BenefitsWhy You'll Love This
Key advantages that make a real difference for your team
Instant Mood Check
Each mention gets a sentiment score automatically. No manual tagging. No guessing. Just clear positive, negative, or neutral labels.
Track Trends Over Time
See how sentiment shifts week over week. Catch reputation changes before they become crises.
More Than Just Keywords
Old school monitoring counts mentions. That tells you volume, not opinion. We analyze the actual language to understand whether someone is praising you, complaining, asking a question, or just mentioning you in passing. Context matters.
- AI powered analysis of full message context
- Detects praise, complaints, questions, neutral references
- Confidence scores so you know how certain the analysis is
- Works across languages and slang
Watch Sentiment Move
One angry tweet doesn't matter. A hundred in a week does. We chart your sentiment over time so you can see patterns. Product launch went well? You'll see the positive spike. Service outage? You'll see the dip. Correlate what you do with how people feel.
ProcessHow It Works
Get started in just a few simple steps
Mentions Come In
We pull mentions from X, Reddit, YouTube, news sites, and more. Every mention enters the analysis pipeline.
AI Reads the Context
Our model analyzes the full text, not just keywords. It understands sarcasm, mixed feelings, and nuance.
Sentiment Gets Scored
Each mention is tagged positive, negative, or neutral. You also get a confidence score for transparency.
You See the Big Picture
Use CasesWho Uses This
Perfect for teams and individuals across different roles
PR Teams
Track how campaigns land. See if that press release shifted sentiment. Catch negative coverage before it spreads.
Product Teams
Monitor sentiment around feature launches. Happy users? Ship more of that. Frustrated users? Time to dig in.
"We launched a pricing change and watched sentiment in real time. Saw the negative spike within an hour. Adjusted messaging the same day. By end of week, sentiment was back to normal. Without this, we would have found out from Twitter screenshots in a news article."
Rachel T.
VP Communications, SaaS Company
FAQFrequently Asked Questions
Common questions about Sentiment Analysis
Our model is accurate on the majority of mentions. It handles straightforward praise and complaints well. Sarcasm and mixed sentiment are harder, which is why we show confidence scores. If we're not sure, you'll know.