interactions to generate interaction data, and building a predictive model using the interaction data, the predictive model identifying a variable relevant to predicting a likelihood of an identified outcome occurring in association with future interactions with customers in the customer group. The method also includes receiving a recording of a current interaction with a first customer, the first customer being in the customer group and analyzing the recording of the current interaction with the first customer to generate current interaction data. Further, the method includes adding the current interaction data to a first customer profile associated with the first customer and applying the predictive model to the first customer profile to predict the likelihood of the identified outcome occurring in association with the current interaction.

Abstract: A method for customer-based outcome prediction that includes receiving recordings of interactions with customers in a customer group, analyzing the recordings of the interactions to generate interaction data, and building a predictive model using the interaction data, the predictive model identifying a variable relevant to predicting a likelihood of an identified outcome occurring in association with future interactions with customers in the customer group. The method also includes receiving a recording of a current interaction with a first customer, the first customer being in the customer group and analyzing the recording of the current interaction with the first customer to generate current interaction data. Further, the method includes adding the current interaction data to a first customer profile associated with the first customer and applying the predictive model to the first customer profile to predict the likelihood of the identified outcome occurring in association with the current interaction.

Abstract: A method for analyzing a telephonic communication between a customer and a contact center is provided. According to the method, a telephonic communication is separated into at least first constituent voice data and second constituent voice data. One of the first and second constituent voice data is analyzed by mining the voice data and applying a predetermined linguistic-based psychological behavioral model to one of the separated first and second constituent voice data. Behavioral assessment data is generated which corresponds to the analyzed voice data.

Abstract: The methods, apparatus, and systems described herein are designed to identify fraudulent callers. A voice print of a call is created and compared to known voice prints to determine if it matches one or more of the known voice prints. The methods include a pre-processing step to separate speech from non-speech, selecting a number of elements that affect the voice print the most, and/or computing an adjustment factor based on the scores of each received voice print against known voice prints.

Abstract: A method for automatically routing a telephonic communication to at least one of a plurality of communication destination addresses is provided. The method is implemented by a computer readable medium having a plurality of code segments. The method comprises the step of receiving customer identifier and communicating with a customer history database configured to store historic data. The method also includes determining whether the received customer identifier corresponds to a stored customer identifier in the customer history database. 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. The associated communication data is transmitted to a switching signal.

Abstract: A method for analyzing a telephonic communication between a customer and a contact center is provided. According to the method, a telephonic communication is separated into at least first constituent voice data and second constituent voice data. One of the first and second constituent voice data is analyzed by mining the voice data and applying a predetermined linguistic-based psychological behavioral model to one of the separated first and second constituent voice data. Behavioral assessment data is generated which corresponds to the analyzed voice data.

Abstract: The invention relates to a method and system for analyzing an electronic communication, more particularly, to analyzing a telephone communication between a customer and a contact center to determine communication objects, forming segments of like communication objects, determining strength of negotiations between the contact center and the customer from the segments, and automate setup time calculation.

Abstract: A method for analyzing a telephonic communication between a customer and a contact center is provided. According to the method, a telephonic communication is separated into at least first constituent voice data and second constituent voice data. One of the first and second constituent voice data is analyzed by mining the voice data and applying a predetermined linguistic-based psychological behavioral model to one of the separated first and second constituent voice data. Behavioral assessment data is generated which corresponds to the analyzed voice data.

Abstract: A computer readable medium for controlling a computer is provided. The computer readable medium comprises a plurality of code segments for controlling a computer. A code segment receives a telephonic communication comprised of voice data and event data. A code segment receives computer application data comprising data associated with at least one computer application in use during the telephonic communication. A code segment analyzes the telephonic communication by translating the received voice data into a text format, the text format defining a plurality of components. At least one component of the text data and communication event data occurring during a time interval is classified into one of a plurality of object types, and the computer application data during the time interval is compared to the object type of the classified components.

Abstract: A computer program for training a customer service representative by analyzing a telephonic communication between a customer and a contact center is provided. A code segment selects at least one identifying criteria. A code segment identifies a pre-recorded first telephonic communication corresponding to the selected identifying criteria. The first telephonic communication has first event data associated therewith. A code segment generates coaching assessment data corresponding to the identified pre-recorded first telephonic communication. A code segment identifies a pre-recorded second telephonic communication corresponding to the selected identifying criteria. The second telephonic communication has second event data associated therewith. A code segment compares the identified pre-recorded second telephonic communication to the identified first telephonic communication within the coaching assessment data.

Abstract: A method for analyzing a telephonic communication between a customer and a contact center is provided. According to the method, a telephonic communication is separated into first and second constituent voice data. One of the first and second constituent voice data is analyzed. The analysis consist of translating one the constituent voice data into a text format and applying a predetermined linguistic-based psychological behavioral model to the translated voice data. In applying the behavioral model, the translated voice data is mined, and behavioral signifiers associated with the psychological behavioral model are identified in the voice data. The behavioral signifiers are automatically associated with at least one of a plurality of personality types associated with the psychological behavioral model. Behavioral assessment data is generated which corresponds to the analyzed voice data.

Abstract: A method and system for determining the gender of a communicant in a communication is provided. According to the method, at least one aural segment corresponding to at least one word spoken by a communicant is identified. The aural segment is then analyzed by applying a gender detection model to the aural segment, and gender detection data is generated based on the application of the gender detection model.

Abstract: A method for analyzing a telephonic communication between a customer and a contact center is provided. According to the method, a telephonic communication is separated into at least first constituent voice data and second constituent voice data. One of the first and second constituent voice data is analyzed by mining the voice data and applying a predetermined linguistic-based psychological behavioral model to one of the separated first and second constituent voice data. Behavioral assessment data is generated which corresponds to the analyzed voice data.

Abstract: A method of determining the complexity of a telephonic communication received by a contact center is provided. The method comprises the step of establishing a call rule based on one or more of a call duration threshold, a non-interaction threshold, a distress event threshold, a third party dialog threshold, and a call transfer threshold. A recorded telephonic communication is received and call attributes associated with the telephonic communication are determined. The call attributes include one or more of the following: call duration data, non-interaction data, distress event data, third party dialog data and call transfer data. The established call rule is compared to the call attributes of the telephonic communication, and data indicative of the complexity of the telephonic communication is generated.

Abstract: A method for analyzing a telephonic communication between a customer and a contact center is provided. According to the method, a telephonic communication is separated into at least first constituent voice data and second constituent voice data. One of the first and second constituent voice data is analyzed by mining the voice data and applying a predetermined linguistic-based psychological behavioral model to one of the separated first and second constituent voice data. Behavioral assessment data is generated which corresponds to the analyzed voice data.