Real-time conversational analytics facility

A system that provides a visual indication of a language analysis and an acoustic analysis of a communication, comprising:

• a receiver for receiving a copy of the communication in near real-time or real-time relative to the origination of the communication;
• a computer-based communications analytics facility for evaluating the received communication in near real-time or real-time relative to the receipt of the copy, comprising:
• a language module for analyzing the communication for a language characteristic and a non-word symbol within the communication text that mimics a verbal element;
• an acoustic analysis module for analyzing the communication for an acoustic characteristic;
• a contextual module for analyzing a context of words within the communication;
• and
• a determination module for determining a category, a score and an alert associated with the communication using the language characteristic, non-word symbol and the acoustic characteristic, wherein the alert concerns a presence or an absence of specific language and wherein the category is one category selected from the group consisting of a behavior, a reason, a procedure, a competitor, a dissatisfaction, an empathy, a repeat contact, a transferred call and a politeness;
• and
• an interface for displaying at least one visual indication representative of each of the category, the score and the alert.

A non-transitory computer readable medium with an executable program for providing a dynamic graphical representation of a category, a score, a sentiment, and an alert wherein the program instructs a processor to perform at least the following steps:

• receiving a communication;
• analyzing the communication in at least near real-time relative to receipt of the communication using a computer-based communications analytics facility for a language characteristic, a non-word symbol that mimics a verbal element, and an acoustic characteristic, wherein analyzing the language characteristic of voice communications includes converting the voice communication to text using computer-based speech recognition;
• analyzing the communication using a contextual analysis that evaluates the voice communication based on a plurality of words of the voice communication spoken before each word of the plurality of words;
• determining the category, the score, the sentiment, and the alert associated with the communication using the language characteristic, non-word symbol, the acoustic characteristic and the contextual analysis, wherein the category is one category selected from the group consisting of a behavior, a reason, a procedure, a dissatisfaction, an empathy, a repeat contact, a transferred call and a politeness;
• and
• providing a dynamic graphical representation of the category, score, sentiment and the alert through a graphical user interface.