Definition
Sentiment analysis
Sentiment analysis is using AI to automatically score whether reviews, messages, and social posts are positive, negative, or neutral, and to surface the themes behind them.
Sentiment analysis is software reading text the way a manager would skim it, then labeling the feeling behind it (positive, negative, or neutral) often down to the specific topic, so "the pasta was incredible but the wait was brutal" registers as two separate signals. For a restaurant it turns a pile of Online review comments, survey replies, and social mentions into a readable pulse, showing you not just your Star rating but why it is what it is.
A number tells you where you stand; sentiment tells you what to fix. Read across hundreds of reviews it surfaces the recurring complaint (slow Friday service, a dish that keeps disappointing) long before it drags your average down, and it flags the raving fans worth turning into regulars. Given 75% of consumers read reviews regularly, and that a one-star swing is worth a 5-9% change in revenue for an independent, catching a negative trend early is money in the bank. It also tells you which reviews to reply to first.
Sentiment analysis is itself an AI capability, powered by Natural language processing (NLP), and it is built into most modern review and guest-experience platforms rather than bought on its own. Paired with a language model it can also draft a reply matched to each review's tone. See review management.
See it in action
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