AI Glossary · CX & Contact Center
Sentiment Analysis
Classifying emotional tone of a call or message in real time or post-hoc — drives coaching, escalation and QA sampling.
Definition
What is Sentiment Analysis?
Sentiment Analysis is classifying emotional tone of a call or message in real time or post-hoc — drives coaching, escalation and QA sampling.
- Category
- CX & Contact Center
- Glossary set
- 18 related terms
- Audience
- Enterprise AI leaders
Why does Sentiment Analysis matter in enterprise AI?
Sentiment Analysis matters in contact-center AI programs because it affects agent workflow, customer resolution, service quality, and the business case for CCaaS modernization.
Related terms in CX & Contact Center
- Agent Assist
- Real-time AI suggestions surfaced to a human agent during a customer interaction — answers, next-best-action, sentiment cues, after-call summary.
- After-Call Work (ACW)
- Post-interaction tasks (wrap codes, notes, dispositions). Auto-summary and auto-disposition are the highest-ROI early CX AI wins.
- Average Handle Time (AHT)
- Mean duration of a customer interaction including hold and wrap. A primary CX KPI reshaped by agent-assist and automation.
- CCaaS (Contact Center as a Service)
- Cloud-native contact center platform — routing, IVR, WFM, analytics, digital channels — delivered as a subscription (e.g., Amazon Connect, Genesys Cloud, NICE CXone, Five9, Google CCAI).
- Containment Rate
- The share of contacts a self-service channel resolves without human escalation. Primary KPI for voice bots, chatbots and IVAs.
- Conversational AI
- AI systems that hold natural-language dialogues across voice and digital channels — combining NLU, dialog management, retrieval and generation.