Definition: Sentiment analysis—also known as opinion mining—is a natural language processing (NLP) technique used to determine the emotional tone behind a body of text. It helps brands assess whether customer feedback, social media posts, reviews, or survey responses express positive, neutral, or negative sentiment.
This analysis allows marketing, sales, and product teams to measure customer perception at scale, uncover brand risks, track public opinion, and tailor communication strategies accordingly.
Use in a Sentence: After running sentiment analysis on social media mentions, the brand identified a spike in negative sentiment related to its new product launch and swiftly addressed the concerns.
Why Sentiment Analysis Matters
- Customer Experience Insights: Understand how people feel about your product, service, or brand in real time.
- Brand Health Monitoring: Track reputation shifts across channels before crises escalate.
- Product Development: Identify recurring complaints or praise to guide roadmap priorities.
- Campaign Effectiveness: Measure emotional impact of marketing efforts and messaging.
- Competitive Benchmarking: Compare sentiment around your brand vs. competitors.
Where Sentiment Analysis Is Used
| Channel | Examples of Use |
|---|---|
| Social Media | Monitoring mentions, hashtags, and trends |
| Customer Reviews | Understanding satisfaction across platforms |
| Surveys & Feedback | Automating open-text response analysis |
| Support Tickets | Flagging emotional frustration or praise |
| News & PR | Gauging tone of earned media and press coverage |
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