Sentiment analysis
What is Sentiment analysis?
Sentiment analysis is the automated classification of a message, chat, or call transcript's emotional tone — typically positive, neutral, or negative, sometimes scored along a continuous scale — using natural language processing instead of a human manually tagging each interaction. In a CPaaS or contact-center context it runs on inbound SMS, chat, email, and voice-call text in near real time, surfacing a customer's frustration or satisfaction to a live agent or triggering an automated escalation before a conversation ends badly.
More detail
Sentiment is usually scored per message and can also roll up into a conversation-level trend, showing whether a customer's tone improved or deteriorated turn by turn rather than only capturing one snapshot at the end.
Voice sentiment analysis layers acoustic signals — tone, pace, volume — on top of the transcribed words, since the same phrase said calmly versus said sharply can carry a very different emotional signal on a call.
On Orbit, the inbox surfaces a per-conversation sentiment sparkline scored from each inbound customer message, so an agent can see at a glance whether a customer's tone is trending up or down across the thread, not just its current value.
Frequently asked
- Does sentiment analysis replace CSAT or NPS surveys?
- No — sentiment analysis is inferred automatically from the language in every message or call, while CSAT and NPS depend on a customer voluntarily answering a survey; teams typically use sentiment as a continuous real-time signal alongside surveys' periodic, self-reported one.
- Can sentiment analysis run on voice calls, or only text?
- Both — text-based sentiment analysis scores transcribed chat, SMS, or email content, while voice sentiment analysis can add acoustic cues like tone and pace on top of the transcript, since identical words spoken calmly versus sharply carry different emotional weight.
See also
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