How it works
Tools scan large amounts of text and score each piece by tone. More advanced models can also tag topics, so you see not only that people are unhappy but whether it's about price, delivery or service.
How marketers use it
Tracking brand sentiment over time, spotting a complaint trend early, comparing how people talk about you versus competitors, and measuring reaction to a campaign or product launch.
Where it gets things wrong
Sarcasm, slang, mixed opinions and industry terms can confuse models. A review saying a horror movie was "terrifying" is praise, not a complaint. Spot-check results by reading real examples.
Why Sentiment Analysis matters
You can't read every review and comment once a brand grows. Sentiment analysis shows the overall mood and flags problems early, so you can respond before they spread.
Catching a delivery problem early
A furniture retailer tracked sentiment in reviews and social mentions. A sudden rise in negative posts mentioning delivery led the team to a failing courier partner, which it replaced before complaints piled up.
Common mistakes
Trusting scores without reading
Automated scores miss context. Read a sample of posts behind each trend.
Only tracking overall sentiment
A single score hides what people are unhappy about. Break it down by topic.
Measuring without responding
Insight only helps if someone acts. Route negative trends to the team that can fix them.
Where we work on this