Metrics & Analytics
Updated March 2026

What is
Sentiment Analysis?

Sentiment analysis uses AI or manual review to classify social media mentions as positive, negative, or neutral.

3 min read
Metrics & Analytics

Definition

Sentiment analysis uses AI or manual review to classify social media mentions as positive, negative, or neutral. It helps you understand how people feel about your brand, products, or campaigns.

Why It Matters

High mention volume means nothing if the sentiment is overwhelmingly negative. Sentiment analysis adds qualitative depth to your quantitative metrics, helping you catch PR issues early, measure campaign reception, and understand customer satisfaction at scale.

In Practice

Real-World Scenario

After launching a new pricing plan, a SaaS brand runs sentiment analysis on Twitter mentions. They find 60% positive, 25% neutral, and 15% negative. The negative mentions cluster around one specific concern — feature limitations on the free tier — giving the team a clear issue to address.

Key Takeaway: Segment sentiment by topic to find specific, actionable issues rather than just an overall positive/negative score.

Pro Tips

1

AI-based sentiment analysis isn't perfect — spot-check results to ensure accuracy, especially with sarcasm and nuance.

2

Track sentiment over time, not just at a point. Shifts in sentiment often precede changes in engagement or churn.

3

Segment sentiment by topic to identify specific strengths and weaknesses rather than just an overall score.

Put this knowledge to work

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Metrics & Analytics

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