Voice Agent Analytics and Call Sentiment Analysis: What to Measure and How to Compare Vendors

What voice agent analytics should report, how call sentiment analysis is scored, and the questions to ask before you buy AI call analytics from any vendor.

Most teams that buy a voice agent start by asking whether it answers the phone. Six weeks later the question changes to whether it is working, and the honest answer depends on what you can measure. AI call analytics is the layer that turns thousands of conversations into figures a manager can act on, and the quality of that layer varies far more between vendors than the voice does.

What voice agent analytics should tell you

A dashboard that shows total calls and average duration is a counter, not analytics. Voice agent analytics earns its name when it answers decisions: do we need more cover on Monday mornings, which call types still reach a person, and is a script change making callers happier or angrier.

• Volume by hour and day: shows when callers actually ring, including the after-hours demand a human team never saw.
• Resolution and hand-off rate: the share of calls the agent completed against the share passed to a person, split by topic.
• Reasons for calling: intent groupings built from transcripts, so you learn that a third of calls are about one thing you could fix upstream.
• Outcomes: booked, qualified, transferred, abandoned. A call without an outcome is a cost with no result attached.
• Sentiment: how callers felt, by topic and over time, so quality is visible and not guessed.

If you want the wider list of operating figures, our guide to measuring an AI voice agent covers the metrics that matter and the ones that flatter.

How call sentiment analysis works

Voice call sentiment analysis reads a conversation as it happens. The call is transcribed, each turn is scored for tone, word choice and intent, and the scores build into a running reading of how the caller feels. The point of doing it live is that the agent can act: soften its approach, prioritise the call, or warm-transfer to a person while the caller is still on the line.

Afterwards, the same scores roll up by topic and outcome. That is where sentiment analysis in a call center earns its keep, because the pattern is invisible call by call. Seeing that billing questions end unhappily twice as often as booking questions tells you where to write a better answer.

Treat the score as a strong directional signal, not a clinical measurement of any single moment. It is most reliable in aggregate and most useful for catching at-risk calls early. For the definition and the underlying method, see what customer sentiment analysis AI is and how it works.

Live scoring against after-the-call scoring

How to compare AI call analytics vendors

Analytics is often sold as a tier, an add-on or a separate product, so the same words can mean different things on two pricing pages. As one example, JustCall's published pricing lists sentiment analysis on its Pro Plus and SalesPro plans and not on Team or Pro, and sells its AI voice agent as an add-on with volume discounts down to $0.15 per minute (read from justcall.io/pricing on November 2, 2026). Neither choice is wrong. It simply means you should check which tier unlocks the feature you are buying the product for.

• Is sentiment live or retrospective?: Live scoring can change a call. Retrospective scoring can only describe it.
• Does it cover every call?: A sample hides the quiet dissatisfaction that costs you customers.
• Which plan unlocks it?: Read the tier table, not the feature page.
• Does the analytics sit with the recording?: A flagged call should be one click from its transcript and summary.
• Can you export it?: Your data should reach your CRM and reporting tools without a manual step.

With Centricall, call analytics and sentiment scoring are part of the voice agent rather than a separate product, and every call is recorded, transcribed and summarised in the same record.

Turning the numbers into changes

• Start with one call type: pick the call that happens most often and read ten of its summaries before looking at a chart.
• Set a threshold for escalation: decide which sentiment drop should trigger a transfer, and review the first week of triggers by hand.
• Change one thing at a time: edit one script or answer, then compare resolution and sentiment for that topic over the next fortnight.
• Review monthly: the reasons people call change with season, pricing and news, and the dashboard will show it first.