Business & Applications

Sentiment Analysis

AI determining the emotional tone of text — positive, negative, or neutral.

Definition

Sentiment analysis uses AI to classify the emotional tone of text — customer reviews, social media mentions, support tickets, employee feedback — as positive, negative, or neutral, often with more granular dimensions like urgency, frustration, or satisfaction. This enables businesses to process large volumes of customer feedback at scale, identify at-risk customers, monitor brand perception, and prioritise high-urgency communications.

Why this matters for your business

Sentiment analysis can be applied to your customer service queue to automatically escalate frustrated customers to senior agents, and to your review data to identify specific pain points driving negative sentiment.

Heard enough terminology — ready to talk outcomes?

We translate AI concepts into measurable business results. No upfront fees — you pay only when independently verified results are delivered.

← Back to glossary

Disclaimer

This definition is provided for educational and informational purposes only. It represents a general explanation of a technical concept and does not constitute professional, technical, or investment advice. Artificial intelligence is a rapidly evolving field; terminology, techniques, and capabilities change frequently. Coaley Peak Ltd makes no warranty as to the accuracy, completeness, or currency of the information provided. Nothing on this page should be relied upon as the sole basis for commercial, technical, legal, or investment decisions without independent professional advice.

Document reference: ISO_webpage_knowledge-base_glossary_v1

Last modified: 29 March 2026

Knowledge Base·Business & Applications·Sentiment Analysis