The present disclosure relates to automatically evaluating an agent-customer interaction utilizing aspects of machine learning to score the quality of the interaction. In some embodiments, one or more machine learning models are utilized to generate an interaction quality score which is a comprehensive evaluation of agent performance during the interaction. The interaction quality score is a combination of two sub-scores, a conversation score and service score which are each based on one or more dimension scores. The conversation score is a measure of how well the agent engages with the customer during the interaction. The service score is an evaluation of the quality of the agent's service during the interaction in terms of customer's perception of the agent's performance. Each of the conversation score and service score are determined by an analysis of one or more dimensions such as fluency, relevance, appropriateness, informativeness, assurance, responsiveness, empathy, compliance, and sentiment.