Abstract: A method and apparatus for predicting customer behavior is disclosed. The method comprises organizing a transcribed, diarized text of a conversation in a call, into a predefined number of sets, determining features corresponding to a sentiment score, a percentage and/or count of positive words, and a percentage and/or count of negative words for each of the a predefined number of sets, determining word count features corresponding to the word count for each of the a predefined number of sets, determining features corresponding to a call talk time, a call hold time and a call hold percentage based on the transcribed text. Based on all the determined features, the method determines whether the customer is satisfied or not, the customer activity based on an activity profile of the customer, and whether the customer used escalation terms based on the transcribed text.

Abstract: A method and apparatus for predicting customer behavior is disclosed. The method comprises organizing a transcribed, diarized text of a conversation in a call, into a predefined number of sets, determining features corresponding to a sentiment score, a percentage and/or count of positive words, and a percentage and/or count of negative words for each of the a predefined number of sets, determining word count features corresponding to the word count for each of the a predefined number of sets, determining features corresponding to a call talk time, a call hold time and a call hold percentage based on the transcribed text. Based on all the determined features, the method determines whether the customer is satisfied or not, the customer activity based on an activity profile of the customer, and whether the customer used escalation terms based on the transcribed text.