What is sentiment analysis?
Sentiment analysis uses AI to read written feedback and judge whether each comment is positive, negative or mixed. For restaurants, the useful version goes one step further and scores sentiment for each part of the experience, like food, service, atmosphere and value.
Why it beats star ratings
A four-star review that says “great food, but we waited 40 minutes for a table” is positive about the food and negative about the wait. A star rating hides that. Sentiment analysis keeps both signals.
How it works
- Reviews are collected from each site.
- Each review is split into the topics it mentions.
- AI scores each topic as positive, negative or mixed.
- Scores are combined into an overall picture for each theme, with example quotes.
What to look for in the results
- Themes with strongly negative sentiment that come up often
- Themes where sentiment is getting worse month to month
- Themes where competitors score much higher than you
- Strengths guests love that you could promote more
Limits to keep in mind
AI can misread sarcasm or very short reviews. That’s why good tools show the guest quotes behind each score, so you can check the reasoning. Sentiment analysis is most reliable across many reviews, not for judging a single one.
Putting it to work
Use the scores to choose a few fixes, share the quotes with your team, and watch whether sentiment for those themes improves over the next two months.
OmniServe’s free Taste Report includes sentiment scores for you and two competitors.
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Want this done for your restaurant?
The free Taste Report compares your reviews with two local competitors and lists the top fixes.