Voice analytics turns phone calls into data: transcripts, sentiment, topics, compliance checks and outcomes. See how it works and how teams use it.
Voice analytics, also called speech analytics, is software that analyzes recorded or live phone calls to find out what was said and how. It transcribes the call, then measures things like sentiment, topics, keywords, silence, talk time and whether required phrases were used, so teams can review every call instead of a small sample.
Quality assurance on every call, not a 2% sample; compliance checks for regulated industries; spotting why customers call and where they get stuck; coaching agents with real examples; and tracking outcomes such as bookings or payments.
Call analytics usually means call metadata: volumes, durations, sources and outcomes. Voice analytics looks inside the conversation itself. Most teams use both.
Every call on Retell AI produces a transcript, a summary, sentiment and any custom fields you define, through post-call analysis, and AI quality assurance scores calls at scale.
Mostly yes. Both describe analyzing the content of calls; some vendors use voice analytics to also include tone and emotion.
Yes. Real-time voice analytics can alert a supervisor or prompt an agent during the call; post-call analytics reviews the whole conversation after it ends.