Sentiment Analysis and Speech Analytics for Contact Centers

Call emotion mapping tracks emotional cues along the conversation timeline for both the caller and the agent. It highlights critical moments such as customer frustration and positive turning points. Supervisors can review specific timeline segments where sentiment shifts occur rather than listening to entire call recordings.

Automated red-flag detection identifies critical risks including hostile agent behavior, privacy violations, improper advice, and customer escalation risks. When high-risk conditions are triggered during an interaction, the system surfaces urgent notifications to supervisors for immediate intervention and operational review.

In addition to voice calls, the platform evaluates text-based interactions including SMS messages, emails, documents, and chat transcripts. Organizations can apply standardized quality rubrics or channel-specific scorecards across all incoming and outgoing customer communication streams within a single system.

Interaction analysis identifies recurring performance patterns and missed rubrics across agent interactions. The system links these quality findings directly to targeted coaching recommendations, structured learning lessons, quizzes, knowledge checks, and AI mock-caller roleplay practice to reinforce proper procedures before live calls.

Yes, quality scores, detected red flags, call outcomes, and performance signals can trigger workflow updates in external applications. Through API connectivity and webhooks, teams can push quality updates directly into CRMs, ticketing systems, internal dashboards, and supervisor management tools.

Manager and reviewer access is provided without additional seat fees under platform plans. Paid agent seats are only required for customer-facing representatives whose interactions are actively scored, or for managers and reviewers if their own calls and messages are evaluated.