Sentiment Analysis
Why AI reads what customers say, not just star ratings
What is it?
Sentiment analysis looks at the actual words in your reviews - not just the star ratings. AI systems don't just count stars; they read and understand what people are saying about you.
A 4-star review that says "Great service, fixed my leak in an hour!" tells AI something very different than a 4-star review that says "Eventually got the job done after some issues."
How AI interprets sentiment
Positive Signals
- "Highly recommend"
- "Best in the area"
- "Will definitely use again"
- "Professional and friendly"
- "Exceeded expectations"
Negative Signals
- "Had to follow up multiple times"
- "Okay but nothing special"
- "Would try others first"
- "Communication could be better"
- "Eventually resolved"
Why star ratings alone don't cut it
Two businesses can both have 4.5 stars, but AI might strongly recommend one and barely mention the other. The difference? The actual sentiment in the reviews.
AI is trained on human language. It picks up on:
- Enthusiasm level: "Amazing!" vs "Fine"
- Specificity: Detailed praise vs generic comments
- Recency: What people are saying lately
- Consistency: Same themes appearing repeatedly
What we measure
Our sentiment analysis breaks down your reviews into:
Example
Mike's Auto Repair had 4.6 stars but low AI visibility. Sentiment analysis revealed that while reviews were positive, they were generic ("good service"). Competitors had reviews with specific praise ("fixed my transmission when two other shops couldn't"). Mike started asking satisfied customers to mention the specific work done - his sentiment score jumped 23% in two months.
Find out what AI thinks about your reviews.
Analyze Your Sentiment