Glossary
Sentiment Analysis
In one line: Sentiment analysis is AI that reads text — reviews, social posts, support messages — and decides whether the writer is happy, unhappy, or neutral.
Why it matters
You can’t read every review or DM a customer writes. Sentiment analysis automates the reading — classifying every customer message so you can track how perception of your business is changing day by day, by product, by location.
Modern aspect-based sentiment
Old sentiment tools labeled a whole review positive or negative. Modern tools (powered by large language models) extract sentiment per topic within a single message: “food was excellent, service was slow.” That’s two data points from one review — one positive on food, one negative on service. The granularity is what makes the tool useful.
Where retailers use it
- Monitor product reviews for emerging quality issues
- Track restaurant reviews for service or food trends
- Prioritize support tickets — angry customers get human attention faster
- Measure marketing campaign reception on social media
Related terms
Menu Engineering, Large Language Model (LLM), Generative AI
See it in practice
Read what your restaurant reviews are actually telling you, or explore AI for F&B.